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المؤلفAyoub, Houssein H.
المؤلفChemaitelly, Hiam
المؤلفSeedat, Shaheen
المؤلفMakhoul, Monia
المؤلفKanaani, Zaina Al
المؤلفKhal, Abdullatif Al
المؤلفKuwari, Einas Al
المؤلفButt, Adeel A.
المؤلفCoyle, Peter
المؤلفJeremijenko, Andrew
المؤلفKaleeckal, Anvar Hassan
المؤلفLatif, Ali Nizar
المؤلفShaik, Riyazuddin Mohammad
المؤلفRahim, Hanan Abdul
المؤلفYassine, Hadi M.
المؤلفKuwari, Mohamed G.Al
المؤلفRomaihi, Hamad Eid Al
المؤلفAl-Thani, Mohamed H.
المؤلفBertollini, Roberto
المؤلفRaddad, Laith J.Abu
تاريخ الإتاحة2022-09-14T11:36:53Z
تاريخ النشر2021-01-01
اسم المنشورJournal of Global Health
المعرّفhttp://dx.doi.org/10.7189/jogh.11.05005
الاقتباسAyoub, H. H., Chemaitelly, H., Seedat, S., Makhoul, M., Al Kanaani, Z., Al Khal, A., ... & Raddad, L. J. A. (2021). Mathematical modeling of the SARS-CoV-2 epidemic in Qatar and its impact on the national response to COVID-19. Journal of global health, 11.‏
الرقم المعياري الدولي للكتاب20472978
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85101248378&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/34026
الملخصBackground Mathematical modeling constitutes an important tool for planning robust responses to epidemics. This study was conducted to guide the Qatari national response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. The study investigated the epidemic’s time-course, forecasted health care needs, predicted the impact of social and physical distancing restrictions, and rationalized and justified easing of restrictions. Methods An age-structured deterministic model was constructed to describe SARS-CoV-2 transmission dynamics and disease progression throughout the population. Results The enforced social and physical distancing interventions flattened the epidemic curve, reducing the peaks for incidence, prevalence, acute-care hospitalization, and intensive care unit (ICU) hospitalizations by 87%, 86%, 76%, and 78%, respectively. The daily number of new infections was predicted to peak at 12 750 on May 23, and active-infection prevalence was predicted to peak at 3.2% on May 25. Daily acute-care and ICUcare hospital admissions and occupancy were forecast accurately and precisely. By October 15, 2020, the basic reproduction number R0 had varied between 1.07-2.78, and 50.8% of the population were estimated to have been infected (1.43 million infections). The proportion of actual infections diagnosed was estimated at 11.6%. Applying the concept of Rt tuning, gradual easing of restrictions was rationalized and justified to start on June 15, 2020, when Rt declined to 0.7, to buffer the increased interpersonal contact with easing of restrictions and to minimize the risk of a second wave. No second wave has materialized as of October 15, 2020, five months after the epidemic peak. Conclusions Use of modeling and forecasting to guide the national response proved to be a successful strategy, reducing the toll of the epidemic to a manageable level for the health care system.
اللغةen
الناشرUniversity of Edinburgh
الموضوعepidemic
epidemiology
forecasting
hospitalization
human
incidence
intensive care unit
العنوانMathematical modeling of the SARSCoV-2 epidemic in Qatar and its impact on the national response to COVID-19
النوعArticle
رقم المجلد11
dc.accessType Open Access


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