COVID-19 contact tracing as an indicator for evaluating a pandemic situation
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2023 |
| Outros Autores: | , , , , , , , , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
| Texto Completo: | http://hdl.handle.net/10362/159525 |
Resumo: | Publisher Copyright: © 2023 JMIR Publications Inc.. All rights reserved. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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COVID-19 contact tracing as an indicator for evaluating a pandemic situationSimulation studyCOVID-19epidemiological modelsinfection transmissionpublic healthpublic health surveillancequarantineHealth InformaticsPublic Health, Environmental and Occupational HealthSDG 3 - Good Health and Well-beingPublisher Copyright: © 2023 JMIR Publications Inc.. All rights reserved.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.NOVA School of Business and Economics (NOVA SBE)RUNMarques-Cruz, ManuelNogueira-Leite, DiogoAlves, João MiguelFernandes, FranciscoFernandes, José MiguelAlmeida, Miguel ÂngeloCorreia, Patrícia CunhaPerestrelo, PaulaCruz-Correia, RicardoBarros, Pedro Pita2023-11-03T22:10:30Z2023-06-042023-06-04T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/159525eng2369-2960PURE: 64196589https://doi.org/10.2196/43836info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:41:55Zoai:run.unl.pt:10362/159525Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:57:34.879216Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
| dc.title.none.fl_str_mv |
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 |
| spellingShingle |
COVID-19 contact tracing as an indicator for evaluating a pandemic situation Marques-Cruz, Manuel COVID-19 epidemiological models infection transmission public health public health surveillance quarantine Health Informatics Public Health, Environmental and Occupational Health SDG 3 - Good Health and Well-being |
| title_short |
COVID-19 contact tracing as an indicator for evaluating a pandemic situation |
| title_full |
COVID-19 contact tracing as an indicator for evaluating a pandemic situation |
| title_fullStr |
COVID-19 contact tracing as an indicator for evaluating a pandemic situation |
| title_full_unstemmed |
COVID-19 contact tracing as an indicator for evaluating a pandemic situation |
| title_sort |
COVID-19 contact tracing as an indicator for evaluating a pandemic situation |
| author |
Marques-Cruz, Manuel |
| author_facet |
Marques-Cruz, Manuel Nogueira-Leite, Diogo Alves, João Miguel Fernandes, Francisco Fernandes, José Miguel Almeida, Miguel Ângelo Correia, Patrícia Cunha Perestrelo, Paula Cruz-Correia, Ricardo Barros, Pedro Pita |
| author_role |
author |
| author2 |
Nogueira-Leite, Diogo Alves, João Miguel Fernandes, Francisco Fernandes, José Miguel Almeida, Miguel Ângelo Correia, Patrícia Cunha Perestrelo, Paula Cruz-Correia, Ricardo Barros, Pedro Pita |
| author2_role |
author author author author author author author author author |
| dc.contributor.none.fl_str_mv |
NOVA School of Business and Economics (NOVA SBE) RUN |
| dc.contributor.author.fl_str_mv |
Marques-Cruz, Manuel Nogueira-Leite, Diogo Alves, João Miguel Fernandes, Francisco Fernandes, José Miguel Almeida, Miguel Ângelo Correia, Patrícia Cunha Perestrelo, Paula Cruz-Correia, Ricardo Barros, Pedro Pita |
| dc.subject.por.fl_str_mv |
COVID-19 epidemiological models infection transmission public health public health surveillance quarantine Health Informatics Public Health, Environmental and Occupational Health SDG 3 - Good Health and Well-being |
| topic |
COVID-19 epidemiological models infection transmission public health public health surveillance quarantine Health Informatics Public Health, Environmental and Occupational Health SDG 3 - Good Health and Well-being |
| description |
Publisher Copyright: © 2023 JMIR Publications Inc.. All rights reserved. |
| publishDate |
2023 |
| dc.date.none.fl_str_mv |
2023-11-03T22:10:30Z 2023-06-04 2023-06-04T00:00:00Z |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/159525 |
| url |
http://hdl.handle.net/10362/159525 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
2369-2960 PURE: 64196589 https://doi.org/10.2196/43836 |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
| collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
| repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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