Robust estimation of diagnostic rate and real incidence of COVID-19 for European policymakers.

Published on Jan 7, 2021in PLOS ONE3.24
· DOI :10.1371/JOURNAL.PONE.0243701
Martí Català7
Estimated H-index: 7
(UPC: Polytechnic University of Catalonia),
David Pino20
Estimated H-index: 20
(UPC: Polytechnic University of Catalonia)
+ 7 AuthorsEnrique Alvarez-Lacalle14
Estimated H-index: 14
(UPC: Polytechnic University of Catalonia)
Policymakers need clear, fast assessment of the real spread of the COVID-19 epidemic in each of their respective countries. Standard measures of the situation provided by the governments include reported positive cases and total deaths. While total deaths indicate immediately that countries like Italy and Spain had the worst situation as of mid-April, 2020, reported cases alone do not provide a complete picture of the situation. Different countries diagnose differently and present very distinctive reported case fatality ratios. Similar levels of reported incidence and mortality might hide a very different underlying pictures. Here we present a straightforward and robust estimation of the diagnostic rate in each European country. From that estimation we obtain a uniform, unbiased incidence of the epidemic. The method to obtain the diagnostic rate is transparent and empirical. The key assumption of the method is that the infection fatality ratio of COVID-19 in Europe is not strongly country-dependent. We show that this number is not expected to be biased due to demography nor to the way total deaths are reported. The estimation protocol is dynamic, and it has been yielding converging numbers for diagnostic rates in all European countries as from mid-April, 2020. Using this diagnostic rate, policy makers can obtain Effective Potential Growth updated every day, providing an unbiased assessment of the countries at greater risk of experiencing an uncontrolled situation. The method developed has been and will be used to track possible improvements in the diagnostic rate in European countries as the epidemic evolves.
#8Terry Jones (Charité)H-Index: 90
#1Martí Català (UPC: Polytechnic University of Catalonia)H-Index: 7
#2Sergio Alonso (UPC: Polytechnic University of Catalonia)H-Index: 20
Last. Clara Prats (UPC: Polytechnic University of Catalonia)H-Index: 14
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#2Shane Crotty (UCSD: University of California, San Diego)H-Index: 87
T cell reactivity against SARS-CoV-2 was observed in unexposed people; however, the source and clinical relevance of the reactivity remains unknown. It is speculated that this reflects T cell memory to circulating ‘common cold’ coronaviruses. It will be important to define specificities of these T cells and assess their association with COVID-19 disease severity and vaccine responses. Recent studies have shown T cell reactivity to SARS-CoV-2 in 20–50% of unexposed individuals; it is speculated t...
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#2David McEvoy (UCD: University College Dublin)H-Index: 7
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#2Rosemary J. Boyton (Imperial College London)H-Index: 28
In efforts to synthesize a clear understanding of SARS-CoV-2 protective immunity, antibody analysis has been paralleled by T cell studies across asymptomatic, mild and severe COVID-19. Defining CD4 and CD8 effector functions in protection is important considering that antibody responses appear short-lived and T cell memory is potentially more durable. To fully understand population level immunity, screening for both antibody and T cell immunity using standardized testing methods would be benefic...
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#2Anthony T. Tan (NUS: National University of Singapore)H-Index: 27
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Memory T cells induced by previous pathogens can shape the susceptibility to, and clinical severity of, subsequent infections1. Little is known about the presence of pre-existing memory T cells in humans with the potential to recognize SARS-CoV-2. Here, we first studied T cell responses to structural (nucleocapsid protein, NP) and non-structural (NSP-7 and NSP13 of ORF1) regions of SARS-CoV-2 in COVID-19 convalescents (n=36). In all of them we demonstrated the presence of CD4 and CD8 T cells rec...
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#3Suzana Sabaiduc (BC Centre for Disease Control)H-Index: 21
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#2Pei-Chuan Ho (UPenn: University of Pennsylvania)H-Index: 1
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