Hi, my name is Lindsay Maher. I'm a professor of civil and environmental engineering at Virginia Tech, and I'm pleased to be co-chairing this workshop with John Samet, Dean of the Colorado School of Public Health. We welcome you to the third in a three-part series of workshops on indoor air management of airborne pathogens. While we are gathered virtually today, the National Academies is physically housed on the traditional lands of the Kutchank and Piscataway peoples past and present. We honor with gratitude the land itself and the people who have stewarded it throughout the generations. We honor and respect the enduring relationship that exists between these peoples and nations in this land. We thank them for their resilience in protecting this land and aspire to uphold our responsibilities to their example. I want to thank the planning committee, the National Academy staff, and today's moderators and participants, all of whom have worked hard to bring together this exciting event. This is the third workshop in a series of three. The first workshop highlighted the progress made in the management of airborne pathogens indoors since 2020. The second workshop focused on reducing airborne pathogen transmission in schools. This workshop series is part of the National Academy's Environmental Health Matters Initiative. The vision of EHMI is to improve the health of all people equitably by promoting evidence-based assessment, prevention, adaptation, and strategic mitigation of complex and interconnected environmental stressors that affect human health and disease. EHMI provides connection, credibility, stewardship, and neutrality. Our sponsors include the Centers for Disease Control and Prevention, the National Institute of Environmental Health Sciences, the Environmental Protection Agency, the National Institutes of Health, and ExxonMobil. In addition to their interest in environmental health issues, the sponsors also recognize the National Academy's core value of operating independently from any sponsorship. This workshop series grew out of a National Academy's virtual workshop in August 2020 on airborne transmission of SARS-CoV-2. In that workshop we established the mechanisms of airborne transmission and evidence for it from emissions of the virus and respiratory droplets and aerosols to exposure to infection. Now we are focusing on how human behavior and the built environment affect and can mitigate exposure to airborne pathogens. Now we'll talk about this present series of workshops on indoor air management of airborne pathogens. I'd like to thank the planning committee members who are shown here. I'm not going to read all their names, but we aim to have a diverse group of multidisciplinary experts to help plan this series. The goals of the overall series are shown here. We have convened an interdisciplinary and multi-sectoral group of scientists together with facilities managers and engineers, workers, and representatives of those using the facilities. The overall goals are to review the state of knowledge concerning building management, ventilation, and air cleaning for airborne pathogens, to discuss experiences with management of enclosed spaces during the pandemic, and to identify promising practices that can be adopted to make these places safer. This slide shows the overall framework of our discussion. We're taking the items on the left, research, practice, and mechanistic understanding, and using them to figure out what works, how we can use what works, what works, and then to verify that it actually does work. We are interested in moving from efficacy or what should work to effectiveness of what really works. I'm going to spend a couple of minutes reviewing what happened in the first couple of workshops. The first workshop covered lessons learned over the past two and a half years about management of airborne pathogens. We discussed scientific advances and innovations along with organizational management and response. Here are some of the main messages from that meeting. First, masking, ventilation, filtration, and UV reduced the amount of virus in the air, the infectious virus, and thus reduced the risk of transmission. These approaches are stronger together than alone. We must also consider energy efficiency in our optimization. Two, we need to start with the basics, ensuring that our existing engineering systems are appropriately designed, sized, and operating. Then we can think about further optimization using CO2 sensors, carbon dioxide sensors, and other innovations. Three, implementation requires attention to human factors. We need to increase people's confidence in the engineering and technological solutions while recognizing that different organizations have different missions and cultures. The second workshop focused on schools. We identified practices that can be adopted and implemented at different levels from an individual classroom all the way up to the federal government in order to reduce transmission of airborne pathogens and make education equitable and safe. Here are some of the main messages from that meeting. There are more than 100,000 schools nationwide, and there is tremendous variation in school buildings and engineering controls and components from school to school. This variability poses a complex set of problems. Two, there are three main engineering controls in school buildings that have been shown to work, ventilation, filtration, and germicidal UV. While we know that these can be effective, it does not mean that they always are, mainly because the actual performance or effectiveness varies from school to school. Thus, we have to continually assess and verify the effectiveness. Three, greater efforts aimed at equitable distribution of resources are needed at the national scale, addressing barriers to improving ventilation and other engineering controls in schools, and identifying facilitators to increase buy-in from school districts. And four, implementation remains a critical barrier for schools. In today's workshop, we are aiming to identify promising practices that can be adopted at different levels to make access to public transportation equitable and safe. In today's workshop, we have three sessions. In session one, we'll review the state of knowledge about research regarding public transportation safety and management to reduce transmission of airborne pathogens equitably. In session two, we'll hear case studies about on-the-ground experiences. These are meant to inspire and serve as a base for concrete implementation. In session three, we'll explore how to overcome barriers to implementation and identify roles for different stakeholders at the federal, state, and local levels in the non-government sector. And then finally, at the end of the workshop series, coming up soon, we will be producing a report in the format of a proceedings in brief. These workshops are designed to be highly interactive and to look at case studies that reflect people's lived experiences during the pandemic. We expect that these workshops will help pave the way for more effective management of indoor air when it comes to airborne pathogens. All right, let's get started. It is my pleasure to introduce the first sessions moderator, Dr. Kath Noakes. She is a professor of environmental engineering for buildings in the School of Civil Engineering at the University of Leeds. Dr. Noakes, the floor is yours. Thank you very much, Lindsay. Thank you. And thank you to the panel for inviting me to chair this session today. So the goals of this first session are to review the state of knowledge surrounding research around public transport safety and management and how we can use that to reduce transmission of airborne pathogens in an equitable way. Throughout this, we'll invite audience members to submit questions at any time using the Slido platform, which the link will be put in the chat and people can vote on those questions. And we'll do as best we can to address as many of these as possible during the panel discussion after the talks today. As you can see on this slide, we have a fantastic line up this session with two speakers. We have Susan Grant-Muller from the University of Leeds and Jodie Holton from the Southeastern Pennsylvania Transportation Authority. And then we will be joined following these two talks by two panelists, Madeline Parker and Jason Debrow. So all of the speakers and panelist bios can be found on our website and the link that will be in the chat. Okay, so without further ado, I'd like to introduce our first speaker, who is Dr. Susan Grant-Muller. Susan is a chair in technologies and informatics for the Institute of Transport Studies at the University of Leeds. And she's going to be talking about factors that influence COVID-19 transmission on public transport. So Susan, if you could unmute and share your screen and Amanda, we've got 15 minutes for the presentation. Thank you very much for that welcome. And it's great to be here today in this very interesting, very challenging topic. I'd like to speak today about some of the factors that influence COVID-19 transmission on ground public transport. Let's start with a key question of concern. Since the onset of the pandemic, virus transmission, the actual amount of virus transmission that happens on public transport has been really difficult to detect. It's difficult to directly attribute it to the public transport setting because of course transport sits within a wider lifestyle. The environment is highly transient, particularly for shorter journeys. There's a lot of variation between different modes and even variation within a single mode because of features like the carriage design, capacity, ventilation system. And of course people switch modes as part of the journey sometimes. And there's a lot of variation between the demographic who carry risk in terms of the potential to be carrying the virus and the risks to themselves if they are infected. So the disease burden. And whilst ticketing and other data can tell us something about the journeys made, the end to end journey data is actually poor for quite a lot of settings. In terms of the epidemiological evidence that directly connects virus spread with the use of transport, I've put three examples here, two from China and one from German. And these are perhaps well known examples. The first two are based on tracking whilst the third uses correlation and dissociation. And perhaps what's notable is the range of difference in terms of the estimated risk coming out between the different studies. And the Dresdler paper, the second one there, questions whether outbreaks related to PT may be under-recorded because infections can't be identified and of course contacts can be difficult to trace. Some of the complex factors impacting on transmission on public transport are shown here, broadly separated into these two groups. In terms of the environment, it is a high occupancy density with close proximity and it engenders connectivity between a large number of people who are essentially strangers. There is limited ability for individuals to control the environment as well as especially the air and it's a high touch frequency setting. And this is an issue for people who really do need to hold on perhaps older people and people who are a little bit frail. And of course that connectivity to hubs including social spaces, food, drink, etc. But for many it's an essential service, especially for those who work in more risky settings. And perhaps to note as well it's a relatively sedentary setting, which could indicate lower aerosol emission. Against that background, I'll say something about the TRAC project. So the TRAC project or transport risk assessment for COVID knowledge, to give to its full name, started in September 2020 as a rapid response project. And in response to the initial stages of the pandemic in the UK, it's funded by the national funding body. So actually Professor Kath Noakes is PI for the project and I'm leading one of the work packages, which is concerned with understanding user behaviour and demographics. The main goal is to try and quantify the risk of infection that might be present in different surface public transport modes. And we focus in particularly there on bus train and metro. And also to explore some of the evidence relating to mitigating actions. We've got a unified model which sits over the whole of the work set of work packages, which considers three routes to infection. In other words, aerosol, close range and contact. And we've labelled this the TVC model, which I'll come back to later. Different partners are also carrying out different packages of work, including the UK Health Security Agency, who are doing some surface sampling, analysis of CCTV data to characterise social distancing and service contact patterns, and research to collect data in model environmental emissions, which I'll also come back to. But overall, we're taking this exposure-based approach to quantifying risk. But the question of who is used in public transport is also an important part of the picture. And that means gathering and understanding of the travelling public's characteristics, so their gender, their age, their ethnicity, their income level, but also the characteristics of the travel and the journey themselves, the trip purpose, the time of day, and more. These population and activity characteristics are really important because some parts of the population are more likely to be infected, for example, due to their occupation. We've collected over 560,000 individual trip traces, i.e., from the origin to destination with trajectory mode, contextual variables using a software app. And these high-resolution mobility profiles are being used to provide realistic parameters to the overall risk model and some of our individual behavioural modelling. We've also had an opportunity to understand some of the changing travel patterns through our close links with bus and train operators. Patronage is a sensitive topic in the UK, but what we can see here is some anonymised data that's been given to us. This illustrates here the percentage patronage levels against the baseline. We can do note this is for the first 15 months of the pandemic, but the broad trends are looking very similar across the different indicators that we've got here. So the 10th and the 90th percentile of the different routes for that operator, which is the grey area. And also there isn't a great deal of difference between the there are two pink lines on here, which is a solid pink and a dash pink, which is the difference between London and outside London. So all are following more or less the same trends. The Google mobility data for leads, which is down here, is city specific and relates to retail and recreational trips only. So we're just showing here discretionary trips. And that was important because there were three lockdown periods showed by the pink shaded areas. And what we can see is some fatigue with that lockdown process as as we were coming towards the end of those periods. So in summary, quantifying the risk on public transport involves the modelling of multiple factors, which we've outlined here. The chance of an infected person being on public transport, the different ways that the virus can be transmitted, allowing for mitigations and behaviours. The exposure that the travel and public have to the virus again linked to these multiple factors, including the duration of the trip, proximity and more. And finally, the actual infection infection process, including the dose, the variant immunity, transmission route. So the track project team, one of our a couple of our partners have looked at ventilation as a particular way of measuring the potential pathway for airborne transmission. And this is involved instrumenting an intercity train carriage and using carbon dioxide and particular measures