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Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007–2018

Growing evidence suggests considerable variation in endemic typhoid fever incidence at some locations over time, yet few settings have multi-year incidence estimates to inform typhoid control measures. We sought to describe a decade of typhoid fever incidence in the Kilimanjaro Region of Tanzania. C...

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Autores principales: Cutting, Elena R., Simmons, Ryan A., Madut, Deng B., Maze, Michael J., Kalengo, Nathaniel H., Carugati, Manuela, Mbwasi, Ronald M., Kilonzo, Kajiru G., Lyamuya, Furaha, Marandu, Annette, Mosha, Calvin, Saganda, Wilbrod, Lwezaula, Bingileki F., Hertz, Julian T., Morrissey, Anne B., Turner, Elizabeth L., Mmbaga, Blandina T., Kinabo, Grace D., Maro, Venance P., Crump, John A., Rubach, Matthew P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286265/
https://www.ncbi.nlm.nih.gov/pubmed/35788572
http://dx.doi.org/10.1371/journal.pntd.0010516
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author Cutting, Elena R.
Simmons, Ryan A.
Madut, Deng B.
Maze, Michael J.
Kalengo, Nathaniel H.
Carugati, Manuela
Mbwasi, Ronald M.
Kilonzo, Kajiru G.
Lyamuya, Furaha
Marandu, Annette
Mosha, Calvin
Saganda, Wilbrod
Lwezaula, Bingileki F.
Hertz, Julian T.
Morrissey, Anne B.
Turner, Elizabeth L.
Mmbaga, Blandina T.
Kinabo, Grace D.
Maro, Venance P.
Crump, John A.
Rubach, Matthew P.
author_facet Cutting, Elena R.
Simmons, Ryan A.
Madut, Deng B.
Maze, Michael J.
Kalengo, Nathaniel H.
Carugati, Manuela
Mbwasi, Ronald M.
Kilonzo, Kajiru G.
Lyamuya, Furaha
Marandu, Annette
Mosha, Calvin
Saganda, Wilbrod
Lwezaula, Bingileki F.
Hertz, Julian T.
Morrissey, Anne B.
Turner, Elizabeth L.
Mmbaga, Blandina T.
Kinabo, Grace D.
Maro, Venance P.
Crump, John A.
Rubach, Matthew P.
author_sort Cutting, Elena R.
collection PubMed
description Growing evidence suggests considerable variation in endemic typhoid fever incidence at some locations over time, yet few settings have multi-year incidence estimates to inform typhoid control measures. We sought to describe a decade of typhoid fever incidence in the Kilimanjaro Region of Tanzania. Cases of blood culture confirmed typhoid were identified among febrile patients at two sentinel hospitals during three study periods: 2007–08, 2011–14, and 2016–18. To account for under-ascertainment at sentinel facilities, we derived adjustment multipliers from healthcare utilization surveys done in the hospital catchment area. Incidence estimates and credible intervals (CrI) were derived using a Bayesian hierarchical incidence model that incorporated uncertainty of our observed typhoid fever prevalence, of healthcare seeking adjustment multipliers, and of blood culture diagnostic sensitivity. Among 3,556 total participants, 50 typhoid fever cases were identified. Of typhoid cases, 26 (52%) were male and the median (range) age was 22 (<1–60) years; 4 (8%) were aged <5 years and 10 (20%) were aged 5 to 14 years. Annual typhoid fever incidence was estimated as 61.5 (95% CrI 14.9–181.9), 6.5 (95% CrI 1.4–20.4), and 4.0 (95% CrI 0.6–13.9) per 100,000 persons in 2007–08, 2011–14, and 2016–18, respectively. There were no deaths among typhoid cases. We estimated moderate typhoid incidence (≥10 per 100 000) in 2007–08 and low (<10 per 100 000) incidence during later surveillance periods, but with overlapping credible intervals across study periods. Although consistent with falling typhoid incidence, we interpret this as showing substantial variation over the study periods. Given potential variation, multi-year surveillance may be warranted in locations making decisions about typhoid conjugate vaccine introduction and other control measures.
