Tackling public health data gaps through Bayesian high-resolution population estimation: A case study of Kasaï-Oriental, Democratic Republic of the Congo.
- DOI
- 10.1371/journal.pgph.0005072
- Published
- 2025
- Container
- PLOS global public health
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pgph.0005072,
title = {Tackling public health data gaps through Bayesian high-resolution population estimation: A case study of Kasaï-Oriental, Democratic Republic of the Congo.},
author = {Boo G and Darin E and Chamberlain HR and Hosner R and Akilimali PK and Kazadi HM and Nnanatu CC and Lázár AN and Tatem AJ},
year = {2025},
journal = {PLOS global public health},
doi = {10.1371/journal.pgph.0005072},
url = {https://doi.org/10.1371/journal.pgph.0005072}
}RIS
TY - JOUR TI - Tackling public health data gaps through Bayesian high-resolution population estimation: A case study of Kasaï-Oriental, Democratic Republic of the Congo. AU - Boo G AU - Darin E AU - Chamberlain HR AU - Hosner R AU - Akilimali PK AU - Kazadi HM AU - Nnanatu CC AU - Lázár AN AU - Tatem AJ PY - 2025 JO - PLOS global public health DO - 10.1371/journal.pgph.0005072 UR - https://doi.org/10.1371/journal.pgph.0005072 ER -
APA
G, B., E, D., HR, C., R, H., PK, A., HM, K., CC, N., AN, L., & AJ, T. (2025). Tackling public health data gaps through Bayesian high-resolution population estimation: A case study of Kasaï-Oriental, Democratic Republic of the Congo.. PLOS global public health. https://doi.org/10.1371/journal.pgph.0005072
Source records
- pubmed · retrieved 2026-09-24T21:47:55.880Z