Evidence map›Paper›PMID 28640895›Full record

ArticlePLoS neglected tropical diseases2017

The interplay of climate, intervention and imported cases as determinants of the 2014 dengue outbreak in Guangzhou.

Qu Cheng, Qinlong Jing, Robert C Spear, John M Marshall, Zhicong Yang, Peng Gong

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. The use and reporting of airline passenger data for infectious disease modelling: a systematic review.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2019
    Pooled it
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  5. Trends and Spatial Pattern Analysis of Dengue Cases in Northeast Malaysia.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2022
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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.

Qu ChengMinistry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, People's Republic of China.
Qinlong JingDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China.
Robert C SpearEnvironmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, United States of America.
John M MarshallDivision of Biostatistics and Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, California, United States of America.
Zhicong YangGuangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, People's Republic of China.
Peng GongMinistry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, People's Republic of China.ORCID http://orcid.org/0000-0003-1513-3765

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dengue is a fast spreading mosquito-borne disease that affects more than half of the population worldwide. An unprecedented outbreak happened in Guangzhou, China in 2014, which contributed 52 percent of all dengue cases that occurred in mainland China between 1990 and 2015. Our previous analysis, based on a deterministic model, concluded that the early timing of the first imported case that triggered local transmission and the excessive rainfall thereafter were the most important determinants of the large final epidemic size in 2014. However, the deterministic model did not allow us to explore the driving force of the early local transmission. Here, we expand the model to include stochastic elements and calculate the successful invasion rate of cases that entered Guangzhou at different times under different climate and intervention scenarios. The conclusion is that the higher number of imported cases in May and June was responsible for the early outbreak instead of climate. Although the excessive rainfall in 2014 did increase the success rate, this effect was offset by the low initial water level caused by interventions in late 2013. The success rate is strongly dependent on mosquito abundance during the recovery period of the imported case, since the first step of a successful invasion is infecting at least one local mosquito. The average final epidemic size of successful invasion decreases exponentially with introduction time, which means if an imported case in early summer initiates the infection process, the final number infected can be extremely large. Therefore, dengue outbreaks occurring in Thailand, Singapore, Malaysia and Vietnam in early summer merit greater attention, since the travel volumes between Guangzhou and these countries are large. As the climate changes, destroying mosquito breeding sites in Guangzhou can mitigate the detrimental effects of the probable increase in rainfall in spring and summer.

Indexed as

ClimateClimate ChangeSeasonsTravelAnimalsChinaCulicidaeDengueDengue VirusDisease OutbreaksHumansMalaysiaModels, TheoreticalSingaporeThailandVietnam

Identifiers

PMID28640895
PMCPMC5507464

What OpenQuestion holds

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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.