The global case fatality rate of coronavirus disease 2019 by continents and national income: A meta-analysis

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Abou Ghayda, Ramy | Lee, Keum-Hwa | Han, Youngjoo | Ryu, Seohyun | Hong, Sunghwi | Yoon, Sojung | Jeong, Gwanghun | Yang, Jaewon | Lee, Hyojeong | Lee, Jinhee | Lee, Jun-Young | Effenberger, Maria | Eisenhut, Michael | Kronbichler, Andreas | Solmi, Marco | Li, Han | Jacob, Louis | Koyanagi, Ai | Radua, Joaquim | Park, Myungbae | Aghayeva, Sevda | Ahmed, Mohamed Lemine Cheikh Brahim | Al Serouri, Abdulwahed Wahed A. | Al-Shamsi, Humaid O. | Amir-Behghadami, Mehrdad | Baatarkhuu, Oidov | Bashour, Hyam N. | Bondarenko, Anastasia | Camacho-Ortiz, Adrián | Castro, Franz | Cox, Horace | Davtyan, Hayk | Douglas, Kirk | Dragioti, Elena | Ebrahim, Shahul | Ferioli, Martina | Harapan, Harapan | Mallah, Saad Imad Yousef | Ikram, Aamer | Inoue, Shigeru | Jankovic, Slobodan | Jayarajah, Umesh | Jesenak, M. | Kakodkar, Pramath | Kebede, Yohannes | Kifle, Meron Mehari | Koh, David | Males, Visnja K. | Kotfis, Katarzyna | Lakoh, Sulaiman | Ling, Lowell | Llibre-Guerra, Juan J. | Machida, Masaki | Makurumidze, Richard | Mamun, Mohammed A. | Masic, Izet | van Minh, Hoang V. | Moiseev, Sergey V. | Nadasdy, Thomas | Nahshon, Chen | Ñamendys-Silva, Silvio A. | Yongsi, Blaise Nguendo | Nielsen, Henning Bay | Nodjikouambaye, Zita Aleyo | Ohnmar, Ohnmar | Oksanen, Atte | Owopetu, Oluwatomi Funbi | Parperis, Konstantinos | Perez, Gonzalo E. | Pongpirul, Krit | Rademaker, Marius | Rosa, Sandro G. | Sah, Ranjit | Sallam, Dina E. | Schober, Patrick | Singhal, Tanu | Tafaj, Silva | Torres, Irene | Torres-Roman, J. Smith | Tsartsalis, Dimitrios N. | Tsolmon, Jadamba | Tuychiev, Laziz Nadirovich | Vukcevic, Batrić | Wanghi, Guy Ikambo | Wollina, Uwe | Xu, Renhe | Yang, Lin | Zaidi, Zoubida | Smith, Lee | Shin, Jae Il I.

Edité par CCSD ; Wiley-Blackwell -

International audience. The aim of this study is to provide a more accurate representation of COVID-19's case fatality rate (CFR) by performing meta-analyses by continents and income, and by comparing the result with pooled estimates. We used multiple worldwide data sources on COVID-19 for every country reporting COVID-19 cases. On the basis of data, we performed random and fixed meta-analyses for CFR of COVID-19 by continents and income according to each individual calendar date. CFR was estimated based on the different geographical regions and levels of income using three models: pooled estimates, fixed- and random-model. In Asia, all three types of CFR initially remained approximately between 2.0% and 3.0%. In the case of pooled estimates and the fixed model results, CFR increased to 4.0%, by then gradually decreasing, while in the case of random-model, CFR remained under 2.0%. Similarly, in Europe, initially, the two types of CFR peaked at 9.0% and 10.0%, respectively. The random-model results showed an increase near 5.0%. In high-income countries, pooled estimates and fixed-model showed gradually increasing trends with a final pooled estimates and random-model reached about 8.0% and 4.0%, respectively. In middle-income, the pooled estimates and fixed-model have gradually increased reaching up to 4.5%. in low-income countries, CFRs remained similar between 1.5% and 3.0%. Our study emphasizes that COVID-19 CFR is not a fixed or static value. Rather, it is a dynamic estimate that changes with time, population, socioeconomic factors, and the mitigatory efforts of individual countries.

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