دورية أكاديمية
Accounting for the Potential of Overdispersion in Estimation of the Time-varying Reproduction Number.
العنوان: | Accounting for the Potential of Overdispersion in Estimation of the Time-varying Reproduction Number. |
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المؤلفون: | Ho F; From the WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China., Parag KV; MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom.; NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, United Kingdom., Adam DC; From the WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China., Lau EHY; From the WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.; Laboratory of Data Discovery for Health Limited, Hong Kong Science Park, New Territories, Hong Kong., Cowling BJ; From the WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.; Laboratory of Data Discovery for Health Limited, Hong Kong Science Park, New Territories, Hong Kong., Tsang TK; From the WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.; Laboratory of Data Discovery for Health Limited, Hong Kong Science Park, New Territories, Hong Kong. |
المصدر: | Epidemiology (Cambridge, Mass.) [Epidemiology] 2023 Mar 01; Vol. 34 (2), pp. 201-205. Date of Electronic Publication: 2022 Dec 13. |
نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
اللغة: | English |
بيانات الدورية: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 9009644 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1531-5487 (Electronic) Linking ISSN: 10443983 NLM ISO Abbreviation: Epidemiology Subsets: MEDLINE |
أسماء مطبوعة: | Publication: <2000>- : Hagerstown, MD : Lippincott Williams & Wilkins Original Publication: [Cambridge, MA : Blackwell Scientific Publications ; Chestnut Hill, MA : Epidemiology Resources, c1990- |
مواضيع طبية MeSH: | COVID-19*/epidemiology , Epidemics*, Humans ; Computer Simulation ; Hong Kong/epidemiology ; Reproduction |
مستخلص: | Background: The time-varying reproduction number, Rt, is commonly used to monitor the transmissibility of an infectious disease during an epidemic, but standard methods for estimating Rt seldom account for the impact of overdispersion on transmission. Methods: We developed a negative binomial framework to estimate Rt and a time-varying dispersion parameter (kt). We applied the framework to COVID-19 incidence data in Hong Kong in 2020 and 2021. We conducted a simulation study to compare the performance of our model with the conventional Poisson-based approach. Results: Our framework estimated an Rt peaking around 4 (95% credible interval = 3.13, 4.30), similar to that from the Poisson approach but with a better model fit. Our approach further estimated kt <0.5 at the start of both waves, indicating appreciable heterogeneity in transmission. We also found that kt decreased sharply to around 0.4 when a large cluster of infections occurred. Conclusions: Our proposed approach can contribute to the estimation of Rt and monitoring of the time-varying dispersion parameters to quantify the role of superspreading. Competing Interests: Disclosure: B.J.C. reports honoraria from AstraZeneca, GSK, Moderna, Roche and Sanofi Pasteur. The other authors report no conflicts of interest. (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.) |
References: | Bettencourt LM, Ribeiro RM. Real time bayesian estimation of the epidemic potential of emerging infectious diseases. PLoS One. 2008;3:e2185. Tsang TK, Wu P, Lau EHY, Cowling BJ. Accounting for imported cases in estimating the time-varying reproductive number of coronavirus disease 2019 in Hong Kong. J Infect Dis. 2021;224:783–787. Cori A, Ferguson NM, Fraser C, Cauchemez S. A new framework and software to estimate time-varying reproduction numbers during epidemics. Am J Epidemiol. 2013;178:1505–1512. Adam DC, Wu P, Wong JY, et al. Clustering and superspreading potential of SARS-CoV-2 infections in Hong Kong. Nat Med. 2020;26:1714–1719. Du Z, Wang C, Liu C, et al. Superspreading of sars-cov-2 infections: a systematic review and meta-analysis. Transboundary and Emerging Diseases . 2021;69:e3007–e3014. Lloyd-Smith JO, Schreiber SJ, Kopp PE, Getz WM. Superspreading and the effect of individual variation on disease emergence. Nature. 2005;438:355–359. Lee H, Nishiura H. Sexual transmission and the probability of an end of the Ebola virus disease epidemic. J Theor Biol. 2019;471:1–12. Djaafara BA, Imai N, Hamblion E, Impouma B, Donnelly CA, Cori A. A quantitative framework for defining the end of an infectious disease outbreak: application to Ebola virus disease. Am J Epidemiol. 2020;190:642–651. Parag KV. Sub-spreading events limit the reliable elimination of heterogeneous epidemics. J R Soc Interface. 2021;18:2021044420210444. Endo A. Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China. Wellcome Open Res. 2020;5:67. Nishiura H, Linton NM, Akhmetzhanov AR. Serial interval of novel coronavirus (COVID-19) infections. Int J Infect Dis. 2020;93:284–286. Becker NG, Watson LF, Carlin JB. A method of non‐parametric back‐projection and its application to AIDS data. Stat Med. 1991;10:1527–1542. Carpenter B, Gelman A, Hoffman MD, et al. Stan: a probabilistic programming language. J stat Soft. 2017;76:1–32. Ali ST, Wang L, Lau EHY, et al. Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions. Science. 2020;369:1106–1109. |
تواريخ الأحداث: | Date Created: 20230201 Date Completed: 20230202 Latest Revision: 20230322 |
رمز التحديث: | 20240628 |
DOI: | 10.1097/EDE.0000000000001563 |
PMID: | 36722802 |
قاعدة البيانات: | MEDLINE |
تدمد: | 1531-5487 |
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DOI: | 10.1097/EDE.0000000000001563 |