Evidence map›Paper›PMID 36167577›Full record

ArticleParasites & vectors2022

Species-specific climate Suitable Conditions Index and dengue transmission in Guangdong, China.

Xinting Lu, Hilary Bambrick, Francesca D Frentiu, Xiaodong Huang, Callan Davis, Zhongjie Li, Weizhong Yang, Gregor J Devine, Wenbiao Hu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Parasites & vectors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
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

9 citing papers in PubMed, 13 citations in OpenAlex.

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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

9 authors at 4 institutions in 2 countries.

Xinting LuSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
Hilary BambrickSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
Francesca D FrentiuCentre for Immunology and Infection Control, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia.
Xiaodong HuangCentre for Immunology and Infection Control, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia.
Callan DavisSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
Zhongjie LiDivision of Infectious Disease, Key Laboratory of Surveillance and Early Warning of Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China.
Weizhong YangDivision of Infectious Disease, Key Laboratory of Surveillance and Early Warning of Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China.
Gregor J DevineMosquito Control Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Wenbiao HuSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia. w2.hu@qut.edu.au.
Queensland University of Technology · AUChinese Center For Disease Control and Prevention · CNPeking Union Medical College Hospital · CNQIMR Berghofer Medical Research Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOptimal climatic conditions for dengue vector mosquito species may play a significant role in dengue transmission. We previously developed a species-specific Suitable Conditions Index (SCI) for Aedes aegypti and Aedes albopictus, respectively. These SCIs rank geographic locations based on their climatic suitability for each of these two dengue vector species and theoretically define parameters for transmission probability. The aim of the study presented here was to use these SCIs together with socio-environmental factors to predict dengue outbreaks in the real world.

methodsA negative binomial regression model was used to assess the relationship between vector species-specific SCI and autochthonous dengue cases after accounting for potential confounders in Guangdong, China. The potential interactive effect between the SCI for Ae. albopictus and the SCI for Ae. aegypti on dengue transmission was assessed.

resultsThe SCI for Ae. aegypti was found to be positively associated with autochthonous dengue transmission (incidence rate ratio: 1.06, 95% confidence interval: 1.03, 1.09). A significant interaction effect between the SCI of Ae. albopictus and the SCI of Ae. aegypti was found, with the SCI of Ae. albopictus significantly reducing the effect of the SCI of Ae. aegypti on autochthonous dengue cases. The difference in SCIs had a positive effect on autochthonous dengue cases.

conclusionsOur results suggest that dengue fever is more transmittable in regions with warmer weather conditions (high SCI for Ae. aegypti). The SCI of Ae. aegypti would be a useful index to predict dengue transmission in Guangdong, China, even in dengue epidemic regions with Ae. albopictus present. The results also support the benefit of the SCI for evaluating dengue outbreak risk in terms of vector sympatry and interactions in the absence of entomology data in future research.

Indexed as

AedesDengueDengue VirusAnimalsChinaMosquito VectorsAedes aegyptiAedes albopictusDengue transmissionInteractive effectSuitable conditional index

Identifiers

PMID36167577
PMCPMC9516795
OpenAlexW4297338398

What OpenQuestion holds

Textmetadata
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.