as a proxy for rebreather. The wonderful picture we've got here of the instrumented carriage has HVAC inlets at the sides of the carriage. And then the outlet is running down the middle of the aisle there. This empirical data is complemented by some in lab simulation and modelling work as well as the air flows. And the image below that is showing the circulation of air and increased velocity, particularly close to that HVAC system there, which is positioned on the ceiling. So we can see as well an area in the middle of the carriage where there is very little air circulation. I should say that these are simulated results that came out after about 30 minutes of simulation. But there are some practicalities of ventilation as well. So in terms of commuter train bus and subway, this may be mechanical or natural. For the shorter journeys ventilation may have less impact, but opening doors and windows can help. For the intercity train, these are usually longer journeys. So usually fully mechanical vents, they're often with demand control. For long journeys, we believe ventilation is important and there is very little opportunity to increase that easily. This may be an issue of longer term redesign in terms of the carriages and the ventilation system. But overall challenges with power consumption where we've got competing demands on the power that is supplied overall between the different systems. So to summarise that TVAC model, which is the overarching model that we were seeking to produce within the project, that TVACs, TDC stands for transmission of virus in carriages, I should say, within the track model. And this is an agent based subway stochastic model in which the agents and passengers, they're bored and alight at different stops. This is a flowchart showing the general flow of the modelling work and the clear boxes are the boxes where we've got parameters we can readily change and explore some scenarios. And these solid boxes there are some of the outputs. So the loading patterns come from empirical underground trips in London with a range of prevalence chosen. And this generates the chance of just being an infected person in the carriage overall. The viral load is assumed to be fixed as is respiratory activity between the agents. And we assume droplets of different size are going to be exhaled, which input to a droplet model. And this generates the emission rate, the geometry ventilation masks, etc. These are all things that we can parameters we can change and explore. And this finally results in the measure of exposure there, based on close and long range exposure and format. So distributions of potential outcomes are derived from a large number of simulations. So these are stochastic projections. And the results of course for the parameters that we've input, we have got various sources to try and tune those parameters including survey data from the project and the opportunity to interface with our work package three model, which will work at a low level of resolution, Lincoln home travel to destinations, school, office and supermarket and the return journey. Some of the key findings I've highlighted there. So predicted risk of exposure is seen to be overall low, but prevalence and loading dominant factors. In terms of the highest doses, while there is a small percentage of people in close proximity to the infected person, who are most at risk. And there is a small percentage of people who could get a high format dose from contaminated surfaces. In general long range airborne exposure is likely to be low with a shorter journey and high ventilation rate. But note the end that that masks can reduce all of the transmission routes. We have done some work as well in terms of understanding whether we can estimate relative airborne risk. And this is a broader question. So what is the risk on transport with respect to other settings? For example, office supermarket schools comparisons are difficult due to variations in mode of transmission, the time spent in the setting, different behaviors, etc, etc. But the results here summarise in a comparison based on airborne risk between a person being in a train for one hour with quite a high number of people or being in the office for eight hours with rather few people. And the quantity rate that is the number of infectious particles needed to infect a susceptible person. So we've got two scenarios at one quite low and one much higher. The overall finding from this, the risk of being in the office for eight hours with 40 people, the risk of infections around six times that of being on a train for one hour. And of course, these are just example scenarios and contexts which could be very different in real life. So the learning so far, individual risk is likely to be lower, especially on short journeys, the population risk is increasing with the number of journeys taken, of course, prevalence and loading likely to dominate the risk. And close range airborne transmission can happen anywhere people are in proximity. Of course, that will be higher with increased loading. Format transmission probably low, but high surface touch in which we get with some people and in some contexts could increase risks. And long range airborne transmission likely to be most important on long distance journeys. We've identified a couple of knowledge gaps and a couple of areas to highlight here. Actual transmission on public transport is still extremely challenging to measure. Hence the exposure approach that we took and which other researchers have taken. There is a need for improved knowledge on public transport risks versus other environments. But a fundamental question which came through in one of our workshops with stakeholders of what is safe air quality on ground public transport. And as by safe, we need to look at some of the trade offs between communicable disease and some of the other safety risks that can occur on this type of transport. So, leading finally to whether air quality can be improved with other operational constraints such as energy efficiency, temperature, etc. Just to say a few words about mitigating actions and these can be separated into policy or operator kind of actions versus those for the individual. And many of these appear to be good common sense and a fairly well established through other research. So, good ventilation, strategists to reduce viral presence, testing isolation, good provision of hygiene facilities, ticketing strategists to minimize crowd and this is an interesting one. But overall a sense that maybe cleaning may be less important than it was perceived to be at the start of the pandemic. And for the individual, key is to avoid travel when sick but wearing face coverings, good hygiene, keeping the windows open where possible and supporting social distancing as well. So, thank you to all, a final thank you to the track team but also the Department for Transport colleagues who have given us terrific support, support from transport operators and stakeholder groups. And this is a couple of absolutely key publications that relate to the work I've presented today, lots more scientific detail and very provoking and terrific papers to look into if anyone would like to know more. Okay, thank you very much Susan for that and thank you for the sort of overview of the breadth there and what you've highlighted. I'm going to go straight on to our next speaker who is Jodi Holton. Jodi is the Chief Planning and Strategy Officer at the Southeastern Pennsylvania Transport Authority and her title is entitled Sector Forward, Response to and Ridership Recovery from the Pandemic. So over to you Jodi, you want to unmute and share your screen. All right, thank you so much for having me. It's a pleasure to be with you all today. I'm going to try to share my screen here. That's great, we've got that. You've got it. Now turn it to full screen. Does that help? Perfect. Okay, great. Well, it's a pleasure to be here with you today. I wanted to give you a perspective of SEPTA which is the Southeastern Pennsylvania Transport Authority and we serve Philadelphia, the Philadelphia region. It's a five county region and give you a sense of how large our public transportation authority is. We are the fifth largest in the United States. We have as you can see here 2800 vehicles that we maintain and operate with our customers. We have over 200, almost 300 subway and rail stations that we manage. We have 9300 employees that we aim to keep safe every day and we have a number of routes throughout the region. And was mentioned before, we are similar to other public transit agencies in that our ridership has higher percentages of people of color. We have higher percentage of people with lower income. We have higher percentage of seniors than our population in general in the region. So we are serving and providing equitable transportation options, affordable options that are reliable and safe for the Philadelphia region. And this gives you a sense of the scale of the region here in Philadelphia. This is showing the density of population and employment in the Philadelphia region and then how we serve that population with rail and bus service as well as subway and elevated service. To give you a sense of where our ridership has been and where it is now and hopefully where it's going, the red line here is 2020. So in April, we hit our low of about 19% of pre-COVID ridership. We serve about a million rides a day pre-pandemic. And today we have reached about 616,000 trips per day in the region. And you can see how for the last year or so in 2021, until the beginning of 2022, we were hovering between 30 and 50% of pre-COVID ridership. And of course, we started out 2020 with the Omicron virus or the Omicon variant. So that reduced our ridership in the beginning of 2022. But we are now at our highest ridership since the pandemic began at 57% of pre-COVID ridership. And you can see that here, we have 616,000 trips per day. We continue to operate as much service as we can. And we had done that through the pandemic to make sure that we were allowing distance for social distancing, trying to get to that six feet between passengers or just give people more room on our vehicles. So we have put out almost 90% of pre-pandemic transit service. And then on our commuter rail or our regional rail, as we call it here in Philadelphia, we are currently operating 77% of pre-COVID ridership. So that has reduced the instance of crowding on any of our vehicles. But we are a public transport company. And mass transit and mass moving a lot of people is what we're set up to do. We've been surveying our customers since the beginning of the pandemic quarterly. And we keep a pulse on what concerns them, what would bring them back to riding transit. And a lot of people site, of course, their ability to work from home. They have flexible work schedules now. They think that the service is not as frequent as it used to be pre-pandemic. And to some extent, as I just said, that is somewhat true. And safety concerns. So safety concerns used to be a little bit more about COVID and about public health concerns like that. But now, through the pandemic, we did have an uptick in the number of vulnerable people or homeless or those who are addicted to drugs riding the system and a fear of crime has become a significant concern as well. So during the pandemic, what did we do to improve our cleaning and air quality? We definitely have established relationships with our local universities, Drexel University, to talk about air exchange in our vehicles and air quality throughout our system. We've installed filters, the MRV-13 filters. We've tested our air exchange rates on our vehicles and assured that it's every two to three minutes we're having in exchange of fresh air. We've also revamped our cleaning procedures. And every 10 days, all of our vehicles get a deep clean every night. And throughout the day, as the vehicles come through our shops and yards, they are wiped down and using our EPA-approved disinfectants that we went through somewhat of a long period of testing with them and then ended up with two that we had already been using, the Avastat D and lemon skies disinfectants that are EPA-approved. We also committed to hiring 200 more cleaners. We are still in the process of hiring them. I think everybody's aware of the labor shortage right now. But we have budgeted and put those heads in place so that we can hire and maintain that cleaning protocol that was established during COVID. It's been a big mission for us to communicate this with the public, so that they're aware of everything that we're doing and that it is as safe as it can be to use public transit. One of the things we did during the pandemic was develop a vehicle capacity dashboard so that people could look at a ridership over the last couple of weeks and see how likely it was that their vehicle would be crowded. Less and less, that's become not something that people go to as much anymore, but it was useful during the time when people were very interested in distancing. And how did we protect our employees? We installed operator shields on every vehicle. So every vehicle where the operator has contact with the public, had a plexiglass shield installed. We distributed masks and held many vaccination clinics. We offered free testing for COVID. We formed partnerships again with our trusted community organizations such as the Black Doctors COVID Consortium to help build awareness and communicate that we have these resources available. In 2021, we adopted a strategic plan really setting the framework for how we can transform our ridership, our service patterns, our organization to be more responsive to the changing needs of the region. And we developed three goals to be a proactive organization, to provide service that is intuitive and is for everyone, and then to provide a more seamless transit network. As part of providing an intuitive system and one that is useful to all as well as being proactive, we developed an internal program called SCOPE, which stands for Safety, Cleaning, Ownership, Partnership, and Engagement. And it's a combination of all these new codifying and making standard, our new cleaning procedures. We partnered as well with universities such as Cabrini and Temple University in Philadelphia to provide additional ambassadors that go out with our police officers and on their own to provide health and human services assistance to those in need in our stations and on our facilities. And I mentioned the rising concern about crime and the perception of crime. And as ridership comes back, the instance and the amount of crime on our system has dropped by 30%. So some of that is due to the fact that we have been hiring more police officers. We've partnered with security, private security companies and developed that ambassador program with where we have the health and human services support that ride along with our transit police. We've also highly publicized our Transit Watch app so that you can report anything on the system discreetly and have a response. We've also done, worked on our fare system so that it's more flexible and affordable for those who need it the most. We offer free transfers now between our modes, children ride free under 12. And we developed a flexible three-day pass and variations of that. One of the things that we noticed during the pandemic was that more and more people were using our SEPTA key, which is our contactless fare payment system. We are allowing mobile ticketing later this year. We're piling it right now. And then we've also developed a program called Key Advantage where our major employers can sign up and pay a very flat and base rate for all of their employees to have access to an anywhere pass on transit. So much like company pays for health insurance for all their employees or cost shares with their employees