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Abstract Background The latent and incubation periods characterize the transmission of infectious viruses and are the basis for the development of outbreak prevention and control strategies. However, systematic studies on the latent period and associated factors with the incubation period for SAS-CoV-2 variants are still lacking. We inferred the two durations of Delta, BA.1, and BA.2 cases and analyzed the associated factors. Methods The Delta, BA.1, and BA.2 (and its lineages BA.2.2 and BA.2.76) cases with clear transmission chains and infectors from 10 local SAS-CoV-2 epidemics in China were enrolled. The latent and incubation periods were fitted by the Gamma distribution, and associated factors were analyzed using the accelerated failure time model. Results The mean latent period for 672 Delta, 208 BA.1, and 677 BA.2 cases was 4.40 (95%CI: 4.24 ~ 4.63), 2.50 (95%CI: 2.27 ~ 2.76), and 2.58 (95%CI: 2.48 ~ 2.69) days, respectively, with 85.65% (95%CI: 83.40 ~ 87.77%), 97.80% (95%CI: 96.35 ~ 98.89%), and 98.87% (95%CI: 98.40 ~ 99.27%) of them starting to shed viruses within 7 days after exposure. In 405 Delta, 75 BA.1, and 345 BA.2 symptomatic cases, the mean latent period was 0.76, 1.07, and 0.79 days shorter than the mean incubation period [5.04 (95%CI: 4.83 ~ 5.33), 3.42 (95%CI: 3.00 ~ 3.89), and 3.39 (95%CI: 3.24 ~ 3.55) days], respectively. No significant difference was observed in the two durations between BA.1 and BA.2 cases. After controlling for the sex, clinical severity, vaccination history, number of infectors, the length of exposure window and shedding window, the latent period [Delta: exp(β) = 0.81, 95%CI: 0.66 ~ 0.98, p = 0.034; Omicron: exp(β) = 0.82, 95%CI: 0.71 ~ 0.94, p = 0.004] and incubation period [Delta: exp(β) = 0.69, 95%CI: 0.55 ~ 0.86, p

Objectives: We aimed to explore the transmission dynamics of the Omicron BA.1.1 variant in an outbreak in China. Methods: We constructed 113 transmission pairs based on the time of exposure and symptom onset for identified infectors and infectees, using the epidemiological data collected during an outbreak in Hangzhou, Zhejiang province, China, between January and February 2022. The key epidemiological parameters were estimated. Results: The mean estimates of the incubation period and latent period distributions were 3.8 days (95% credible interval: 3.5, 4.1) and 3.1 days (2.8, 3.5), respectively. The overall transmission risk peaked at symptom onset, and we estimated that 33.6% (24.8, 42.5) of transmission occurred before symptom onset. The forward generation time decreased from 5.2 days (4.7, 5.7) at the start of the outbreak to 2.2 days (2.0, 2.5) by the end. Allowing this variation over time in the generation time distribution, we estimated that the reproduction number dropped rapidly from 9.5 (3.5, 18.4) to 0.8 (0.3, 1.5) over the outbreak. Conclusion: Shorter incubation period and latent period were estimated for the Omicron BA.1.1 variant. Stringent public health measures prevented a large epidemic by reducing transmission, as indicated by the shortened generation time.

Summary: Background: Hong Kong followed a strict COVID-19 elimination strategy in 2020. We estimated the impact of the COVID-19 pandemic responses on all-cause and cause-specific hospitalizations and deaths in 2020. Methods: Interrupted time-series analysis using negative binomial regression accounting for seasonality and long-term trend was used on weekly 2010–2020 data to estimate the change in hospitalization risk and excess mortality occurring both within and out of hospitals. Findings: In 2020, as compared to a 2010–2019 baseline, we observed an overall reduction in all-cause hospitalizations, and a concurrent increase in deaths. The overall hospitalization reduction (per 100,000 population) was 4809 (95% CI: 4692, 4926) in 2020, with respiratory diseases (632, 95% CI: 607, 658) and cardiovascular diseases (275, 95% CI: 264, 286) contributing most. The overall excess mortality (per 100,000 population) was 25 (95% CI: 23, 27) in 2020, mostly among individuals with pre-existing cardiovascular diseases (12, 95% CI: 11, 13). A reduction in excess in-hospital mortality (−10 per 100,000, 95% CI: −12, −8) was accompanied by an increase in excess out-of-hospital mortality (32, 95% CI: 29, 34). Interpretation: The COVID-19 pandemic might have caused indirect impact on population morbidity and mortality likely through changed healthcare seeking particularly in youngest and oldest individuals and those with cardiovascular diseases. Better healthcare planning is needed during public health emergencies with disruptions in healthcare services. Funding: Health and Medical Research Fund, Collaborative Research Fund, AIR@InnoHK and RGC Senior Research Fellow Scheme, Hong Kong.

Reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants due to immune escape is challenging for the global response to the pandemic. We estimated the Omicron reinfection prevalence among people who had a previous SARS-CoV-2 infection in Shanghai, China. We conducted a telephone survey in December 2022 with those who had previously been infected with Omicron between March and May 2022. Information on their demographics, coronavirus disease 2019 (COVID-19) testing, and vaccination history was collected. The overall and subgroup reinfection rates were estimated and compared. Among the 1981 respondents who were infected between March and May 2022, 260 had positive nucleic acid or rapid antigen tests in December 2022, with an estimated reinfection rate of 13.1% (95% confidence interval [95% CI]: 11.6–14.6). The reinfection rate for those who had a booster vaccination was 11.4% (95% CI: 9.2–13.7), which was significantly lower than that for those with an incomplete vaccination series (15.2%, 95% CI: 12.3–18.1) (adjusted odds ratio [aOR]: 0.579; 95% CI: 0.412–0.813). Reinfection with the Omicron variant was lower among individuals with a previous SARS-CoV-2 infection and those who had a booster vaccination, suggesting that hybrid immunity may offer protection against reinfection with Omicron sublineages.