Evidence map›Paper›PMID 33906628›Full record

ArticleBMC public health2021

Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand.

Gerhart Knerer, Christine S M Currie, Sally C Brailsford

Abstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. ExploitingPathogens (Basel, Switzerland) · 2025
    Review
  3. Review
  4. [Rapid review: effectiveness of theRevista panamericana de salud publica = Pan American journal of public health · 2024
    Article
  5. Review
  6. Article
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Gerhart KnererMathematical Sciences, University of Southampton, Highfield, Southampton, SO17 1BJ, UK. gk205@soton.ac.uk.
Christine S M CurrieMathematical Sciences, University of Southampton, Highfield, Southampton, SO17 1BJ, UK.
Sally C BrailsfordSouthampton Business School, University of Southampton, Highfield, Southampton, SO17 1BJ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the challenges that dengue fever (DF) presents to healthcare systems and societies, public health officials must determine where best to allocate scarce resources and restricted budgets. Constrained optimization (CO) helps to address some of the acknowledged limitations of conventional health economic analyses and has typically been used to identify the optimal allocation of resources across interventions subject to a variety of constraints.

methodsA dynamic transmission model was developed to predict the number of dengue cases in Thailand at steady state. A CO was then applied to identify the optimal combination of interventions (release of Wolbachia-infected mosquitoes and paediatric vaccination) within the constraints of a fixed budget, set no higher than cost estimates of the current vector control programme, to minimize the number of dengue cases and disability-adjusted life years (DALYs) lost. Epidemiological, cost, and effectiveness data were informed by national data and the research literature. The time horizon was 10 years. Scenario analyses examined different disease management and intervention costs, budget constraints, vaccine efficacy, and optimization time horizon.

resultsUnder base-case budget constraints, the optimal coverage of the two interventions to minimize dengue incidence was predicted to be nearly equal (Wolbachia 50%; paediatric vaccination 49%) with corresponding coverages under lower bound (Wolbachia 54%; paediatric vaccination 10%) and upper bound (Wolbachia 67%; paediatric vaccination 100%) budget ceilings. Scenario analyses indicated that the most impactful situations related to the costs of Wolbachia and paediatric vaccination with decreases/ increases in costs of interventions demonstrating a direct correlation with coverage (increases/ decreases) of the respective control strategies under examination.

conclusionsDetermining the best investment strategy for dengue control requires the identification of the optimal mix of interventions to implement in order to maximize public health outcomes, often under fixed budget constraints. A CO model was developed with the objective of minimizing dengue cases (and DALYs lost) over a 10-year time horizon, within the constraints of the estimated budgets for vector control in the absence of vaccination and Wolbachia. The model provides a tool for developing estimates of optimal coverage of combined dengue control strategies that minimize dengue burden at the lowest budget.

Indexed as

CulicidaeDengueWolbachiaAnimalsChildHumansMosquito VectorsThailandConstrained optimizationDengueVaccination Wolbachia

Identifiers

PMID33906628
PMCPMC8080389

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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.