Basic reproduction number of the COVID-19 Delta variant: Estimation from multiple transmission datasets.

The basic reproduction number, $ R_0 $, plays a central role in measuring the transmissibility of an infectious disease, and it thus acts as the fundamental index for planning control strategies. In the present study, we apply a branching process model to meticulously observed contact tracing data from Wakayama Prefecture, Japan, obtained in early 2020 and mid-2021. This allows us to efficiently estimate $ R_0 $ and the dispersion parameter $ k $ of the wild-type COVID-19, as well as the relative transmissibility of the Delta variant and relative transmissibility among fully vaccinated individuals, from a very limited data. $ R_0 $ for the wild type of COVID-19 is estimated to be 3.78 (95% confidence interval [CI]: 3.72-3.83), with $ k = 0.236 $ (95% CI: 0.233-0.240). For the Delta variant, the relative transmissibility to the wild type is estimated to be 1.42 (95% CI: 0.94-1.90), which gives $ R_0 = 5.37 $ (95% CI: 3.55-7.21). Vaccine effectiveness, determined by the reduction in the number of secondary transmissions among fully vaccinated individuals, is estimated to be 91% (95% CI: 85%-97%). The present study highlights that basic reproduction numbers can be accurately estimated from the distribution of minor outbreak data, and these data can provide further insightful epidemiological estimates including the dispersion parameter and vaccine effectiveness regarding the prevention of transmission.

Systematic review and meta-analyses of superspreading of SARS-CoV-2 infections.

Superspreading, or overdispersion in transmission, is a feature of SARS-CoV-2 transmission which results in surging epidemics and large clusters of infection. The dispersion parameter is a statistical parameter used to characterize and quantify heterogeneity. In the context of measuring transmissibility, it is analogous to measures of superspreading potential among populations by assuming that collective offspring distribution follows a negative-binomial distribution. We conducted a systematic review and meta-analysis on globally reported dispersion parameters of SARS-CoV-2 infection. All searches were carried out on 10 September 2021 in PubMed for articles published from 1 January 2020 to 10 September 2021. Multiple estimates of the dispersion parameter have been published for 17 studies, which could be related to where and when the data were obtained, in 8 countries (e.g. China, the United States, India, Indonesia, Israel, Japan, New Zealand and Singapore). High heterogeneity was reported among the included studies. The mean estimates of dispersion parameters range from 0.06 to 2.97 over eight countries, the pooled estimate was 0.55 (95% CI: 0.30, 0.79), with changing means over countries and decreasing slightly with the increasing reproduction number. The expected proportion of cases accounting for 80% of all transmissions is 19% (95% CrI: 7, 34) globally. The study location and method were found to be important drivers for diversity in estimates of dispersion parameters. While under high potential of superspreading, larger outbreaks could still occur with the import of the COVID-19 virus by traveling even when an epidemic seems to be under control.

Secondary transmission of SARS-CoV-2 during the first two waves in Japan: Demographic characteristics and overdispersion.

OBJECTIVES: Super-spreading events caused by overdispersed secondary transmission are crucial in the transmission of COVID-19. However, the exact level of overdispersion, demographics, and other factors associated with secondary transmission remain elusive. In this study, we aimed to elucidate the frequency and patterns of secondary transmission of SARS-CoV-2 in Japan. METHODS: We analyzed 16,471 cases between January 2020 and August 2020. We generated the number of secondary cases distribution and estimated the dispersion parameter (k) by fitting the negative binomial distribution in each phase. The frequencies of the secondary transmission were compared by demographic and clinical characteristics, calculating the odds ratio using logistic regression models. RESULTS: We observed that 76.7% of the primary cases did not generate secondary cases with an estimated dispersion parameter k of 0.23. The demographic patterns of primary-secondary cases differed between phases, with 20-69 years being the predominant age group. There were higher proportions of secondary transmissions among older individuals, symptomatic patients, and patients with 2 days or more between onset and confirmation. CONCLUSIONS: The study showed the estimation of the frequency of secondary transmission of SARS-CoV-2 and the characteristics of people who generated the secondary transmission.