Health-related vulnerability to climate extremes in homoclimatic zones of Amazonia and Northeast region of Brazil

Abstract

Amazonia and the Northeast region of Brazil exhibit the highest levels of climate vulnerability in the country. While Amazonia is characterized by an extremely hot and humid climate and hosts the world largest rainforest, the Northeast is home to sharp climatic contrasts, ranging from rainy areas along the coast to semiarid regions that are often affected by droughts. Both regions are subject to extremely high temperatures and are susceptible to many tropical diseases. This study develops a multidimensional Extreme Climate Vulnerability Index (ECVI) for Brazilian Amazonia and the Northeast region based on the Alkire-Foster method. Vulnerability is defined by three components, encompassing exposure (proxied by seven climate extreme indicators), susceptibility (proxied by sociodemographic indicators), and adaptive capacity (proxied by sanitation conditions, urbanization rate, and healthcare provision). In addition to the estimated vulnerability levels and intensity, we break down the ECVI by indicators, dimensions, and regions, in order to explore how the incidence levels of climate-sensitive infectious and parasitic diseases correlate with regional vulnerability. We use the Grade of Membership method to reclassify the mesoregions into homoclimatic zones based on extreme climatic events, so climate and population/health data can be analyzed at comparable resolutions. We find two homoclimatic zones: Extreme Rain (ER) and Extreme Drought and High Temperature (ED-HT). Vulnerability is higher in the ED-HT areas than in the ER. The contribution of each dimension to overall vulnerability levels varies by homoclimatic zone. In the ER zone, adaptive capacity (39%) prevails as the main driver of vulnerability among the three dimensions, in contrast with the approximately even dimensional contribution in the ED-HT. When we compare areas by disease incidence levels, exposure emerges as the most influential dimension. Our results suggest that climate can exacerbate existing infrastructure deficiencies and socioeconomic conditions that are correlated with tropical disease incidence in impoverished areas.

Profiling sociodemographic attributes and extreme precipitation events as mediators of climate-induced disasters in municipalities in the state of Minas Gerais, Brazil

“…For the purposes of our analysis, we selected a range of indicators, encompassing the municipal Human Development Index, the urban population percentage, the percentage of households lacking adequate access to clean water or basic sanitation, the percentage of households lacking adequate access to garbage collection and disposal, and the percentage of households with walls built using poor-quality materials. These indicators were selected as they are highly sensitive to extreme events and reflective of a municipality's degree of resilience (Menezes et al, 2018;Andrade L. et al, 2021). Here, we seek to highlight two of the (IPCC, 2014)'s central vulnerability dimensions, specifically, exposure and resilience, as adaptive capacity requires a more demanding analysis in terms of empirical indicators and appropriate longitudinal information.…”

“…Although extreme weather events are natural phenomena, their transformation into disasters depends on a society's risk exposure, resilience, and adaptive capacity, the combination of which defines its degree of vulnerability (Tominaga, 2015;Andrade L. et al, 2021). For example, similar extreme weather events observed in New Zealand, Japan, and the Netherlands have caused fewer human losses than those in Thailand, the Philippines, and the United States.…”

“…Brazil is also more economically unequal and less prepared to face these types of events than the U.S. due to fewer investments in climaterobust infrastructure in recent years (Marengo et al, 2008;Cutter and Finch, 2018). Spatially, the occurrence of climate-induced disasters is more frequently observed in areas of greater social vulnerability, therefore posing a serious problem to governments, non-governmental agents, and local communities (Marengo et al, 2011;Nobre and Marengo, 2017;Andrade L. et al, 2021).…”

Networks Analysis Of Brazilian Climate Data Based On The DCCA Cross-Correlation Coefficient

“…Due to its territorial immensity (8, 511, 965Km 2 ), with 93% of the territory located in the Southern Hemisphere and 7% in the Northern Hemisphere, with a location in the intertropical zone of the planet, Brazil has different types of climates, such as: equatorial, tropical, highland tropical, humid tropical, semi-arid and subtropical. This distribution of climates, depending on the region, can have well-distributed rainfall (e.g.…”

“…the North region of Brazil, where the Amazon forest is located), mountain and plateau regions (e.g. the Southeast region of Brazil, which is characterized by low thermal amplitude and average temperature oscillating between 17 • C and 22 • C) [1][2][3][4] .…”