A time-series approach to mapping livestock density using household survey data
Abstract More than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock have broad utility across a range of applications, efforts t...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-16118-1 |
| _version_ | 1828327731471843328 |
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| author | Julianne Meisner Agapitus Kato Marshall Lemerani Erick Mwamba Miaka Acaga Taban Ismail Jonathan Wakefield Ali Rowhani-Rahbar David Pigott Jonathan Mayer Peter Rabinowitz |
| author_facet | Julianne Meisner Agapitus Kato Marshall Lemerani Erick Mwamba Miaka Acaga Taban Ismail Jonathan Wakefield Ali Rowhani-Rahbar David Pigott Jonathan Mayer Peter Rabinowitz |
| author_sort | Julianne Meisner |
| collection | DOAJ |
| description | Abstract More than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock have broad utility across a range of applications, efforts to map the distribution of livestock on a large scale are limited to the Gridded Livestock of the World (GLW) project. We present a complimentary effort to map the distribution of cattle and pigs in Malawi, Uganda, Democratic Republic of Congo, and South Sudan. In contrast to GLW, which uses dasymmetric modeling applied to census data to produce time-stratified estimates of livestock counts and spatial density, our work uses complex survey data and distinct modeling methods to generate a time-series of livestock distribution, defining livestock density as the ratio of animals to humans. In addition to favorable cross-validation results and general agreement with national density estimates derived from external data on national human and livestock populations, our results demonstrate extremely good agreement with GLW-3 estimates, supporting the validity of both efforts. Our results furthermore offer a high-resolution time series result and employ a definition of density which is particularly well-suited to the study of livestock-origin zoonoses. |
| first_indexed | 2024-04-13T20:00:19Z |
| format | Article |
| id | doaj.art-580d256413214f7f9cb7bccd9854a989 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-13T20:00:19Z |
| publishDate | 2022-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-580d256413214f7f9cb7bccd9854a9892022-12-22T02:32:14ZengNature PortfolioScientific Reports2045-23222022-08-0112112110.1038/s41598-022-16118-1A time-series approach to mapping livestock density using household survey dataJulianne Meisner0Agapitus Kato1Marshall Lemerani2Erick Mwamba Miaka3Acaga Taban Ismail4Jonathan Wakefield5Ali Rowhani-Rahbar6David Pigott7Jonathan Mayer8Peter Rabinowitz9Department of Environmental and Occupational Health Sciences, Center for One Health Research, University of WashingtonUganda Virus Research InstituteMinistry of HealthProgramme National de Lutte contre la Trypanosomiase Humaine AfricaineIntraHealth InternationalDepartment of Biostatistics, University of WashingtonDepartment of Epidemiology, University of WashingtonDepartment of Health Metrics Sciences, University of WashingtonDepartment of Epidemiology, University of WashingtonDepartment of Environmental and Occupational Health Sciences, Center for One Health Research, University of WashingtonAbstract More than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock have broad utility across a range of applications, efforts to map the distribution of livestock on a large scale are limited to the Gridded Livestock of the World (GLW) project. We present a complimentary effort to map the distribution of cattle and pigs in Malawi, Uganda, Democratic Republic of Congo, and South Sudan. In contrast to GLW, which uses dasymmetric modeling applied to census data to produce time-stratified estimates of livestock counts and spatial density, our work uses complex survey data and distinct modeling methods to generate a time-series of livestock distribution, defining livestock density as the ratio of animals to humans. In addition to favorable cross-validation results and general agreement with national density estimates derived from external data on national human and livestock populations, our results demonstrate extremely good agreement with GLW-3 estimates, supporting the validity of both efforts. Our results furthermore offer a high-resolution time series result and employ a definition of density which is particularly well-suited to the study of livestock-origin zoonoses.https://doi.org/10.1038/s41598-022-16118-1 |
| spellingShingle | Julianne Meisner Agapitus Kato Marshall Lemerani Erick Mwamba Miaka Acaga Taban Ismail Jonathan Wakefield Ali Rowhani-Rahbar David Pigott Jonathan Mayer Peter Rabinowitz A time-series approach to mapping livestock density using household survey data Scientific Reports |
| title | A time-series approach to mapping livestock density using household survey data |
| title_full | A time-series approach to mapping livestock density using household survey data |
| title_fullStr | A time-series approach to mapping livestock density using household survey data |
| title_full_unstemmed | A time-series approach to mapping livestock density using household survey data |
| title_short | A time-series approach to mapping livestock density using household survey data |
| title_sort | time series approach to mapping livestock density using household survey data |
| url | https://doi.org/10.1038/s41598-022-16118-1 |
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