Tackling public health data gaps through Bayesian high-resolution population estimation: A case study of Kasaï-Oriental, Democratic Republic of the Congo.
Most low- and middle-income countries face significant public health challenges, exacerbated by the lack of reliable demographic data supporting effective planning and intervention. In such data-scarce settings, statistical models combining geolocated survey data with geospatial datasets enable the...
Tallennettuna:
| Päätekijät: | , , , , , , , , |
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| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Public Library of Science (PLoS)
2025-01-01
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| Sarja: | PLOS Global Public Health |
| Linkit: | https://doi.org/10.1371/journal.pgph.0005072 |
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