Economic costing methodologies for drug-resistant bacterial infections in humans in low-and middle-income countries: a systematic review
Edward Masoambeta1✉, Charity Mkwanda1, Edna Ibrahim1, Chantal Morel2, Chikondi Chapuma3, Edsaon Mwinjiwa1, Kenneth Chizani1,3, Chisomo Msefula1, Jobiba Chinkhumba1
- 1 Kamuzu University of Health Sciences, Blantyre, Malawi
- 2 University of Bern, Bern, Switzerland
- 3 Malawi Liverpool Welcome Trust
Received 14 October 2026 · Accepted 14 October 2026 · Published 14 October 2026
DOI: https://doi.org/10.5281/zenodo.23371600
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Abstract
Introduction
Accurate and robust estimates of the economic burden of antimicrobial resistance (AMR) are necessary to develop reliable and actionable policies. Extensive research exists on the clinical burden of AMR in low- and middle-income countries (LMICs), but comprehensive economic cost estimates are limited partly due to a lack of standard methodologies. The study aims to identify relevant cost variables for economic costing in AMR-related infections and to investigate the level of costing and types of infections widely researched in LMICs.
Materials and methods
A systematic review was conducted including quantitative papers on economic costing methodologies of drug-resistant bacterial infections in humans in LMICs. Data sources included PubMed, CINAHL, Embase, Cochrane library, and other global databases. Studies were screened and assessed for quality using a modified JBI tool and data extraction was done using a modified Covidence template. Reviews and commentaries were excluded.
Results
The majority of papers used a micro-costing approach, followed by gross costing, with some using both. Most studies analyzed costs descriptively, while fewer used regression-based techniques or propensity score matching. Cost variables were identified at the patient level (direct, non-medical, and indirect costs) and health system level (drug use, hospital stay, personnel, equipment). China had the most papers on general infections, and tuberculosis was the most common infection studied in South Africa. Many papers were of good quality for inclusion.
Conclusion
Most studies in LMIC settings fail to fully capture or quantify the economic burden of AMR. Descriptive statistics are useful but insufficient to account for the complex nature of AMR. Regression-based methodologies, though less commonly used, could provide more plausible estimates but require significant data and resources. Future research should include wide societal costs and detailed healthcare system impacts, and encourage use of more analytical methodologies to triangulate results.
Original poster
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