The Global Case-Fatality Rate of COVID-19 Has Been Declining Since May 2020
The objective of this study was to evaluate the trend of reported case fatality rate (rCFR) of COVID-19 over time, using globally reported COVID-19 cases and mortality data. We collected daily COVID-19 diagnoses and mortality data from the WHO’s daily situation reports dated January 1 to December 31...
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Published in | The American journal of tropical medicine and hygiene Vol. 104; no. 6; pp. 2176 - 2184 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Institute of Tropical Medicine
01.06.2021
The American Society of Tropical Medicine and Hygiene |
Subjects | |
Online Access | Get full text |
ISSN | 0002-9637 1476-1645 1476-1645 |
DOI | 10.4269/ajtmh.20-1496 |
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Abstract | The objective of this study was to evaluate the trend of reported case fatality rate (rCFR) of COVID-19 over time, using globally reported COVID-19 cases and mortality data. We collected daily COVID-19 diagnoses and mortality data from the WHO’s daily situation reports dated January 1 to December 31, 2020. We performed three time-series models [simple exponential smoothing, auto-regressive integrated moving average, and automatic forecasting time-series (Prophet)] to identify the global trend of rCFR for COVID-19. We used beta regression models to investigate the association between the rCFR and potential predictors of each country and reported incidence rate ratios (IRRs) of each variable. The weekly global cumulative COVID-19 rCFR reached a peak at 7.23% during the 17th week (April 22–28, 2020). We found a positive and increasing trend for global daily rCFR values of COVID-19 until the 17th week (pre-peak period) and then a strong declining trend up until the 53rd week (post-peak period) toward 2.2% (December 29–31, 2020). In pre-peak of rCFR, the percentage of people aged 65 and above and the prevalence of obesity were significantly associated with the COVID-19 rCFR. The declining trend of global COVID-19 rCFR was not merely because of increased COVID-19 testing, because COVID-19 tests per 1,000 population had poor predictive value. Decreasing rCFR could be explained by an increased rate of infection in younger people or by the improvement of health care management, shielding from infection, and/or repurposing of several drugs that had shown a beneficial effect on reducing fatality because of COVID-19. |
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AbstractList | The objective of this study was to evaluate the trend of reported case fatality rate (rCFR) of COVID-19 over time, using globally reported COVID-19 cases and mortality data. We collected daily COVID-19 diagnoses and mortality data from the WHO's daily situation reports dated January 1 to December 31, 2020. We performed three time-series models [simple exponential smoothing, auto-regressive integrated moving average, and automatic forecasting time-series (Prophet)] to identify the global trend of rCFR for COVID-19. We used beta regression models to investigate the association between the rCFR and potential predictors of each country and reported incidence rate ratios (IRRs) of each variable. The weekly global cumulative COVID-19 rCFR reached a peak at 7.23% during the 17th week (April 22-28, 2020). We found a positive and increasing trend for global daily rCFR values of COVID-19 until the 17th week (pre-peak period) and then a strong declining trend up until the 53rd week (post-peak period) toward 2.2% (December 29-31, 2020). In pre-peak of rCFR, the percentage of people aged 65 and above and the prevalence of obesity were significantly associated with the COVID-19 rCFR. The declining trend of global COVID-19 rCFR was not merely because of increased COVID-19 testing, because COVID-19 tests per 1,000 population had poor predictive value. Decreasing rCFR could be explained by an increased rate of infection in younger people or by the improvement of health care management, shielding from infection, and/or repurposing of several drugs that had shown a beneficial effect on reducing fatality because of COVID-19.The objective of this study was to evaluate the trend of reported case fatality rate (rCFR) of COVID-19 over time, using globally reported COVID-19 cases and mortality data. We collected daily COVID-19 diagnoses and mortality data from the WHO's daily situation reports dated January 1 to December 31, 2020. We performed three time-series models [simple exponential smoothing, auto-regressive integrated moving average, and automatic forecasting time-series (Prophet)] to identify the global trend of rCFR for COVID-19. We used beta regression models to investigate the association between the rCFR and potential predictors of each country and reported incidence rate ratios (IRRs) of each variable. The weekly global cumulative COVID-19 rCFR reached a peak at 7.23% during the 17th week (April 22-28, 2020). We found a positive and increasing trend for global daily rCFR values of COVID-19 until the 17th week (pre-peak period) and then a strong declining trend up until the 53rd week (post-peak period) toward 2.2% (December 29-31, 2020). In pre-peak of rCFR, the percentage of people aged 65 and above and the prevalence of obesity were significantly associated with the COVID-19 rCFR. The declining trend of global COVID-19 rCFR was not merely because of increased COVID-19 