Applying a zero-corrected, gravity model estimator reduces bias due to heterogeneity in healthcare utilization in community-scale, passive surveillance datasets of endemic diseases

Data on population health are vital to evidence-based decision making but are rarely adequately localized or updated in continuous time. They also suffer from low ascertainment rates, particularly in rural areas where barriers to healthcare can cause infrequent touch points with the health system. H...

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Detalles Bibliográficos
Autores principales: Evans, Michelle V., Ihantamalala, Felana A., Randriamihaja, Mauricianot, Aina, Andritiana Tsirinomen’ny, Bonds, Matthew H., Finnegan, Karen E., Rakotonanahary, Rado J. L., Raza-Fanomezanjanahary, Mbolatiana, Razafinjato, Bénédicte, Raobela, Oméga, Raholiarimanana, Sahondraritera Herimamy, Randrianavalona, Tiana Harimisa, Garchitorena, Andres
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10693580/
https://www.ncbi.nlm.nih.gov/pubmed/38042891
http://dx.doi.org/10.1038/s41598-023-48390-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10693580/
https://www.ncbi.nlm.nih.gov/pubmed/38042891
http://dx.doi.org/10.1038/s41598-023-48390-0

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