Bayesian geostatistics in health cartography: the perspective of malaria.
Maps of parasite prevalences and other aspects of infectious diseases that vary in space are widely used in parasitology. However, spatial parasitological datasets rarely, if ever, have sufficient coverage to allow exact determination of such maps. Bayesian geostatistics (BG) is a method for finding...
| Glavni autori: | , , , |
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| Format: | Journal article |
| Jezik: | English |
| Izdano: |
2011
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| _version_ | 1826293657618087936 |
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| author | Patil, A Gething, P Piel, F Hay, S |
| author_facet | Patil, A Gething, P Piel, F Hay, S |
| author_sort | Patil, A |
| collection | OXFORD |
| description | Maps of parasite prevalences and other aspects of infectious diseases that vary in space are widely used in parasitology. However, spatial parasitological datasets rarely, if ever, have sufficient coverage to allow exact determination of such maps. Bayesian geostatistics (BG) is a method for finding a large sample of maps that can explain a dataset, in which maps that do a better job of explaining the data are more likely to be represented. This sample represents the knowledge that the analyst has gained from the data about the unknown true map. BG provides a conceptually simple way to convert these samples to predictions of features of the unknown map, for example regional averages. These predictions account for each map in the sample, yielding an appropriate level of predictive precision. |
| first_indexed | 2024-03-07T03:33:32Z |
| format | Journal article |
| id | oxford-uuid:bb8564ec-3c40-42a6-8f69-18bb54f0e26c |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T03:33:32Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | oxford-uuid:bb8564ec-3c40-42a6-8f69-18bb54f0e26c2022-03-27T05:17:33ZBayesian geostatistics in health cartography: the perspective of malaria.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:bb8564ec-3c40-42a6-8f69-18bb54f0e26cEnglishSymplectic Elements at Oxford2011Patil, AGething, PPiel, FHay, SMaps of parasite prevalences and other aspects of infectious diseases that vary in space are widely used in parasitology. However, spatial parasitological datasets rarely, if ever, have sufficient coverage to allow exact determination of such maps. Bayesian geostatistics (BG) is a method for finding a large sample of maps that can explain a dataset, in which maps that do a better job of explaining the data are more likely to be represented. This sample represents the knowledge that the analyst has gained from the data about the unknown true map. BG provides a conceptually simple way to convert these samples to predictions of features of the unknown map, for example regional averages. These predictions account for each map in the sample, yielding an appropriate level of predictive precision. |
| spellingShingle | Patil, A Gething, P Piel, F Hay, S Bayesian geostatistics in health cartography: the perspective of malaria. |
| title | Bayesian geostatistics in health cartography: the perspective of malaria. |
| title_full | Bayesian geostatistics in health cartography: the perspective of malaria. |
| title_fullStr | Bayesian geostatistics in health cartography: the perspective of malaria. |
| title_full_unstemmed | Bayesian geostatistics in health cartography: the perspective of malaria. |
| title_short | Bayesian geostatistics in health cartography: the perspective of malaria. |
| title_sort | bayesian geostatistics in health cartography the perspective of malaria |
| work_keys_str_mv | AT patila bayesiangeostatisticsinhealthcartographytheperspectiveofmalaria AT gethingp bayesiangeostatisticsinhealthcartographytheperspectiveofmalaria AT pielf bayesiangeostatisticsinhealthcartographytheperspectiveofmalaria AT hays bayesiangeostatisticsinhealthcartographytheperspectiveofmalaria |