Evidence map›Paper›PMID 37759167›Full record

ArticleBMC public health2023

Hysteresis effects of different levels of storm flooding on susceptible enteric infectious diseases in a central city of China.

Piao-Yi Luo, Meng-Xiang Chen, Wen-Tao Kuang, Han Ni, Jin Zhao, Hao-Yun Dai, Xiang Ren, Shang-Hui Yi, Xiu-Qin Hong, Wen-Ting Zha and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 28% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
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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

11 authors at 1 institution in 1 country.

Piao-Yi Luo *Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
Meng-Xiang Chen *Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
Wen-Tao KuangKey Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
Han NiKey Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
Jin ZhaoKey Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
Hao-Yun DaiKey Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
Xiang RenKey Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
Shang-Hui YiKey Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
Xiu-Qin HongHunan Provincial People's Hospital Affiliated to Hunan Normal University, Changsha, 410000, Hunan, China.
Wen-Ting ZhaKey Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China. 183259829@qq.com.
Yuan LvKey Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China. 284792906@qq.com.
Hunan Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecently, attention has focused on the impact of global climate change on infectious diseases. Storm flooding is an extreme weather phenomenon that not only impacts the health of the environment but also worsens the spread of pathogens. This poses a significant challenge to public health security. However, there is still a lack of research on how different levels of storm flooding affect susceptible enteric infectious diseases over time.

methodsData on enteric infectious diseases, storm flooding events, and meteorology were collected for Changsha, Hunan Province, between 2016 and 2020. The Wilcoxon Rank Sum Test was used to identify the enteric infectious diseases that are susceptible to storm flooding. Then, the lagged effects of different levels of storm flooding on susceptible enteric infectious diseases were analyzed using a distributed lag nonlinear model.

resultsThere were eleven storm flooding events in Changsha from 2016 to 2020, concentrated in June and July. 37,882 cases of enteric infectious diseases were reported. During non-flooding days, the daily incidence rates of typhoid/paratyphoid and bacillary dysentery were 0.3/100,000 and 0.1/100,000, respectively. During flooding days, the corresponding rates increased to 2.0/100,000 and 0.8/100,000, respectively. The incidence rates of both diseases showed statistically significant differences between non-flooding and flooding days. Correlation analysis shows that the best lags for typhoid/paratyphoid and bacillary dysentery relative to storm flooding events may be 1 and 3 days. The results of the distributed lag nonlinear model showed that typhoid/paratyphoid had the highest cumulative RR values of 2.86 (95% CI: 1.71-4.76) and 8.16 (95% CI: 2.93-22.67) after 4 days of general flooding and heavy flooding, respectively; and bacillary dysentery had the highest cumulative RR values of 1.82 (95% CI: 1.40-2.35) and 3.31 (95% CI: 1.97-5.55) after 5 days of general flooding and heavy flooding, respectively.

conclusionsTyphoid/paratyphoid and bacillary dysentery are sensitive enteric infectious diseases related to storm flooding in Changsha. There is a lagging effect of storm flooding on the onset of typhoid/paratyphoid and bacillary dysentery, with the best lagging periods being days 1 and 3, respectively. The cumulative risk of typhoid/paratyphoid and bacillary dysentery was highest at 4/5 days lag, respectively. The higher of storm flooding, the higher the risk of disease, which suggests that the authorities should take appropriate preventive and control measures before and after storm flooding.

Indexed as

Communicable DiseasesDysentery, BacillaryTyphoid FeverChinaHumansUrbanizationDistributed lag nonlinear modelEnteric infectious diseasesLagged effectsStorm flooding

Identifiers

PMID37759167
PMCPMC10537077
OpenAlexW4387096596

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.