for that benefit. They can also do that now for transit. These are ways that in which we're trying to build back our ridership and make it more useful to more people. We also have a wayfinding branding program going on so that people feel more comfortable and have a better understanding of our system and where they're going when they're in a station. We found that people get nervous and fear and have more concerns over safety when it is unclear where they're going. So wayfinding and branding has been an important part of our strategic plan. We also understand that ridership has changed and we don't all commute from nine to five anymore, not every day. People use transit in the Philadelphia region for a variety of trips already. So we're looking at all of our service, whether it's regional rail or commuter rail and our bus network to make sure that we're providing service throughout the weekday, around the clock and on the weekends in a way that gets everybody to work and to their daily activities. Throughout the pandemic, of course, we had a lot of essential workers that were riding on our system and they do so at a variety of different times, whether it shifts that start at 6 a.m. or 1 p.m. We have a lot of service out there and we've been calling it flattening the peak but providing that service consistently throughout the day and starting as early and as late at night as we can. I'll just end with this slide. There's a lot of numbers on here but this is showing our operating budget and the black is the one-time subsidy that we've received from the federal government for our operating budget to make up for that fair revenue that we have lost during the pandemic. You can see the green bars at the bottom. Those are our fair revenue pre-COVID was about over $500 million a year and just this year or this fiscal year we expect to have about $316 million in fair revenue. We still have a gap and we're dependent on that that COVID relief from the federal government making up $416 million of our operating budget. By doing that, that allows us to run a lot of service so that we're providing those this essential service to the public. Unfortunately as we move forward and forecast out into the future, we don't see ridership coming back to pre-COVID levels anytime soon. We do expect it to increase but we will still have a budget gap and of course all the cleaning and the security that we've provided has increased the expenses in our operating budget. We want to continue to provide those services but again this puts us in a compromising situation with our budget highly dependent on fair revenue. I'll leave you with that and that's the perspective we've had for the last couple of years in Philadelphia riding through the pandemic. Thank you. Thank you very much for that Jodie that was great to see and to see that real perspective from an operator and the challenges that you face and are still facing there. Okay we're going to move now into a panel discussion and before we go into that detailed discussion I'd like to introduce our panelists as well as as Dr Grant Muller and Ms Holton who've already taught today. I want to introduce Madeline Parker who's a PhD candidate at the University of California Berkeley and Dr Jason McGraw who's a researcher at the Oak Ridge National Lab.  So Madeline should we go over to you first please. Thank you good afternoon and it's a pleasure to be here and to join these excellent presentations. I'm going to speak very briefly on research I conducted with a team at UC Berkeley on the impacts of COVID-19 on transit riders. So in this work we studied GPS travel data in combination with multiple waves of surveys of panelists across the United States from August 2020 to October 2022. And we found in our 2020 research that the travel patterns of transit riders as one would expect were much more significantly disrupted by the pandemic than the travel of non-riders. So through the end of 2020 transit riders reduced their travel by about 50% more than non-riders even when controlling for other factors and three quarters of transit riders reported taking transit less since the pandemic. This is likely due to a combination of being affected by transit service reductions concerns about infection risk on transit and trip reductions due to the pandemic. The combination of fears of virus transmission and transit service reductions affected over 90% of transit riders in our study. Less than 10% of riders reported that they were comfortable using transit despite infection risk and weren't affected by transit service reductions. So the top factors that riders described would increase their use of transit. This was back in the end of 2020 described as first widespread use of face masks followed by increased sanitation and cleaning and effective an effective COVID-19 treatment or vaccine reduction of COVID-19 rates in the area and reduced crowding. Riders also cited that they would take transit more with a return to regular service levels or schedule frequency. And comparing these results from 2020 to two years later in our very recent October 2022 survey, the percent of respondents who said that they were comfortable taking transit increased from around 10% to 20%. But a significant portion still described that reduced crowding, a widespread use of face masks and increased sanitation and cleaning would increase their use of transit. So we really found that riders are still very hesitant to use transit due to concerns about COVID-19 transmission and their travel patterns being impacted as a result of that. And I'll pass it over to Jason. Thank you, Marjorie. So for me to do Jason now. Thank you. Also glad to be here. Hopefully my internet connection will hold. They have come to bury the line again. So I've been dropping on and off. I was a member of the ASHRAE Task Force. I wanted to say a little bit about that. I was the lead of the transportation subgroup where we put together some transportation guidance. Looking through the attendance list, I saw at least one person from that group is gratifying to see him here. We had in a very short time put together guidance for multi modes of transport. And I think one of the things that we found that has been echoed in the takeaways from the previous workshops is variability in particularly in public transportation is very important and presents a very difficult problem. The concerns for one transportation authority and one part of our world can be very different than those from other parts of the world. And it can be, as was noted in the first presentation, the demographics play a role. There was variation within the modes themselves and there's the difference between the modes. One of the things that we did encounter in putting together our transportation guidance was that many people in the HVAC in our world wanted to treat transportation cabins as just little moving buildings. And that's just not very appropriate. And while there are things that are similar, there are more things that are different. And that can be difficult for us HVAC guys to get around because we tend to think very highly of ourselves. So one of the things that I hope that people take away from this session today is that even though there is a lot of variability, even though there are very difficult problems here, there are things that can be done to mitigate these impacts. Now, there are, we can't control everything obviously, but with proper guidance, I do believe that we should be better prepared for the next time. Hopefully not in my lifetime, but if that next time does come, I think we have learned things and there are paths forward. Thank you. I'll set my piece there. Okay, thank you very much for that, Jason. And thank you for the introductions from both yourself and Madeline there. So we've got quite a number of questions from the public, but I want to just start by a question that perhaps we haven't touched on yet in the presentations. Ventilation has been highlighted as a measure that's important, but we haven't touched on air cleaning. And I wonder whether any members of the panel heading we saw was on whether air cleaning strategies do have a place in public transport, and if so, whether they might be a short-term fix or a long-term solution. I don't know whether anybody would like to tackle that one at all. I know Jason, you mentioned HVAC, I wonder whether you come across that with ASHRAE. Yeah, so within the membership of ASHRAE, there were plenty of people that sent us recommendations, oh, we need to do air cleaning. You should do air cleaning. You need to use UV. You need to do these different things. I do think there is a place for air cleaning in the transportation sector, particularly public transportation, not just in the cabins, but also in the stations and things like that. But it has to be done carefully. And it shouldn't be done in an ad-hoc way. It has to be done deliberately and carefully with engaging with the appropriate expertise, particularly with cabins. You do not wish to be introducing things into that space that can be dangerous. It's not the same thing. If a rooftop unit catches on fire, that's very bad, but it's up on top of the building or their chances to do something different. If a similar thing happens with a bus that's in a tunnel, it's a whole different deal. So one of the things that we hit on hard with our guidance was, yes, do these things, consider these things, but always do it with the proper guidance. That's great. Thank you. I don't know whether you wanted to comment at all from the perspective of an operator here, whether they should come across your desk. Yeah, I think we did, I guess, experiment. Maybe it would be the right way to say it with UV cleaning. But then we pretty much have gone with just installing MERC 13 filters on, especially for our bus fleet. We found them a bit in the ventilation equipment and that seemed to be the best route for us to go. That's great. Thank you. So perhaps I'd direct the next question to Madeline and to Susan about what do you think might be some of the barriers to implementing best practice in public transport from some of the things you've come across, whether that's about individual behavior or whether it's about the sort of more structural things that can be done. I don't know whether. I can just speak very briefly on the behavior side, one factor that came up frequently in our research was just masking and the ways that that can both sort of increase perceptions of safety as well as I think it's Susan mentioned in her presentation, actual safety, but definitely our concerns in different locations in the US and parts of locations, just about enforcement of mask mandates and other sort of behavioral factors around those as well. Thanks for that. Susan, do you want to comment on anything around Barry? Yes, I'll just add to that, actually, because I was very, very interested by your remarks, Madeline, very similar to some of the findings we've had through alongside the monitoring work. We've done some focus groups to understand people's perceptions and we've collected perceptions over time as well and particularly during the pandemic, the heat of the pandemic in the UK, there was a lot of anger, let's say, and frustration amongst the travel in public that it wasn't possible to enforce mask wearing and there are all sorts of practical reasons why that actually was the case, but this created a kind of a split between the demographic between people who were very keen to have mask wearing enforced on their journeys and those who were actually very keen to be able to exercise their right not to not to wear one or what they perceive to be their right. And of course, in the middle of all this, maybe the service staff on the trains and the buses themselves who are in a very difficult position, they have to concern about their own safety, but how to deal with these competing views between people as they travel. That's great. Thank you, Susan. So I will jump into some of the questions that have come through to us on Slido now. So the first one I'd like to ask is you'll be focused very much on public transit here, but how do we think some of these results might be useful to say school buses? For example, school buses, children in rural areas might have quite long bus runs they might be children with disabilities, they're on those buses twice a day. Would anybody like to comment around that? I'd be happy to say that variability is going to play a very big role there. You have a lot of variation with those vehicles and is going to be thus therefore very difficult to make sort of general statements about there may still be some, but because of just the variability of those, the model's age, all those things, all their role and that's going to be very good. Do you want to comment as well, Susan? Yeah, I'll just maybe step in to say, I think that the longer journeys are a little bit of a concern that maybe the quality of the buses could or could not be the same. So maybe some of the engineering aspects are not quite that different, but what will be different is the behaviour of those students on the buses to compare with the general population. So there is more likely to be activity such as maybe shouting conversation, maybe people, young people getting up a little bit, moving around, turning around, speaking with people around them and all those activities actually can raise the risk. So I think that similar kinds of studies could focus directly on the school buses, but we would expect to get maybe some different types of risk coming out. Great, thank you. I think this next one's really for Jodie. I'm going to combine a couple of questions here, which is as a passenger, how can they find out what the ventilation standards are on a particular bus or train? And is there any sort of website where you show that vehicles have the higher changes? What sort of interventions have been put in place there? Yes, over the last couple of years, as we've installed different different filters, we've put together a toolkit for our employers because it was important for them when they brought back their employees to tell them that the public transport was safe or safer way to get to work. And so we have it on our website, iseptafilly, and then also just septa.org under the employer toolkit. You can see that just the two to three minute exchange rate, and then the MERV 13 filters. I don't think we break it down by vehicle, but that's a good suggestion. We can put that up there. I think related question about kinds of dashboards that are available, and perhaps as to what is already available, perhaps also to the panelists here about what could be available, I think. Well, I had mentioned the crowding dashboard. So the number of riders that you can typically expect on a certain route on a certain day or time of day, and that's available on our website as well, just septa.org. And it's on the left hand side of the webpage. We have our ridership by route and all that as a dashboard on our septa website as well. Perhaps I could ask this, perhaps either to Jason or to Susan here around. Susan, you highlighted dead zones for ventilation. Do we know if these might be mitigated by passenger movement? And how does that influence air circulation? And are we looking at this? You're on mute, Susan. Oh, dear, sorry about that. Yes, I think that the study that we looked at that was looked at within track, which was Hugh Woodward's work, the reference I gave at the end. I believe that he did look at the potential for people who were standing up and moving, creating some stir in terms of the air flow, etc. So I think that there is an opportunity to look at this in a little bit more detail, but those findings were very clear. Actually, that showed on that slide that there is definitely that dead zone, and that must be a little bit of a