Evidence map›Paper›PMID 34520691›Full record

ArticleJournal of the Royal Society, Interface2021

Hyperendemicity associated with increased dengue burden.

Jue Tao Lim, Borame Sue Dickens, Ken Wei Tan, Joel Ruihan Koo, Annabel Seah, Soon Hoe Ho, Janet Ong, Jayanthi Rajarethinam, Stacy Soh, Alex R Cook and 1 more

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  9. Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models.International journal of environmental research and public health · 2022
    Review
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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

11 authors.

Jue Tao LimEnvironmental Health Institute, National Environmental Agency, Singapore.ORCID 0000-0002-2245-0331
Borame Sue DickensSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Ken Wei TanSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Joel Ruihan KooSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Annabel SeahEnvironmental Health Institute, National Environmental Agency, Singapore.
Soon Hoe HoEnvironmental Health Institute, National Environmental Agency, Singapore.
Janet OngEnvironmental Health Institute, National Environmental Agency, Singapore.
Jayanthi RajarethinamEnvironmental Health Institute, National Environmental Agency, Singapore.
Stacy SohEnvironmental Health Institute, National Environmental Agency, Singapore.
Alex R CookSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Lee Ching NgEnvironmental Health Institute, National Environmental Agency, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over 105 million dengue infections are estimated to occur annually. Understanding the disease dynamics of dengue is often difficult due to multiple strains circulating within a population. Interactions between dengue serotype dynamics may result in complex cross-immunity dynamics at the population level and create difficulties in terms of formulating intervention strategies for the disease. In this study, a nationally representative 16-year time series with over 43 000 serotyped dengue infections was used to infer the long-run effects of between and within strain interactions and their impacts on past outbreaks. We used a novel identification strategy incorporating sign-identified Bayesian vector autoregressions, using structural impulse responses, historical decompositions and counterfactual analysis to conduct inference on dengue dynamics post-estimation. We found that on the population level: (i) across-serotype interactions on the population level were highly persistent, with a one time increase in any other serotype associated with long run decreases in the serotype of interest (range: 0.5-2.5 years) and (ii) over 38.7% of dengue cases of any serotype were associated with across-serotype interactions. The findings in this paper will substantially impact public health policy interventions with respect to dengue.

Indexed as

DengueDengue VirusBayes TheoremDisease OutbreaksHumansSerogroupBayesian statisticsdenguehyperendemicitymodellingserotypes

Identifiers

PMID34520691
PMCPMC8440027

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.