{"title":"From top to bottom: gridded human population estimates in data-poor situations.","authors":"K B Stevens","doi":"10.20506/rst.42.3354","DOIUrl":null,"url":null,"abstract":"<p><p>Where disease risks are heterogeneous across population groups or space, or dependent on transmission between individuals, spatial data on population distributions - human, livestock and wildlife - are required to estimate infectious disease risks, burdens and dynamics. As a result, large-scale, spatially explicit, high-resolution human population data are being increasingly used in a wide range of animal- and public-health planning and policy development scenarios. Official census data, aggregated by administrative unit, provide the only complete enumeration of a country's population. While census data from developed countries are generally up-to-date and of high quality, in resource-poor settings they are often incomplete, out of date, or only available at the country or province level. The challenges associated with producing accurate population estimates in regions that lack high-quality census data have led to the development of census-independent approaches to small-area population estimations. Known as bottom-up models, as opposed to the census-based top-down approaches, these methods combine microcensus survey data with ancillary data to provide spatially disaggregated population estimates in the absence of national census data. This review highlights the need for high-resolution gridded population data, discusses problems associated with using census data as top-down model inputs, and explores census-independent, or bottom-up, methods of producing spatially explicit, high-resolution gridded population data, together with their advantages.</p>","PeriodicalId":49596,"journal":{"name":"Revue Scientifique et Technique-Office International Des Epizooties","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revue Scientifique et Technique-Office International Des Epizooties","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.20506/rst.42.3354","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"VETERINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Where disease risks are heterogeneous across population groups or space, or dependent on transmission between individuals, spatial data on population distributions - human, livestock and wildlife - are required to estimate infectious disease risks, burdens and dynamics. As a result, large-scale, spatially explicit, high-resolution human population data are being increasingly used in a wide range of animal- and public-health planning and policy development scenarios. Official census data, aggregated by administrative unit, provide the only complete enumeration of a country's population. While census data from developed countries are generally up-to-date and of high quality, in resource-poor settings they are often incomplete, out of date, or only available at the country or province level. The challenges associated with producing accurate population estimates in regions that lack high-quality census data have led to the development of census-independent approaches to small-area population estimations. Known as bottom-up models, as opposed to the census-based top-down approaches, these methods combine microcensus survey data with ancillary data to provide spatially disaggregated population estimates in the absence of national census data. This review highlights the need for high-resolution gridded population data, discusses problems associated with using census data as top-down model inputs, and explores census-independent, or bottom-up, methods of producing spatially explicit, high-resolution gridded population data, together with their advantages.
期刊介绍:
The Scientific and Technical Review is a periodical publication containing scientific information that is updated constantly. The Review plays a significant role in fulfilling some of the priority functions of the OIE. This peer-reviewed journal contains in-depth studies devoted to current scientific and technical developments in animal health and veterinary public health worldwide, food safety and animal welfare. The Review benefits from the advice of an Advisory Editorial Board and a Scientific and Technical Committee composed of top scientists from across the globe.