concern, particularly on the long distance journeys. And brother Jason, I don't know whether you might be able to think, does this anything, something that some of the astro work has looked at at all about the mixing of? Yeah, there are different expectations, different vehicles with how movement is going to play a role. I mean, obviously, we're talking about public transportation today, but obviously with airplanes, you don't move around very much with trains and buses, you may move around a little more. So there is, again, variability. We did find in some other unrelated research that movement would basically play a pretty big role in how much of a space you could fill with potentially infectious particles, though. So I would expect that movement would play a big role. Great, thank you. And perhaps I'd like to ask this one to Madeline about the equitability of it. So, you know, if we're trying to improve indoor air management and public transport, how can we do this in an equitable way? Thank you. I think that in order to really ensure that these improvements are equitable, it's important to consider the most crowded nodes. So for example, we know that bus ridership is closer to pre-pandemic levels than say commuter rail. And also to make sure that any improvements in filtration are making their way to all public transit modes, including ADA paratransit service for people with disabilities. And building on what Jody was describing earlier in terms of communication, just to make sure that there is broad communication to make sure that that passengers feel safe taking transit. And that sort of as spoken as a personal transit rider myself, I've seen a lot of variation in information about safety measures across different transit systems. That's great. I think the last question I'm going to ask here is I think around the use of different methods. So for example, there's still quite a bit of focus, it's even from the public, that surface cleaning is important. Yeah, a lot of the evidence is suggesting that that is of lower priority. And I'm wondering whether, how can this be balanced? And is there, do we think actually that surface cleaning might be something that could be reduced, particularly given around budgetary constraints? I'll just quickly comment, Kappa. I think it's a question of public confidence and people like to see a clean environment and that is attractive to the ridership. I think it's also the case that there can be some practical issues around cleaning, perhaps as much as people might want as some of the service operators might want to be able to clean. It is expensive and practically very difficult, particularly when there are some very quick turn rounds in terms of passengers getting on and getting off and vehicles being reused, etc. So I think it needs looking at a little bit more. That's great. And I don't know, the Joe, do you want to comment some of that? I think from our perspective, we're going to keep up the cleaning protocols that we have right now. But just because it does help people feel like the system is safe, it's a perception issue, I think, more than anything else. But I hope, you know, maybe a year from now, we can slow up on disinfecting every handrail we see twice a day. Yeah, I agree. I think I think, I mean, certainly a lot of the stuff we've looked at would suggest that hand hygiene, the risks off surfaces are quite low. But what little risk there is there, hand hygiene might be the better route than the surface cleaning. But at the same time, you're right, it's a public perception. So I'm going to say thank you to all of our speakers and panellists today for feeding into this. It's a very big topic and we have only just scratched the surface of it. It allows us to move very nicely into the next sessions. So thank you for the thoughtful presentations, the thoughtful responses to questions in here. I think for me, some of the take home from this is that public transport is a complex environment. It's an environment where, as I think Jason put it, they're not many buildings. And we need to think about that in the specifics of what happens in those environments, the fact that people are in much closer proximity perhaps than in other environments. And close proximity, things like ventilation are important, but they won't mitigate everything because of that, because of the close proximity there. I think one of the things that came out very clearly here is that public transport is a necessary environment for many people. And that's not necessarily equitably distributed. The people who probably have the most choice about how they travel are those who have the most resource. Those who often have no choice but to use public transportation are often those who have the least and are probably having to deal with other inequities in their lives as well and how they live. There is a massive aspect around public confidence and public perception. And we need to think about how the communications we do around transmission relate to that because it doesn't always necessarily tie up to what is the most important route of transmission, but at the same time public perception and confidence is very important in that. So for me, those were some of the take-home environments. It's a complex setting and every public transport mode is different and there will be different challenges in different places. So thank you again to everybody on our panel for giving your time and thoughts for this. And I'm going to hand over now to session two, which will be moderated by Dr. Lucas Rocha Melongo. All right, thank you, Kath. Hello, everyone. And thank you for joining us for the second session of today's workshop. I am Lucas and I'm a senior health scientist at ICF, where I work on environmental epidemiology consulting projects for federal agencies in the US. Eric, if you could show the speakers, please. Thank you. On the screen, you can see the names of the speakers we have lined up for the session. The goal of this second session is to highlight a set of case studies in different geographic locations where participants work directly with local communities during the pandemic. These participants will discuss their experience balancing the safety of riders and transport workers while navigating external expectations in post-policies and technologies with varying levels of proven efficacies. Our first case study is titled COVID-19 Research Driven by Public Transit and University Partnerships. This is a case study of a septa drug sale university collaboration in Philadelphia that will be presented by Dr. Christopher Sales, Professor of Civil and Environmental Engineering at Drexel University. To our audience, please visit the event's website to find all the speakers and panelists' bios. For our speakers, please remember that you have seven to 10 minutes for your presentations. A two-minute warning will be posted on the chat. Chris, please turn on your camera and mute and share your screen. The floor is yours. Thank you, Lucas. Let me share my screen. Get it into screen mode and switch screens. All right. Thank you for the introduction, Lucas. I really like the first session. So I'll talk today about our septa drug sale collaboration, our partnership in the city of Philadelphia. And I'll be using the Star Plus story format to tell you the situation, the tasks that we undertook, actions we did, and some of the results that we're getting in the future next steps for the collaboration. But before I start, I really wanted to acknowledge Jim Fox, who is formerly the Assistant General Manager of Systems Safety at SEPTA, who is very critical in this collaboration, this partnership between Drexel University and SEPTA in Philadelphia. So we heard from Jody, if you're in the first session, that in the spring of 2020, there is just a major shutdown across the world in cities and in public transits across the world face these shutdowns. Nobody was going to work. And a lot of these services, these public transit agencies, saw a ridership drop down into the teens. And even now, a few years later, since the start of the pandemic, we're still at some places only up to about 50 to 60% ridership. And so really, at this time, SEPTA was concerned about how could they get ridership back to get that revenue that's needed and build confidence that it's safe to ride public transit. They were, as described by Jody, they had some cleaning protocols. And a lot of it was visual to appease kind of the ridership, their perception of how clean riding on public transit was. So a lot of it was focused on surface cleaning, also enforcing masks, those mass mandates on transit vehicles, as well as that social distancing on board these public transit systems where really the purpose is actually to carry a lot of people so that that was often difficult. So the task that we undertook in spring of 2020 was actually spawned by a small business, a plasma. And they talked to some people at SEPTA and brought us on board, brought structural researchers on board to discuss with SEPTA their concerns about the effect of the pandemic on the public transit system in the Philadelphia region. And so a few weeks later, in May 27, 2020, we actually took a tour of their Frankfurt Transportation Center. We got to see their workers who are still working, even though it was pretty much the start of the pandemic, cleaning the buses and trying to maintain them for public use. And then eventually in the middle of the summer of 2020, we proposed a partnership between SEPTA and Drexel to bring together the expertise of researchers across the university from the College of Medicine, College of Engineering, School of Public Health, Nursing, even Criminology and the School of Business to try to help SEPTA out with what they're dealing with with the COVID-19 pandemic. And so part of this partnership in that memo, we really wanted to analyze customer perceptions that limited their use of public transit and determine what factors that reduce their reluctance to ride mass transit. We also wanted to examine potential exposure scenarios and risks, mainly related to airborne transmission, as well as contaminated surfaces using indoor air modeling, air quality modeling with a quantitative microbial risk assessment framework to determine what the most significant risks were or could be. And then we also wanted to validate indicators. So I think at that time, there was a lot of companies trying to sell disinfection technologies that could be effective at decontaminating buses and vehicles. But we wanted to assess whether those indicators that they were reporting in their flyers, kind of selling those technologies, if they're actually effective. So we wanted to provide agencies with methods to generate qualitative and quantitative data that they can use and share with the public to ensure that it's safe to ride mass transit. And lastly, we wanted to develop and test different disinfection technologies and risk mitigation strategies, whether they're masking or improved ventilation, and how it could be used to reduce COVID-19 transmission, not only for the public, but also for the employees of SEPTA or other public transit agencies. So the actions that we took after setting up that memo and the partnership was to bring together Drexel researchers, staff members from SEPTA or their vehicle engineers, their safety specialists, even their data informatics people that can get data on ridership, bring them together and to figure out ways we can address their issues dealing with the COVID-19 pandemic. Because of the university and SEPTA being a big agency, it did take a while for an MOU to get in place. But not too long after, there was a call by the Federal Transit Administration for us to actually, as researchers, work with SEPTA to apply for some COVID-19 funding from the Department of Transportation, specifically the Federal Transit Administration. And so I won't read this entire slide, but in November of 2020, the FCA put out a program, a funding opportunity announcement called Public Transportation COVID-19 Research Demonstration Grant Program. And when we looked at what they were looking at for these proposals, we really keyed in on vehicle facility equipment and infrastructure cleaning and disinfection, as well as exposure mitigation measures. So we actually put together a proposal, a team of researchers from Drexel as well as SEPTA submitted the proposal in November 2020. And we actually heard in January of 2021 that we received funding from DOT for this COVID-19 project. And there was 37 projects nationwide funded by this funding opportunity at that time. It took a while for us to get contracted, but we started doing research, literature research, and eventually we started making headway on the project. And the proposed project framework that we came up with is really built around simulations. So doing cabin-wide, well-mixed model simulations, so indoor air quality models of aerosols that might contain SARS-CoV-2, the virus causes COVID-19, as well as close-range computational fluid dynamic models or CFD model simulations. And then to feed into that, those simulations, we had to get information from SEPTA on vehicle routes, riderships, mask wearing, and social distancing compliance. So they actually have some videos and recorded information on what proportion of riders were wearing masks and such. And we also wanted to conduct laboratory testing of different air purification technologies that would be advertised and trying to be sold to mass transit agencies. And we also wanted to do some cabin testing to refine some of the ventilation rate calculations that we're putting into some of these models. And from that, we wanted to do a cost-benefit analysis to figure out which strategies were the best for public transit agencies to adapt to reduce COVID-19 transmission and eventually kind of make some reports and recommendations to the industry based on our project. So we didn't get funded to do the cost-benefit analysis, but we're still, you know, those are just common, just things that are going to come out of what we do automatically or just by default to some degree. We might be able to not do the kind of economic cost-benefit analysis that we wanted to, but we'll still at least come up with some hopefully good recommendations and guidance for the industry. So some results to date. We've been trying to derive COVID-19 risks on board accepted vehicles. And like I said, one of our approaches is using that well-mixed indoor air quality box model. So trying to figure out model sources, how things might be removed from these vehicles. And so these well-mixed models help determine volume average concentrations and estimate risks, average risks on vehicle journeys. And so the simulations can be scaled up and adapted to a wide variety of different vehicles and routes and also engineering controls, whether they have MIRV 8 filters, MIRV 13 filters, or maybe if there's no the HVAC system isn't on. And then we also wanted to, on these trips, these routes, try to assess the evolution of risk over time during those trips. So we're able to determine the infectious particle concentration based on a number of factors, including the occupancy and the percent infected based on community infection rates. And so this is really useful for statistical examination of the outcomes. And I really have to have a shout out for Brian and Cummings and Professor Wehring, as well as Professor Haas, who are leading these efforts on this well-mixed indoor air quality box models. Now some results from this first approach, these well-mixed models. We've been able to produce a lot of data from these stochastic models, these Monte Carlo models. So for instance, we're able to assess the impact of HVAC operation on the system. So I think I saw one of the questions on, you know, if you sit on buses or on