Diagnostic Approaches for Acute Febrile Illness in Low-Income Contexts

Acute febrile illness (AFI) in resource-limited settings presents a complex diagnostic challenge due to non-specific clinical presentations, overlapping symptomatology among malaria, bacterial and viral infections, and scarce laboratory infrastructure. Historically, presumptive treatment—most notably for malaria—has dominated clinical practice, often resulting in inappropriate antimicrobial use and unrecognised alternative aetiologies. Recent advances seek to redefine case management through expanded point-of-care testing, syndromic algorithms and integrated diagnostic platforms. Rapid diagnostic tests (RDTs) for malaria have improved parasitological confirmation but remain limited by sensitivity, species coverage and quality control. Molecular assays, including multiplex PCR and metagenomic sequencing, offer broader detection of bacterial, viral and parasitic pathogens but face barriers of cost, technical expertise and turnaround time. Probabilistic decision models and syndromic surveillance tools are being refined to guide empirical therapy when confirmatory tests are unavailable. Innovations in modular and portable platforms aim to decentralise diagnostics, reduce time to result and inform antimicrobial stewardship. Strengthening regional reference laboratories, aligning diagnostic strategies with local epidemiology and fostering public–private partnerships are critical to ensure sustainable access. These approaches—when combined with training, quality assurance and data linkage to health systems—have the potential to transform AFI management, reduce mortality, curb antimicrobial resistance and advance universal health coverage in low-income regions.

Research from Nature Portfolio

Recent modelling work has examined how declining malaria prevalence alters antibiotic prescribing in paediatric populations. A probabilistic decision-tree framework, calibrated with hospital data from Ghana, predicts that a 50 per cent reduction in malaria incidence could reduce antibiotic use in febrile children by around 10 per cent. The study highlights that while successful malaria control lessens empirical antibiotic exposure, substantial overprescription persists in the absence of accurate non-malarial diagnostics. This underscores the need for field-adapted assays capable of distinguishing alternative causes of AFI and for decision support tools that integrate local epidemiological trends into prescribing algorithms.

Diagnostic Approaches for Acute Febrile Illness in Low-Income Contexts publication trend

The graph below shows the total number of articles in diagnostic approaches for acute febrile illness in low-income contexts across all publications each year (not limited to Nature Index journals).

Technical terms

Acute febrile illness (AFI): A rapid-onset fever syndrome often caused by diverse pathogens and characterised by non-specific clinical signs.

Metagenomic next-generation sequencing (mNGS): High-throughput, unbiased sequencing that detects multiple pathogens simultaneously from clinical samples.

Syndromic surveillance: Monitoring of aggregated symptom patterns to detect and characterise disease outbreaks when specific aetiologies are undetermined.

Probabilistic decision tree model: A computational tool that uses conditional probabilities to predict clinical outcomes and guide empirical treatment choices.

References

1. Advancing Access to Diagnostic Tools Essential for Universal Health Coverage and Antimicrobial Resistance Prevention: An Overview of Trials in Sub-Saharan Africa. Clinical Infectious Diseases (2023).
2. Prevalence of fever of unidentified aetiology in East African adolescents and adults: a systematic review and meta-analysis. Infectious Diseases of Poverty (2023).
3. Next-generation sequencing survey of acute febrile illness in Senegal (2020–2022). Frontiers in Microbiology (2024).
4. Modeling pediatric antibiotic use in an area of declining malaria prevalence. Scientific Reports (2024).