The effects of spatial population dataset choice on estimates of population at risk of disease

Table 2 Disease-related studies that have utilized large area gridded population datasets.

Disease	Application	Population map used [Reference]
Malaria	Populations at risk	GPW [47–52], LandScan [53, 54], UNEP [55], GRUMP [24, 25, 28, 30–32, 56–58]
	Clinical cases	GPW [59], GRUMP [8]
	Intervention coverage	GRUMP [60]
	Funding coverage	GRUMP [57, 61]
	Risk mapping	GPW [62–64], UNEP [65], GRUMP [66]
	Infection movements	GRUMP [29, 30]
	Urbanization effects	GPW [67], GRUMP [15]
Hookworm	Populations at risk	GPW [68, 69]
Influenza	Epidemic modeling	GPW [70–73], LandScan [7, 74, 75], GRUMP [76]
	Risk mapping	LandScan [77, 78]
Yellow fever	Populations at risk	GRUMP [79]
Dengue	Populations at risk	GRUMP [79]
	Risk mapping	USGS [21], LandScan [80, 81]
Filariasis	Populations at risk	UNEP [82]
Helminths	Populations at risk	GPW [52, 83], UNEP[84]
Bovine TB	Risk mapping	LandScan [85, 86], GPW [86]
Trypanosomiasis	Risk mapping	UNEP [87]
Onchocerciasis	Populations at risk	GPW [88]
Leprosy	Risk mapping	GPW [89]
HIV	Prevalence analyses	LandScan [90]
General	Trends in emerging diseases	GPW [91]
	Health of schoolchildren	UNEP [92]

GPW = Gridded Population of the World, GRUMP = Global Rural Urban Mapping Project, UNEP = United Nations Environment Programme Global Population Databases, USGS = United States Geological Survey Population datasets.

ISSN: 1478-7954