Exploring determinants of antimicrobial resistance: A comprehensive analysis of health, socio-economic, and environmental Factors | ||||
| Microbes and Infectious Diseases | ||||
| Article 18, Volume 5, Issue 2, May 2024, Page 599-607 PDF (646.5 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mid.2024.255699.1717 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Amany A Salem  1; Mohamed H Husein1; Amal S Sedrak1; Nermin Ghith2
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| 1Public Health and Community Medicine Department, Faculty of Medicine, Cairo University, Egypt | ||||
| 2Childhood Cancer Research Group, Danish Cancer Society Research Center, Copenhagen, Denmark | ||||
| Abstract | ||||
| Background: Antimicrobial resistance (AMR) is considered one of the key health challenges facing the globe. It has various implications for shaping the future of the health and healthcare industries. Aim: This study aims to explore potential socioeconomic and health system factors shaping the AMR burden globally. Methods: This secondary data-analysis study was conducted during the period from 2022 to 2023 between Cairo and Copenhagen. Data from the “global sewage surveillance project” in addition to several published datasets were composed, validated, and cleaned. Several exploratory data analyses were applied to examine the relationship between AMR and different factors, especially health system-related and socio-economic conditions and environmental and behavioral-related factors. Mathematical modeling using generalized multiple mixed models (GLMM) modeling techniques was applied to shape and describe these relations. The dependent variable was AMR burden measured by the number of resistant genes in the sewage sample that were expressed by FPKM; the independent variables were more than forty, covering various proposed factors. Results: The stepwise multiple fixed effects modeling showed that the proportion of the population with basic drinking water, care for newborns index, and the number of all health workers in the 10,000 population are the main determinants with negative coefficients. When a random effect model was fitted, it showed a significant association between AMR burden and region (p < 0.001). Conclusion: This study highlights the importance of basic hygienic measures and the empowered healthcare system in reducing the burden of antimicrobial resistance globally. Regional variations in AMR prevalence emphasize the need for tailored interventions that address specific regional contexts to combat this global health challenge effectively. | ||||
| Keywords | ||||
| Generalized linear mixed model (GLMM); antimicrobial resistance (AMR); Global sewage surveillance project; Health system; WASH | ||||
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