Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics

Accurately estimating the burden of tuberculosis is challenging due to incomplete registration systems and the relationship with HIV. Here, the authors develop a Bayesian modelling strategy accounting for these factors that estimates age- and country-specific annual risks of infection and the propor...
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Autor*in:	Peter J. Dodd [verfasserIn] Debebe Shaweno [verfasserIn] Chu-Chang Ku [verfasserIn] Philippe Glaziou [verfasserIn] Carel Pretorius [verfasserIn] Richard J. Hayes [verfasserIn] Peter MacPherson [verfasserIn] Ted Cohen [verfasserIn] Helen Ayles [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Übergeordnetes Werk:	In: Nature Communications - Nature Portfolio, 2016, 14(2023), 1, Seite 10
Übergeordnetes Werk:	volume:14 ; year:2023 ; number:1 ; pages:10

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1038/s41467-023-37314-1

Katalog-ID:	DOAJ087544083

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author	Peter J. Dodd
spellingShingle	Peter J. Dodd misc Science misc Q Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics
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topic_title	Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics
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title	Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics
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title_full	Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics
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author_browse	Peter J. Dodd Debebe Shaweno Chu-Chang Ku Philippe Glaziou Carel Pretorius Richard J. Hayes Peter MacPherson Ted Cohen Helen Ayles
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title_sort	transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized hiv epidemics
title_auth	Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics
abstract	Accurately estimating the burden of tuberculosis is challenging due to incomplete registration systems and the relationship with HIV. Here, the authors develop a Bayesian modelling strategy accounting for these factors that estimates age- and country-specific annual risks of infection and the proportion resulting from recent infection.
abstractGer	Accurately estimating the burden of tuberculosis is challenging due to incomplete registration systems and the relationship with HIV. Here, the authors develop a Bayesian modelling strategy accounting for these factors that estimates age- and country-specific annual risks of infection and the proportion resulting from recent infection.
abstract_unstemmed	Accurately estimating the burden of tuberculosis is challenging due to incomplete registration systems and the relationship with HIV. Here, the authors develop a Bayesian modelling strategy accounting for these factors that estimates age- and country-specific annual risks of infection and the proportion resulting from recent infection.
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title_short	Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics
url	https://doi.org/10.1038/s41467-023-37314-1 https://doaj.org/article/0cce2638a937478c85d2f7fa28dfeac9 https://doaj.org/toc/2041-1723
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