Supplementary file Table S1. Data used in the study Data Description Sources Epidemiological data Human leptospirosis case in Upper Yangtze River Basin (UYRB) and Pearl River Basin (PRB) Notification data (2005-2016) containing information on age, gender, code of county, county’s coordinates, case classification (suspected, probable, confirmed). China Center for Disease Control and Prevention Environmental variables Precipitation Gridded precipitation data (1-km x 1-km). Values were sampled at county-level using ArcGIS software. WorldClim (https://www.worldclim.org/ ) Land surface temperature (LST) Raster data with 1-km spatial resolution. Monthly LST for each county for period of 2005-2016 is sampled using ArcGIS software. Values were sampled at county-level using ArcGIS software. MODIS Terra, MODIS11A2 8-day, 1 km spatial resolution (https://modis.gsfc.nasa.gov/data/datapro d/mod11.php ) Normalized difference vegetation index (NDVI) Monthly NDVI value for each county for period of 2005-2016 were sampled using ArcGIS software. The NDVI value ranges from -1 to 1. MODIS Terra 13Q1 v006 Vegetation Indices 16-Day L3 Global, 250 meter spatial resolution (https://lpdaac.usgs.gov/products/mod13q1 v006/ ) Normalized difference water Monthly NDWI value for each county for period of 2005-2016 were sampled using ArcGIS software. NDWI MODIS Terra MOD09A1.V6 8-day, 500 m spatial resolution
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Supplementary file
Table S1. Data used in the study
Data Description Sources
Epidemiological dataHuman leptospirosis case in Upper Yangtze River Basin (UYRB) and Pearl River Basin (PRB)
Notification data (2005-2016) containing information on age, gender, code of county, county’s coordinates, case classification (suspected, probable, confirmed).
China Center for Disease Control and Prevention
Environmental variablesPrecipitation Gridded precipitation data (1-km x 1-km). Values were sampled at
county-level using ArcGIS software.WorldClim (https://www.worldclim.org/)
Land surface temperature (LST)
Raster data with 1-km spatial resolution. Monthly LST for each county for period of 2005-2016 is sampled using ArcGIS software. Values were sampled at county-level using ArcGIS software.
MODIS Terra, MODIS11A2 8-day, 1 km spatial resolution (https://modis.gsfc.nasa.gov/data/dataprod/mod11.php)
Normalized difference vegetation index (NDVI)
Monthly NDVI value for each county for period of 2005-2016 were sampled using ArcGIS software. The NDVI value ranges from -1 to 1.
MODIS Terra 13Q1 v006 Vegetation Indices 16-Day L3 Global, 250 meter spatial resolution (https://lpdaac.usgs.gov/products/mod13q1v006/)
Normalized difference water Index (NDWI)
Monthly NDWI value for each county for period of 2005-2016 were sampled using ArcGIS software. NDWI calculated by using formula (RNIR-RSWIR) / (RNIR + RSWIR). The value of the index ranges from -1 to 1.
MODIS Terra MOD09A1.V6 8-day, 500 m spatial resolution (https://modis.gsfc.nasa.gov/data/dataprod/mod09.php)
Elevation GTOPO30 Digital elevation model (DEM), 1-km (30-arc seconds) spatial resolution. Values are sample at county-level using ArcGIS software
sampled.Land cover Land cover types for 2005 and 2015. Reclassified into 6 categories:
Cultivated land (1), Forested land (2), Grassland (3), Waterbodies (4), Artificial surfaces (5), and Bare land
Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences (RESDC) (http://www.resdc.cn/)
Hydrological features Yangtze River Basin and Pearl River Basin boundaries and streams HYDRO1k - USGShttps://gcmd.nasa.gov/records/GCMD_HYDRO1k.html;
World Bank. Major River Basins of the Worldhttps://datacatalog.worldbank.org/dataset/major-river-basins-world
Gassert, F., T. Luo, T. Shiao, and M. Luck. 2013. “Yangtze River Basin Study.” Working Paper. Washington, DC: World Resources Institute.https://www.wri.org/resources/data-sets/yangtze-river-basin-study
Livestock density (Pig and Cattle density)
Gridded pigs and cattle density with year of reference is 2010. Cell resolution 0.00833 (1-km x 1-km). Values are sample at county-level using ArcGIS software.
FAO-GeoNetwork model of livestock density (GLW 2.01) (http://www.fao.org/geonetwork/srv/en/main.home)
Urban/rural Raster data for urban or rural classification with a 5x5 km resolution. A 5x5 km resolution rural/urban surface derived from the Global Rural-Urban Mapping Project (GRUMP), (http://sedac.ciesin.columbia.edu/data/set/grump-v1-urban-extents ).
Socioeconomic variablesPopulation Annual population data by county (2005-2015) for incidence
estimation. For spatial modelling, raster (gridded) population data (in people per hectare) of 2010 and 2015 for China at the resolution of 100 m were used.
China National Bureau of Statistics (http://www.stats.gov.cn/english/)WorldPop database (https://www.worldpop.org/project/categories?id=3).
Population density Gridded (raster) population density map with 1-km spatial resolution based on UN WPP-Adjusted Population Density, v4.10 (2010, 2015)
Socioeconomic data and application centers (SEDAC) – Center for International Health Science Information Network (CIESIN) ( http://sedac.ciesin.columbia.edu/data/set/gpw-v4- population-density-adjusted-to-2015-unwpp-country-
Table S5. Results of non-spatial multivariable analysis between environmental, socioeconomic factors and leptospirosis count, Upper Yangtze River Basin (UYRB)
Figure S2. Temporal variation of incidence of leptospirosis in PRB, by quarter, 2005-2016
Figure S3. Maps of standard deviation of predicted incidence of human leptospirosis (top), spatially-structured random effect (center), and probability of non-zero case of leptospirosis (bottom) in Upper Yangtze River Basin (UYRB)
Figure S4. Maps of standard deviation of predicted incidence of human leptospirosis (top), spatially-structured random effect (center), and probability of non-zero case of leptospirosis (bottom) in Pearl River Basin (PRB)