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Modeling COVID‐19 contact‐tracing using the ratio regression capture–recapture approach

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  • Dankmar Böhning
  • Rattana Lerdsuwansri
  • Patarawan Sangnawakij
Abstract
Contact‐tracing is one of the most effective tools in infectious disease outbreak control. A capture–recapture approach based upon ratio regression is suggested to estimate the completeness of case detection. Ratio regression has been recently developed as flexible tool for count data modeling and has proved to be successful in the capture–recapture setting. The methodology is applied here to Covid‐19 contact tracing data from Thailand. A simple weighted straight line approach is used which includes the Poisson and geometric distribution as special cases. For the case study data of contact tracing for Thailand, a completeness of 83% could be found with a 95% confidence interval of 74%–93%.

Suggested Citation

  • Dankmar Böhning & Rattana Lerdsuwansri & Patarawan Sangnawakij, 2023. "Modeling COVID‐19 contact‐tracing using the ratio regression capture–recapture approach," Biometrics, The International Biometric Society, vol. 79(4), pages 3818-3830, December.
    • Handle: RePEc:bla:biomet:v:79:y:2023:i:4:p:3818-3830
    DOI: 10.1111/biom.13842
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    References listed on IDEAS

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    1. Anne Chao & John Bunge, 2002. "Estimating the Number of Species in a Stochastic Abundance Model," Biometrics, The International Biometric Society, vol. 58(3), pages 531-539, September.
    2. Dankmar Böhning & Helen E. Ogden, 2021. "General flation models for count data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(2), pages 245-261, February.
    3. Dankmar Böhning & Panicha Kaskasamkul & Peter G. M. Heijden, 2019. "A modification of Chao’s lower bound estimator in the case of one-inflation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(3), pages 361-384, April.
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