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Mycoses ; 63(2): 151-161, 2020 Feb.
Article in English | MEDLINE | ID: mdl-31758620

ABSTRACT

BACKGROUND: The infections caused by fungi represent a global concern and an important cause of hospital admissions in endemic areas. The influence of socio-environmental factors in infectious diseases has been documented; however, this phenomenon remains unclear regarding mycoses. OBJECTIVES: This study aimed to analyse the spatio-temporal dynamics of hospitalisations for mycoses (HM) and the association with socio-economic and climate data in the Amazon-Savanna Transition Region in the state of Maranhão, Brazil. METHODS: In this study, Spearman's correlation was applied to determine the correlation between HM, socio-economic and climatic data obtained from national databases in the period from 1998 to 2016. Hospitalisations for mycoses data were spatialised and analysed using the local Moran's index. RESULTS: Our data revealed a negative and significant correlation between HM and socio-economic data regarding population, demographic density, human development index, health facilities and sanitary sewage. Significant correlations were observed between HM and precipitation, maximum temperature and minimum temperature. The main modulating climatic variable was the minimum temperature. The spatial autocorrelation analysis showed the dynamics of HM in municipalities belonging to the different regions of the state influenced by socio-economic conditions. We observed the presence of municipalities with high incidence of HM surrounded by others with low HM cases and vice versa. CONCLUSIONS: Our results indicate that hospitalisations for mycoses represent an important indicator of socio-environmental vulnerability in the Amazon-Savanna transition region in Brazil. We encourage the adoption of measures to mitigate social and environmental impact on these diseases, especially in municipalities with low socio-economic status.


Subject(s)
Hospitalization/statistics & numerical data , Mycoses/epidemiology , Brazil/epidemiology , Climate , Delivery of Health Care/statistics & numerical data , Demography , Humans , Incidence , Prevalence , Rain , Sanitation/statistics & numerical data , Seasons , Socioeconomic Factors , Spatio-Temporal Analysis , Statistics, Nonparametric
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