Evidence map›Paper›PMID 33276742›Full record

ArticleBMC infectious diseases2020

Revealing two dynamic dengue epidemic clusters in Thailand.

Jue Tao Lim, Yiting Han, Borame Sue Lee Dickens, Esther Li Wen Choo, Lawrence Zheng Xiong Chew, Alex R Cook

Abstract read
In one paragraph

Article in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Mapping landscape changes to address dengue fever risk in Laos and Thailand.Current research in parasitology & vector-borne diseases · 2026
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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

6 authors.

Jue Tao LimSaw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore, Singapore. ephljt@nus.edu.sg.
Yiting HanSaw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore, Singapore.
Borame Sue Lee DickensSaw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore, Singapore.
Esther Li Wen ChooSaw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore, Singapore.
Lawrence Zheng Xiong ChewSaw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore, Singapore.
Alex R CookSaw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore, Singapore.

Funding

National Medical Research Council NMRC/CG/C026/2017 NUHS
6 · The paper itself

Abstract

backgroundThailand is home to around 69 million individuals. Dengue is hyper-endemic and all 4 serotypes are in active circulation in the country. Dengue outbreaks occur almost annually within Thailand in at least one province but the spatio-temporal and environmental interface of these outbreaks has not been studied.

methodsWe develop Bayesian regime switching (BRS) models to characterize outbreaks, their persistence and infer their likelihood of occurrence across time for each administrative province where dengue case counts are collected. BRS was compared against two other classification tools and their agreement is assessed. We further examine how these spatio-temporal clusters of outbreak clusters arise by comparing reported dengue case counts, urban population, urban land cover, climate and flight volumes on the province level.

resultsTwo dynamic dengue epidemic clusters were found nationally. One cluster consists of 47 provinces and is highly outbreak prone. Provinces with a large number of case counts, urban population, urban land cover and incoming flight passengers are associated to the epidemic prone cluster of dengue. Climate has an effect on determining the probability of outbreaks over time within provinces, but have less influence on whether provinces belong to the epidemic prone cluster. BRS found high agreement with other classification tools.

conclusionsImportation and urbanization drives the risk of outbreaks across regions strongly. In provinces estimated to have high epidemic persistence, more resource allocation to vector control should be applied to those localities as heightened transmission counts are likely to occur over a longer period of time. Clustering of epidemic and non-epidemic prone areas also highlights the need for prioritization of resource allocation for disease mitigation over provinces in Thailand.

Indexed as

EpidemicsModels, StatisticalBayes TheoremClimateCluster AnalysisDengueDengue VirusEndemic DiseasesHealth Care RationingHumansSerogroupThailandUrbanizationUrban PopulationClustersDengueOutbreaksThailand

Identifiers

PMID33276742
PMCPMC7718674

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.