subway cars, it doesn't always seem like the air is always on, even though they're designed to be on. And they have certain kind of engineering design criteria. And so we can actually assess what happens when the fan is off or really what the effectiveness is of going from MIRV 8 to MIRV 13 filters. And then we can also perform some sensitivity analyses to figure out what factors either strongly increase risk of COVID-19 transmission or lower the risk. And we're finding that it really relates to this hierarchy of controls. So for instance, you know, having the number of fraction of passengers that are mass strongly affects, lowers the risk of COVID-19 transmission. And we also see that there's engineering controls, things that maybe CEPTA or other public transit agencies can do to modify, for instance, the recirculation rate if they can, the types of filters, the HVAC filter efficiency, and also the ventilation rates can also strongly lower the risk. And we've even seen that if you actually have good N95 fitted masks on operators, they can significantly reduce 10 to 100 times the risk of COVID-19 transmission. We've also had another approach using CFD modeling simulations, and this is led by Professor James Lowe and his PhD student, Zainab, at Drexel University. And we're trying to track the distribution of aerosol particles inside vehicles. And we can run simulations based on ventilation rate, ventilation flow rate, the number of infectious emitters, and how they're grouped and distributed throughout the vehicle. So it's kind of hard to see in the figure, but we're seeing that if you're sitting in between possibly an infected rider, that between the infected rider and the intake, the return for the HVAC systems, sometimes those particles that might be parent that are infectious could run towards you if you're kind of sitting in between those two places. We also see dead zones, which I saw questions about as well. And then we're also looking at the relative risks in the breathing zone of each seated passenger and be able to get more of an individualized risk for passengers, not just the average risk that we're getting from the well-mixed model. So currently, we're halfway through this two-year FDA COVID project. And so we want to complete simulations on buses, trolleys, regional railcars, and subway cars that are part of the septic system. We also want to do in-vehicle validation testing of cabin ventilation rates. And then try to integrate those two approaches of determining and predicting risks that well-mixed model and the CFD simulations. And we're also planning to do some induct experiments to evaluate different airborne disinfect technologies like UV at different wavelengths, as well as bipolar ionization and plasma. And really, we want to ask, are they really needed? And which technologies, if they're going to be used, are they effective and safe to use for riders as well as operators and people that clean and maintain these vehicles? So beyond the research project that we have, we're hoping to take the research information, not just put it into academic literature, peer-reviewed literature, but actually effectively share that information from those scientific studies with the public to really go after the goal that we had at first, which is to regain the public's trust in using public transit and that is safe for them to use. We also want to develop guidelines and standards that are backed up by work that research, like we're doing, but also informed by industry. So make sure that technologies that may be used, mitigation strategies that might be used, really fit the industry and the type of vehicles they use and how they operate them. So for instance, guidelines and standards for ventilation, air filtration as well as disinfect technology requirements that might be used on transit vehicles. And lastly, we want to implore the government that we cannot wait until the next pandemic. So we can't go 10, 15 years like we did from SARS to COVID to fund research that addresses airborne pathogen transmission on mass transit. So that's my case study that I wanted to share from Philadelphia. And thank you. Thank you very much, Grace, for sharing about your experience collaborating with SEPTA. A friendly reminder to the rest of our speakers, please keep your presentations to seven to 10 minutes so everyone has a chance to present their case. Our next case study is titled Preventing Outbreaks on Ground Transportation, and it will be presented by Dr. Yu Guo Li, Professor in the Department of Mechanical Engineering at the University of Hong Kong. Yu Guo, please turn on your camera and mute and share your screen. The floor is yours. Thank you. Lucas, can you hear me? Yes, we can. Thank you. Thank you. Thank you for inviting me and its pleasure to share some of my preliminary thoughts and work with the case study. So many of us probably have now subscribed to the idea that inhalation transmission predominates the spread of SARS-CoV-2, and transmission by surface touch is most likely insignificant. So very close range inhalation presents the highest transmission risk, and in public transport there are opportunities for close contact at boarding and alighting, and of course between neighboring seas during trouble. Some of us talk about the continuum of short and long-range inhalation. A good room dilution reduced short-range inhalation beyond 40 centimeters, and by reducing the virus concentration in the entrained air, and the entrained air amount at this distance is much greater than the exhaled flow rate. However, the dilution does not affect very close range, say within the first 40 centimeters. Wearing masks in public transport can block the direct expiry jet of the source patients. However, the expiry jet needs to be released from the mask cavity anyhow, so the secondary side mask jet may affect our neighboring passengers. So ventilation is not alone in dilution, as we talked about, and setting the activation and filtration all and remove infectious particles. They provide effective dilution air, or clean air, or non-infectious air. Is there some combined effects that matter? So what determines the minimum effective dilution air flow rates? At low risk, the classical steady-well-serial equation can be linearized. It's a simple product of counter-relation rate, the ratio of inhalation rate to the effective dilution rate and exposure time. So we are interested in what conditions the number of secondary infections is less than one. The greater the quantum generation, the greater the required dilution. Here is perhaps our educated guess. If the typical infectious quantum release rate is 100 quanta per hour for the ancestral SARS-CoV-2 virus, then we would require 10 liter per second per person dilution for passengers at rest. Obviously, if everybody wears a mask at 50% filtration, the only 2.5 liter per second per person is needed. So for Omicrons, the transmissivity is much higher, probably say the four times greater, then we require 40 liter per second per person dilution. Obviously, if everybody wears a mask at 50% filtration and for efficiency, then we need 10 liter per second per person. So if the travel time is less than, say, one hour, then requirement could be less. Of course, you and I cannot forget about drivers, who is there all the time. So most buildings have an effective dilution rate at 2 to 3 liter per second per person, I guess, so that the mask wearing works in the first two years, but not for Omicron. Such a minimum requirement to me in effective dilution is not a function of settings or room types, apart from the exposure time, but the quantum emission rate, activity, and exposure time. In the two Hunan bus outbreaks we studied earlier, the effective dilution rate was estimated to be 2.1 on bus 1 and 3.7 on bus 2. So the outbreak occurred very early in the pandemic. Most passengers did not wear a mask, including the same in-depth case in two outbreaks. Plus, rides were only 30 minutes apart, with a higher effective dilution bus 2 had a lower attack rate. So on buses, as the air volume is small with crowdedness, the clean air contributed from settling and the natural deactivation is fairly small. Interestingly, studies of in-flight outbreaks may offer some guides to buses, subways, and some other ground transportation, although we spoke earlier. People probably pay more attention to in-flight outbreaks for various reasons, and of course the data is useful because the seating is more or less fixed. To me there is another reason, the cabin environment system maintenance may be more regular and systematic for air transportation than ground transportation. Amazingly, to me there have not been many reported in-flight outbreaks during the first one and a half years of the pandemic. In-flight outbreaks were reported for a flight duration of one hour or less, at least in the literature. Attack rates in those reported in-flight outbreaks were also much less than other outbreaks. So if you estimate the effective dilution rate, that's about 10 liters per second per person for narrow-body cabins and 12 for the wide-body cabins, so it's interesting. There have been many monitoring studies of CO2 levels in public transport since 1990s. Many have reported concentration larger than 3,000 ppm at full occupancy. In Korean, there's the site of here study led by Professor Jack Spankler at Harvard in 2008. Transport of course is a major greenhouse gas emitter, so some government only require a very low ventilation rate about 3 liters per segment per person, much lower than many other indoor environments such as offices. This appears to be a bit low for infection control. Using filtration and GUV may be useful and for Omicron, the numbers tell us if we have 10 liters per segment per person dilution air and I've heard earlier 30-hour change per hour and the transmission should be minimum if everyone wear a mask. And this required dilution rate also applies to other indoor environment and not just for public transport. Anyway, you have seen my recommended simple measures to in a simple way for long range providers about 10 liters per segment per person dilution, but for Omicron, we need wear masks and we can also optimize boarding and lighting dynamics to minimize crucial-range contacts. Thank you very much. Thank you very much, Hugo, for sharing with us your research on preventing outbreaks on ground transportation. Our next case study is titled New York City Transit Workers and Essential Workforce and it will be presented by Dr. Robin Gershen, clinical professor of epidemiology at New York University. Robin, please turn on your camera and mute and share your screen. The floor is yours. Thank you so much. I'm just looking for my slides and I think I found them. Yes. Thank you. Thank you so much, all of you. It's clearly an honor to be in this incredible group and I must say, being here with you is, it warms my heart because these are things we've been thinking, the warring and just aggravating ourselves over for at least two and a half years now and to hear from Stefter, to hear from my other colleagues, it's just fabulous. So thank you so much, all of you. Now in the very, very brief time that I have, I want to tell you very quickly about some work that we've been doing and first just to acknowledge my wonderful colleagues, including our graduate students and then a little bit about the facts. So some backstory here. Of course, I think you all realize that the MTA is the largest public transportation network, not only in the US, but in all of North America, a very large workforce of over 40,000. It has a huge operating budget close to 19 billion and the ridership pre-pandemic was very high over nearly eight million people a day on the transit on the subway and about two million on buses. Now for both buses and subways, we're down to about 60%. The numbers are increasing. Importantly, we have a huge number of vehicles to worry about. 6,000 buses and over 7,000 subway cars. So in the very early part of the pandemic in the first wave of March 15th to June 30th, and especially during our pause, which was March 22nd to June 13th, when everything, all non-essential workplaces, all non-essential workers, everything was closed. Schools, work, everything. The subway, however, and the buses stayed operational. This was a bit of a problem because on March 6th, unfortunately an MTA, an MTA as I think you realize is Metropolitan Transportation Authority. It's a quasi-governmental partnership for the public good that runs the transit system in New York City. The MTA put out this memo saying they were forbidding all their transit workers from wearing face masks, even the ones they can make themselves. Now on March 6th, I can tell you because I was here, there was not a mask to be had in all of New York City. Alcohol, wipes, Kleenex, paper towels, Clorox, any kind of disinfection or certainly any kind of mask was absolutely not available. So it was kind of a mood issue to be honest. And of course at that time, even CDC was saying no masks were needed, the WHO was saying no masks, even Dr. Fauci was saying no masks. Unfortunately though, this combined with the incredible and rapid spread of COVID in New York City led to a very high rate of infection. It led to home isolation of nearly a quarter of the workforce, either home isolation or home quarantine, very high rates of hospitalization in this workforce. And unfortunately, a fairly sizable number of fatalities, the exact number of which is not clear, but it's somewhere between I estimate 75 and 150. We will get to the bottom of the actual number at some point. Now at the same time all this was happening, the MTA workers were mourning the loss of their families and friends because neighborhoods where they tend to live in the zip codes, they tend to live experience very, very high rates of infection and fatalities. Now by March 20th, fortunately, face masks were now allowed. They did get their hands on some face masks. I'm not exactly sure how. I believe there was some that were cashed and they were able to use those. Still, CDC did not recognize aerosol transmission. The masks that were given out were not for the most part N95s. They was simple, just medical masks. CDC did not recognize aerosols till May, as I said, of 2021, WHO none until the end of that year of 2021. Now, some early interventions that the MTA implemented and to be absolutely there, this moving target of a rapidly evolving pandemic that was just simply horrific during the early phase. Those of us who lived in the city will never forget the sound of ambulances because we were losing up to 700 people a day and night and day ambulances were constant, a constant refrain. So it was a very difficult and trying time for everyone concerned. But by April 17th, face masks were now required of all the riders and the workers. As soon as that happened, the transit worker harassment, physical and verbal abuse began and assaults, actual assaults because a lot of riders did not want to wear the mask. Excuse me. Now, at that point in May of 2020, there was nighttime cleaning that began. A lot of our other speakers talked about the cleaning, deep disinfection and cleaning UBC. Look, we looked into this quite a bit. And from our perspective, this provided the illusion of safety. And that's not a small thing. That's an important thing to get ridership to feel confident of coming back. But as we well know now, that absolutely is not necessary. Sterilizing the floors and the subways is not needed. Around that time, because I had wonderful relationships with the TW Local 100, that's the union for the MTA for the most part, from early annoy studies and other work I've done on subway, I was able to contact them. We met quickly by Zoom. And we quickly developed a survey, a pilot study on what is going on with their workers. How