Evidence map›Paper›PMID 36877958›Full record

ArticleJMIR public health and surveillance2023

COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study.

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

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Manuel Marques-CruzDepartment of Community Medicine, Information and Decision in Health, Faculty of Medicine, University of Porto, Porto, Portugal.ORCID 0000-0002-9827-2551
Diogo Nogueira-LeiteDepartment of Community Medicine, Information and Decision in Health, Faculty of Medicine, University of Porto, Porto, Portugal.ORCID 0000-0002-3163-8694
João Miguel AlvesDepartment of Community Medicine, Information and Decision in Health, Faculty of Medicine, University of Porto, Porto, Portugal.ORCID 0000-0003-1248-4631
Francisco FernandesPublic Health Unit Baixo Mondego, Agrupamento de Centros de Saúde Baixo Mondego, Administração Regional de Saúde do Centro, Figueira da Foz, Portugal.ORCID 0000-0002-1788-1524
José Miguel FernandesPublic Health Unit Alto Ave, Agrupamento de Centos de Saúde Alto Ave, Administração Regional de Saúde do Norte, Fafe, Portugal.ORCID 0000-0001-5987-5838
Miguel Ângelo AlmeidaPublic Health Unit Póvoa de Varzim, Agrupamento de Centros de Saúde Póvoa de Varzim - Vila do Conde, Administração Regional de Saúde do Norte, Vila do Conde, Portugal.ORCID 0000-0002-6560-4513
Patrícia Cunha CorreiaPublic Health Unit of Local Health Unit of Guarda, Unidade Local de Saúde da Guarda, Guarda, Portugal.ORCID 0000-0002-4126-2723
Paula PerestreloNOVA Health Economics & Management Knowledge Center, NOVA School of Business and Economics, NOVA University of Lisbon, Lisboa, Portugal.ORCID 0000-0002-7298-7858
Ricardo Cruz-CorreiaDepartment of Community Medicine, Information and Decision in Health, Faculty of Medicine, University of Porto, Porto, Portugal.ORCID 0000-0002-3764-5158
Pedro Pita BarrosNOVA Health Economics & Management Knowledge Center, NOVA School of Business and Economics, NOVA University of Lisbon, Lisboa, Portugal.ORCID 0000-0002-0881-4928

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundContact 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.

objectiveThis 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.

methodsWe 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.

resultsAn 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.

conclusionsWe 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.

Indexed as

COVID-19Communicable Disease ControlContact TracingHumansPandemicsSARS-CoV-2COVID-19epidemiological modelsinfection transmissionpublic healthpublic health surveillancequarantine

Identifiers

PMID36877958
PMCPMC10131915

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.