tetano
Editor, Senior Moderator
J Med Virol
. 2022 Jan 31.
doi: 10.1002/jmv.27610. Online ahead of print.
Global case fatality rate of coronavirus disease 2019 (COVID-19) by continents and national income: a meta-analysis
Ramy Abou Ghayda[SUP] 1 [/SUP], Keum Hwa Lee[SUP] 2 [/SUP], Young Joo Han[SUP] 3 [/SUP], Seohyun Ryu[SUP] 4 [/SUP], Sung Hwi Hong[SUP] 4 [/SUP], Sojung Yoon[SUP] 4 [/SUP], Gwang Hun Jeong[SUP] 5 [/SUP], Jae Won Yang[SUP] 6 [/SUP], Hyo Jeong Lee[SUP] 4 [/SUP], Jinhee Lee[SUP] 7 [/SUP], Jun Young Lee[SUP] 6 [/SUP], Maria Effenberger[SUP] 8 [/SUP], Michael Eisenhut[SUP] 9 [/SUP], Andreas Kronbichler[SUP] 10 [/SUP], Marco Solmi[SUP] 11 12 [/SUP], Han Li[SUP] 13 [/SUP], Louis Jacob[SUP] 14 15 [/SUP], Ai Koyanagi[SUP] 15 16 [/SUP], Joaquim Radua[SUP] 17 18 19 [/SUP], Myung Bae Park[SUP] 20 [/SUP], Sevda Aghayeva[SUP] 21 [/SUP], Mohamed Lemine Cheikh Brahim Ahmed[SUP] 22 [/SUP], Abdulwahed Al Serouri[SUP] 23 [/SUP], Humaid O Al-Shamsi[SUP] 24 25 [/SUP], Mehrdad Amir-Behghadami[SUP] 26 27 [/SUP], Oidov Baatarkhuu[SUP] 28 [/SUP], Hyam Bashour[SUP] 29 [/SUP], Anastasiia Bondarenko[SUP] 30 [/SUP], Adrian Camacho-Ortiz[SUP] 31 [/SUP], Franz Castro[SUP] 32 [/SUP], Horace Cox[SUP] 33 [/SUP], Hayk Davtyan[SUP] 34 [/SUP], Kirk Douglas[SUP] 35 [/SUP], Elena Dragioti[SUP] 36 [/SUP], Shahul Ebrahim[SUP] 37 [/SUP], Martina Ferioli[SUP] 38 [/SUP], Harapan Harapan[SUP] 39 [/SUP], Saad I Mallah[SUP] 40 [/SUP], Aamer Ikram[SUP] 41 [/SUP], Shigeru Inoue[SUP] 42 [/SUP], Slobodan Jankovic[SUP] 43 [/SUP], Umesh Jayarajah[SUP] 44 [/SUP], Milos Jesenak[SUP] 45 [/SUP], Pramath Kakodkar[SUP] 46 [/SUP], Yohannes Kebede[SUP] 47 [/SUP], Meron Kifle[SUP] 48 [/SUP], David Koh[SUP] 49 [/SUP], Visnja Kokic Males[SUP] 50 [/SUP], Katarzyna Kotfis[SUP] 51 [/SUP], Sulaiman Lakoh[SUP] 52 [/SUP], Lowell Ling[SUP] 53 [/SUP], Jorge Llibre-Guerra[SUP] 54 [/SUP], Masaki Machida[SUP] 42 [/SUP], Richard Makurumidze[SUP] 55 [/SUP], Mohammed Mamun[SUP] 56 [/SUP], Izet Masic[SUP] 57 [/SUP], Hoang Van Minh[SUP] 58 [/SUP], Sergey Moiseev[SUP] 59 [/SUP], Thomas Nadasdy[SUP] 60 [/SUP], Chen Nahshon[SUP] 61 [/SUP], Silvio A Ñamendys-Silva[SUP] 62 [/SUP], Blaise Nguendo Yongsi[SUP] 63 [/SUP], Henning Bay Nielsen[SUP] 64 [/SUP], Zita Aleyo Nodjikouambaye[SUP] 65 [/SUP], Ohnmar Ohnmar[SUP] 66 [/SUP], Atte Oksanen[SUP] 67 [/SUP], Oluwatomi Owopetu[SUP] 68 [/SUP], Konstantinos Parperis[SUP] 69 [/SUP], Gonzalo Emanuel Perez[SUP] 70 [/SUP], Krit