are they doing? How are they faring? That survey went out and it was a convenient sample. We had over about 650 responses in just a couple of weeks. It was a web-based survey. And the sample looked very much like their workforce as a whole, which is predominantly male, minority, middle-aged, many of them with chronic diseases. One or more was over almost 40% had one or more cardiac diabetes, asthma, things of that nature. And when we did our survey at the point of August 2020, a large proportion stated that they had been infected using some very simple metrics, had been hospitalized, had a physician told you and so forth. So it was a very high proportion. Now, the MTA pushed back on that number. They felt their numbers were closer to 15, maybe 17%, but our numbers mirror much closer to the Department of Health numbers for other frontline essential workers who kept on showing up through the COVID early phases. At the same time, August 2020 in our survey, about 90% of the sample said they were afraid of getting infected at work, but a lot of them, of course, fearful of long-term health impacts, but a lot of them over 70% were fearful for their personal safety and security at work. Many of them knew people who had died or had been infected, but still even then in August 2020, this is pre-vaccine, vaccine was still coming. Only 30% said they would take the vaccine. Now, at this time in August of 2020, many of them, 80% reported mental health problems. And so their major problem with mental health had to do with fear for their personal safety, physical safety at work. Several workplace interventions were rolled out by the MTA, including on-site vaccine clinics, all kinds of sampling clinics, bonus wages. They were even saying, okay, vaccine will not be mandated because they were afraid of losing too many workers. At this time, also, people who could retire started to retire. These are not jobs that can be just in time training. These are very experienced kinds of transport workers. And so losing these very kindly experienced people was problematic to say the least. Also, MTA did the plexiglass shields and buses, lots of PPE, lots of safety supplies, disinfection, all sorts of things. And so far, it looks like 77% of MTA workers have now been vaccinated compared to about 90% of all of New York City folks. Also, at the time, another intervention both that they did and the TWU is a focus on the bereavement and the loss to respected and to acknowledge that loss. So, murals were made, things went up at the website, at the headquarters, including maps of all the people, the stations where they were, where they lived, and their names and what division they worked in. So, I think a lot of attention to that, and that was good. The current challenges right now are rider and worker safety. These are issues top and center for every single person riding now. It's always look behind your back, watch to make sure no one's about to push you onto the track. Some of these horrific incidents of completely random events, just horrible, including, of course, the mass shooting, which did not do much. Nevertheless, even though the perception is that it's terribly dangerous out there, we're approaching pre-pandemic levels, which are much lower than, say, the 1980s, even the 1990s. So, we're actually pretty low. We had about 1,400 violent incidents, including some fatalities, of course, since the beginning of 2022, that's way lower than earlier decades. Now, so, based on this pilot data, we applied similar to my colleague just before me, we applied for funding that came out of NIH. Our studies, public health focused, as I told you, we're looking at interventions to assess the health and well-being of our workforce. We are focused on the workforce. The ridership is important, but we're focused on the worker. And basically, we are about to roll out a fairly robust study we've just been funded. It's a five-year project. Basically, we're very focused on preparedness for a pandemic. The 2012 H191 pandemic plan they had, which is what they had to fall back on, has a lot of gaps in it. And we hope to develop a best practices plan that will be applicable to all transit, as well as other essential work groups that are non-healthcare. We feel there were a lot of things that could have been done, that should have been done. But look, it was a very fast-paced pandemic, and they had to do things on the fly. We feel it's essential that we help this non-healthcare essential workforce, because otherwise we are creating inequities, exacerbating inequities, occupational health disparities, because even though they had tremendous risk, no doubt, they were not afforded the same protections, either infection control, either training, supervision, equipment, and supplies, or what have you. So that's where we're headed now. And that's the best I could go, Lucas. Thank you very much, Robin. It was great hearing about your experience working with New York City's Transit workers. Our next case study is titled Washington Metropolitan Area Transit Authorities Response to COVID-19, and it will be presented by Keith Conroy, Manager of Strategy and Policy at the Washington Metropolitan Area Transit Authority. Please turn on your camera and mute and share your screen. The floor is yours. Thanks, Lucas. Hi, everyone. As Lucas said, my name is Keith Conroy. I'm a Manager of Strategy and Policy at the Washington Metropolitan Area Transit Authority, which is also known as Metro. We serve riders in Washington, D.C., Maryland, and Virginia. Before I get started, I just want to make sure I thank the National Academies, everyone who helped organize the event, the other presenters who've already talked about a lot of great stuff, so I'll try to not repeat them too much. And all the attendees who came as well for supporting, I think, a really interesting and really important discussion. Next slide, please. Metro is one of the busiest transit agencies in the United States, supporting millions of passenger trips each year. And we maintain a vehicle fleet of approximately 1,600 buses, as well as approximately 1,300 rail cars. We have over 11,000 bus stops and nearly 100 rail stations, which help riders throughout the region get where they need to go. All that's to say, Metro is a busy system. And like all of our peers in the transit industry, we really need to respond quickly and effectively to the COVID-19 pandemic, which began really in earnest in March 2020. Next slide. Thanks. So yeah, so two and a half years ago when the pandemic began, ridership was drastically impacted as the region adapted to evolving health and safety guidelines. Remote work arrangements also shifted the nature of ridership patterns and behavior. Initially in the first few weeks of the pandemic, the general approach to COVID-19 mitigation was surface cleaning. So spraying or wiping down surfaces, frequent hand washing, et cetera. And Dr. Gertron touched on this a little bit, but another angle I had here was, if you recall, the Surgeon of the United States in March 2020 even tweeted, seriously, people stopped buying masks. Obviously there was an angle there on making sure medical professionals could get them, but I think it just kind of shows how much our understanding has shifted over time. And as time went on, sorry, still last slide, as time went on and better research became available, it became clear that coronavirus was largely transmitted through the air. And as this information became available, we at Metro worked really quickly to adjust our approach. We handed out millions of masks, we required them on buses and trains and in the stations. We supported efforts to reduce crowding and we did everything we could to improve air filtration wherever we could. I also, yeah, I thought it was really notable that the riding public really began to focus on air quality as well and crowding. And so we made sure to communicate details about the air quality in our system. As you can see in the poster on the left there and the kind of teal, that was information we were sharing with our riders and it meant something to them and they found it valuable. It improved our transparency and empowered our riders to make more informed decisions. Next slide, please. And so our focus on air quality really only increased over time as more research became available. Metro adjusted its approach as a result. We applied for and received a grant from the Federal Pandit Administration to study the efficacy of several technologies and improving air quality in railcars. I'll stop here real quick to just say air changes per hour, which is one of the measures we looked at, is defined as the number of times that the total air volume in a room or space is completely removed and replaced in an hour. It's one of several key variables driving the overall quality of air in the space. And the general rule of thumb I've heard, people may have heard slightly different things, but in like a classroom environment, you want at least five air changes per hour to help prevent the transmission of COVID-19. Metro's railcars before the pandemic were already doing 15 to 20 air changes per hour. So I think that baseline was really important for us to keep in mind and we made sure to communicate that to our riders who were paying for attention. And that really helped. Next slide, please. So this slide highlights the design of Metro's railcar HVAC systems, and it summarizes the approach we took to our FTA Supportive Research Program. Each railcar has two roof-mounted HVAC systems, which operate sort of diagonally across the top of the vehicle, as you can see in that second image where that line bisects the car. Early in the pandemic, a lot of transit agencies shared success in installing higher-grade air filters or ultraviolet light equipment in their vehicles. What was unique about our proposal at the time was our plan to evaluate these in a lone and in tandem to see where we could gain the most improvement. It also represented a promising opportunity to generate additional data and research in a somewhat unique environment, which is a railcar. The use of both of these technologies was really well-rooted in existing research findings, and in deciding on this approach, I do want to mention that we did need to be very intentional about what we said no to. We received a lot of proposals for technologies that range anywhere from promising but unproven, all the way to essentially snake oil, and so we made sure to evaluate proposed technologies really critically, and this was an important factor in our work to keep riders and employees safe. We consulted with guidance from trusted organizations like the American Society of Heating, Refrigerating, and Air Conditioning Engineers, which is also called ASHRAE. I did not know they would be on the call, so I'm glad that that happened, as well as the CDC and the EPA. Someone from the EPA is also on the call, so I'm glad she joined as well. Next slide, please. As I mentioned, the research design of our evaluation was to test these technologies in isolation and in tandem. The x-axis here is the number of air changes performed by a system, and the y-axis is the share of uncaptured COVID-19 particles under several conditions. The goal of this chart is to illustrate the efficacy of our control group, which is our existing railcars with the MIRV-9 filter, which is that red line, as well as two of our three experimental blue typically the Korean blue lines. Given the similar theoretical efficacy of MIRV-13 filters when compared to the theoretical efficacy of ultraviolet seed light and capturing and utilizing a viral particle like COVID-19, if we did include ultraviolet light on its own in this chart, it would be right there under that green line. As you can see, just getting one of these mitigations in place, so going from red to green, is a huge improvement from the baseline. While there are gains to be made from additional improvements, so going from the green line to the blue line, they're marginal, so something like one air change instead of two air changes to get close to nearly full removal. I want to also note that our research findings have generally borne out these theoretical figures, but due to the drafting and publication schedule of our research with a third party, I'm not yet able to share the exact numbers. I will note that in the field study, we struggled to verify the efficacy of ultraviolet light because by the time particles had gone through the filters that we had in the HVAC system, there was just such a small universe of remaining particles for the ultraviolet light to essentially get a chance to deactivate, so the data there might be a little bit puzzling. Next slide, please. Sometimes a picture really is worth a thousand data points, which this slide really illustrates for me. We released a set amount of vapor particles in a rail car and reported how quickly those particles would be removed under different filtering conditions, so this is just like a visual sense of what we know about these filters already. As you can see, the MERV9 filter took about nine minutes all the way at the top there to get to the level of visibility that the MERV13 filter accomplished before, so if you think about those smoke particles like COVID-19 particles and you think about which rail car you'd rather get in, I think you'd rather get in the one with MERV13. The use of this sort of improvement to keep our riders and employees safe, and even outside of the COVID-19 pandemic, we have a really strong interest in reducing transmission of illnesses like seasonal cold and flu, and rolling these improvements out fleet-wide, which we plan to do, will also put us in a better position for the future pandemic. Next slide, please. And to summarize our lessons learned here, the three key tactics I would highlight. First, really focus on improving technology and pest efficacy in real-world relevant circumstances. Talk to your peers and trusted sources and really be ready to adjust to new information. Second, establish confidence in your baseline circumstances. This has been touched on a little bit by some other speakers, but for us it was air change per hour. Knowing that that was good, it helped us prioritize improvements in the right sequence, which made improving filters a higher priority. Third, really trusting and power operation staff. Theoretical concepts are only as valuable as the real-life implementation, and if you and your colleagues are not on the same page, then ideas may not even make it to effective implementation. Our ongoing efforts and next steps include finalizing our research report, further implementation of the improvements we talked about, finding what's effective, and then implementing that fleet-wide. And finally, and I'll share my email in the chat as well, knowledge sharing is really important, both in the trends that you can see industry and outside of it. So I will put my email in the chat. It is cconwayatwomata.com, that's cconwayatwomata.com. Please email me if you're interested in learning more about our findings once we have them, and if you have any questions. Thank you all and stay safe. Thank you very much, Keith, for providing that big picture of Metro's response to the COVID-19 pandemic. Our next and final case study will be about COVID-19 research on London's transport network, and it will be presented by Lena Siric and Liora Malke-Efstein from the University of College London. Lena and Liora, please turn on your cameras and mute and share your screen. Okay, thank you very much. I am going first, and I'm going to tell you a little bit about the context of the project and some of the microbiological surveys that we did on the London Underground network, and Liora is going to tell you a little bit more about the predecessor of that work. So I'll start a little bit with the context. At