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The serial interval distribution is used to approximate the generation time distribution, an essential parameter to predict the effective reproductive number "Rt", a measure of transmissibility. However, serial interval distributions may change as an epidemic progresses rather than remaining constant. Here we show that serial intervals in Hong Kong varied over time, closely associated with the temporal variation in COVID-19 case profiles and public health and social measures that were implemented in response to surges in community transmission. Quantification of the variation over time in serial intervals led to improved estimation of Rt, and provided additional insights into the impact of public health measures on transmission of infections. One-Sentence SummaryReal-time estimates of serial interval distributions can improve assessment of COVID-19 transmission dynamics and control.
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BackgroundThe generation time distribution, reflecting the time between successive infections in transmission chains, is one of the fundamental epidemiological parameters for describing COVID-19 transmission dynamics. However, because exact infection times are rarely known, it is often approximated by the serial interval distribution, reflecting the time between illness onsets of infector and infectee. This approximation holds under the assumption that infectors and infectees share the same incubation period distribution, which may not always be true. MethodsWe analyzed data on observed incubation period and serial interval distributions in China, during January and February 2020, under different sampling approaches, and developed an inferential framework to estimate the generation time distribution that accounts for variation over time due to changes in epidemiology, sampling biases and public health and social measures. ResultsWe analyzed data on a total of 2989 confirmed cases for COVID-19 during January 1 to February 29, 2020 in Mainland China. During the study period, the empirical forward serial interval decreased from a mean of 8.90 days to 2.68 days. The estimated mean backward incubation period of infectors increased from 3.77 days to 9.61 days, and the mean forward incubation period of infectees also increased from 5.39 days to 7.21 days. The estimated mean forward generation time decreased from 7.27 days (95% confidence interval: 6.42, 8.07) to 4.21 days (95% confidence interval: 3.70, 4.74) days by January 29. We used simulations to examine the sensitivity of our modelling approach to a number of assumptions and alternative dynamics. ConclusionsThe proposed method can provide more reliable estimation of the temporal variation in the generation time distribution, enabling proper assessment of transmission dynamics.
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Hong Kong reported 12,631 confirmed COVID-19 cases and 213 deaths in the first two years of the pandemic but experienced a major wave predominantly of Omicron BA.2.2 in early 2022 with over 1.1 million reported SARS-CoV-2 infections and more than 7900 deaths. Our data indicated a shorter incubation period, serial interval, and generation time of infections with Omicron than other SARS-CoV-2 variants. Omicron BA.2.2 cases without a complete primary vaccination series appeared to face a similar fatality risk to those infected in earlier waves with the ancestral strain.
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We estimated mean serial interval and superspreading potential for the predominant Delta variant of SARS-CoV-2. Mean serial intervals were similar with 3.7 and 3.5 days during early and latter periods, respectively. Furthermore, the risk of superspreading events was similar with 23% and 25% of cases seeded 80% of all transmissions.
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BackgroundThe Delta variant of SARS-CoV-2 has become predominant globally. We evaluated the transmission dynamics and epidemiological characteristics of the Delta variant in an outbreak in southern China. MethodsData on confirmed cases and their close contacts were retrospectively collected from the outbreak that occurred in Guangdong, China in May-June 2021. Key epidemiological parameters, temporal trend of viral loads and secondary attack rates were estimated and compared between the Delta variant and the wild-type SARS-CoV-2 virus. We also evaluated the association of vaccination with viral load and transmission. ResultsWe identified 167 patients infected with the Delta variant in the Guangdong outbreak. The mean estimates of the latent period and the incubation period were 4.0 days and 5.8 days, respectively. A relatively higher viral load was observed in Delta cases than in wild-type infections. The secondary attack rate among close contacts of Delta cases was 1.4%, and 73.9% (95% confidence interval: 67.2%, 81.3%) of the transmissions occurred before onset. Index cases without vaccination (OR: 2.84, 95% confidence interval: 1.19, 8.45) or with one dose of vaccination (OR: 6.02, 95% confidence interval: 2.45, 18.16) were more likely to transmit infection to their contacts than those who had received 2 doses of vaccination. DiscussionPatients infected with the Delta variant had more rapid symptom onset. The shorter and time-varying serial interval should be accounted in estimation of reproductive numbers. The higher viral load and higher risk of pre-symptomatic transmission indicated the challenges in control of infections with the Delta variant.
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ObjectiveThis study investigates how the SARS-CoV-2 transmission potential varied in North Dakota, South Dakota, Montana, Wyoming, and Idaho from March 2020 through January 2021. MethodsTime-varying reproduction numbers, Rt, of a 7-day-sliding-window and of non-overlapping-windows between policy changes were estimated utilizing the instantaneous reproduction number method. Linear regression was performed to evaluate if per-capita cumulative case-count varied across counties with different population size. ResultsThe median 7-day-sliding-window Rt estimates across the studied region varied between 1 and 1.25 during September through November 2020. Between November 13 and 18, Rt was reduced by 14.71% (95% credible interval, CrI, [14.41%, 14.99%]) in North Dakota following a mask mandate; Idaho saw a 1.93% (95% CrI [1.87%, 1.99%]) reduction and Montana saw a 9.63% (95% CrI [9.26%, 9.98%]) reduction following the tightening of restrictions. High-population counties had higher per-capita cumulative case-count in North Dakota at four time points (June 30, August 31, October 31, and December 31, 2020). In Idaho, North Dakota, and South Dakota, there was a positive correlation between population size and per-capita weekly incident case-count, adjusted for calendar time and social vulnerability index variables. ConclusionsRt decreased after mask mandate during the regions case-count spike suggested reduction in SARS-CoV-2 transmission.
