Low government spending on social infrastructure , ethnic discrimination and social exclusion reduce healthcare access, leaving poor people in entire regions mostly undiagnosed or untreated. In a context of privatisation policies of healthcare systems, research shows that marginal people lack identifying documents needed to access public services in Buenos Aires , Mexico City  and Santiago de Chile , some of the most developed cities in the region. The consequences of this situation are underreporting, low diagnosis and low treatment of diseases such as vector-borne diseases such as dengue and risk of diarrhoeal diseases originating from frequent flooding in Amazonian riverine communities. Bias in reporting on access to healthcare and the incidence of diseases in marginal populations is usually region-dependent. For example, in Brazil's Amazonian north in 2018, there were 2.2 medical doctors per 1000 inhabitants, while 4.95 medical doctors per 1000 inhabitants and 9.52 doctors in São Paulo and Santa Catarina respectively. Another example is pregnant women in remote Amazonian municipalities, who receive less prenatal care than women in urban areas. These social inequities underlie systemic biases in health data quality, hindering reliable estimation of disease burdens such as the distribution of disease or birth and death registrations. For example, in Guatemala, alternative Indigenous healthcare systems are responding to local needs in Mayan communities. However, this remains unrecognised. The existence of health institutions based on IK can reinforce the lack of universal coverage by central government healthcare, addressing the miscalculation of morbidity, mortality and cause of death among disadvantaged groups.
IPCC
Climate Change 2022: Impacts, Adaptation and Vulnerability
IPCC Report