Evidence map›Paper›PMID 39473593›Full record

ArticleFrontiers in public health2024

Spatiotemporal modeling of COVID-19 spread: unveiling socioeconomic disparities and patterns, across social classes in the urban population of Kermanshah, Iran.

Alireza Zangeneh, Nasim Hamidipour, Zahra Khazir, Arash Ziapour, Homa Molavi, Zeinab Gholami Kiaee, Raziyeh Teimouri, Ebrahim Shakiba, Moslem Soofi, Fatemeh Khosravi Shadmani

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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.

Alireza ZangenehSocial Development and Health Promotion Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Nasim HamidipourSchool of Nursing and Midwifery, Dezful University of Medical Sciences, Dezful, Iran.
Zahra KhazirDepartment of Public Health, Torbat Jam Faculty of Medical Sciences, Torbat Jam, Iran.
Arash ZiapourCardiovascular Research Center, Imam-Ali Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Homa MolaviDepartment of Engineering Management, School of Engineering, The University of Manchester, Manchester, United Kingdom.
Zeinab Gholami KiaeeDepartment of Statistics, School of Mathematical Science, AmirKabir University of Technology, Tehran, Iran.
Raziyeh TeimouriUniSA Creative, University of South Australia, Adelaide, SA, Australia.
Ebrahim ShakibaSocial Development and Health Promotion Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Moslem SoofiSocial Development and Health Promotion Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Fatemeh Khosravi ShadmaniResearch Center for Environmental Determinants of Health (RCEDH), Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Presenting ongoing outbreaks and the potential for their spread to nearby neighborhoods and social classes may offer a deeper understanding, enable a more efficient reaction to outbreaks, and enable a comprehensive understanding of intricate details for strategic response planning. Hence, this study explored the spatiotemporal spread of COVID-19 outbreaks and prioritization of the risk areas among social classes in the Kermanshah metropolis. Methods: Results: The results revealed that the average epicenter of the disease shifted from the city center in 2020-2021 to the eastern part of the city in 2021. The results related to the SD of the disease showed that more than 70% of the patients were concentrated in this area of the city. The SD of COVID-19 in 2020 compared to 2021 also indicated an increased spread throughout the city. Moran's I test and the hotspot test results showed the emergence of a clustered pattern of the disease. In the Kermanshah metropolis, 58,951 COVID-19 cases were recorded, with 55.76% males and 44.24% females. Social class distribution showed 28.86% upper class, 55.95% middle class, and 15.19% working class. A higher disease prevalence among both males and females in the upper class compared to others. Discussion: Our study designed a spatiotemporal disease spread model, specifically tailored for a densely populated urban area. This model allows for the observation of how COVID-19 propagates both spatially and temporally, offering a deeper understanding of outbreak dynamics in different neighborhoods and social classes of the city.

Indexed as

COVID-19Social ClassSpatio-Temporal AnalysisUrban PopulationAdultCross-Sectional StudiesFemaleHumansIranMaleMiddle AgedSARS-CoV-2Socioeconomic Disparities in HealthSocioeconomic FactorsCOVID-19crisis response strategiesdisease transmissionepidemic managementGISsocioeconomic status

Identifiers

PMID39473593
PMCPMC11519981

What Socratic holds

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LicenceCC BY
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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 Socratic graph.