Differences in the superspreading potentials of COVID-19 across contact settings.

BACKGROUND: Superspreading events (SSEs) played a critical role in fueling the COVID-19 outbreaks. Although it is well-known that COVID-19 epidemics exhibited substantial superspreading potential, little is known about the risk of observing SSEs in different contact settings. In this study, we aimed to assess the potential of superspreading in different contact settings in Japan. METHOD: Transmission cluster data from Japan was collected between January and July 2020. Infector-infectee transmission pairs were constructed based on the contact tracing history. We fitted the data to negative binomial models to estimate the effective reproduction number (R) and dispersion parameter (k). Other epidemiological issues relating to the superspreading potential were also calculated. RESULTS: The overall estimated R and k are 0.561 (95% CrI: 0.496, 0.640) and 0.221 (95% CrI: 0.186, 0.262), respectively. The transmission in community, healthcare facilities and school manifest relatively higher superspreading potentials, compared to other contact settings. We inferred that 13.14% (95% CrI: 11.55%, 14.87%) of the most infectious cases generated 80% of the total transmission events. The probabilities of observing superspreading events for entire population and community, household, health care facilities, school, workplace contact settings are 1.75% (95% CrI: 1.57%, 1.99%), 0.49% (95% CrI: 0.22%, 1.18%), 0.07% (95% CrI: 0.06%, 0.08%), 0.67% (95% CrI: 0.31%, 1.21%), 0.33% (95% CrI: 0.13%, 0.94%), 0.32% (95% CrI: 0.21%, 0.60%), respectively. CONCLUSION: The different potentials of superspreading in contact settings highlighted the need to continuously monitoring the transmissibility accompanied with the dispersion parameter, to timely identify high risk settings favoring the occurrence of SSEs.

Uncovering Construction Site–Specific Transmission Patterns of COVID-19: A Spatiotemporal Connectivity Analysis in Hong Kong

To adapt to the prolonged pandemic, the construction industry, which has a high vulnerability to coronavirus disease 2019 (COVID-19) infection, has sought more sector-specific and individual-level nonpharmaceutical interventions (NPIs). Understanding infection transmission patterns can determine what, when, and how NPIs should be implemented. This study examined infection transmission proceeding from construction sites using spatiotemporal analysis with COVID-19 case cluster data from construction sites in Hong Kong. The study revealed that COVID-19 transmission diffuses from the workplace to residential neighborhoods where infected construction workers live but not to the surroundings of infected construction sites. The average number of offspring cases infected by each seed case in the first to fifth transmission generations were 7.8, 26.1, 10.6, 3.6, and 1.3, respectively. Around 18% of cases were responsible for 79.6% of all COVID-19 transmission, driven mainly by workplace and household settings. The study found that closing a workplace within two working days after a primary case is identified can help reduce the attack rate by 5.33%. Encouraging household members of infected construction workers to follow quarantines can reduce offspring cases by 15.84% on average. A priori identification of superspreaders can help remove half of COVID-19 cases. [ FROM AUTHOR]

Post pandemic fatigue: what are effective strategies?

Recurrent updates in non-pharmaceutical interventions (NPIs) aim to control successive waves of the coronavirus disease 2019 (COVID-19) but are often met with low adherence by the public. This study evaluated the effectiveness of gathering restrictions and quarantine policies based on a modified Susceptible-Exposed-Infectious-Hospitalized-Recovered (SEIHR) model by incorporating cross-boundary travellers with or without quarantine to study the transmission dynamics of COVID-19 with data spanning a nine-month period during 2020 in Hong Kong. The asymptotic stability of equilibria reveals that the model exhibits the phenomenon of backward bifurcation, which in this study is a co-existence between a stable disease-free equilibrium (DFE) and an endemic equilibrium (EE). Even if the basic reproduction number ([Formula: see text]) is less than unity, this disease cannot be eliminated. The effect of each parameter on the overall dynamics was assessed using Partial Rank Correlation Coefficients (PRCCs). Transmission rates (i.e., [Formula: see text] and [Formula: see text]), effective contact ratio [Formula: see text] between symptomatic individuals and quarantined people, and transfer rate [Formula: see text] related to infection during quarantine were identified to be the most sensitive parameters. The effective contact ratios between the infectors and susceptible individuals in late July were found to be over twice as high as that in March of 2020, reflecting pandemic fatigue and the potential existence of infection during quarantine.