ABSTRACT
Background: China lifted strict non-pharmacological interventions (NPIs) to prevent outbreaks of SARS-CoV-2 Omicron variants in December 2022. Relatively low levels of immunity and of vaccine booster coverage in the Chinese population raise concerns that future outbreaks will rapidly result in high rates of death and severe illness and will overwhelm health services. Methods: This was a compartmental, discrete-time population dynamic model. It compared projected deaths and hospitalisation under various scenarios, including booster vaccine coverage and strictness of NPIs. Results: We projected between 268,300 to 398,700 COVID-19 deaths, and peak numbers of hospitalised severe/critical cases between 3.2 to 6.4 per 10,000 population, before the outbreak wave recedes by February 2023. The COVID-19 deaths are reduced by 8% and 30%, respectively, under the weak and strict NPI scenarios, compared with the scenario without NPI measures. Early achievement of high coverage of three vaccine doses will further reduce COVID-19 deaths. Conclusion: We projected fewer COVID-19 deaths and hospitalisations than some other models have. Rapid expansion of booster vaccine coverage will only be effective if combined with strict NPIs and/or the high coverage of booster vaccination could be achieved early.
Subject(s)
COVID-19 , DeathABSTRACT
ObjectivesTo project impacts of mass vaccination against COVID-19, and investigate possible impacts of different types of naturally acquired and vaccine-induced immunity on future dynamics of SARS-CoV-2 transmission from 2021 to 2029 in England. DesignDeterministic, discrete-time population dynamic modelling. ParticipantsPopulation in England. Interventionsmass vaccination programmes. Outcome measuresdaily and cumulative number of deaths from COVID-19. ResultsIf vaccine efficacy is [≥] 70%, the vaccine-induced sterilising immunity lasts [≥] 182 days, and the reinfectivity is greatly reduced (by [≥] 40%), mass vaccination programmes can prevent further COVID-19 outbreaks in England. Under such optimistic scenarios, the cumulative number of COVID-19 deaths is estimated to be from 113,000 to 115,000 by the end of 2029 in England. However, under plausible scenarios with lower vaccine efficacy, shorter durability of immunity, and smaller reduction in reinfectivity, repeated vaccination programmes could not prevent further COVID-19 outbreaks. ConclusionsUnder optimistic scenarios, mass immunisation using efficacious vaccines may enable society safely to return to normality. However, under plausible scenarios with low vaccine efficacy and short durability of immunity, COVID-19 could continue to cause recurrent waves of severe morbidity and mortality despite frequent vaccinations. It is crucial to monitor the vaccination effects in the real world, and to better understand characteristics of naturally acquired and vaccine induced immunity against SARS-CoV-2. ARTICLE SUMMARYO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIWe used a population dynamic model to assess impacts of vaccination programmes on future dynamics of SARS-CoV-2 transmission dynamics, and to explicitly investigate the impacts of different types of immune responses to SARS-CoV-2 infection and vaccines on the COVID-19 epidemic in England. C_LIO_LIThe model has been verified based on historically observed outcome data in England, and a large number of projection scenarios are explored. C_LIO_LIFindings from our study improves the understanding of key immunological parameters relevant to future SARS-CoV-2 transmission dynamics and vaccination strategies. C_LIO_LIThis is a deterministic simulation model, and uncertainty in estimated parameters may have not been fully accommodated. There remain many uncertainties regarding durability and types of naturally acquired and vaccine-induced immunity. C_LI
Subject(s)
COVID-19ABSTRACT
Background: Past infection with COVID-19 or vaccination against SARS-CoV-2 may induce immune responses that prevent infection (sterilising immunity), reduce disease severity and infectivity after being reinfected. Methods: We developed a deterministic, discrete-time population dynamic model to assess impacts of vaccination programmes on future dynamics of SARS-CoV-2 transmission in England. The model explicitly considered durability and different types of naturally acquired and vaccine-induced immunity against SARS-CoV-2 and their impacts on COVID-19 transmission dynamics from 2020 to 2029 in England. We explored a large number of projection scenarios. Findings: If vaccine efficacy is ≥70%, the vaccine-induced sterilising immunity lasts ≥182 days on average, and the reinfectivity is greatly reduced (by ≥40%), annual mass vaccination programmes can prevent further COVID-19 outbreaks in England. Under such optimistic scenarios, the cumulative number of COVID-19 deaths is estimated to be from 113,000 to 115,000 by the end of 2029 in England. However, under plausible scenarios with lower vaccine efficacy, shorter durability of immunity, and smaller reduction in reinfectivity, repeated vaccination programmes could not prevent further COVID-19 outbreaks. Interpretations: Because of great uncertainty in the impacts of mass vaccination on COVID-19 pandemics, it is crucial to monitor vaccination effects in the real world, and to better understand characteristics of naturally acquired and vaccine induced immunity against SARS-CoV-2. Funding: No specific funding received for this study.Declaration of Interests: No competing interests declared.
Subject(s)
COVID-19ABSTRACT
Background: After the outbreak of Coronavirus disease in 2019 (COVID-19), stringent lockdown measures were imposed in Wuhan between January 23, 2020 and April 8, 2020. To provide evidence on the post-lockdown risk of COVID-19 epidemic in Wuhan, the city government conducted a citywide nucleic acid screening of SARS-CoV-2 infection between May 14 and June 1, 2020. Methods: All city residents aged [≥]6 years were potentially eligible to participate the screening programme. The rate of detection of asymptomatic infected cases was calculated, and their demographic and geographic distributions were investigated. ArcGIS 10.0 was used to draw a geographic distribution of asymptomatic infected persons. Results: The screening programme recruited a total of 9,899,828 persons (response rate, 92.9%). The screening found no newly confirmed patients with COVID-19, and identified 300 asymptomatic infected cases (detection rate 0.303/10,000). In addition, 107 of 34,424 previously recovered patients with a history of COVID-19 diagnosis were tested positive (relapse rate, 0.31%). Virus culture of SARS-CoV-2 was negative for all 300 asymptomatic cases and all 107 recovered COVID-19 patients. A total of 1,174 close contacts of asymptomatic cases were traced and all of them had a negative nucleic acid testing result. Conclusions: Prevalence of COVID-19 nucleic acid test positivity was very low in the Wuhan general population, in recovered cases and in contacts of asymptomatic cases, five to eight weeks after the end of lockdown. These findings help resolve concerns about the post-lockdown risk of COVID-19 epidemic, and promote the recovery of economy and normal social life in Wuhan.