Evidence map›Paper›PMID 35225205›Full record

ArticlePrehospital and disaster medicine2022

Emergency Medical Teams' Responses during the West Japan Heavy Rain 2018: J-SPEED Data Analysis.

Odgerel Chimed-Ochir, Yui Yumiya, Akihiro Taji, Eisaku Kishita, Hisayoshi Kondo, Akinori Wakai, Kouki Akahoshi, Kayoko Chishima, Yoshiki Toyokuni, Yuichi Koido and 1 more

Abstract read
In one paragraph

Article in Prehospital and disaster medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  5. Review
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  7. Article
  8. Article
  9. Exploring the Gender and Age Demographics of Patients Treated by Emergency Medical Teams during Disasters.International journal of environmental research and public health · 2024
    Article
  10. Article
  11. Article
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.

Odgerel Chimed-OchirDepartment of Public Health and Health Policy, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Yui YumiyaDepartment of Public Health and Health Policy, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Akihiro TajiDepartment of Public Health and Health Policy, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Eisaku KishitaHiroshima Prefectural Health and Welfare Bureau, Hiroshima, Japan.
Hisayoshi KondoNational Hospital Organization Headquarters DMAT Secretariat MHLW Japan, Tokyo, Japan.
Akinori WakaiNational Hospital Organization Headquarters DMAT Secretariat MHLW Japan, Osaka City, Japan.
Kouki AkahoshiNational Hospital Organization Headquarters DMAT Secretariat MHLW Japan, Tokyo, Japan.
Kayoko ChishimaNational Hospital Organization Headquarters DMAT Secretariat MHLW Japan, Tokyo, Japan.
Yoshiki ToyokuniNational Hospital Organization Headquarters DMAT Secretariat MHLW Japan, Tokyo, Japan.
Yuichi KoidoNational Hospital Organization Headquarters DMAT Secretariat MHLW Japan, Tokyo, Japan.
Tatsuhiko KuboDepartment of Public Health and Health Policy, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.ORCID https://orcid.org/0000-0001-8822-9181

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionRainfall-induced floods and landslides accounted for 20.7% of all disaster events in Japan from 1985 through 2018 and caused a variety of health problems, both directly and indirectly, including injuries, infectious diseases, exacerbation of pre-existing medical conditions, and psychological issues. More evidence of health problems caused by floods or heavy rain is needed to improve preparedness and preventive measures; however, collecting health data surrounding disaster events is a major challenge due to environmental hazards, logistical constraints, political and economic issues, difficulties in communication among stakeholders, and cultural barriers. In response to the West Japan Heavy Rain in July 2018, Emergency Medical Teams (EMTs) used Japan - Surveillance in Post-Extreme Emergencies and Disasters (J-SPEED) as a daily reporting template, collecting data on the number and type of patients they treated and sending it to an EMT coordination cell (EMTCC) during the response. STUDY

objectiveThe aim of the study was to conduct a descriptive epidemiology study using J-SPEED data to better understand the health problems during floods and heavy rain disasters.

methodsThe number and types of health problems treated by EMTs in accordance with the J-SPEED (Ver 1.0) form were reported daily by 85 EMTs to an EMTCC, where data were compiled during the West Japan Heavy Rain from July 8 through September 11, 2018. Reported items in the J-SPEED form were analyzed by age, gender, area (prefecture), and time period.

resultsThe analysis of J-SPEED data from the West Japan Heavy Rain 2018 revealed the characteristics of a total of 3,617 consultations with the highest number of consultations (2,579; 71.3%) occurring between Day 5 and Day 12 of the 65-day EMT response. During the response period, skin disease was the most frequently reported health event (17.3%), followed by wounds (14.3%), disaster stress-related symptoms (10.0%), conjunctivitis (6.3%), and acute respiratory infections (ARI; 5.4%).

conclusionDuring the response period, skin disease was the most frequently reported health event, followed by wounds, stress, conjunctivitis, and ARIs. The health impacts of a natural disaster are determined by a variety of factors, and the current study's findings are highly context dependent; however, it is expected that as more data are gathered, the consistency of finding will increase.

Indexed as

Emergency Medical TeamEmergency Medical Team minimum data setJapanJ-SPEEDWest Japan heavy rain

Identifiers

PMID35225205
PMCPMC8958047

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Registered trials

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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.