Evidence map›Paper›PMID 38106890›Full record

ArticleFrontiers in public health2023

Prior water availability modifies the effect of heavy rainfall on dengue transmission: a time series analysis of passive surveillance data from southern China.

Qu Cheng, Qinlong Jing, Philip A Collender, Jennifer R Head, Qi Li, Hailan Yu, Zhichao Li, Yang Ju, Tianmu Chen, Peng Wang and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 7 institutions in 3 countries.

Qu Cheng *Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Qinlong Jing *Department of Infectious Diseases, Guangzhou Center for Disease Control and Prevention, Guangzhou, China.
Philip A CollenderDivision of Environmental Health Sciences, School of Public Health, , University of California, Berkeley, Berkeley, CA, United States.
Jennifer R HeadDivision of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA, United States.
Qi LiDepartment of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Hailan YuDepartment of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhichao LiKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Yang JuSchool of Architecture and Urban Planning, Nanjing University, Nanjing, China.
Tianmu ChenState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China.
Peng WangDepartment of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Eimear ClearyWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom.
Shengjie LaiWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom.
Huazhong University of Science and Technology · CNUniversity of California, Berkeley · USUniversity of Southampton · GBChinese Academy of Sciences · CNGuangzhou Center for Disease Control and Prevention · CNNanjing University · CNXiamen University · CN

Funding

Human mobility models to forecast disease dynamics and the effectiveness of public health interventionsR01AI160780 · NIAID · JOHNS HOPKINS UNIVERSITY · PI CUMMINGS, DEREK A, WESOLOWSKI, AMY · 2021 to 2025
$3.3M
NIAID NIH HHS R01 AI160780
6 · The paper itself

Abstract

Introduction: Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions, potentially due to the neglect of prior water availability in mosquito breeding sites as an effect modifier. Methods: In this study, we addressed this research gap by considering the impact of prior water availability for the first time. We measured prior water availability as the cumulative precipitation over the preceding 8 weeks and utilized a distributed lag non-linear model stratified by the level of prior water availability to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China. Results: Our findings suggest that the effects of heavy rainfall are likely to be modified by prior water availability. A 24-55 day lagged impact of heavy rainfall was associated with an increase in dengue risk when prior water availability was low, with the greatest incidence rate ratio (IRR) of 1.37 [95% credible interval (CI): 1.02-1.83] occurring at a lag of 27 days. In contrast, a heavy rainfall lag of 7-121 days decreased dengue risk when prior water availability was high, with the lowest IRR of 0.59 (95% CI: 0.43-0.79), occurring at a lag of 45 days. Discussion: These findings may help to reconcile the inconsistent conclusions reached by previous studies and improve our understanding of the complex relationship between heavy rainfall and dengue infection risk.

Indexed as

DengueAnimalsChinaIncidenceTime FactorsWaterWaterdengueDLNMGuangzhouheavy rainfall eventsprior water availability

Identifiers

PMID38106890
PMCPMC10722414
OpenAlexW4389265527

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.