Global burden of antimicrobial resistance in lower respiratory infections in 2021: a systematic analysis

Xingyu Wan; Run Miao; Ning Zhang; Wei Huang; Zhengyang Wu; Haiwei Wang; Yang Yang; Yinyin Xie; Yinan Du

doi:10.1016/j.ijantimicag.2024.107431

Global burden of antimicrobial resistance in lower respiratory infections in 2021: a systematic analysis

Int J Antimicrob Agents. 2024 Dec 27:107431. doi: 10.1016/j.ijantimicag.2024.107431. Online ahead of print.

Authors

Xingyu Wan¹, Run Miao², Ning Zhang³, Wei Huang⁴, Zhengyang Wu⁴, Haiwei Wang⁴, Yang Yang⁴, Yinyin Xie⁵, Yinan Du⁶

Affiliations

¹ School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China; Second School of Clinical Medicine, Anhui Medical University, Hefei, Anhui 230032, China.
² Second School of Clinical Medicine, Anhui Medical University, Hefei, Anhui 230032, China.
³ Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; First School of Clinical Medicine, Anhui Medical University, Hefei, Anhui 230032, China.
⁴ First School of Clinical Medicine, Anhui Medical University, Hefei, Anhui 230032, China.
⁵ College of Life Sciences, Anhui Medical University, Hefei, Anhui 230032, China. Electronic address: [email protected].
⁶ School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China. Electronic address: [email protected].

PMID: 39734053
DOI: 10.1016/j.ijantimicag.2024.107431

Abstract

Objectives: The research aimed to provide a worldwide evaluation of antimicrobial resistance (AMR), focusing specifically on AMR related to lower respiratory infections (LRI).

Methods: The data were derived from the Global Antimicrobial Resistance Burden 2021 (GARB 2021). Two counterfactuals were utilized to estimate the deaths attributable to AMR and the deaths associated with AMR. The primary estimation process involved various statistical methodologies, including polynomial estimation and ensemble spatiotemporal Gaussian regression models. Using the DisMod-MR 2.1 modeling framework, the incidence and prevalence of LRI were estimated, the mortality rates were subsequently calculated, and stratified by pathogens, regions, and age groups. In addition, these indexes were identified and visualized to present global burden of AMR.

Results: In 2021, there were 20.89 (95% uncertain interval: 18.27-23.50) deaths per 100,000 individuals associated with AMR in LRI, and 5.05 (95% UI: 4.29-5.51) deaths per 100,000 individuals attributable to AMR in LRI. Trimethoprim-sulfamethoxazole-resistant S. pneumoniae exhibited the highest mortality rate of 5.15 (95% UI: 3.96- 6.34) deaths per 100,000 individuals associated with AMR, while Carbapenem -resistant S. pneumoniae exhibited the highest mortality rate of 0.66 (95% UI: 0.45-0.86) deaths per 100,000 individuals attributable to AMR. S. pneumoniae exhibited the greatest burden of AMR, followed by S. aureus. Central Sub-Saharan Africa had the highest AMR burden, with mortality rates of 73.75 (95% UI: 56.61-90.89) deaths per 100,000 individuals associated with AMR and 17.73 (95% UI: 12.71-22.74) deaths per 100,000 individuals attributable to AMR, followed by Eastern Sub-Saharan Africa and Western Sub-Saharan Africa. The individuals aged under 5 and over 65 years exhibited high prevalence of antibiotic resistance especially to Carbapenems, Methicillin, and Fluoroquinolones.

Conclusion: AMR in the LRI is still a pressing global health issue, particularly in developing countries and neonatal age groups. Global interventions need to be taken to reduce the prevalence of AMR.

Keywords: AMR; GARB; LRI; antimicrobial resistance; global burden; lower respiratory infections.