Literature DB >> 32243813

Estimating case fatality rates of COVID-19.

Marc Lipsitch1.   

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Year:  2020        PMID: 32243813      PMCID: PMC7270796          DOI: 10.1016/S1473-3099(20)30245-0

Source DB:  PubMed          Journal:  Lancet Infect Dis        ISSN: 1473-3099            Impact factor:   25.071


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In their Correspondence, David Baud and colleagues suggest that case fatality rates (CFRs) for coronavirus disease 2019 have been underestimated and propose to divide deaths at time t by cases at time t minus 14 days to correct this underestimation and provide so-called real estimates. Many biases in both directions afflict CFR estimates during outbreaks, and experts have spent 2 decades (since the outbreak of severe acute respiratory syndrome coronavirus) finding ways to overcome these. The delay problem highlighted by Baud and colleagues produces falsely low estimates, whereas the under-ascertainment of mild cases produces falsely high estimates. These issues are well appreciated in the field and have been discussed in the popular press in recent weeks.5, 6 No expert thinks the 3·6% raw ratio of deaths to cases on March 1 is an accurate estimate of the CFR because it suffers from all of these biases. The authors make the situation worse: correcting for delay (with an invalid method) without correcting for ascertainment of mild cases inflates the estimates, bringing them further from what most experts believe are the true numbers, around the 1–2% range for symptomatic cases.7, 8 Baud and colleagues' estimates are not real; they are in fact less real than the biased calculations they claim to correct. Especially in a time of great urgency, authors have a responsibility to read and understand relevant background literature and look for obvious flaws in their own analysis. This work does not appear to have met that standard. The fact that peer review did not pick up these flaws should be a caution against hastening the peer review process at the expense of due care.
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Authors:  Christl A Donnelly; Azra C Ghani; Gabriel M Leung; Anthony J Hedley; Christophe Fraser; Steven Riley; Laith J Abu-Raddad; Lai-Ming Ho; Thuan-Quoc Thach; Patsy Chau; King-Pan Chan; Tai-Hing Lam; Lai-Yin Tse; Thomas Tsang; Shao-Haei Liu; James H B Kong; Edith M C Lau; Neil M Ferguson; Roy M Anderson
Journal:  Lancet       Date:  2003-05-24       Impact factor: 79.321

  1 in total
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1.  Distinct type I interferon responses between younger women and older men contribute to the variability of COVID-19 outcomes: Hypothesis generating insights from COVID-19 convalescent individuals.

Authors:  Clio P Mavragani; Charalampos Skarlis; Ioannis V Kostopoulos; Eirini Maratou; Paraskevi Moutsatsou; Evangelos Terpos; Ourania E Tsitsilonis; Meletios-Athanasios Dimopoulos; Petros P Sfikakis
Journal:  Cytokine       Date:  2022-07-18       Impact factor: 3.926

2.  Understanding and Addressing Older Adults' Needs During COVID-19.

Authors:  Laura P Sands; Steven M Albert; J Jill Suitor
Journal:  Innov Aging       Date:  2020-06-02

3.  Employing drug delivery strategies to create safe and effective pharmaceuticals for COVID-19.

Authors:  Kevin J McHugh
Journal:  Bioeng Transl Med       Date:  2020-05-13

Review 4.  Mechanisms of Dysregulated Humoral and Cellular Immunity by SARS-CoV-2.

Authors:  Nima Taefehshokr; Sina Taefehshokr; Bryan Heit
Journal:  Pathogens       Date:  2020-12-08

5.  Is COVID-19 the worst pandemic?

Authors:  Jack Feehan; Vasso Apostolopoulos
Journal:  Maturitas       Date:  2021-02-06       Impact factor: 4.342

6.  Incorporating and addressing testing bias within estimates of epidemic dynamics for SARS-CoV-2.

Authors:  Yasir Suhail; Junaid Afzal
Journal:  BMC Med Res Methodol       Date:  2021-01-07       Impact factor: 4.615

7.  Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America.

Authors:  Shashank Vaid; Caglar Cakan; Mohit Bhandari
Journal:  J Bone Joint Surg Am       Date:  2020-07-01       Impact factor: 6.558

Review 8.  Considerations for an Individual-Level Population Notification System for Pandemic Response: A Review and Prototype.

Authors:  Mohammad Nazmus Sakib; Zahid A Butt; Plinio Pelegrini Morita; Mark Oremus; Geoffrey T Fong; Peter A Hall
Journal:  J Med Internet Res       Date:  2020-06-05       Impact factor: 5.428

9.  Authors' reply.

Authors:  David Baud; Karin Nielsen-Saines; Xiaolong Qi; Didier Musso; Léo Pomar; Guillaume Favre
Journal:  Lancet Infect Dis       Date:  2020-03-31       Impact factor: 25.071

10.  The confounded crude case-fatality rates (CFR) for COVID-19 hide more than they reveal-a comparison of age-specific and age-adjusted CFRs between seven countries.

Authors:  Manfred S Green; Victoria Peer; Naama Schwartz; Dorit Nitzan
Journal:  PLoS One       Date:  2020-10-21       Impact factor: 3.240

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