Indicadores sociais, mudanças na paisagem e clima: efeitos em doenças emergentes e reemergentes

Abstract

The research addressed the relationship between environmental factors and environmental degradation, caused by human actions on human health in the dynamics of the increase in emerging and reemerging diseases. The objective of the research was to verify the possible relationships between health and the environment in the domain of confirmed notifications of emerging and reemerging diseases, evaluating how environmental factors and environmental degradation can potentiate the incidence of some diseases in the municipalities of southern Bahia. Seventy municipalities that make up the southern mesoregion of Bahia were evaluated, including the profile of the following emerging diseases: Chikunguya, Zika Virus, Yellow Fever, American Cutaneous Leishmaniasis (ACL), H1N1 and H3N2 and reemerging disease: Dengue. Data were obtained from the TABNET databases of the Bahia State Department of Health (SESAB/BA) and the Information System of Diseases and Notification (SINAN) of the Ministry of Health in the period between 2009 and 2019. The environmental factors included the analysis of the land use and forests (Project Map Biomas), analysis of climatological data on precipitation and temperature (WorldClim) and fire outbreaks (Burns Program of the National Institute for Space Research - INPE). Data were analyzed using generalized mixed linear models, multiple partial regression, and redundancy analysis to assess health and environmental relationships. The data presented showed a positive relationship between fires and fires with the increase in the incidence of Dengue, Zika virus and Chikungunya, despite the low correlation with Yellow Fever, ATL, H1N1 and H3N2 for the municipalities. A positive relationship was found between the Municipal Human Development Index and cases of Dengue and a negative relationship with H1N1 and H3N2, there was no significant relationship with the Gini Index and diseases. With regard to climatic factors, there was a positive correlation between temperature and precipitation with diseases, except for Yellow Fever. Zika Virus, agriculture with ATL and planted forest with H1N1. In the multivariate analysis, the best explanation model was the LTA with 80%