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Review
. 2023 Nov 17;12(1):e12.
doi: 10.22037/aaem.v12i1.2157. eCollection 2024.

The Impact of The COVID-19 Pandemic on Hospital Admissions Due to Road Traffic Crashes; a Systematic Review and Meta-Analysis

Neda Kabiri  1 , Amin Abbasi  2 , Fariba Pashazadeh  1 , Sakineh Hajebrahimi  1   3 , Hassan Soleimanpour  4
Affiliations
Review

The Impact of The COVID-19 Pandemic on Hospital Admissions Due to Road Traffic Crashes; a Systematic Review and Meta-Analysis

Neda Kabiri et al. Arch Acad Emerg Med. .

Abstract

Introduction: During the unprecedented COVID-19 lockdowns, road traffic was limited, and a change in the traumatic emergency admission pattern was anticipated. We conducted the current systematic review and meta-analysis to assess the impact of the COVID-19 pandemic on hospital admissions due to road traffic crashes.

Methods: This systematic review and meta-analysis was conducted based on the Joanna Briggs Institute (JBI) instructions. The following databases were searched: PubMed, ISI Web of Knowledge, Scopus, ProQuest, and the Cochrane Library. Two independent reviewers screened articles based on the inclusion criteria for the review and assessed the methodological quality of the included studies using an appropriate appraisal checklist, introduced by the JBI, based on the study type. The meta-analysis was performed using Comprehensive meta-analysis (CMA) software. Considering the heterogeneity among studies, a random effect model was adopted to estimate the pooled effect with 95% confidence interval (CI) for binary outcomes.

Results: A total of 13 studies were included in this systematic review, and all of them were considered for meta-analysis. According to the meta-analysis, differences in hospital admission rates during the COVID-19 pandemic and one year before this pandemic were statistically significant [RR: 0.685 CI 95% (0.578 -0.813) p<0.00001]. The heterogeneity assessment of the included studies in the meta-analysis showed high heterogeneity (I2=78%, p<0.00001).

Conclusion: The results of this systematic review showed that the COVID-19 pandemic dramatically reduced the number of hospital admissions related to road traffic crashes because of both quarantines and lifestyle changes. Health policymakers and top health managers might use the results of this systematic review in similar contexts in the future.

Keywords: Accidents; COVID-19; meta-analysis; systematic review; traffic.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram of study
Figure 2
Figure 2
Forest plot of comparison of hospital admissions due to road traffic crashes during COVID-19 period versus non-COVID-19 period. CI: confidence interval
Figure 3
Figure 3
The funnel plot assessing publication bias
See this image and copyright information in PMC

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References

    1. Lefrançois T, Malvy D, Atlani-Duault L, Benamouzig D, Druais P-L, Yazdanpanah Y, Delfraissy J-F, Lina B. After 2 years of the COVID-19 pandemic, translating One Health into action is urgent. Lancet. 2023;401:789–794. - PMC - PubMed
    1. Shahsavarinia K, Amiri P, Mousavi Z, Gilani N, Saadati M, Soleimanpour H. Prediction of PTSD related to COVID-19 in emergency staff based on the components of self-compassion and perceived social support. BMC Psychiatry. 2022;22:1. - PMC - PubMed
    1. Doucette ML, Tucker A, Auguste ME, Watkins A, Green C, Pereira FE, et al. Initial impact of COVID-19's stay-at-home order on motor vehicle traffic and crash patterns in Connecticut: an interrupted time series analysis. Inj Prev. 2021;27(1):3–9. - PubMed
    1. Rahmani F, Rezazadeh F, Ala A, Soleimanpour M, Mehdizadeh R, Soleimanpour H. Evaluation of Overcrowding of Emergency Department in Imam Reza Hospital in 2015 by Implementing 2 Scales: NEDOCS and EDWIN. Iran Red Crescent Med J. 2017;19(6):e15609.
    1. Ghafil C, Matsushima K, Ding L, Henry R, Inaba K. Trends in Trauma Admissions During the COVID-19 Pandemic in Los Angeles County, California. JAMA Netw Open. 2021;4(2):e211320. - PMC - PubMed

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