From Surveillance to Disease Burden: Evidence Gaps for WHO Priority Bacterial Pathogens in South Asia and the Eastern Mediterranean

Abstract

Antimicrobial resistance (AMR) is assessed through laboratory surveillance, which measures resistance among tested isolates, and burden estimation, which quantifies associated and attributable mortality and disability. This structured narrative review examines what these evidence streams establish about WHO Bacterial Priority Pathogens List 2024 pathogens in South Asia and the WHO Eastern Mediterranean Region, where their connection remains uncertain, and priorities for strengthening it. Global and regional surveillance reports, modeled burden analyses, and peer-reviewed studies available through October 2026 were reviewed. Reported median resistance across infection types reached 30.0% in the Eastern Mediterranean Region and 31.1% in the WHO South-East Asia Region in 2023; the latter is not geographically equivalent to South Asia. Burden estimates indicate approximately 380,000 AMR-associated deaths in the Eastern Mediterranean Region in 2021 and a projected 11.8 million AMR-attributable deaths in South Asia during 2025–2050. However, surveillance and burden estimates remain incompletely connected. Hospital-based sampling, particularly in tertiary centres, limits population representativeness. Population denominators, infection incidence, care-seeking patterns, blood-culture utilization, and outcomes by resistance status are insufficiently measured, requiring modeling assumptions and externally derived parameters. Higher reported resistance in countries with weaker surveillance further complicates interpretation. The central gap is therefore insufficient linking data to translate resistance proportions into population-level disease burden. Priorities include surveillance within defined population catchments, linking microbiological and clinical outcomes, measuring diagnostic utilization, harmonizing reporting across WHO regional boundaries, and transparently communicating modeling assumptions and uncertainty. These improvements are essential for translating AMR evidence into defensible regional policy and investment priorities.