Area-level socioeconomic status inequalities shape patterns of antimicrobial resistance in China, 2014-2023: a Bayesian spatiotemporal modelling analysis.

ABSTRACT:

Background

Antimicrobial resistance (AMR) represents an escalating global health challenge, with socioeconomic status (SES) being a significant influencing factor. This study aimed to quantify area-level SES and assess its association with drug-resistant bacteria in China.

Methods

AMR data were collected from China Antimicrobial Resistance Surveillance System (CARSS, 2014-2023). Area-level SES across China was captured by County-level Area Deprivation Index (CADI) and Townsend Deprivation Index (TDI). Spatiotemporal distributions of drug-resistant bacteria were explored by spatial autocorrelation and spatiotemporal scan analyses. Key AMR risk factors were identified by GeoDetector analysis. Six Bayesian models were established through the Bayesian spatiotemporal modelling an

SUBMITTER: Yang Y 

PROVIDER: S-EPMC12663029 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature