Effect of testing criteria for infectious disease surveillance: The case of COVID-19 in Norway
During the COVID-19 pandemic in Norway, the testing criteria and capacity changed numerous times. In this study, we aim to assess consequences of changes in testing criteria for infectious disease surveillance. We plotted the proportion of positive PCR tests and the total number of PCR tests for dif...
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description | During the COVID-19 pandemic in Norway, the testing criteria and capacity changed numerous times. In this study, we aim to assess consequences of changes in testing criteria for infectious disease surveillance. We plotted the proportion of positive PCR tests and the total number of PCR tests for different periods of the pandemic in Norway. We fitted regression models for the total number of PCR tests and the probability of positive PCR tests, with time and weekday as explanatory variables. The regression analysis focuses on the time period until 2021, i.e. before Norway started vaccination. There were clear changes in testing criteria and capacity over time. In particular, there was a marked difference in the testing regime before and after the introduction of self-testing, with a drastic increase in the proportion of positive PCR tests after the introduction of self-tests. The probability of a PCR test being positive was higher for weekends and public holidays than for Mondays-Fridays. The probability for a positive PCR test was lowest on Mondays. This implies that there were different testing criteria and/or different test-seeking behaviour on different weekdays. Though the probability of testing positive clearly changed over time, we cannot in general conclude that this occurred as a direct consequence of changes in testing policies. It is natural for the testing criteria to change during a pandemic. Though smaller changes in testing criteria do not seem to have large, abrupt consequences for the disease surveillance, larger changes like the introduction and massive use of self-tests makes the test data less useful for surveillance. |
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In this study, we aim to assess consequences of changes in testing criteria for infectious disease surveillance. We plotted the proportion of positive PCR tests and the total number of PCR tests for different periods of the pandemic in Norway. We fitted regression models for the total number of PCR tests and the probability of positive PCR tests, with time and weekday as explanatory variables. The regression analysis focuses on the time period until 2021, i.e. before Norway started vaccination. There were clear changes in testing criteria and capacity over time. In particular, there was a marked difference in the testing regime before and after the introduction of self-testing, with a drastic increase in the proportion of positive PCR tests after the introduction of self-tests. The probability of a PCR test being positive was higher for weekends and public holidays than for Mondays-Fridays. The probability for a positive PCR test was lowest on Mondays. This implies that there were different testing criteria and/or different test-seeking behaviour on different weekdays. Though the probability of testing positive clearly changed over time, we cannot in general conclude that this occurred as a direct consequence of changes in testing policies. It is natural for the testing criteria to change during a pandemic. Though smaller changes in testing criteria do not seem to have large, abrupt consequences for the disease surveillance, larger changes like the introduction and massive use of self-tests makes the test data less useful for surveillance.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0308978</identifier><identifier>PMID: 39146327</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Communicable diseases ; Contact tracing ; COVID-19 ; COVID-19 - diagnosis ; COVID-19 - epidemiology ; COVID-19 Nucleic Acid Testing - statistics & numerical data ; COVID-19 Testing - methods ; Criteria ; Disease transmission ; Health surveillance ; Hospitals ; Humans ; Infections ; Infectious diseases ; Influenza ; Laboratories ; Mathematical models ; Medicine and Health Sciences ; Norway - epidemiology ; Pandemics ; People and Places ; Public health ; Regression analysis ; Regression models ; Restrictions ; SARS-CoV-2 - genetics ; SARS-CoV-2 - isolation & purification ; Self testing ; Serology ; Severe acute respiratory syndrome coronavirus 2 ; Statistical analysis ; Surveillance ; Trends ; Vaccination</subject><ispartof>PloS one, 2024-08, Vol.19 (8), p.e0308978</ispartof><rights>Copyright: © 2024 Engebretsen, Aldrin. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Engebretsen, Aldrin. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Engebretsen, Aldrin 2024 Engebretsen, Aldrin</rights><rights>2024 Engebretsen, Aldrin. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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In this study, we aim to assess consequences of changes in testing criteria for infectious disease surveillance. We plotted the proportion of positive PCR tests and the total number of PCR tests for different periods of the pandemic in Norway. We fitted regression models for the total number of PCR tests and the probability of positive PCR tests, with time and weekday as explanatory variables. The regression analysis focuses on the time period until 2021, i.e. before Norway started vaccination. There were clear changes in testing criteria and capacity over time. In particular, there was a marked difference in the testing regime before and after the introduction of self-testing, with a drastic increase in the proportion of positive PCR tests after the introduction of self-tests. The probability of a PCR test being positive was higher for weekends and public holidays than for Mondays-Fridays. The probability for a positive PCR test was lowest on Mondays. This implies that there were different testing criteria and/or different test-seeking behaviour on different weekdays. Though the probability of testing positive clearly changed over time, we cannot in general conclude that this occurred as a direct consequence of changes in testing policies. It is natural for the testing criteria to change during a pandemic. 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In this study, we aim to assess consequences of changes in testing criteria for infectious disease surveillance. We plotted the proportion of positive PCR tests and the total number of PCR tests for different periods of the pandemic in Norway. We fitted regression models for the total number of PCR tests and the probability of positive PCR tests, with time and weekday as explanatory variables. The regression analysis focuses on the time period until 2021, i.e. before Norway started vaccination. There were clear changes in testing criteria and capacity over time. In particular, there was a marked difference in the testing regime before and after the introduction of self-testing, with a drastic increase in the proportion of positive PCR tests after the introduction of self-tests. The probability of a PCR test being positive was higher for weekends and public holidays than for Mondays-Fridays. The probability for a positive PCR test was lowest on Mondays. This implies that there were different testing criteria and/or different test-seeking behaviour on different weekdays. Though the probability of testing positive clearly changed over time, we cannot in general conclude that this occurred as a direct consequence of changes in testing policies. It is natural for the testing criteria to change during a pandemic. Though smaller changes in testing criteria do not seem to have large, abrupt consequences for the disease surveillance, larger changes like the introduction and massive use of self-tests makes the test data less useful for surveillance.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>39146327</pmid><doi>10.1371/journal.pone.0308978</doi><tpages>e0308978</tpages><orcidid>https://orcid.org/0000-0002-7064-0869</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Communicable diseases Contact tracing COVID-19 COVID-19 - diagnosis COVID-19 - epidemiology COVID-19 Nucleic Acid Testing - statistics & numerical data COVID-19 Testing - methods Criteria Disease transmission Health surveillance Hospitals Humans Infections Infectious diseases Influenza Laboratories Mathematical models Medicine and Health Sciences Norway - epidemiology Pandemics People and Places Public health Regression analysis Regression models Restrictions SARS-CoV-2 - genetics SARS-CoV-2 - isolation & purification Self testing Serology Severe acute respiratory syndrome coronavirus 2 Statistical analysis Surveillance Trends Vaccination |
title | Effect of testing criteria for infectious disease surveillance: The case of COVID-19 in Norway |
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