Evidence map›Paper›PMID 41573804›Full record

Observational studyFrontiers in public health2025

Assessing the correlation between STAR health risk forecasts with actual health emergencies in West and Central Africa: a three-year analysis.

Daniel Yota, Christian Eric Massidi, Ambrose Talisuna, Omer Njajou Tchikamgoua

Abstract readObservational Study
In one paragraph

Observational study in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Daniel YotaWorld Health Organization, Dakar, Senegal.
Christian Eric MassidiWorld Health Organization, Dakar, Senegal.
Ambrose TalisunaWorld Health Organization, Nairobi, Kenya.
Omer Njajou TchikamgouaPublic Health Department, Université des Montagnes, Bangangté, Cameroon.

Funding

World Health Organization 001
6 · The paper itself

Abstract

Introduction: This study evaluates the Strategic Tool for Assessing Risks (STAR), developed by the World Health Organization (WHO), for its effectiveness in predicting public health emergencies across West and Central Africa during the period 2022-2024. STAR applies a composite risk scoring system based on four dimensions likelihood, severity, vulnerability, and coping capacity to classify hazards such as measles, cholera, and meningitis into five risk categories ranging from very low to very high. Methods: Using a retrospective observational design, the study integrates quantitative outbreak data with qualitative assessments of preparedness actions across nine countries. The analysis demonstrates that STAR's predictive accuracy varies significantly by hazard and context. Results: Meningitis forecasts were consistently accurate, primarily due to the disease's strong seasonality and well-established epidemiological patterns in the African meningitis belt. In contrast, predictions for measles and cholera were less reliable, influenced by fluctuating immunization coverage, socio-political instability, and environmental factors such as water and sanitation conditions. Case studies illustrate these discrepancies: Burkina Faso's cholera risk was overestimated, resulting in zero reported cases despite a high-risk classification, while Guinea's measles outbreak closely matched STAR's high-risk prediction. The findings also highlight that effective preparedness measures, including vaccination campaigns, hygiene promotion, and cross-border coordination, can mitigate high-risk scenarios, as observed in Gabon and Burkina Faso. Key themes emerging from the analysis include STAR's strength in forecasting predictable hazards and its limitations due to static inputs and low geographic granularity. Discussion: While STAR is not a statistical forecasting model, its participatory, multi-sectoral approach provides strategic value by guiding planning, prioritization, and resource allocation for health emergency preparedness. It enables countries to optimize limited resources, prioritize highrisk hazards (scores 16-25), and implement preventive actions. Recommendations for improvement include recalibrating scoring parameters, integrating real-time surveillance and climate data, enhancing seasonality modeling, and increasing geographic resolution. When combined with dynamic data systems and collaborative efforts, STAR remains a critical strategic tool for strengthening regional public health resilience and supporting WHO's Health Emergency Framework and all-hazards preparedness planning.

Indexed as

Disease OutbreaksEmergenciesPublic HealthAfrica, CentralAfrica, WesternCholeraForecastingHumansMeaslesMeningitisRetrospective StudiesRisk AssessmentWorld Health Organizationemergency preparednessoccurrencepredictionrisk assessmentSTAR tool

Identifiers

PMID41573804
PMCPMC12819622

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.