{"title":"Climate change and antimicrobial resistance: a global-scale analysis.","authors":"Yaqin Ni, Jin Zhao, Yuhua Yuan, Baihuan Feng","doi":"10.1186/s12879-025-11616-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Antimicrobial resistance (AMR) represents a major global health threat. Although regional studies have explored the relationship between climate change and AMR, a comprehensive global analysis incorporating extreme climate events has not yet been conducted.</p><p><strong>Methods: </strong>We analyzed global data from 2000 to 2023, encompassing over 28 million bacterial isolates from eight common pathogens and 14 antibiotic categories. Climate data were sourced from NOAA, and resistance data were obtained from ResistanceMap, ECDC, and PLISA databases. Linear mixed-effects models (LMMs) were applied to evaluate the associations between climate indices and resistance rates.</p><p><strong>Results: </strong>Temperature was consistently positively correlated with resistance rates across most bacterial species. The mean temperature was significantly associated with resistance rates even after adjusting for covariates. Extreme temperature indicators, including intensity indices (TXx, TNx, TXn and TNn), absolute threshold indices (SU, TR and DTR), relative threshold indices (TN90p and TX90p), and duration indices (CSDI and WSDI) exhibited significant positive correlations with resistance rates. In contrast, cold-related indices (FD, ID, TN10p and TX10p) were negatively correlated with resistance rates. Among the precipitation indices, only CDD demonstrated a significant positive association with aggregated AMR after full adjustment; all the other precipitation metrics showed no statistically significant correlation. Furthermore, subgroup analyses of WHO priority pathogens confirmed the robust effect of temperature, but revealed that precipitation indices, particularly CDD, had opposing correlations with resistance across different pathogens.</p><p><strong>Conclusions: </strong>This study provides robust global evidence that rising temperatures and extreme heat are consistent drivers of AMR, whereas the impact of precipitation is complex and pathogen dependent. These findings underscore the need for climate-informed public health strategies that integrate climate surveillance into AMR action plans to develop targeted interventions against these intertwined global threats.</p>","PeriodicalId":8981,"journal":{"name":"BMC Infectious Diseases","volume":"25 1","pages":"1191"},"PeriodicalIF":3.0000,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12482477/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Infectious Diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12879-025-11616-9","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Antimicrobial resistance (AMR) represents a major global health threat. Although regional studies have explored the relationship between climate change and AMR, a comprehensive global analysis incorporating extreme climate events has not yet been conducted.
Methods: We analyzed global data from 2000 to 2023, encompassing over 28 million bacterial isolates from eight common pathogens and 14 antibiotic categories. Climate data were sourced from NOAA, and resistance data were obtained from ResistanceMap, ECDC, and PLISA databases. Linear mixed-effects models (LMMs) were applied to evaluate the associations between climate indices and resistance rates.
Results: Temperature was consistently positively correlated with resistance rates across most bacterial species. The mean temperature was significantly associated with resistance rates even after adjusting for covariates. Extreme temperature indicators, including intensity indices (TXx, TNx, TXn and TNn), absolute threshold indices (SU, TR and DTR), relative threshold indices (TN90p and TX90p), and duration indices (CSDI and WSDI) exhibited significant positive correlations with resistance rates. In contrast, cold-related indices (FD, ID, TN10p and TX10p) were negatively correlated with resistance rates. Among the precipitation indices, only CDD demonstrated a significant positive association with aggregated AMR after full adjustment; all the other precipitation metrics showed no statistically significant correlation. Furthermore, subgroup analyses of WHO priority pathogens confirmed the robust effect of temperature, but revealed that precipitation indices, particularly CDD, had opposing correlations with resistance across different pathogens.
Conclusions: This study provides robust global evidence that rising temperatures and extreme heat are consistent drivers of AMR, whereas the impact of precipitation is complex and pathogen dependent. These findings underscore the need for climate-informed public health strategies that integrate climate surveillance into AMR action plans to develop targeted interventions against these intertwined global threats.
期刊介绍:
BMC Infectious Diseases is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of infectious and sexually transmitted diseases in humans, as well as related molecular genetics, pathophysiology, and epidemiology.