the beginning of the pandemic in London, so this would have been March time, there was a significant amount of fear amongst the bus driving, the bus drivers on the various services in London, because quite a large number of the or a disproportionately large number of bus drivers lost their lives at the beginning of the pandemic. So this headline here that I'm showing you coronavirus five London bus drivers, bus workers die, union informs, confirms even. This was published on the 4th of April 2020. At this point, we had approximately, well about 64 per million confirmed cases of COVID-19 and about 13 per million confirmed deaths as a result of COVID-19. And at this point on the 4th of April, the national lockdown had been in place for about 10 days. So there was a lot of unrest and worry understandably. And TFL approached one of our colleagues for help on what could be done so that they could protect their drivers better. So Liora is going to tell you about the work that we did there, but before she does that, I'm going to tell you a little bit about the project that led out of this initial bit of work. So while we were working with TF transport for London, which is the main sort of transport operator and overseer of other transport operators in London, we were also interested in the safety of the passengers. So initially we were looking at the drivers, but we were also interested in the passengers. And at this point UKRI, which I believe is the sort of equivalent of the NSF for you in the US, had announced a call for COVID-19 studies. And we applied for this and we were successful. So in this case, we wanted to look at the transmission of how we could reduce the risk of virus transmission on London's public transport vehicles. And this project had a number of different components to it. It had air quality analysis, which is something that Liora has been working on, the microbiological surveys on the same vehicles as well. It's also included some airflow simulations and then looking at passenger crowding and behavior using CCTV. So I'm going to tell you over the next couple of minutes about the microbiological surveys that we carried out. I wanted to give you just a little bit of background on transport for London. They are a large, large operator. They cover London Underground, which is all of the tube network. They also outsource to about 20 different bus operators to cover the bus network. And there's also an overland network and a network of tram. So it's a huge complex organization. Pre-pandemic, they were fulfilling something like four million journeys per day on the tube and six million journeys on buses. At the height of that first lockdown, these numbers went down to as low as a few thousand bus journeys and in the low hundreds of thousands for the tube. Now we're back up to about 2.7 million tube journeys and about 5.3 million bus journeys. So the use has not recovered since the two pre-pandemic numbers at all. So throughout the project, we worked very closely with Transport for London. It was really important that we talk to them about how to sample and where to sample and when to sample. So what we were doing here was taking environmental samples from tube carriages or underground train carriages, both from the surfaces and from the air. So with them, we identified how we would do this and where and when. We identified some locations that we would sample and piloted some of our methods. And then we collected surface and air samples from eight live train carriages on each of three different lines. So 24 different trains were sampled or train carriages were sampled. We then analyzed these for bacterial colony forming units, which gave us a sort of general quantifiable unit of cleanliness. And we also looked for SARS-CoV-2 RNA copies in each of the samples, and we quantified these. We standardized them so that we were either looking at number of copies or colony forming units per 100 centimetres squared for area for surfaces or number of colony forming units or SARS-CoV-2 RNA copies per metre cubed of air. We then correlated these with observed passenger numbers. So I mentioned that the study also involved looking at CCTV footage. So we looked at any correlations with passenger numbers, observed passenger numbers, observed surface touches, overall proportion of the London underground network use, and the numbers of new conformed COVID-19 cases in London at the time of sampling. So I'm just going to tell you a little bit about this graph on the left. It's pretty common. Well, it is, and it is complicated. So in red, you can see the numbers of new cases of COVID-19 in London confirmed by lateral flow tests and PCR tests. And you can see these sort of dipping, then a little bit of a peak here, and then this is as the Omicron variant really started to surge towards the end of last year in December 2021. We also have the London underground network use in blue. So these are the numbers of journeys people were taking. So the sampling that we carried out happened on the district line, which is one of the three lines that we sampled. This was in May. We then sampled the Jubilee line in November and the Victoria line in December. So the Victoria line was the only one where the Omicron variant had started taking off and cases were really surging. So looking at the bacterial contamination, this was pretty consistent across all of our lines. So I think it was a mixture of environmental microorganisms and anything that had come off humans. Looking at the SARS-CoV-2 RNA copy contamination, we found that these were higher when cases in the community were higher, as one might expect. The sort of numbers that we were seeing were up to 10 to the 7 copies. So that's in the tens of millions per 100 centimetres squared on surfaces. And we were seeing up to 10 to the 5, so in the hundreds of thousands copies per metre cubed of air. And my last slide. So one of the main things that we did see was that there was a correlation between SARS-CoV-2 RNA copy surface contamination and the number of observed touches. We also saw that SARS-CoV-2 RNA air contamination correlated with the number of passengers using the London underground network. One interesting thing that we did see was that I'll just show you this graph again. So we carried out a load of sampling here in November 21. And then again in December 21, the difference between these two times of sampling, however, was that there was a no mandate for the wearing of face coverings on the TFL network during this first set of samples, but there was during the second set of samples. And indeed what we found was that when people were wearing face coverings, although I don't have a number for you for percentage compliance or anything like that, we were finding that even though there was a higher rate of cases in the community, we were finding much lower numbers of SARS-CoV-2 RNA copies in the air and on surfaces, whereas when cases were lower but people weren't wearing masks, the numbers that we were finding were quite a lot higher, sometimes a thousand times higher than when people were wearing masks. So I think that is all I have to say. Thank you again for inviting us. I was so excited at the beginning to start talking that I forgot to say thank you. So it's really a delight to be here and to hear your stories and compare and contrast how different and similar things are across the Atlantic. I will mute myself and I will stop sharing. Over to you, Lila. Thank you, Lena. Can you see my screen being shared now? Yes, putting this into slideshow mode. So thanks, Lena. Lena already introduced the challenge that we had. I just wanted to talk a bit more about those very early days and I really feel for everything that Robin has said, because New York City and London are very similar cities and we had exactly the same problems in London, including huge issues with safety of key workers and bus drivers around the network. So when Transport for London contacted us, we were observing with alarm the huge rate at which the pandemic was actually progressing around the world, comparing it with the earlier pandemic of SARS, which also progressed quite quickly and was recognized as airborne. And we're really influenced by all the advocacy and work, public work that Olivia Muravska did on making the world recognize that COVID was airborne. I have to admit we were convinced perhaps before the CDC and the WHO, because of the case of the London bus drivers that we were asked to review, because we could not really find any other mechanism that could explain why their deaths were so high compared to the rest of the community. The news stories you see here are from May. There was a very rapid health review to understand whether their death rates were really disproportionately high. That was also done by another team at University College London and they have found that they had a twofold excess mortality in that time, and especially between March and May of 2020. And London, I think, entered the lockdown of the 18th of March or in the 20th. So with all of that suspicion, we knew that bus drivers needed extra protection because of their often belonging to more vulnerable populations. We knew that buses are absolutely packed in London, so at rush hour, a double-decker bus could easily have 90 or 100 passengers on it, which actually means very little ventilation because of simply having less air available. We knew that infection rates in the community were rampant, as Lana showed before. And we just, based on the precautionary principle of public health, we said if COVID is airborne, then a hierarchy of interventions are needed and used, the team members, I have to acknowledge all of them on the slide, use CFD simulations to start with on our UCL proprietary code, and then supplemented those with experiments on our own double-decker bus later. So we've seen a lot of these CFD studies during the pandemic. What I wanted to show you here is that bus drivers in London actually have assault screens. Those are there to protect them against physical attacks that are unfortunately necessary. Before the pandemic, these were never really considered needed for protection against airborne hazards. And the implications here were that these assault screens needed to be modified. So transport for London initially were worried about droplets, sprays of droplets by coughing passengers, maybe going through some of the holes around the screen. We said actually that what was needed was to simulate the exhaled breath, which had unknown quantities of virus in it, and see how that actually could enter the cabin of the driver. So it looked at nine different case studies. And as you know with the CFD, you get concentration maps and you get airflow maps. And these had to be run on the UK Met Office supercomputer, which is the largest in Europe as an urgency measure. And of course, there's a limit to how many of these simulations you can run. And what is the actual question that would be helpful to ask? So we started looking at this as an air quality question, trying to find one single parameter that actually made sense and look at what the impact of different operational scenarios meant for that one parameter. So looking at things like should the passenger board from the middle door of the bus so that they're away from the bus driver? Should they stand at a distance? Does that make any difference? What about operational scenarios of doors and windows? And what we found is and also looking at modifications of screen design to different degrees of modification. And you can see the table on the left that describes all of this. So from this we created a very, again this was a very rapid project, created a decision support tool for all the different interventions, which is simply a table of the results of the simulations based on just one single parameter, which is exposure of the bus driver to exhaled breath from the passenger. Looking at an exposure per minute, so the fraction of exhaled breath that the driver is exposed to compared to the reference case one, which is before the pandemic and before any modifications at all. And basically try to group those under what is the best intervention. So the modification of assault screens by far was the best intervention. It also didn't require any behavioral modifications and we already knew by then there was opposition to face masks across the board. They weren't available. They weren't recommended by public health England for key workers. And the public were not willing to wear them initially. We also recommended that bus drivers operate the doors that both of them are open at every stop, which is every 90 seconds in London, that they open their own windows, but there were many concerns about safety in relation to opening windows as well. And therefore modifying the assault screen was by far the most effective intervention. So transport for London already started implementing these solutions by May 2020. The buses returned to front door boarding. They opened the bus stops at every stop. They started retrofitting all the screens on 9000 London buses and recommending the opening the windows. And by November 2020, and that's really where we would end this talk, is that they fitted all the buses that needed to be fitted with additional separate ventilation systems for the bus driver that avoids recirculation between the passenger cabin and the drivers themselves, checked all the ventilation systems, maintained them, and started really intense messaging for all stickers on all windows on buses to passengers, please open the windows, asking bus drivers to open their own windows, and eventually face coverings became mandatory on the entire transport for London network, which we felt was a very welcome intervention. So sorry for all of us overrunning. Thank you for listening. Thank you very much both Lina and Liora for sharing about your research and its impact in London's public transport network. And thank you to our previous speakers for sharing with us these case studies that serve as examples for concrete implementation in ground public transportation systems. Some key takeaways from these case studies are that first, risk assessment, computationally dynamics modeling and practical microbiology techniques are available tools that can help us understand the impact of different interventions in public transportation vehicles. Second, the understanding of aerosol physics is key to develop robust engineering interventions and optimize behavioral dynamics to minimize close range contacts to prevent outbreaks. And third, multi-level interventions focused on proven technologies are necessary to reduce risks and enhance workers' resilience, actively involving them in the decision making process. In this light, we will continue the workshop with session three, focusing on implementing the lessons learned and identifying gaps at different levels. Dr. Robin Gershwin from the NYU School of Public Health, we just heard from, will be moderating session three now. Hello, thank you. Thank you, Lucas. And welcome back. If you've taken a quick break to have a bite to eat, I hope you had a chance to do that. Welcome to the session three, implementation, knowledge and research to action. Now, we have a great lineup of speakers and in the interest of making sure we do not run out of time for them, I'm going to make this intro very, very short. Basically, what we're going to be doing here is taking a look at the barriers to adoption of some of the practices, the best practices for reducing risk. We would like to find out from our wonderful panelists here, if they have any practical suggestions or solutions for us to actually implement other than the issue about money. We've heard a lot already about problems with having enough funding to do what we may think is best practices. I'm not sure