Naghavi, M;
Mestrovic, T;
Gray, A;
Hayoon, AG;
Swetschinski, LR;
Aguilar, GR;
Weaver, ND;
Ikuta, KS;
Chung, E;
Wool, EE;
et al.
Naghavi, M; Mestrovic, T; Gray, A; Hayoon, AG; Swetschinski, LR; Aguilar, GR; Weaver, ND; Ikuta, KS; Chung, E; Wool, EE; Han, C; Araki, DT; Albertson, SB; Bender, R; Bertolacci, G; Browne, AJ; Cooper, BS; Cunningham, MW; Dolecek, C; Doxey, M; Dunachie, SJ; Ghoba, S; Haines-Woodhouse, G; Hay, SI; Hsu, RL; Iregbu, KC; Kyu, HH; Ledesma, JR; Ma, J; Moore, CE; Mosser, JF; Mougin, V; Naghavi, P; Novotney, A; Rosenthal, VD; Sartorius, B; Stergachis, A; Troeger, C; Vongpradith, A; Walters, MK; Wunrow, HY; Murray., CJL
(2024)
Global burden associated with 85 pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019.
LANCET INFECTIOUS DISEASES, 24 (8).
pp. 868-895.
ISSN 1473-3099
https://doi.org/10.1016/S1473-3099(24)00158-0
SGUL Authors: Moore, Catrin Elisabeth
Abstract
Background
Despite a global epidemiological transition towards increased burden of non-communicable diseases, communicable diseases continue to cause substantial morbidity and mortality worldwide. Understanding the burden of a wide range of infectious diseases, and its variation by geography and age, is pivotal to research priority setting and resource mobilisation globally.
Methods
We estimated disability-adjusted life-years (DALYs) associated with 85 pathogens in 2019, globally, regionally, and for 204 countries and territories. The term pathogen included causative agents, pathogen groups, infectious conditions, and aggregate categories. We applied a novel methodological approach to account for underlying, immediate, and intermediate causes of death, which counted every death for which a pathogen had a role in the pathway to death. We refer to this measure as the burden associated with infection, which was estimated by combining different sources of information. To compare the burden among all pathogens, we used pathogen-specific ratios to incorporate the burden of immediate and intermediate causes of death for pathogens modelled previously by the GBD. We created the ratios by using multiple cause of death data, hospital discharge data, linkage data, and minimally invasive tissue sampling data to estimate the fraction of deaths coming from the pathway to death chain. We multiplied the pathogen-specific ratios by age-specific years of life lost (YLLs), calculated with GBD 2019 methods, and then added the adjusted YLLs to age-specific years lived with disability (YLDs) from GBD 2019 to produce adjusted DALYs to account for deaths in the chain. We used standard GBD methods to calculate 95% uncertainty intervals (UIs) for final estimates of DALYs by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. We provided burden estimates pertaining to all ages and specifically to the under 5 years age group.
Findings
Globally in 2019, an estimated 704 million (95% UI 610–820) DALYs were associated with 85 different pathogens, including 309 million (250–377; 43·9% of the burden) in children younger than 5 years. This burden accounted for 27·7% (and 65·5% in those younger than 5 years) of the previously reported total DALYs from all causes in 2019. Comparing super-regions, considerable differences were observed in the estimated pathogen-associated burdens in relation to DALYs from all causes, with the highest burden observed in sub-Saharan Africa (314 million [270–368] DALYs; 61·5% of total regional burden) and the lowest in the high-income super-region (31·8 million [25·4–40·1] DALYs; 9·8%). Three leading pathogens were responsible for more than 50 million DALYs each in 2019: tuberculosis (65·1 million [59·0–71·2]), malaria (53·6 million [27·0–91·3]), and HIV or AIDS (52·1 million [46·6–60·9]). Malaria was the leading pathogen for DALYs in children younger than 5 years (37·2 million [17·8–64·2]). We also observed substantial burden associated with previously less recognised pathogens, including Staphylococcus aureus and specific Gram-negative bacterial species (ie, Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, Acinetobacter baumannii, and Helicobacter pylori). Conversely, some pathogens had a burden that was smaller than anticipated.
Interpretation
Our detailed breakdown of DALYs associated with a comprehensive list of pathogens on a global, regional, and country level has revealed the magnitude of the problem and helps to indicate where research funding mismatch might exist. Given the disproportionate impact of infection on low-income and middle-income countries, an essential next step is for countries and relevant stakeholders to address these gaps by making targeted investments.
Statistics
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