Volume 1, Issue 1 (1-2022)                   2022, 1(1): 7-16 | Back to browse issues page

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Foroughi M, Bazrafshan E, Alafchi B, Sarmadi M, Abbaspour S. The worldwide challenge of COVID-19 patient overload on hospitals: A modelling, meta-analysis-based study. Journal title 2022; 1 (1) :7-16
URL: http://jrhms.thums.ac.ir/article-1-29-en.html
Torbat Heydariyeh University of Medical Sciences , msarmadi2@gmail.com
Abstract:   (2045 Views)
Since a huge load of infected incoming people in the time of COVID-19 needs to be managed in medical facilities, estimation of the load extent of the outbreak and design of the facilities accordingly, can help the authorities to be equipped for such challenges. The basic reproduction number (R0) was obtained from a random-effects model in the meta-analysis procedure. The cumulative death numbers (CDN) were then estimated using the cubic curve estimations, which in turn, was based to estimate the required beds in each country. The shortages of beds were calculated from the difference between the available and required beds. Finally, a multiple barriers strategy was proposed according to epidemiological parameters to decrease patient overload during the outbreaks. The mean pooled R0 was found to be 3.04 (95%CI: 2.62-3.45). The correlation coefficients for the cubic curve estimations for different countries were 0.97-0.99. From hospital beds shortage standpoint, the results showed that Australia, South Korea, and Turkey are in a better position relative to other countries studied. However, Italy, Spain, France, the USA, and the UK will experience limitations if no action be taken to prevent COVID-19 from spreading. If the exponential growth of infection remains for the next weeks, the related authorities should consider much more hospital beds (as well as related supplementary equipment and medical-based staff) for COVID-19 infected cases. Although the considerable changes in the medical-based footprints can allocate the side effects of the challenge, it seems that we need to refine our frameworks to prevent or minimize, at least, the life losses.
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Type of Study: Research | Subject: Special
Received: 2021/04/10 | Accepted: 2021/05/24 | Published: 2021/12/22

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