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Local weather, flooding history and childhood diarrhoea caused by the parasite Cryptosporidium spp.: A systematic review and meta-analysis

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 674, Issue -, Pages 300-306

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2019.02.365

Keywords

Climate; Children; Infectious; Health; Spatial

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Scientists have long predicted the impacts of climate-related infectious disease emergence. Yet, the combined effect of local socioeconomic and demographic factors and weather variation on child health is poorly understood. With a focus on childhood diarrhoea caused by the parasite Cryptosporidium spp., - an infection easily controlled by public health interventions but also strongly linked to environmental conditions through waterborne spread, we systematically review and empirically model the effects of local weather and flooding history, after controlling for seasonality, publication bias, access to improved sanitation, health resources and population density at a global scale. We examined 1588 papers on childhood cryptosporidiosis and identified 36 studies representing a range of geographic locations and climatic, environmental and socio-economic conditions. Local rainfall and population density were related with cryptosporidiosis across latitudes as shown by mixed effects, spatio-temporal models for equatorial, subtropical and temperate climates. In equatorial (0-20 degrees) latitudes, the previous month's rainfall and population density were inversely related with childhood cryptosporidiosis with a significant random effect for flooding history. In tropical-subtropical (20-35 degrees) latitudes, rainfall in December was inversely related with cryptosporidiosis, compared to rainfall in April (the wet season). In temperate latitudes (>35 degrees), there was a significant negative association of reported disease with population density. This global empirical analysis indicates differential spatio-temporal patterns of childhood cryptosporidiosis in low, mid and high latitude regions. Models that couple weather conditions with demographic factors are needed to assess disease distributional shifts and risks due to environmental change. These results may provide impetus to develop environment-focused public health policies to manage disease risks associated with climate change for future generations. (C) 2019 Published by Elsevier B.V.

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