Pongpirul[SUP] 71 [/SUP], Marius Rademaker[SUP] 72 [/SUP], Sandro Rosa[SUP] 73 [/SUP], Ranjit Sah[SUP] 74 [/SUP], Dina Sallam[SUP] 75 [/SUP], Patrick Schober[SUP] 76 [/SUP], Tanu Singhal[SUP] 77 [/SUP], Silva Tafaj[SUP] 78 [/SUP], Irene Torres[SUP] 79 [/SUP], J Smith Torres-Roman[SUP] 80 [/SUP], Dimitrios Tsartsalis[SUP] 81 [/SUP], Jadamba Tsolmon[SUP] 82 [/SUP], Laziz Tuychiev[SUP] 83 [/SUP], Batric Vukcevic[SUP] 84 [/SUP], Guy Wanghi[SUP] 85 [/SUP], Uwe Wollina[SUP] 86 [/SUP], Ren-He Xu[SUP] 87 [/SUP], Lin Yang[SUP] 88 89 [/SUP], Zoubida Zaidi[SUP] 90 [/SUP], Lee Smith[SUP] 91 [/SUP], Jae Il Shin[SUP] 2 [/SUP]
Affiliations
Abstract
The aim of this study is to provide a more accurate representation of COVID-19's 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. Based on the data, we performed random and fixed meta-analyses for CFR of COVID-19 by continents and income according to each individual calendar date. CFR were estimated based on the different geographical regions and level 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 individuals countries. This article is protected by copyright. All rights reserved.
Keywords: COVID-19; case fatality rate (CFR); continents; proportion meta-analysis.
. 2022 Jan 31.
doi: 10.1002/jmv.27610. Online ahead of print.
Global case fatality rate of coronavirus disease 2019 (COVID-19) by continents and national income: a meta-analysis
Ramy Abou Ghayda[SUP] 1 [/SUP], Keum Hwa Lee[SUP] 2 [/SUP], Young Joo Han[SUP] 3 [/SUP], Seohyun Ryu[SUP] 4 [/SUP], Sung Hwi Hong[SUP] 4 [/SUP], Sojung Yoon[SUP] 4 [/SUP], Gwang Hun Jeong[SUP] 5 [/SUP], Jae Won Yang[SUP] 6 [/SUP], Hyo Jeong Lee[SUP] 4 [/SUP], Jinhee Lee[SUP] 7 [/SUP], Jun Young Lee[SUP] 6 [/SUP], Maria Effenberger[SUP] 8 [/SUP], Michael Eisenhut[SUP] 9 [/SUP], Andreas Kronbichler[SUP] 10 [/SUP], Marco Solmi[SUP] 11 12 [/SUP], Han Li[SUP] 13 [/SUP], Louis Jacob[SUP] 14 15 [/SUP], Ai Koyanagi[SUP] 15 16 [/SUP], Joaquim Radua[SUP] 17 18 19 [/SUP], Myung Bae Park[SUP] 20 [/SUP], Sevda Aghayeva[SUP] 21 [/SUP], Mohamed Lemine Cheikh Brahim Ahmed[SUP] 22 [/SUP], Abdulwahed Al Serouri[SUP] 23 [/SUP], Humaid O Al-Shamsi[SUP] 24 25 [/SUP], Mehrdad Amir-Behghadami[SUP] 26 27 [/SUP], Oidov Baatarkhuu[SUP] 28 [/SUP], Hyam Bashour[SUP] 29 [/SUP], Anastasiia Bondarenko[SUP] 30 [/SUP], Adrian Camacho-Ortiz[SUP] 31 [/SUP], Franz Castro[SUP] 32 [/SUP], Horace Cox[SUP] 33 [/SUP], Hayk Davtyan[SUP] 34 [/SUP], Kirk Douglas[SUP] 35 [/SUP], Elena Dragioti[SUP] 36 [/SUP], Shahul Ebrahim[SUP] 37 [/SUP], Martina Ferioli[SUP] 38 [/SUP], Harapan Harapan[SUP] 39 [/SUP], Saad I Mallah[SUP] 40 [/SUP], Aamer Ikram[SUP] 41 [/SUP], Shigeru Inoue[SUP] 42 [/SUP], Slobodan Jankovic[SUP] 43 [/SUP], Umesh Jayarajah[SUP] 44 [/SUP], Milos Jesenak[SUP] 45 [/SUP], Pramath Kakodkar[SUP] 46 [/SUP], Yohannes Kebede[SUP] 47 [/SUP], Meron Kifle[SUP] 48 [/SUP], David Koh[SUP] 49 [/SUP], Visnja Kokic Males[SUP] 50 [/SUP], Katarzyna Kotfis[SUP] 51 [/SUP], Sulaiman Lakoh[SUP] 52 [/SUP], Lowell Ling[SUP] 53 [/SUP], Jorge Llibre-Guerra[SUP] 54 [/SUP], Masaki Machida[SUP] 42 [/SUP], Richard Makurumidze[SUP] 55 [/SUP], Mohammed Mamun[SUP] 56 [/SUP], Izet Masic[SUP] 57 [/SUP], Hoang Van Minh[SUP] 58 [/SUP], Sergey Moiseev[SUP] 59 [/SUP], Thomas Nadasdy[SUP] 60 [/SUP], Chen Nahshon[SUP] 61 [/SUP], Silvio A Ñamendys-Silva[SUP] 62 [/SUP], Blaise Nguendo Yongsi[SUP] 63 [/SUP], Henning Bay Nielsen[SUP] 64 [/SUP], Zita Aleyo Nodjikouambaye[SUP] 65 [/SUP], Ohnmar Ohnmar[SUP] 66 [/SUP], Atte Oksanen[SUP] 67 [/SUP], Oluwatomi Owopetu[SUP] 68 [/SUP], Konstantinos Parperis[SUP] 69 [/SUP], Gonzalo Emanuel Perez[SUP] 70 [/SUP], Krit Pongpirul[SUP] 71 [/SUP], Marius Rademaker[SUP] 72 [/SUP], Sandro Rosa[SUP] 73 [/SUP], Ranjit Sah[SUP] 74 [/SUP], Dina Sallam[SUP] 75 [/SUP], Patrick Schober[SUP] 76 [/SUP], Tanu Singhal[SUP] 77 [/SUP], Silva Tafaj[SUP] 78 [/SUP], Irene Torres[SUP] 79 [/SUP], J Smith Torres-Roman[SUP] 80 [/SUP], Dimitrios Tsartsalis[SUP] 81 [/SUP], Jadamba Tsolmon[SUP] 82 [/SUP], Laziz Tuychiev[SUP] 83 [/SUP], Batric Vukcevic[SUP] 84 [/SUP], Guy Wanghi[SUP] 85 [/SUP], Uwe Wollina[SUP] 86 [/SUP], Ren-He Xu[SUP] 87 [/SUP], Lin Yang[SUP] 88 89 [/SUP], Zoubida Zaidi[SUP] 90 [/SUP], Lee Smith[SUP] 91 [/SUP], Jae Il Shin[SUP] 2 [/SUP]
Affiliations
- PMID: 35099819
- DOI: 10.1002/jmv.27610
Abstract
The aim of this study is to provide a more accurate representation of COVID-19's 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. Based on the data, we performed random and fixed meta-analyses for CFR of COVID-19 by continents and income according to each individual calendar date. CFR were estimated based on the different geographical regions and level 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 individuals countries. This article is protected by copyright. All rights reserved.
Keywords: COVID-19; case fatality rate (CFR); continents; proportion meta-analysis.