Data use

    Modelling Chagas disease in the Atlantic Forest of south-eastern Brazil

    Published 7/13/2023

    Study finds that humidity, temperature and mammalian richness influence vector occurrence and infection rates of disease-causing parasite

    GBIF-mediated data resources used : 3,636 species occurrences
    <i>Triatoma vitticeps</i> (Stål, 1859) <a href="/occurrence/3408240006">observed</a> in Diamantina, Mina Gerais, Brazil by a_f_r (<a href="http://creativecommons.org/licenses/by-nc/4.0/">CC BY-NC 4.0</a>)

    Trypanosoma cruzi is a haemoflagellate protozoan with a complex life cycle and the causal agent of Chagas disease, affecting millions of people in Latin America, especially in rural areas. Little is known about the transmission patterns and the effect of the environment on this vector-borne disease.

    This study based in the Atlantic Forest of Espírito Santo (ES) State, Brazil, explores the biotic and abiotic variables that modulated the occurrence of a highly infected insect vector, Triatoma vitticeps, and T. cruzi infections.

    Using data collected via citizens capturing insects in their residences and submitting them for analysis at municipal public health agencies, the authors created models of vector occurrence and parasite infection based on variables for soil, vegetation, elevation, climate and mammalian species richness. Derived from GBIF-mediated species occurrences, the mammalian species richness was included as previous studies had identified a direct relationship between loss of mammal richness and increase of resilient T. cruzi reservoirs and thus, infection risk.

    Assessing correlations of vector occurrence and parasite infection with environmental variables, the authors found that the patterns were best explained by relative humidity, average temperature, soil type, altitude and mammalian richness. The central and southern regions of ES presented as transmission hotspots—with the highest distributions of T. vitticeps and T. cruzi infections—with optimal conditions for all variables present in these regions.

    Citation

    Country or areaBrazil
    TopicHuman health
    AudienceData networkData users
    TopicData analysis
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