Public health impact of UK COVID-19 booster vaccination programs during Omicron predominance.

BACKGROUND: We aimed to estimate the public health impact of booster vaccination against COVID-19 in the UK during an Omicron-predominant period. RESEARCH DESIGN AND METHODS: A dynamic transmission model was developed to compare public health outcomes for actual and alternative UK booster vaccination programs. Input sources were publicly available data and targeted literature reviews. Base case analyses estimated outcomes from the UK's Autumn-Winter 2021-2022 booster program during January-March 2022, an Omicron-predominant period. Scenario analyses projected outcomes from Spring and in Autumn 2022 booster programs over an extended time horizon from April 2022-April 2023, assuming continued Omicron predominance, and explored hypothetical program alternatives with modified eligibility criteria and/or increased uptake. RESULTS: Estimates predicted that the Autumn-Winter 2021-2022 booster program averted approximately 12.8 million cases, 1.1 million hospitalizations, and 290,000 deaths. Scenario analyses suggested that Spring and Autumn 2022 programs would avert approximately 6.2 million cases, 716,000 hospitalizations, and 125,000 deaths; alternatives extending eligibility or targeting risk groups would improve these benefits, and increasing uptake would further strengthen impact. CONCLUSIONS: Boosters were estimated to provide substantial benefit to UK public health during Omicron predominance. Benefits of booster vaccination could be maximized by extending eligibility and increasing uptake.

Public health impact of booster vaccination against COVID-19 in the UK during Delta variant dominance in autumn 2021.

AIM: To evaluate the public health impact of the UK COVID-19 booster vaccination program in autumn 2021, during a period of SARS-CoV-2 Delta variant predominance. MATERIALS AND METHODS: A compartmental Susceptible-Exposed-Infectious-Recovered model was used to compare age-stratified health outcomes for adult booster vaccination versus no booster vaccination in the UK over a time horizon of September-December 2021, when boosters were introduced in the UK and the SARS-CoV-2 Delta variant was predominant. Model input data were sourced from targeted literature reviews and publicly available data. Outcomes were predicted COVID-19 cases, hospitalizations, post-acute sequelae of COVID-19 (PASC) cases, deaths, and productivity losses averted, and predicted healthcare resources saved. Scenario analyses varied booster coverage, virus infectivity and severity, and time horizon parameters. RESULTS: Booster vaccination was estimated to have averted approximately 547,000 COVID-19 cases, 36,000 hospitalizations, 147,000 PASC cases, and 4,200 deaths in the UK between September and December 2021. It saved over 316,000 hospital bed-days and prevented the loss of approximately 16.5 million paid and unpaid patient work days. In a scenario of accelerated uptake, the booster rollout would have averted approximately 3,400 additional deaths and 25,500 additional hospitalizations versus the base case. A scenario analysis assuming four-fold greater virus infectivity and lower severity estimated that booster vaccination would have averted over 105,000 deaths and over 41,000 hospitalizations versus the base case. A scenario analysis assuming pediatric primary series vaccination prior to adult booster vaccination estimated that expanding vaccination to children aged ≥5 years would have averted approximately 51,000 additional hospitalizations and 5,400 additional deaths relative to adult booster vaccination only. LIMITATIONS: The model did not include the wider economic burden of COVID-19, hospital capacity constraints, booster implementation costs, or non-pharmaceutical interventions. CONCLUSIONS: Booster vaccination during Delta variant predominance reduced the health burden of SARS-CoV-2 in the UK, releasing substantial NHS capacity.

COVID-19 Risk Analysis in South Asia with Respect to Europe and North America

Coronavirus Disease 2019 (COVID-19) was identified in late 2019 and the world health Organization (WHO) declared it as a pandemic on March 11, 2019. World top researchers, physicians, and pharmacists are trying to find out remedy but it is still in the research phase. COVID-19 spread through the air by coughing or sneezing also depends on the environment. In this paper, our main goal is to COVID-19 threat analysis in South Asian people based on their habits, culture, consciousness, etc. compare to Europe and North American culture. The research work is formulated in three steps. Firstly, we formulate a dynamic infection transmission model by considering the fertility rate, mortality rate, transmission rate, and cure rate of the COVID-19 caused death rate as variables. Secondly, we define the variables of the model based on the census of south Asia. Finally, we propose some risk reduction, infection prevention, and control in South Asian countries. ©AJSE 2021.

Dependence of COVID-19 Policies on End-of-Year Holiday Contacts in Mexico City Metropolitan Area: A Modeling Study.

Background. Mexico City Metropolitan Area (MCMA) has the largest number of COVID-19 (coronavirus disease 2019) cases in Mexico and is at risk of exceeding its hospital capacity in early 2021. Methods. We used the Stanford-CIDE Coronavirus Simulation Model (SC-COSMO), a dynamic transmission model of COVID-19, to evaluate the effect of policies considering increased contacts during the end-of-year holidays, intensification of physical distancing, and school reopening on projected confirmed cases and deaths, hospital demand, and hospital capacity exceedance. Model parameters were derived from primary data, literature, and calibrated. Results. Following high levels of holiday contacts even with no in-person schooling, MCMA will have 0.9 million (95% prediction interval 0.3-1.6) additional COVID-19 cases between December 7, 2020, and March 7, 2021, and hospitalizations will peak at 26,000 (8,300-54,500) on January 25, 2021, with a 97% chance of exceeding COVID-19-specific capacity (9,667 beds). If MCMA were to control holiday contacts, the city could reopen in-person schools, provided they increase physical distancing with 0.5 million (0.2-0.9) additional cases and hospitalizations peaking at 12,000 (3,700-27,000) on January 19, 2021 (60% chance of exceedance). Conclusion. MCMA must increase COVID-19 hospital capacity under all scenarios considered. MCMA's ability to reopen schools in early 2021 depends on sustaining physical distancing and on controlling contacts during the end-of-year holiday.

Impact of temperature on the dynamics of the COVID-19 outbreak in China.

A COVID-19 outbreak emerged in Wuhan, China at the end of 2019 and developed into a global pandemic during March 2020. The effects of temperature on the dynamics of the COVID-19 epidemic in China are unknown. Data on COVID-19 daily confirmed cases and daily mean temperatures were collected from 31 provincial-level regions in mainland China between Jan. 20 and Feb. 29, 2020. Locally weighted regression and smoothing scatterplot (LOESS), distributed lag nonlinear models (DLNMs), and random-effects meta-analysis were used to examine the relationship between daily confirmed cases rate of COVID-19 and temperature conditions. The daily number of new cases peaked on Feb. 12, and then decreased. The daily confirmed cases rate of COVID-19 had a biphasic relationship with temperature (with a peak at 10 °C), and the daily incidence of COVID-19 decreased at values below and above these values. The overall epidemic intensity of COVID-19 reduced slightly following days with higher temperatures with a relative risk (RR) was 0.96 (95% CI: 0.93, 0.99). A random-effect meta-analysis including 28 provinces in mainland China, we confirmed the statistically significant association between temperature and RR during the study period (Coefficient = -0.0100, 95% CI: -0.0125, -0.0074). The DLNMs in Hubei Province (outside of Wuhan) and Wuhan showed similar patterns of temperature. Additionally, a modified susceptible-exposed-infectious-recovered (M-SEIR) model, with adjustment for climatic factors, was used to provide a complete characterization of the impact of climate on the dynamics of the COVID-19 epidemic.