Global burden associated with 85 pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019

疾病负担 疾病 疾病负担 全球卫生 医学 公共卫生 内科学 病理
作者
Mohsen Naghavi,Tomislav Meštrović,Authia P Gray,Anna Gershberg Hayoon,Lucien R Swetschinski,Gisela Robles Aguilar,Nicole Davis Weaver,Kevin S Ikuta,Erin Chung,Eve E Wool,Chieh Han,Daniel T Araki,Samuel B Albertson,Rose G Bender,Greg Bertolacci,Annie J Browne,Ben S. Cooper,Matthew Cunningham,Christiane Dolecek,Matthew C Doxey
出处
期刊:Lancet Infectious Diseases [Elsevier BV]
卷期号:24 (8): 868-895 被引量:115
标识
DOI:10.1016/s1473-3099(24)00158-0
摘要

Summary

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.

Funding

Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
充电宝应助烂漫成仁采纳,获得10
刚刚
chx驳回了SciGPT应助
刚刚
DONG发布了新的文献求助10
刚刚
明理高山完成签到,获得积分10
刚刚
xinxin发布了新的文献求助10
1秒前
1秒前
cdragon发布了新的文献求助20
1秒前
1秒前
时尚沅发布了新的文献求助10
1秒前
上官若男应助xiaowei采纳,获得10
2秒前
11111111完成签到,获得积分10
2秒前
冷酷的文博完成签到 ,获得积分10
2秒前
君莫笑完成签到,获得积分10
2秒前
2秒前
2秒前
梦里又何妨完成签到,获得积分10
3秒前
香蕉觅云应助瘦瘦的寒珊采纳,获得10
3秒前
3秒前
3秒前
今天进步了吗完成签到,获得积分10
3秒前
hui完成签到,获得积分20
3秒前
3秒前
印第安老斑鸠应助syea采纳,获得10
4秒前
华仔应助sdl采纳,获得10
4秒前
科研花完成签到 ,获得积分10
4秒前
Owen应助zz采纳,获得30
4秒前
王强发布了新的文献求助10
5秒前
南至发布了新的文献求助10
5秒前
cdercder应助11111111采纳,获得20
6秒前
6秒前
6秒前
6秒前
sumwang完成签到,获得积分10
6秒前
默默寒珊发布了新的文献求助10
6秒前
斯文败类应助踏实紊采纳,获得10
7秒前
7秒前
天真怀梦完成签到,获得积分10
7秒前
haonanchen完成签到,获得积分10
7秒前
gszy1975发布了新的文献求助10
7秒前
8秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Multiple Self-States Drawing Technique 600
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Rosenblum, Global Change Biology 500
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7769771
求助须知:如何正确求助?哪些是违规求助? 9312748
关于积分的说明 20330652
捐赠科研通 7355024
什么是DOI,文献DOI怎么找? 3316114
关于科研通互助平台的介绍 2464976
邀请新用户注册赠送积分活动 2330817