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A fast-spreading SARS-CoV-2 variant identified in the United Kingdom in December 2020 has raised international alarm. We estimate that, in all 15 countries analyzed, there is at least a 50% chance the variant was imported by travelers from the United Kingdom by December 7th.
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BackgroundA range of public health measures have been implemented to delay and reduce local transmission of COVID-19 in Hong Kong, and there have been major changes in behaviours of the general public. We examined the effect of these interventions and behavioral changes on the incidence of COVID-19 as well as on influenza virus infections which may share some aspects of transmission dynamics with COVID-19. MethodsWe reviewed policy interventions and measured changes in population behaviours through two telephone surveys, on January 20-23 and February 11-14. We analysed data on laboratory-confirmed COVID-19 cases, influenza surveillance data in outpatients of all ages, and influenza hospitalisations in children. We estimated the daily effective reproduction number (Rt), for COVID-19 and influenza A(H1N1). FindingsCOVID-19 transmissibility has remained at or below 1, indicating successful containment to date. Influenza transmission declined substantially after the implementation of social distancing measures and changes in population behaviours in late January, with a 44% (95% confidence interval, CI: 34% to 53%) reduction in transmissibility in the community, and a 33% (95% CI: 24% to 43%) reduction in transmissibility based on paediatric hospitalization rates. In the two surveys we estimated that 74.5% and 97.5% of the general adult population wore masks when going out, and 61.3% and 90.2% avoided going to crowded places, respectively. ImplicationsContainment measures, social distancing measures and changes in population behaviour have successfully prevented spread of COVID-19. The social distancing measures and behavioural changes led to a substantial reduction in influenza transmission in early February 2020. However, it may be challenging to avoid fatigue and sustain these measures and population behaviours as COVID-19 continues to spread globally. FundingHealth and Medical Research Fund, Hong Kong
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ImportanceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the city of Wuhan, China, in December 2019 and then spread globally. Limited information is available for characterizing epidemiological features and transmission patterns in the regions outside of Hubei Province. Detailed data on transmission at the individual level could be an asset to understand the transmission mechanisms and respective patterns in different settings. ObjectiveTo reconstruct infection events and transmission clusters of SARS-CoV-2 for estimating epidemiological characteristics at household and non-household settings, including super-spreading events, serial intervals, age- and gender-stratified risks of infection in China outside of Hubei Province. Design, Setting, and Participants9,120 confirmed cases reported online by 264 Chinese urban Health Commissions in 27 provinces from January 20 to February 19, 2020. A line-list database is established with detailed information on demographic, social and epidemiological characteristics. The infection events are categorized into the household and non-household settings. ExposuresConfirmed cases of SARS-CoV-2 infections. Main Outcomes and MeasuresInformation about demographic characteristics, social relationships, travel history, timelines of potential exposure, symptom onset, confirmation, and hospitalization were extracted from online public reports. 1,407 infection events formed 643 transmission clusters were reconstructed. ResultsIn total 34 primary cases were identified as super spreaders, and 5 household super-spreading events were observed. The mean serial interval is estimated to be 4.95 days (standard deviation: 5.24 days) and 5.19 days (standard deviation: 5.28 days) for households and non-household transmissions, respectively. The risk of being infected outside of households is higher for age groups between 18 and 64 years, whereas the hazard of being infected within households is higher for age groups of young (<18) and elderly (>65) people. Conclusions and RelevanceThe identification of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of age between 18 and 64 indicate a significant barrier to the case identification and management, which calls for intensive non-pharmaceutical interventions (e.g. cancellation of public gathering, limited access of public services) as the potential mitigation strategies. Key PointsO_ST_ABSQuestionC_ST_ABSWhat epidemiological characteristics and risk factors are associated with household and non-household transmissions of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China outside of Hubei Province? FindingsIn this epidemiological study analyzing 1,407 SARS-CoV-2 infection events reported between 20 January 2020 and 19 February 2020, 643 transmission clusters were reconstructed to demonstrate the non-negligible frequency of super-spreading events, short duration of serial intervals, and a higher risk of being infected outside of household for male people of age between 18 and 64 years. MeaningThese findings provide epidemiological features and risk estimates for both household and non-household transmissions of SARS-CoV-2 in China outside of Hubei Province.
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BackgroundIn March 2020, overall, 37,000 international students from the country at risk of the 2019-novel coronavirus (COVID-19) infection will arrive in Seoul, South Korea. Individuals from the country at risk of COVID-19 infection have been included in a home-quarantine program, but the efficacy of the program is uncertain. MethodsTo estimate the possible number of infected individuals within the large influx of international students, we used a deterministic compartmental model for epidemic and perform a simulation-based search of different rates of compliance with home-quarantine. ResultsUnder the home-quarantine program, the total number of the infected individuals would reach 24-53 from March 17-March 20, 50-86 from March 18- March 16, and 234- 343 from March 4- March 23 with the arrival of 0.1%, 0.2%, and 1% of pre-infectious individuals, in Seoul, South Korea, respectively. Our findings indicated when incoming international students showed strict compliance with quarantine, epidemics were less likely to occur in Seoul, South Korea. ConclusionTo mitigate possible epidemics, additional efforts to improve the compliance of home-quarantine are warranted along with other containment policies.
