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COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study
BACKGROUND: Contact tracing is a fundamental intervention in public health. When systematically applied, it enables the breaking of chains of transmission, which is important for controlling COVID-19 transmission. In theoretically perfect contact tracing, all new cases should occur among quarantined...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131915/ https://www.ncbi.nlm.nih.gov/pubmed/36877958 http://dx.doi.org/10.2196/43836 |
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author | Marques-Cruz, Manuel Nogueira-Leite, Diogo Alves, João Miguel Fernandes, Francisco Fernandes, José Miguel Almeida, Miguel Ângelo Cunha Correia, Patrícia Perestrelo, Paula Cruz-Correia, Ricardo Pita Barros, Pedro |
author_facet | Marques-Cruz, Manuel Nogueira-Leite, Diogo Alves, João Miguel Fernandes, Francisco Fernandes, José Miguel Almeida, Miguel Ângelo Cunha Correia, Patrícia Perestrelo, Paula Cruz-Correia, Ricardo Pita Barros, Pedro |
author_sort | Marques-Cruz, Manuel |
collection | PubMed |
description | BACKGROUND: Contact tracing is a fundamental intervention in public health. When systematically applied, it enables the breaking of chains of transmission, which is important for controlling COVID-19 transmission. In theoretically perfect contact tracing, all new cases should occur among quarantined individuals, and an epidemic should vanish. However, the availability of resources influences the capacity to perform contact tracing. Therefore, it is necessary to estimate its effectiveness threshold. We propose that this effectiveness threshold may be indirectly estimated using the ratio of COVID-19 cases arising from quarantined high-risk contacts, where higher ratios indicate better control and, under a threshold, contact tracing may fail and other restrictions become necessary. OBJECTIVE: This study assessed the ratio of COVID-19 cases in high-risk contacts quarantined through contact tracing and its potential use as an ancillary pandemic control indicator. METHODS: We built a 6-compartment epidemiological model to emulate COVID-19 infection flow according to publicly available data from Portuguese authorities. Our model extended the usual susceptible-exposed-infected-recovered model by adding a compartment Q with individuals in mandated quarantine who could develop infection or return to the susceptible pool and a compartment P with individuals protected from infection because of vaccination. To model infection dynamics, data on SARS-CoV-2 infection risk (IR), time until infection, and vaccine efficacy were collected. Estimation was needed for vaccine data to reflect the timing of inoculation and booster efficacy. In total, 2 simulations were built: one adjusting for the presence and absence of variants or vaccination and another maximizing IR in quarantined individuals. Both simulations were based on a set of 100 unique parameterizations. The daily ratio of infected cases arising from high-risk contacts (q estimate) was calculated. A theoretical effectiveness threshold of contact tracing was defined for 14-day average q estimates based on the classification of COVID-19 daily cases according to the pandemic phases and was compared with the timing of population lockdowns in Portugal. A sensitivity analysis was performed to understand the relationship between different parameter values and the threshold obtained. RESULTS: An inverse relationship was found between the q estimate and daily cases in both simulations (correlations >0.70). The theoretical effectiveness thresholds for both simulations attained an alert phase positive predictive value of >70% and could have anticipated the need for additional measures in at least 4 days for the second and fourth lockdowns. Sensitivity analysis showed that only the IR and booster dose efficacy at inoculation significantly affected the q estimates. CONCLUSIONS: We demonstrated the impact of applying an effectiveness threshold for contact tracing on decision-making. Although only theoretical thresholds could be provided, their relationship with the number of confirmed cases and the prediction of pandemic phases shows the role as an indirect indicator of the efficacy of contact tracing. |
format | Online Article Text |
id | pubmed-10131915 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-101319152023-04-27 COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study Marques-Cruz, Manuel Nogueira-Leite, Diogo Alves, João Miguel Fernandes, Francisco Fernandes, José Miguel Almeida, Miguel Ângelo Cunha Correia, Patrícia Perestrelo, Paula Cruz-Correia, Ricardo Pita Barros, Pedro JMIR Public Health Surveill Original Paper BACKGROUND: Contact tracing is a fundamental intervention in public health. When systematically applied, it enables the breaking of chains of transmission, which is important for controlling COVID-19 transmission. In theoretically perfect contact tracing, all new cases should occur among quarantined individuals, and an epidemic should vanish. However, the availability of resources influences the capacity to perform contact tracing. Therefore, it is necessary to estimate its effectiveness threshold. We propose that this effectiveness threshold may be indirectly estimated using the ratio of COVID-19 cases arising from quarantined high-risk contacts, where higher ratios indicate better control and, under a threshold, contact tracing may fail and other restrictions become necessary. OBJECTIVE: This study assessed the ratio of COVID-19 cases in high-risk contacts quarantined through contact tracing and its potential use as an ancillary pandemic control indicator. METHODS: We built a 6-compartment epidemiological model to emulate COVID-19 infection flow according to publicly available data from Portuguese authorities. Our model extended the usual susceptible-exposed-infected-recovered model by adding a compartment Q with individuals in mandated quarantine who could develop infection or return to the susceptible pool and a compartment P with individuals protected from infection because of vaccination. To model infection dynamics, data on SARS-CoV-2 infection risk (IR), time until infection, and vaccine efficacy were collected. Estimation was needed for vaccine data to reflect the timing of inoculation and booster efficacy. In total, 2 simulations were built: one adjusting for the presence and absence of variants or vaccination and another maximizing IR in quarantined individuals. Both simulations were based on a set of 100 unique parameterizations. The daily ratio of infected cases arising from high-risk contacts (q estimate) was calculated. A theoretical effectiveness threshold of contact tracing was defined for 14-day average q estimates based on the classification of COVID-19 daily cases according to the pandemic phases and was compared with the timing of population lockdowns in Portugal. A sensitivity analysis was performed to understand the relationship between different parameter values and the threshold obtained. RESULTS: An inverse relationship was found between the q estimate and daily cases in both simulations (correlations >0.70). The theoretical effectiveness thresholds for both simulations attained an alert phase positive predictive value of >70% and could have anticipated the need for additional measures in at least 4 days for the second and fourth lockdowns. Sensitivity analysis showed that only the IR and booster dose efficacy at inoculation significantly affected the q estimates. CONCLUSIONS: We demonstrated the impact of applying an effectiveness threshold for contact tracing on decision-making. Although only theoretical thresholds could be provided, their relationship with the number of confirmed cases and the prediction of pandemic phases shows the role as an indirect indicator of the efficacy of contact tracing. JMIR Publications 2023-04-06 /pmc/articles/PMC10131915/ /pubmed/36877958 http://dx.doi.org/10.2196/43836 Text en ©Manuel Marques-Cruz, Diogo Nogueira-Leite, João Miguel Alves, Francisco Fernandes, José Miguel Fernandes, Miguel Ângelo Almeida, Patrícia Cunha Correia, Paula Perestrelo, Ricardo Cruz-Correia, Pedro Pita Barros. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 06.04.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Marques-Cruz, Manuel Nogueira-Leite, Diogo Alves, João Miguel Fernandes, Francisco Fernandes, José Miguel Almeida, Miguel Ângelo Cunha Correia, Patrícia Perestrelo, Paula Cruz-Correia, Ricardo Pita Barros, Pedro COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study |
title | COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study |
title_full | COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study |
title_fullStr | COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study |
title_full_unstemmed | COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study |
title_short | COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study |
title_sort | covid-19 contact tracing as an indicator for evaluating a pandemic situation: simulation study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131915/ https://www.ncbi.nlm.nih.gov/pubmed/36877958 http://dx.doi.org/10.2196/43836 |
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