Evidence map›Paper›PMID 40153405›Full record

ArticlePLoS neglected tropical diseases2025

Integrated rapid risk assessment for dengue fever in settings with limited diagnostic capacity and uncertain exposure: Development of a methodological framework for Tanzania.

Matthias Hans Belau, Juliane Boenecke, Jonathan Ströbele, Mirko Himmel, Daria Dretvić, Ummul-Khair Mustafa, Katharina Sophia Kreppel, Elingarami Sauli, Johanna Brinkel, Ulfia Annette Clemen and 6 more

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Article in PLoS neglected tropical diseases, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

16 authors.

Matthias Hans BelauUniversity Medical Centre Hamburg-Eppendorf, Institute of Medical Biometry and Epidemiology, Hamburg, Germany.ORCID 0000-0003-2141-2162
Juliane BoeneckeDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany.
Jonathan StröbeleDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany.
Mirko HimmelDepartment for Microbiology and Biotechnology, University of Hamburg, Institute for Plant Sciences and Microbiology, Hamburg, Germany.
Daria DretvićDepartment for Microbiology and Biotechnology, University of Hamburg, Institute for Plant Sciences and Microbiology, Hamburg, Germany.
Ummul-Khair MustafaThe Nelson Mandela African Institution of Sciences and Technology, School of Life Sciences and Bioengineering, Arusha, Tanzania.
Katharina Sophia KreppelThe Nelson Mandela African Institution of Sciences and Technology, School of Life Sciences and Bioengineering, Arusha, Tanzania.
Elingarami SauliThe Nelson Mandela African Institution of Sciences and Technology, School of Life Sciences and Bioengineering, Arusha, Tanzania.
Johanna BrinkelDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany.
Ulfia Annette ClemenDepartment Computer Sciences, Hamburg University of Applied Sciences, Hamburg, Germany.
Thomas ClemenDepartment Computer Sciences, Hamburg University of Applied Sciences, Hamburg, Germany.
Wolfgang StreitDepartment for Microbiology and Biotechnology, University of Hamburg, Institute for Plant Sciences and Microbiology, Hamburg, Germany.
Jürgen MayDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany.
Amena Almes AhmadDepartment Health Sciences, Hamburg University of Applied Sciences, Hamburg, Germany.
Ralf ReintjesDepartment Health Sciences, Hamburg University of Applied Sciences, Hamburg, Germany.
Heiko BecherHeidelberg University Hospital, Heidelberg Institute of Global Health, Heidelberg, Germany.

Funding

Epidemiologic Surveillance for Infectious Diseases in Sub-Saharan Africa (ESIDA)German Federal Ministry of Education and Research (BMB)
6 · The paper itself

Abstract

backgroundDengue fever is one of the world's most important re-emerging but neglected infectious diseases. We aimed to develop and evaluate an integrated risk assessment framework to enhance early detection and risk assessment of potential dengue outbreaks in settings with limited routine surveillance and diagnostic capacity.

methodsOur risk assessment framework utilizes the combination of various methodological components: We first focused on (I) identifying relevant clinical signals based on a case definition for suspected dengue, (II) refining the signal for potential dengue diagnosis using contextual data, and (III) determining the public health risk associated with a verified dengue signal across various hazard, exposure, and contextual indicators. We then evaluated our framework using (i) historical clinical signals with syndromic and laboratory-confirmed disease information derived from WHO's Epidemic Intelligence from Open Sources (EIOS) technology using decision tree analyses, and (ii) historical dengue outbreak data from Tanzania at the regional level from 2019 (6,795 confirmed cases) using negative binomial regression analyses adjusted for month and region. Finally, we evaluated a test signal across all steps of our integrated framework to demonstrate the implementation of our multi-method approach.

resultsThe result of the suspected case refinement algorithm for clinically defined syndromic cases was consistent with the laboratory-confirmed diagnosis (dengue yes or no). Regression between confirmed dengue fever cases in 2019 as the dependent variable and a site-specific public health risk score as the independent variable showed strong evidence of an increase in dengue fever cases with higher site-specific risk (rate ratio = 2.51 (95% CI = [1.76, 3.58])).

conclusionsThe framework can be used to rapidly determine the public health risk of dengue outbreaks, which is useful for planning and prioritizing interventions or for epidemic preparedness. It further allows for flexibility in its adaptation to target diseases and geographical contexts.

Indexed as

DengueDisease OutbreaksHumansPublic HealthRisk AssessmentTanzania

Identifiers

PMID40153405
PMCPMC11978086

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