Evidence map›Paper›PMID 35093019›Full record

ArticleBMC infectious diseases2022

Sensitivity of contact-tracing for COVID-19 in Thailand: a capture-recapture application.

R Lerdsuwansri, P Sangnawakij, D Böhning, C Sansilapin, W Chaifoo, Jonathan A Polonsky, Victor J Del Rio Vilas

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Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

R LerdsuwansriDepartment of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Pathum Thani, Thailand. rattana@mathstat.sci.tu.ac.th.ORCID http://orcid.org/0000-0002-5904-7757
P SangnawakijDepartment of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Pathum Thani, Thailand.
D BöhningSouthampton Statistical Sciences Research Institute and Mathematical Sciences, University of Southampton, Southampton, UK.
C SansilapinDepartment of Disease Control, Ministry of Public Health, Nonthaburi, Thailand.
W ChaifooDepartment of Disease Control, Ministry of Public Health, Nonthaburi, Thailand.
Jonathan A PolonskyWorld Health Organization, Geneva, Switzerland.
Victor J Del Rio VilasWorld Health Organization, World Health Emergencies, South East Asia Regional Office, New Delhi, India.

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundWe investigate the completeness of contact tracing for COVID-19 during the first wave of the COVID-19 pandemic in Thailand, from early January 2020 to 30 June 2020.

methodsUni-list capture-recapture models were applied to the frequency distributions of index cases to inform two questions: (1) the unobserved number of index cases with contacts, and (2) the unobserved number of index cases with secondary cases among their contacts.

resultsGeneralized linear models (using Poisson and logistic families) did not return any significant predictor (age, sex, nationality, number of contacts per case) on the risk of transmission and hence capture-recapture models did not adjust for observed heterogeneity. Best fitting models, a zero truncated negative binomial for question 1 and zero-truncated Poisson for question 2, returned sensitivity estimates for contact tracing performance of 77.6% (95% CI = 73.75-81.54%) and 67.6% (95% CI = 53.84-81.38%), respectively. A zero-inflated negative binomial model on the distribution of index cases with secondary cases allowed the estimation of the effective reproduction number at 0.14 (95% CI = 0.09-0.22), and the overdispersion parameter at 0.1.

conclusionCompleteness of COVID-19 contact tracing in Thailand during the first wave appeared moderate, with around 67% of infectious transmission chains detected. Overdispersion was present suggesting that most of the index cases did not result in infectious transmission chains and the majority of transmission events stemmed from a small proportion of index cases.

Indexed as

Contact TracingCOVID-19HumansPandemicsSARS-CoV-2ThailandCapture-recaptureContact tracingCOVID-19SensitivityThailand

Identifiers

PMID35093019
PMCPMC8799986

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LicenceCC BY
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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.