Evidence map›Paper›PMID 39733127›Full record

ArticleScientific reports2024

The epidemiological profile and morbidity-mortality patterns of technological disasters in the Americas from 2000 to 2021: a cross-sectional study.

Andrea Fernández García, Rick Kye Gan, José Antonio Cernuda Martínez, Pedro Arcos González

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Andrea Fernández GarcíaUnit for Research in Emergency and Disaster, Department of Preventive Medicine and Public Health, Universidad de Oviedo, Oviedo, 33006, Spain.
Rick Kye GanUnit for Research in Emergency and Disaster, Department of Preventive Medicine and Public Health, Universidad de Oviedo, Oviedo, 33006, Spain.
José Antonio Cernuda MartínezUnit for Research in Emergency and Disaster, Department of Preventive Medicine and Public Health, Universidad de Oviedo, Oviedo, 33006, Spain. cernudajose@uniovi.es.
Pedro Arcos GonzálezUnit for Research in Emergency and Disaster, Department of Preventive Medicine and Public Health, Universidad de Oviedo, Oviedo, 33006, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Technological disasters in the Americas have significant public health and environmental implications, but there is limited epidemiological analysis of these events. This study aims to characterize the epidemiological profile of technological disasters in the Americas from 2000 to 2021, focusing on morbidity and mortality trends. A retrospective cross-sectional study was conducted. The ANOVA test was applied in the mean rates calculated for each type of disaster. The Mann-Kendall test assessed the presence or absence of temporal trends, and the Dickey-Fuller augmented test was used to determine if the time series were stationary. Predictions were made up to the year 2030 to mean mortality rate per million inhabitants, mean rate of people affected per million inhabitants, and mean rate of people injured per million inhabitants. A total of 733 technological disasters were recorded in the Americas. Statistically significant differences were found between the mean rates of people affected and the mean mortality rates per million inhabitants for each type of technological disaster. No trends were identified. The highest mean mortality rates occurred because of industrial accidents.

Indexed as

DisastersAccidents, OccupationalAmericasCross-Sectional StudiesHumansMorbidityMortalityRetrospective StudiesEpidemiological ProfileMorbidityMortalityPublic Health CrisisTechnological Disasters

Identifiers

PMID39733127
PMCPMC11682408

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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.