Evidence map›Paper›PMID 25881185›Full record

ArticleMalaria journal2015

Malaria incidence from 2005-2013 and its associations with meteorological factors in Guangdong, China.

Cui Guo, Lin Yang, Chun-Quan Ou, Li Li, Yan Zhuang, Jun Yang, Ying-Xue Zhou, Jun Qian, Ping-Yan Chen, Qi-Yong Liu

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
6.6field-weighted citation impact, top 3% 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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 115 citations in OpenAlex.

  1. Differences of Rainfall-Malaria Associations in Lowland and Highland in Western Kenya.International journal of environmental research and public health · 2019
    Pooled it
  2. Article
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  6. The malaria transmission in Anhui province China.Infectious Disease Modelling · 2023
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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

10 authors at 3 institutions in 2 countries.

Cui GuoState Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. guocui815@163.com.
Lin YangDepartment of Nursing, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China. l.yang@polyu.edu.hk.
Chun-Quan OuState Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. ouchunquan@hotmail.com.
Li LiState Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. lylygdsg@163.com.
Yan ZhuangState Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. zhuangy178@126.com.
Jun YangState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. smart_yjun@163.com.
Ying-Xue ZhouState Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. ying2360@126.com.
Jun QianDepartment of Mathematics and Physics, School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China. qianjun_gz@126.com.
Ping-Yan ChenState Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. chenpy99@126.com.
Qi-Yong LiuState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. liuqiyong@cdc.cn.
Southern Medical University · CNNational Institute for Communicable Disease Control and Prevention · CNHong Kong Polytechnic University · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe temporal variation of malaria incidence has been linked to meteorological factors in many studies, but key factors observed and corresponding effect estimates were not consistent. Furthermore, the potential effect modification by individual characteristics is not well documented. This study intends to examine the delayed effects of meteorological factors and the sub-population's susceptibility in Guangdong, China.

methodsThe Granger causality Wald test and Spearman correlation analysis were employed to select climatic variables influencing malaria. The distributed lag non-linear model (DLNM) was used to estimate the non-linear and delayed effects of weekly temperature, duration of sunshine, and precipitation on the weekly number of malaria cases after controlling for other confounders. Stratified analyses were conducted to identify the sub-population's susceptibility to meteorological effects by malaria type, gender, and age group.

resultsAn incidence rate of 1.1 cases per 1,000,000 people was detected in Guangdong from 2005-2013. High temperature was associated with an observed increase in malaria incidence, with the effect lasting for four weeks and a maximum relative risk (RR) of 1.57 (95% confidence interval (CI): 1.06-2.33) by comparing 30°C to the median temperature. The effect of sunshine duration peaked at lag five and the maximum RR was 1.36 (95% CI: 1.08-1.72) by comparing 24 hours/week to 0 hours/week. A J-shaped relationship was found between malaria incidence and precipitation with a threshold of 150 mm/week. Over the threshold, precipitation increased malaria incidence after four weeks with the effect lasting for 15 weeks, and the maximum RR of 1.55 (95% CI: 1.18-2.03) occurring at lag eight by comparing 225 mm/week to 0 mm/week. Plasmodium falciparum was more sensitive to temperature and precipitation than Plasmodium vivax. Females had a higher susceptibility to the effects of sunshine and precipitation, and children and the elderly were more sensitive to the change of temperature, sunshine duration, and precipitation.

conclusionTemperature, duration of sunshine and precipitation played important roles in malaria incidence with effects delayed and varied across lags. Climatic effects were distinct among sub-groups. This study provided helpful information for predicting malaria incidence and developing the future warning system.

Indexed as

Meteorological ConceptsAdolescentAdultChildChild, PreschoolChinaFemaleHumansIncidenceInfantInfant, NewbornMalariaMaleMiddle AgedNonlinear DynamicsRisk

Identifiers

PMID25881185
PMCPMC4389306
OpenAlexW2129315810

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.