ArticleStochastic environmental research and risk assessment : research journal2023
A multi-type branching process model for epidemics with application to COVID-19.
Article in Stochastic environmental research and risk assessment : research journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- [Analysis of Coronavirus Disease 2019 Prediction Studies in the Republic of Korea].Jugan geon-gang gwa jilbyeong · 2025Review
- Attitudes towards booster, testing and isolation, and their impact on COVID-19 response in winter 2022/2023 in France, Belgium, and Italy: a cross-sectional survey and modelling study.The Lancet regional health. Europe · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper we model an infectious disease epidemic using Multi-type Branching Process where the number of offsprings of different types follow non-identical Poisson distributions whose parameters may vary over time. We allow for variation in parameters due to the behavior of citizens, government interventions in the form of lockdown, testing and contact tracing and the infectiousness of the variant of the virus in circulation at a time-point in a location. The model can be used to estimate several unknown quantities of interest in an epidemic such as the number of undetected cases and number of people quarantined following contact tracing. The model is fitted to the publicly available COVID-19 caseload data of India, South Korea, UK and US and is seen to provide good fit. It also provides good short-term forecast of the caseload for these countries. This model can be useful for health policy planners in assessing the impact of various intervention strategies such as testing, contact tracing, quarantine etc.
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Registered trials
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