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Spatial distribution of leptospirosis incidence in the Upper Yangtze and Pearl River Basin, China: Tools to support intervention and elimination. | LitMetric

Spatial distribution of leptospirosis incidence in the Upper Yangtze and Pearl River Basin, China: Tools to support intervention and elimination.

Sci Total Environ

School of Veterinary Science, The University of Queensland, Gatton, Queensland 4343, Australia; Children's Health and Environment Program, Child Health Research Centre, The University of Queensland, South Brisbane, QLD 4101, Australia. Electronic address:

Published: July 2020

Background: Since 2011 human leptospirosis incidence in China has remained steadily low with persistent pockets of notifications reported in communities within the Upper Yangtze River Basin (UYRB) and Pearl River Basin (PRB). To help guide health authorities within these residual areas to identify communities where interventions should be targeted, this study quantified the local effect of socioeconomic and environmental factors on the spatial distribution of leptospirosis incidence and developed predictive maps of leptospirosis incidence for UYRB and PRB.

Methods: Data on all human leptospirosis cases reported during 2005-2016 across the UYRB and PRB regions were geolocated at the county-level and included in the analysis. Bayesian conditional autoregressive (CAR) models with zero-inflated Poisson link for leptospirosis incidence were developed after adjustment of environmental and socioeconomic factors such as precipitation, normalized difference vegetation index (NDVI), modified normalized difference water index (MNDWI), land surface temperature (LST), elevation, slope, land cover, crop production, livestock density, gross domestic product and population density.

Results: The relationship of environmental and socioeconomic variables with human leptospirosis incidence varied between both regions. While across UYRB incidence of human leptospirosis was associated with MNDWI and elevation, in PRB human leptospirosis incidence was significantly associated with NDVI, livestock density and land cover. Precipitation was significantly and positively associated with the spatial variation of incidence of leptospirosis in both regions. After accounting for the effect of environmental and socioeconomic factors, the predicted distribution of residual high-incidence county is potentially more widespread both in the UYRB and PRB compared to the observed distribution. In the UYRB, the highest predicted incidence was found along the border of Chongqing and Guizhou towards Sichuan basin and northwest Yunnan. The highest predicted incidence was also identified in counties in the central and lower reaches of the PRB.

Conclusions: This study demonstrated significant geographical heterogeneity in leptospirosis incidence within UYRB and PRB, providing an evidence base for prioritising targeted interventions in counties identified with the highest predicted incidence. Furthermore, environmental drivers of leptospirosis incidence were highly specific to each of the regions, emphasizing the importance of localized control measures. The findings also suggested the need to expand interventional coverage and to support surveillance and diagnostic capacity on the predicted high-risk areas.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2020.138251DOI Listing

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