testing, because COVID-19 tests per 1,000 population had poor predictive value. Decreasing rCFR could be explained by an increased rate of infection in younger people or by the improvement of health care management, shielding from infection, and/or repurposing of several drugs that had shown a beneficial effect on reducing fatality because of COVID-19. The objective of this study was to evaluate the trend of reported case fatality rate (rCFR) of COVID-19 over time, using globally reported COVID-19 cases and mortality data. We collected daily COVID-19 diagnoses and mortality data from the WHO’s daily situation reports dated January 1 to December 31, 2020. We performed three time-series models [simple exponential smoothing, auto-regressive integrated moving average, and automatic forecasting time-series (Prophet)] to identify the global trend of rCFR for COVID-19. We used beta regression models to investigate the association between the rCFR and potential predictors of each country and reported incidence rate ratios (IRRs) of each variable. The weekly global cumulative COVID-19 rCFR reached a peak at 7.23% during the 17th week (April 22–28, 2020). We found a positive and increasing trend for global daily rCFR values of COVID-19 until the 17th week (pre-peak period) and then a strong declining trend up until the 53rd week (post-peak period) toward 2.2% (December 29–31, 2020). In pre-peak of rCFR, the percentage of people aged 65 and above and the prevalence of obesity were significantly associated with the COVID-19 rCFR. The declining trend of global COVID-19 rCFR was not merely because of increased COVID-19 testing, because COVID-19 tests per 1,000 population had poor predictive value. Decreasing rCFR could be explained by an increased rate of infection in younger people or by the improvement of health care management, shielding from infection, and/or repurposing of several drugs that had shown a beneficial effect on reducing fatality because of COVID-19. |
Author | Hasan, Mohammad Nayeem Uddin, Md. Jamal Stigler, Florian L. Kock, Richard A. McCoy, David Haider, Najmul Khan, Rumi Ahmed Zumla, Alimuddin |
Author_xml | – sequence: 1 givenname: Mohammad Nayeem surname: Hasan fullname: Hasan, Mohammad Nayeem organization: 1Department of Statistics, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh – sequence: 2 givenname: Najmul surname: Haider fullname: Haider, Najmul organization: 2The Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire, United Kingdom – sequence: 3 givenname: Florian L. surname: Stigler fullname: Stigler, Florian L. organization: 3Austrian Sickness Fund, Vienna, Austria – sequence: 4 givenname: Rumi Ahmed surname: Khan fullname: Khan, Rumi Ahmed organization: 4Department of Critical Care Medicine, Orlando Regional Medical Centre, Orlando, Florida – sequence: 5 givenname: David surname: McCoy fullname: McCoy, David organization: 5Institute of Population Health Sciences, Barts and London Medical and Dental School, Queen Mary University of London, London, United Kingdom – sequence: 6 givenname: Alimuddin surname: Zumla fullname: Zumla, Alimuddin organization: 6Department of Infection, Division of Infection and Immunity, Centre for Clinical Microbiology, Royal Free Campus, University College London, London, United Kingdom;, 7National Institute for Health Research Biomedical Research Centre, University College London Hospitals, London, United Kingdom – sequence: 7 givenname: Richard A. surname: Kock fullname: Kock, Richard A. organization: 2The Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire, United Kingdom – sequence: 8 givenname: Md. Jamal surname: Uddin fullname: Uddin, Md. Jamal organization: 1Department of Statistics, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 These authors contributed equally to this work. Authors’ addresses: Mohammad Nayeem Hasan, Department of Statistics, Shahjalal University of Science and Technology, Sylhet, Bangladesh, E-mail: nayeem5847@gmail.com. Najmul Haider, The Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire, United Kingdom, E-mail: nhaider@rvc.ac.uk. Florian L. Stigler, Austrian Sickness Fund, Vienna, Austria, E-mail: florian.stigler@medunigraz.at. Rumi Ahmed Khan, Department of Critical Care Medicine, Orlando Regional Medical Centre, Orlando, FL, E-mail: rumi.ahmed@gmail.com. David McCoy, Institute of Population Health Sciences, Barts and London Medical and Dental School, Queen Mary University of London, London, UK, E-mail: d.mccoy@qmul.ac.uk. Alimuddin Zumla, Department of Infection, Division of Infection and Immunity, Centre for Clinical Microbiology, Royal Free Campus, University College London, and National Institute for Health Research Biomedical Research Centre, University College London Hospitals, London, United Kingdom, E-mail: a.i.zumla@gmail.com. Richard A. Kock, The Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire, United Kingdom, E-mail: rkock@rvc.ac.uk. Md. Jamal Uddin, Department of Statistics, Shahjalal University of Science and Technology, Sylhet, Bangladesh, E-mail: jamal-sta@sust.edu. |
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SubjectTerms | Coronaviruses COVID-19 COVID-19 - epidemiology COVID-19 - mortality COVID-19 diagnostic tests COVID-19 Testing Fatalities Global Health Humans Incidence SARS-CoV-2 Time Factors |
Title | The Global Case-Fatality Rate of COVID-19 Has Been Declining Since May 2020 |
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