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Table 1 Data collection and resources in this study

From: Specific urban units identified in tuberculosis epidemic using a geographical detector in Guangzhou, China

Data group

Selected variables by previous studies

Data type

Source

Socioeconomic factor

TB incidence rates in 2016 (Incid-2016) [9, 16]

Vector

Guangzhou Center for Disease Control and Prevention

Population density (Pop) in 2015 [9, 12, 15, 16]

Raster (1 km)

Resource and Environment Science and data center

(https://www.resdc.cn/)

Gross domestic product per capita (GDP) in 2015 [7, 15]

Raster (1 km)

Officially appointed medical institutions (Hosp) [2, 28]

Vector

Guangzhou Municipal People's Government (http://www.gz.gov.cn/)

Density of road network (Road_net) [17]

Vector

Open Street Map

(http://download.geofabrik.de/)

Numbers of subway stations (Subway)[17]

Vector

Counts of bus stops (Bus) [17]

Vector

Percentage of residential land (Residential) [16]

Vector

Tsinghua University

(http://data.ess.tsinghua.edu.cn) [30]

Percentage of commercial service land (Commercial) [16]

Vector

Percentage of land for public services (Pub-serv) [16]

Vector

Percentage of urban village area (UV) [29]

Vector

Our earlier study [31]

Environmental condition

Monthly average of the normalized difference vegetation index (NDVI) [15]

Raster (1 km)

MODIS (https://modis.gsfc.nasa.gov/)

Monthly average of the fine particulate matter concentration (PM2.5) [15]

Raster (1 km)

Socioeconomic Data and Applications Center

(https://sedac.ciesin.columbia.edu/data/sets/browse)

Average temperature from March to June (Temp) [13, 15]

Raster (1 km)

China Meteorological Data Service Center

(http://data.cma.cn/)

Average precipitation from March to June (Prec) [13, 15]

Raster (1 km)

Average humidity from March to June (Humi) [13, 15]

Raster (1 km)