Evidence map›Paper›PMID 35051176›Full record

ArticlePLoS computational biology2022

Fine-scale estimation of effective reproduction numbers for dengue surveillance.

Janet Ong, Stacy Soh, Soon Hoe Ho, Annabel Seah, Borame Sue Dickens, Ken Wei Tan, Joel Ruihan Koo, Alex R Cook, Daniel R Richards, Leon Yan-Feng Gaw and 2 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2022. 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.

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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

12 authors.

Janet OngEnvironmental Health Institute, National Environment Agency, Singapore.ORCID 0000-0001-8792-318X
Stacy SohEnvironmental Health Institute, National Environment Agency, Singapore.ORCID 0000-0002-4503-7419
Soon Hoe HoEnvironmental Health Institute, National Environment Agency, Singapore.
Annabel SeahEnvironmental Health Institute, National Environment Agency, Singapore.ORCID 0000-0002-0172-0224
Borame Sue DickensSaw Swee Hock School of Public Health, National University of Singapore, Singapore.ORCID 0000-0003-1592-1745
Ken Wei TanSaw Swee Hock School of Public Health, National University of Singapore, Singapore.
Joel Ruihan KooSaw Swee Hock School of Public Health, National University of Singapore, Singapore.ORCID 0000-0002-9798-1751
Alex R CookSaw Swee Hock School of Public Health, National University of Singapore, Singapore.
Daniel R RichardsManaaki Whenua-Landcare Research, Lincoln, New Zealand.ORCID 0000-0002-8196-8421
Leon Yan-Feng GawSchool of Design and Environment, National University of Singapore, Singapore.ORCID 0000-0002-9344-4385
Lee Ching NgEnvironmental Health Institute, National Environment Agency, Singapore.
Jue Tao LimEnvironmental Health Institute, National Environment Agency, Singapore.ORCID 0000-0002-2245-0331

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effective reproduction number Rt is an epidemiological quantity that provides an instantaneous measure of transmission potential of an infectious disease. While dengue is an increasingly important vector-borne disease, few have used Rt as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of Rt for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010-2020, we estimated Rt by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of Rt from each proposed method and determined exogenous temporal and spatial drivers for Rt in relation to a wide range of environmental and anthropogenic factors. At the national level, both methods achieved satisfactory model performance (R2EpiEstim = 0.95, R2EpiFilter = 0.97), but disparities in performance were large at finer spatial scales when case counts are low (MASE EpiEstim = 1.23, MASEEpiFilter = 0.59). Impervious surfaces and vegetation with structure dominated by human management (without tree canopy) were positively associated with increased transmission intensity. Vegetation with structure dominated by human management (with tree canopy), on the other hand, was associated with lower dengue transmission intensity. We showed that dengue outbreaks were preceded by sustained periods of high transmissibility, demonstrating the potential of Rt as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of Rt at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response.

Indexed as

Population SurveillanceAnimalsDengueDisease OutbreaksHumansMosquito VectorsSingapore

Identifiers

PMID35051176
PMCPMC8836367

What OpenQuestion holds

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LicenceCC BY
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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.