A novel nonparametric mixture model for the detection pattern of COVID-19 on Diamond Princess cruise

Abstract

The outbreak of COVID-19 on the Diamond Princess cruise ship has attracted much attention. Motivated by the PCR testing data on the Diamond Princess, we propose a novel cure mixture nonparametric model to investigate the detection pattern. It combines a logistic regression for the probability of susceptible subjects with a nonparametric distribution for the detection of infected individuals. Maximum likelihood estimators are proposed. The resulting estimators are shown to be consistent and asymptotically normal. Simulation studies demonstrate that the proposed approach is appropriate for practical use. Finally, we apply the proposed method to PCR testing data on the Diamond Princess to show its practical utility.

Keywords:

• Cure model
• logistic regression
• maximum likelihood estimator
• mixture

Acknowledgments

The authors thank the Editor, Professor Jun Shao, an Associate Editor and three reviewers for their insightful comments and suggestions that greatly improved the article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is partly supported by the National Natural Science Foundation of China [grant numbers 71931004, 11901200, 71971083, and 11971170] and the National Key R&D Program of China [grant numbers 2021YFA1000100, 2021YFA1000101].