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spelling pubmed-92862652022-07-16 Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007–2018 Cutting, Elena R. Simmons, Ryan A. Madut, Deng B. Maze, Michael J. Kalengo, Nathaniel H. Carugati, Manuela Mbwasi, Ronald M. Kilonzo, Kajiru G. Lyamuya, Furaha Marandu, Annette Mosha, Calvin Saganda, Wilbrod Lwezaula, Bingileki F. Hertz, Julian T. Morrissey, Anne B. Turner, Elizabeth L. Mmbaga, Blandina T. Kinabo, Grace D. Maro, Venance P. Crump, John A. Rubach, Matthew P. PLoS Negl Trop Dis Research Article Growing evidence suggests considerable variation in endemic typhoid fever incidence at some locations over time, yet few settings have multi-year incidence estimates to inform typhoid control measures. We sought to describe a decade of typhoid fever incidence in the Kilimanjaro Region of Tanzania. Cases of blood culture confirmed typhoid were identified among febrile patients at two sentinel hospitals during three study periods: 2007–08, 2011–14, and 2016–18. To account for under-ascertainment at sentinel facilities, we derived adjustment multipliers from healthcare utilization surveys done in the hospital catchment area. Incidence estimates and credible intervals (CrI) were derived using a Bayesian hierarchical incidence model that incorporated uncertainty of our observed typhoid fever prevalence, of healthcare seeking adjustment multipliers, and of blood culture diagnostic sensitivity. Among 3,556 total participants, 50 typhoid fever cases were identified. Of typhoid cases, 26 (52%) were male and the median (range) age was 22 (<1–60) years; 4 (8%) were aged <5 years and 10 (20%) were aged 5 to 14 years. Annual typhoid fever incidence was estimated as 61.5 (95% CrI 14.9–181.9), 6.5 (95% CrI 1.4–20.4), and 4.0 (95% CrI 0.6–13.9) per 100,000 persons in 2007–08, 2011–14, and 2016–18, respectively. There were no deaths among typhoid cases. We estimated moderate typhoid incidence (≥10 per 100 000) in 2007–08 and low (<10 per 100 000) incidence during later surveillance periods, but with overlapping credible intervals across study periods. Although consistent with falling typhoid incidence, we interpret this as showing substantial variation over the study periods. Given potential variation, multi-year surveillance may be warranted in locations making decisions about typhoid conjugate vaccine introduction and other control measures. Public Library of Science 2022-07-05 /pmc/articles/PMC9286265/ /pubmed/35788572 http://dx.doi.org/10.1371/journal.pntd.0010516 Text en © 2022 Cutting et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cutting, Elena R.
Simmons, Ryan A.
Madut, Deng B.
Maze, Michael J.
Kalengo, Nathaniel H.
Carugati, Manuela
Mbwasi, Ronald M.
Kilonzo, Kajiru G.
Lyamuya, Furaha
Marandu, Annette
Mosha, Calvin
Saganda, Wilbrod
Lwezaula, Bingileki F.
Hertz, Julian T.
Morrissey, Anne B.
Turner, Elizabeth L.
Mmbaga, Blandina T.
Kinabo, Grace D.
Maro, Venance P.
Crump, John A.
Rubach, Matthew P.
Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007–2018
title Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007–2018
title_full Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007–2018
title_fullStr Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007–2018
title_full_unstemmed Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007–2018
title_short Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007–2018
title_sort facility-based disease surveillance and bayesian hierarchical modeling to estimate endemic typhoid fever incidence, kilimanjaro region, tanzania, 2007–2018
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286265/
https://www.ncbi.nlm.nih.gov/pubmed/35788572
http://dx.doi.org/10.1371/journal.pntd.0010516
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