Evidence map›Paper›PMID 37693392›Full record

ArticleResearch square2023

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 · greenAbstract readPreprint
In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 8 institutions in 3 countries.

Qu ChengHuazhong University of Science and Technology.
Qinlong JingGuangzhou Center for Disease Control and Prevention.
Philip A CollenderUniversity of California.
Jennifer R HeadUniversity of California, Berkeley.
Qi LiHuazhong University of Science and Technology.
Hailan YuHuazhong University of Science and Technology.
Zhichao LiChinese Academy of Sciences.
Yang JuNanjing University.
Tianmu ChenXiamen University.
Peng WangHuazhong University of Science and Technology.
Eimear ClearyUniversity of Southampton.
Shengjie LaiUniversity of Southampton.
Huazhong University of Science and Technology · CNUniversity of Southampton · GBChinese Academy of Sciences · CNGuangzhou Center for Disease Control and Prevention · CNNanjing University · CNUniversity of California, Berkeley · USUniversity of California System · USXiamen 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

Background: 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. Methods: In this study, we use a distributed lag non-linear model to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China, stratified by prior water availability. 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. Conclusions: 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

dengueheavy rainfall eventsprior water availability

Identifiers

PMID37693392
PMCPMC10491345
OpenAlexW4386307341

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.