Evidence map›Paper›PMID 34114103›Full record

ArticleInternational journal of biometeorology2021

The impacts of precipitation patterns on dengue epidemics in Guangzhou city.

Haorong Meng, Jianpeng Xiao, Tao Liu, Zhihua Zhu, Dexin Gong, Min Kang, Tie Song, Zhiqiang Peng, Aiping Deng, Wenjun Ma

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of biometeorology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
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.

Haorong Meng *Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Jianpeng Xiao *Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Tao LiuGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Zhihua ZhuGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Dexin GongGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Min KangGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Tie SongGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Zhiqiang PengGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Aiping DengGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Wenjun MaGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China. mawj@gdiph.org.cn.

Funding

National Key Research and Development Program of China 2018YFA0606200, 2018YFB0505500, 2018YFB0505503National Natural Science Foundation of China 81773497, 41701460Natural Science Foundation of Guangdong Province 2018A030313729Science and Technology Planning Project of Guangdong Province 2018B020207006, 2019B020208005
6 · The paper itself

Abstract

Some studies have demonstrated that precipitation is an important risk factor of dengue epidemics. However, current studies mostly focused on a single precipitation variable, and few studies focused on the impact of precipitation patterns on dengue epidemics. This study aims to explore optimal precipitation patterns for dengue epidemics. Weekly dengue case counts and meteorological data from 2006 to 2018 in Guangzhou of China were collected. A generalized additive model with Poisson distribution was used to investigate the association between precipitation patterns and dengue. Precipitation patterns were defined as the combinations of three weekly precipitation variables: accumulative precipitation (Pre_A), the number of days with light or moderate precipitation (Pre_LMD), and the coefficient of precipitation variation (Pre_CV). We explored to identify optimal precipitation patterns for dengue epidemics. With a lead time of 10 weeks, minimum temperature, relative humidity, Pre_A, and Pre_LMD were positively associated with dengue, while Pre_CV was negatively associated with dengue. A precipitation pattern with Pre_A of 20.67-55.50 mm per week, Pre_LMD of 3-4 days per week, and Pre_CV less than 1.41 per week might be an optimal precipitation pattern for dengue epidemics in Guangzhou. The finding may be used for climate-smart early warning and decision-making of dengue prevention and control.

Indexed as

DengueEpidemicsChinaClimateHumansIncidencePoisson DistributionTemperatureDengueGeneralized additive modelPrecipitation patternsWeather

Identifiers

What OpenQuestion holds

Textmetadata
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.