we're all in consensus on best practices at this point, but why don't we get started right away by letting me introduce Catherine Ratcliffe. She is, if you could please, Catherine. Oh, thank you so much. Thank you for joining us. Catherine, and by the way, all of the speakers, bios and the slides from today, everything is going to be up on your website. So that'll be very helpful to us. Basically, Catherine, if you could start us off by maybe just telling us a little bit about your job at the US EPA and discussing some of your ideas for strategies for implementation. Great. Thanks so much and thanks for the invitation to be here today. I am a physical scientist within the EPA's Office of Research and Development. I work primarily under the Homeland Security Research Program there. And I first want to start out by mentioning that EPA has played several different roles throughout the COVID-19 pandemic. From a regulatory standpoint, EPA is tasked with pesticide registration under the Federal Insecticide, Fungicide, and Regendicide Act, or FIFRA, as well as for developing different test methods and enforcing pesticide products and devices and cut their compliance to FIFRA. From a response standpoint, we've been working closely with other agencies and stakeholders to develop different forms of guidance for things like cleaning and disinfection. And where I sit within the Office of Research and Development, we have been instrumental in supporting both the response and regulatory missions of EPA by providing our technical expertise as researchers and then conducting research on a variety of different topics throughout the pandemic. So again, throughout the pandemic, we've been working very closely with different partners inside and outside of EPA, including our pesticide programs and our Office of Air and Radiation within EPA, as well as CDC and NIST and other agencies and our research stakeholders, which have included large transit agencies like WMATA, like MTA, like LA Metro, all across the country to be able to really hone in and prioritize and focus our research on the things that are most important to these stakeholders and our partners. So specifically, my research over the past year or so has been focused on evaluating the wide range of different air cleaning technologies, some of which we've mentioned today. So there's lots of different types of these air cleaning technologies that have been proposed for use in different occupied or enclosed spaces such as transit environments, and they've all been proposed to potentially reduce concentrations of those infectious pathogens in the air like SARS-CoV-2 with the hopes of reducing the risk of disease transmission. So again, as you've heard, we've mentioned today, there's lots of different types of these air cleaning technologies on the market, including different types of filtration, different types of ultraviolet radiation, bipolar ionization and photo catalytic devices, as well as different portable air cleaning devices. And no big surprise, I'm sure you all are well aware that these technologies have been increasingly marketed and popular as a result of the pandemic. So early on, we were working again very closely with different stakeholders, including these transit agencies who are coming to us initially with questions based on reducing the loading of different pathogens on surfaces like COVID-19. But that has shifted, obviously, as we talked about today, towards more of the airborne transmission concern. But with different stakeholders coming and asking what sort of technology should they consider using in different environments. As we mentioned today, there's very complex environments related to the transit industry, subways, trains, buses, etc. And so it's really challenging to understand due to the complexity of those environments and what sort of technologies would be most appropriate to be used in different settings. But the complexity goes beyond there. There's major challenges due to the way that these technologies are currently regulated. So many of these technologies are considered pesticide devices, which are regulated under FIFRA, and that the manufacturers are not allowed to make false or misleading claims about the device performance. But under the current framework, EPA doesn't routinely review the safety or efficacy data for these pesticide devices in the same way that EPA does a more comprehensive pre-market review for actual pesticide products. So there's an EPA number on these devices, but it's a little bit misleading, because EPA doesn't actually do that pre-market review of those devices. Another complication or challenge is that the different technologies are tested in many different ways. The ways that they are tested is often not representative of realistic conditions. So for example, you can imagine putting an air cleaner in a really small lab chamber, and then the challenge that then comes with trying to extrapolate those results to something more full-scale like a subway car or a different transit vehicle. They're often also tested clearly in very pristine or clean laboratory environments, and we know that transient environments are often not clean, perfectly clean and pristine like a lab setting. So there can be challenges with extrapolating findings from the lab to the field settings in that regard as well. So essentially without these standardized ways to test and without knowing how the results from the lab test can go and be translated to the field, it's essentially impossible to understand what a false or misleading claim is under FIFRA. So within the EPA's Office of Research and Development, we've been testing both in-room and in-duct type of technologies against an airborne virus using a systematic approach in a large test chamber with the Mock HVAC system to try to provide a more apples-to-apples comparison of how these different technologies perform against bio aerosols. So this work has been really critical in that it provides insights on how effective these technologies are against airborne bio aerosols, airborne virus, and it also is helping to inform the development of standardized test methods. We're also trying to bridge, again, the understanding of how these technologies work in the lab to those real life settings. So for example, we've conducted research, I'm looking at MARV 13 filters that are pristine or new, as well as MARV 13 filters that have been deployed in transit vehicles in a large transit system for varying lengths of time. And we found that even within one week, the performance of these filters degrades significantly. So I would say a common theme from the research that we've conducted so far is that there's lots of promising technologies out there, but they're often less effective in our lab testing or in the more applied testing than they are in the manufacturer commission testing that is done potentially the smaller scaler or more pristine environment. So I would just say that there's a lot of exciting things out there, but we also have a lot of tried and true technologies to lean on. And just looking forward to seeing how these other technologies evolve so that we can figure out how to use them most effectively. Thank you. Thank you so much, Katherine. That is so interesting. I hope that you will get a lot of questions. I have a feeling you will. That's amazing work. Thank you so much for doing that. Our next speaker is Jennifer DeVro. And I hope I'm not watching up her name too badly. Thank you, Jennifer. Jennifer, if you could just tell us a little bit about your role as director for Virginia Department of Rail and Public Transportation. Good afternoon. Thank you, Robin. And hello, everyone. It's a pleasure to be here today. I'm Jennifer DeVro. I'm the director of the Virginia Department of Rail and Public Transportation. We are the state transportation agency that supports transit and passenger rail and freight rail around the Commonwealth. My story today is a little different than what you've heard so far, much less on the technical side and much more on the public policy and political side. In 2020, early 2020, before really we saw the onset of COVID, we had gone through a pretty landmark change in our transportation funding package here in Virginia. We had an omnibus transportation bill that passed our legislature or state legislature in March of 2020, literally days before we all went home to stay safe from COVID. But that program increased the amount of funding that was available from on the state side for our transit agencies, and it created a new transit ridership incentive program that was intended to use some tools to support regional transit routes and to also support zero fare pilot programs around the Commonwealth as a tool to increase our transit ridership. We very quickly pivoted after it became very apparent that we were in a situation that we had not dealt with before, that we were able to push some state funding out very quickly to our transit partners to allow them to make some good decisions to help keep their operators safe while we were still transporting our essential workers and folks that were transit dependent needed to get where they needed to go during a pandemic. And one of the tools that was very helpful for us is basically taking that little bit of legislative language that says go try zero fare and rolling that off almost on a statewide basis in early 2020 as a way to separate transit riders from the operators and help keep our operators safe. So 25 of our 40 transit systems went zero fare for much of 2020. And as we have hopefully started to put this behind us, we have pivoted back into that transit ridership incentive program, the zero fare component going from being a small portion of that program to being almost the entirety of the program as we continue to pilot zero fare initiatives around the common wealth as a way to keep our operators safe, but also to improve the equity and accessibility of our transit systems for Virginia residents and folks that work here. We also around the same time completed a landmark study of Virginia transit equity and modernization study that's looked at a variety of tools that are available and made recommendations to my agency into the Virginia General Assembly about how we can improve transit accessibility and transit safety for our riders and for our operators. And we're working on the implementation of those tools now, but that includes continuation of zero fare initiatives and the implementation of technology in our systems to help keep our riders and operators safe. So from the public policy perspective, money is always a topic. We're very blessed here in Virginia that we have a supportive governor and legislature that allows us to make good public policy decisions to support our transit agencies and to make sure that we keep that accessibility available to the public even in trying times like a pandemic. With that, I'll turn it back over to you, Robin, and happy to answer questions later. Thank you so much. So interesting and so much appreciation for the incredible conundrum you've had of too much money, too fast. So thank you for that. Our next panelist is Kath Noakes. And Kath, if you could please unmute yourself and tell us a little bit about your role in the Environmental Engineering for Buildings in the School of Civil Engineering in the University of Leeds. Thank you. Thank you, Robin. So I think some of you probably know already, I've had quite a number of roles through the pandemic working around transmission of disease. And we've had a number of projects looking at lots of different environments, including schools, including workplaces, general environments, and including transport. And in session one, Dr. Susan Grant Muller, who is part of our team, talked quite significantly about our track project. I also had another role during the pandemic, which was to be involved with the UK government's SAGE committee. So that was in terms of how we looked at evidence to feed into national decision making. And that was one of the reasons, I guess, I got involved with the track project, which was it came out fairly early on in the pandemic, that there was a real lack of knowledge pre-pandemic, but also in the early days of the pandemic about transmission risk on public transport and what actually, what those risks were and what the right mitigations were. And I think over the past two and a half years or so, we and many others around the world and people who've spoken here have identified a huge range of things. But I think there are still a number of questions that we still have in this. I mean, Susan highlighted a number of the key findings from our study. So I won't sort of go over that. But I think the key aspects that for me to go forward and think about, you know, what we can do and how we can mitigate, particularly thinking around air management. I think there is a challenge that public transport is not a uniform thing at all. It is bespoke even within the same category of transport buses. There are varying different designs. Some will be predominantly mechanically ventilated. Some will have more natural ventilation. There'll be different sizes, different airflow systems, different loading. They will be serving different communities. And that goes across just about all public transport. So any sort of intervention is bespoke. And any intervention also has to consider what exists now and what the potential is to do something with it. And I think we are already also in a position where we are still trying to mitigate COVID, but we also want to be thinking about how we develop public transport to be resilient for future pandemics. And again, as already highlighted, one of the real challenges with public transport is it is an environment where you are in close proximity to other people. And that means that, you know, strategies around ventilation, air cleaning, et cetera, will have a limited impact on that close proximity transmission. And that might mean that in certain settings, the ventilation perhaps has less of a relative impact than it done in some other environments where people are more distanced. So that's always going to be a challenge that is very difficult to mitigate. And, you know, masks is one mechanism that obviously we've seen worldwide that there are different desires to wear masks in different groups of the population. And that is probably beyond where we are in this seminar today, but it is something that really needs to be thought about and going forward and when and where you should put those masks in because they clearly are effective. And of course, other strategies to prevent people or limit people who are sick from travelling. And, you know, obviously some of that is around policies that are outside of the control of transport operators. It becomes into things like workplace sickness benefits and things like that. But actually, even within, there are things within the control of transport operators, for example, making it easier to get a refund on your ticket if you can't travel because you're sick, will certainly find ways of, you know, perhaps discouraging people who are sick from travelling. So thinking about what we can do in terms of the air, short term, I think it is quite a challenge. I'm thinking about, you know, this winter, what can be done. I think most of it comes around to simpler interventions around messaging and particularly where something has a form of natural ventilation to enable doors and windows to be opened, particularly windows during travel. But obviously messaging needs to focus very carefully on the right message for the right people. There's no point messaging if you can't do anything, so you can only message to people where they can make a change. It needs to be really simple, consistent, be really precise about what is required. And I think it need