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Menzies, N.A.* ; Allwood, B.W.* ; Dean, A.S.* ; Dodd, P.J.* ; Houben, R.M.G.J.* ; James, L.P.* ; Knight, G.M.* ; Meghji, J.* ; Nguyen, L.N.* ; Rachow, A. ; Schumacher, S.G.* ; Mirzayev, F.* ; Cohen, T.*

Global burden of disease due to rifampicin-resistant tuberculosis: A mathematical modeling analysis.

Nat. Commun. 14:6182 (2023)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
In 2020, almost half a million individuals developed rifampicin-resistant tuberculosis (RR-TB). We estimated the global burden of RR-TB over the lifetime of affected individuals. We synthesized data on incidence, case detection, and treatment outcomes in 192 countries (99.99% of global tuberculosis). Using a mathematical model, we projected disability-adjusted life years (DALYs) over the lifetime for individuals developing tuberculosis in 2020 stratified by country, age, sex, HIV, and rifampicin resistance. Here we show that incident RR-TB in 2020 was responsible for an estimated 6.9 (95% uncertainty interval: 5.5, 8.5) million DALYs, 44% (31, 54) of which accrued among TB survivors. We estimated an average of 17 (14, 21) DALYs per person developing RR-TB, 34% (12, 56) greater than for rifampicin-susceptible tuberculosis. RR-TB burden per 100,000 was highest in former Soviet Union countries and southern African countries. While RR-TB causes substantial short-term morbidity and mortality, nearly half of the overall disease burden of RR-TB accrues among tuberculosis survivors. The substantial long-term health impacts among those surviving RR-TB disease suggest the need for improved post-treatment care and further justify increased health expenditures to prevent RR-TB transmission.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Uncertainty
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Zeitschrift Nature Communications
Quellenangaben Band: 14, Heft: 1, Seiten: , Artikelnummer: 6182 Supplement: ,
Verlag Nature Publishing Group
Verlagsort London
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of AI for Health (AIH)
Förderungen Medical Research Council
NIAID NIH HHS