Evidence map›Paper›PMID 28137250›Full record

ArticleMalaria journal2017

Describing interaction effect between lagged rainfalls on malaria: an epidemiological study in south-west China.

Yunyun Wu, Zhijiao Qiao, Nan Wang, Hongjie Yu, Zijian Feng, Xiaosong Li, Xing Zhao

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

Article in Malaria journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 9% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Pooled it
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  5. Impact of Climate Variability and Interventions on Malaria Incidence and Forecasting in Burkina Faso.International journal of environmental research and public health · 2024
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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

7 authors at 2 institutions in 1 country.

Yunyun WuWest China School of Public Health, Sichuan University, No. 17 Section 3, South Renmin Road, 610041, Chengdu, China.
Zhijiao QiaoWest China School of Public Health, Sichuan University, No. 17 Section 3, South Renmin Road, 610041, Chengdu, China.
Nan WangWest China School of Public Health, Sichuan University, No. 17 Section 3, South Renmin Road, 610041, Chengdu, China.
Hongjie YuWest China School of Public Health, Sichuan University, No. 17 Section 3, South Renmin Road, 610041, Chengdu, China.
Zijian FengOffice for Disease Control and Emergency Response, Chinese Centre for Disease Control and Prevention, NE Pacific Street, 102206, Beijing, China.
Xiaosong LiWest China School of Public Health, Sichuan University, No. 17 Section 3, South Renmin Road, 610041, Chengdu, China.
Xing ZhaoWest China School of Public Health, Sichuan University, No. 17 Section 3, South Renmin Road, 610041, Chengdu, China. zhaoxing731@gmail.com.
Sichuan University · CNChinese Center For Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhen discussing the relationship between meteorological factors and malaria, previous studies mainly focus on the interaction between different climatic factors, while the possible interaction within one particular climatic predictor at different lag periods has been largely neglected. In this study, this issue was investigated by exploring the interaction of lagged rainfalls and its impact on malaria epidemics, which is a typical example of those meteorological variables.

methodsThe weekly data of malaria cases and three climatic variables of 30 counties in southwest China from 2004 to 2009 were analysed with the varying coefficient-distributed lag non-linear model. The correlation patterns of the 6th, 9th and 12th week lags would vary over different rainfall levels at the 4th-week lag.

resultsThe non-linear patterns for rainfall at different rainfall levels are distinct from each other. In the low rainfall level at the 4th week lag, the increasing rainfall may promote the transmission of malaria. However, for the high rainfall level at the 4th week lag, evidence shows that the excessive rainfall decreases the risk of malaria.

conclusionThis study reports for the first time that the interaction effect between lagged rainfalls on malaria exists, and highlights the importance of integrating the interaction between lagged predictors in relevant studies, which could help to better understand and predict malaria transmission.

Indexed as

RainChinaClimateHumansIncidenceMalariaNonlinear DynamicsRiskSeasonsTime FactorsInteractionLagMalariaNonlinearRainfall

Identifiers

PMID28137250
PMCPMC5282846
OpenAlexW2580372799

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.