Laboratory Capacity And Epidemiological Surveillance For AMR: A Situational Analysis In Low-Resource Settings For Global Health Security

Abstract

Background

Antimicrobial resistance (AMR) has emerged as a preeminent threat to global health security, often described as a "silent pandemic" that compromises the efficacy of modern medicine. The burden of AMR is disproportionately concentrated in Low- and Middle-Income Countries (LMICs), particularly within sub-Saharan Africa and South Asia, where the convergence of high infectious disease incidence, unregulated antimicrobial access, and fragile health systems creates a perfect storm for the emergence of multidrug-resistant (MDR) pathogens. In these Low-Resource Settings (LRS), the prevalence of critical priority pathogens—such as extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae and methicillin-resistant Staphylococcus aureus (MRSA)—is alarmingly high, yet critically underreported due to surveillance gaps. Intervention 2, the current standard of care for AMR surveillance in these contexts, relies predominantly on conventional, manual culture-based microbiology and paper-based reporting systems. These methods are characterized by labor-intensive workflows, high susceptibility to contamination, prolonged turnaround times (TAT), and significant data loss during manual aggregation, resulting in a "data void" that hinders the development of evidence-based National Action Plans (NAPs). Intervention 1, comprising enhanced laboratory capacity through automated systems (e.g., automated blood culture, molecular diagnostics like GeneXpert, Whole Genome Sequencing) and integrated digital surveillance (e.g., LIMS, WHONET, One Health platforms), has been proposed as a promising alternative to bridge this diagnostic and epidemiological gap.

Objective

The primary aim of this systematic review is to systematically compare the effectiveness of Intervention 1 (Enhanced Diagnostic and Digital Surveillance Systems) versus Intervention 2 (Conventional Manual Microbiology and Paper-Based Reporting) on key outcomes for populations in Low-Resource Settings with suspected drug-resistant infections. Specifically, the review evaluates improvements in diagnostic yield (recovery rates), time-to-detection (TTD), data completeness, and the subsequent utility of surveillance data for clinical decision-making and national policy formulation.

Methods

A systematic review was conducted adhering to the PRISMA 2020 guidelines. We searched major databases including PubMed, Scopus, Embase, and relevant grey literature sources (WHO, Fleming Fund, MSF Science Portal) for studies published up to 2024. The PICO framework was utilized to define the scope: Population (patients and surveillance systems in LRS); Intervention (automated diagnostics and digital data platforms); Comparison (manual culture and paper-based reporting); and Outcomes (diagnostic yield, contamination rates, TTD, and surveillance system maturity scores). The quality of included studies was assessed using the Cochrane Risk of Bias tool for comparative diagnostic studies and the WHO Laboratory Assessment Tool (LAT) or SLIPTA checklists for observational surveillance reports.

Results

The review identified a distinct dichotomy in performance between the two interventions. Automated blood culture systems (Intervention 1) demonstrated a significantly higher pathogen recovery rate (36.5%) compared to manual methods (24.0%) and reduced the time-to-detection by approximately 2.5 days. However, the analysis revealed that contamination rates remained high across both methods in LRS contexts (~43-48%), highlighting that pre-analytical variables such as phlebotomy technique are critical determinants of success independent of the diagnostic platform. Molecular platforms like GeneXpert showed high sensitivity (>90%) for specific pathogens like Mycobacterium tuberculosis but demonstrated variable concordance with culture for broad bacterial surveillance. In terms of surveillance systems, early implementation of WHO GLASS revealed that while digital platforms like WHONET improve data standardization, over 40% of African countries lacked recent data due to foundational laboratory weaknesses.

Conclusion

Enhanced laboratory and surveillance systems (Intervention 1) offer superior technical performance regarding diagnostic capability and data speed compared to conventional methods. However, their effectiveness in LRS is heavily modulated by infrastructural determinants, including supply chain stability, electricity consistency, and staff capacity. Automation solves the "sensitivity gap" but does not resolve the "sustainability gap" without concomitant health system strengthening. The review concludes that a hybrid approach—leveraging simplified, quality-assured bacteriology (e.g., MSF Mini-Labs) alongside strategic automation at reference nodes—is critical for sustainable Global Health Security.