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Ross River Virus and the Necessity of Multiscale, Eco-epidemiological Analyses.
Journal of Infectious Diseases 2018 Februrary 15
Background: Zoonotic vector-borne disease prevalence is affected by vector, human, and reservoir host factors, which are influenced by habitat and climate; these 5 components interact on microhabitat-to-landscape scales but are often analyzed at a single spatial scale.
Methods: We present an information theoretic, multiscale, multiple regression analysis of the ecological drivers of Ross River virus. We analyze the spatial pattern of 20 years of Ross River virus infections from South Australia (1992-2012; n = 5261), using variables across these 5 components of disease ecology at 3 spatial scales.
Results: We found that covariate importance depended on the spatial scale of the analysis; some biotic variables were more important at fine scales and some abiotic variables were more important at coarser spatial scales. The urban score of an area was most predictive of infections, and mosquito variables did not improve the explanatory power of these models.
Conclusions: Through this multiscale analysis, we identified novel drivers of the spatial distribution of disease and recommend public health interventions. Our results underline that single-scale analyses may paint an incomplete picture of disease drivers, potentially creating a major flaw in epidemiological analyses. Multiscale, ecological analyses are needed to better understand infectious disease transmission.
Methods: We present an information theoretic, multiscale, multiple regression analysis of the ecological drivers of Ross River virus. We analyze the spatial pattern of 20 years of Ross River virus infections from South Australia (1992-2012; n = 5261), using variables across these 5 components of disease ecology at 3 spatial scales.
Results: We found that covariate importance depended on the spatial scale of the analysis; some biotic variables were more important at fine scales and some abiotic variables were more important at coarser spatial scales. The urban score of an area was most predictive of infections, and mosquito variables did not improve the explanatory power of these models.
Conclusions: Through this multiscale analysis, we identified novel drivers of the spatial distribution of disease and recommend public health interventions. Our results underline that single-scale analyses may paint an incomplete picture of disease drivers, potentially creating a major flaw in epidemiological analyses. Multiscale, ecological analyses are needed to better understand infectious disease transmission.
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