On testing for infections during epidemics, with application to Covid-19 in Ontario, Canada

被引:4
|
作者
Lawless, Jerald F. [1 ]
Yan, Ping [1 ,2 ]
机构
[1] Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON N2L 3G1, Canada
[2] Publ Hlth Agcy Canada, 130 Colonnade Rd, Ottawa, ON K1A 0K9, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Count data; COVID-19; Modelling; Testing strategies; Ascertainment rate;
D O I
10.1016/j.idm.2021.07.003
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
During an epidemic, accurate estimation of the numbers of viral infections in different regions and groups is important for understanding transmission and guiding public health actions. This depends on effective testing strategies that identify a high proportion of infections (that is, provide high ascertainment rates). For the novel coronavirus SARS-CoV-2, ascertainment rates do not appear to be high in most jurisdictions, but quantitative analysis of testing has been limited. We provide statistical models for studying testing and ascertainment rates, and illustrate them on public data on testing and case counts in Ontario, Canada. (C) 2021 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.
引用
收藏
页码:930 / 941
页数:12
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