Modeling of Human Rabies Cases in Brazil in Different Future Global Warming Scenarios.

Bat species have been observed to have the potential to expand their distribution in response to climate change, thereby influencing shifts in the spatial distribution and population dynamics of human rabies cases. In this study, we applied an ensemble niche modeling approach to project climatic suitability under different future global warming scenarios for human rabies cases in Brazil, and assessed the impact on the probability of emergence of new cases. We obtained notification records of human rabies cases in all Brazilian cities from January 2001 to August 2023, as reported by the State and Municipal Health Departments. The current and future climate data were sourced from a digital repository on the WorldClim website. The future bioclimatic variables provided were downscaled climate projections from CMIP6 (a global model ensemble) and extracted from the regionalized climate model HadGEM3-GC31-LL for three future socioeconomic scenarios over four periods (2021-2100). Seven statistical algorithms (MAXENT, MARS, RF, FDA, CTA, GAM, and GLM) were selected for modeling human rabies. Temperature seasonality was the bioclimatic variable with the highest relative contribution to both current and future consensus models. Future scenario modeling for human rabies indicated a trend of changes in the areas of occurrence, maintaining the current pace of global warming, population growth, socioeconomic instability, and the loss of natural areas. In Brazil, there are areas with a higher likelihood of climatic factors contributing to the emergence of cases. When assessing future scenarios, a change in the local climatic suitability is observed that may lead to a reduction or increase in cases, depending on the region.

Modeling the Climatic Suitability of COVID-19 Cases in Brazil.

Studies have shown that climate may affect the distribution of coronavirus disease (COVID-19) and its incidence and fatality rates. Here, we applied an ensemble niche modeling approach to project the climatic suitability of COVID-19 cases in Brazil. We estimated the cumulative incidence, mortality rate, and fatality rate of COVID-19 between 2020 and 2021. Seven statistical algorithms (MAXENT, MARS, RF, FDA, CTA, GAM, and GLM) were selected to model the climate suitability for COVID-19 cases from diverse climate data, including temperature, precipitation, and humidity. The annual temperature range and precipitation seasonality showed a relatively high contribution to the models, partially explaining the distribution of COVID-19 cases in Brazil based on the climatic suitability of the territory. We observed a high probability of climatic suitability for high incidence in the North and South regions and a high probability of mortality and fatality rates in the Midwest and Southeast regions. Despite the social, viral, and human aspects regulating COVID-19 cases and death distribution, we suggest that climate may play an important role as a co-factor in the spread of cases. In Brazil, there are regions with a high probability that climatic suitability will contribute to the high incidence and fatality rates of COVID-19 in 2020 and 2021.