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  1. Article: Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach.

    Phipps, Steven J / Grafton, R Quentin / Kompas, Tom

    Royal Society open science

    2020  Volume 7, Issue 11, Page(s) 200909

    Abstract: ... within each country over time, make it difficult to estimate the true (population) infection rate based ... of the population who test positive and the implied true detection rate. Despite an overall improvement in detection ... on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate ...

    Abstract Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3-10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8-4.5) for South Korea to 17.5 (95% CI: 12.2-30.7) for Italy.
    Language English
    Publishing date 2020-11-18
    Publishing country England
    Document type Journal Article
    ZDB-ID 2787755-3
    ISSN 2054-5703
    ISSN 2054-5703
    DOI 10.1098/rsos.200909
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Robust estimates of the true (population) infection rate for COVID-19

    Steven J. Phipps / R. Quentin Grafton / Tom Kompas

    Royal Society Open Science, Vol 7, Iss

    a backcasting approach

    2020  Volume 11

    Abstract: ... within each country over time, make it difficult to estimate the true (population) infection rate based ... of the population who test positive and the implied true detection rate. Despite an overall improvement in detection ... on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate ...

    Abstract Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3–10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8–4.5) for South Korea to 17.5 (95% CI: 12.2–30.7) for Italy.
    Keywords covid-19 ; sars-cov-2 ; infection rate ; parameter uncertainty ; Science ; Q
    Subject code 310
    Language English
    Publishing date 2020-11-01T00:00:00Z
    Publisher The Royal Society
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Book ; Online: Robust estimates of the true (population) infection rate for COVID-19

    Phipps, Steven John / Grafton, R. Quentin / Kompas, Tom

    a backcasting approach

    2020  

    Abstract: ... within each country over time, make it difficult to estimate the true (population) infection rate based ... of the population who test positive and the implied true detection rate. Despite an overall improvement in detection ... on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate ...

    Abstract Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3–10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8–4.5) for South Korea to 17.5 (95% CI: 12.2–30.7) for Italy.
    Keywords COVID-19 ; SARS-CoV-2 ; pandemic ; public health ; infection rate ; parameter uncertainty ; covid19
    Subject code 310
    Publishing date 2020-11-18
    Publishing country eu
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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