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• Vaccine-derived herd immunity against COVID-19 can be achieved if at least 60% of the population is fully-vaccinated. • COVID-19 elimination is feasible by June 2022 if the current baseline full vaccination coverage is increased by about 20%. • Elimination prospects are improved significantly if vaccination is combined with the use of moderate to high-quality masks. • Having more people wear surgical masks is more beneficial than having fewer people wear the highly-effective N95 masks. • Treatment of symptomatic individuals has a significant impact on reducing daily hospitalizations. The effectiveness of control interventions against COVID-19 is threatened by the emergence of SARS-CoV-2 variants of concern. We present a mathematical model for studying the transmission dynamics of two of these variants (Delta and Omicron) in the United States, in the presence of vaccination, treatment of individuals with clinical symptoms of the disease and the use of face masks. The model is parameterized and cross-validated using observed daily case data for COVID-19 in the United States for the period from November 2021 (when Omicron first emerged) to March 2022. Rigorous qualitative analysis of the model shows that the disease-free equilibrium of the model is locally-asymptotically stable when the control reproduction number of the model (denoted by R c) is less than one. This equilibrium is shown to be globally-asymptotically stable for a special case of the model, where disease-induced mortality is negligible and both vaccine-derived immunity in fully-vaccinated individuals and natural immunity do not wane, when the associated reproduction number is less than one. The epidemiological implication of the latter result is that the combined vaccination-boosting strategy can lead to the elimination of the pandemic if its implementation can bring (and maintain) the associated reproduction number to a value less than one. An analytical expression for the vaccine-derived herd immunity threshold is derived. Using this expression, together with the baseline values of the parameters of the parameterized model, we showed that the vaccine-derived herd immunity can be achieved in the United States (so that the pandemic will be eliminated) if at least 68 % of the population is fully-vaccinated with two of the three vaccines approved for use in the United States (Pfizer or Moderna vaccine). Furthermore, this study showed (as of the time of writing in March 2022) that the control reproduction number of the Omicron variant was approximately 3.5 times that of the Delta variant (the reproduction of the latter is computed to be ≈ 0.2782), indicating that Delta had practically died out and that Omicron has competitively-excluded Delta (to become the predominant variant in the United States). Based on our analysis and parameterization at the time of writing of this paper (March 2022), our study suggests that SARS-CoV-2 elimination is feasible by June 2022 if the current baseline level of the coverage of fully-vaccinated individuals is increased by about 20 %. The prospect of pandemic elimination is significantly improved if vaccination is combined with a face mask strategy that prioritizes moderately effective and high-quality masks. Having a high percentage of the populace wearing the moderately-effective surgical mask is more beneficial to the community than having low percentage of the populace wearing the highly-effective N95 masks. We showed that waning natural and vaccine-derived immunity (if considered individually) offer marginal impact on disease burden, except for the case when they wane at a much faster rate (e.g., within three months), in comparison to the baseline (estimated to be within 9 months to a year). Treatment of symptomatic individuals has marginal effect in reducing daily cases of SARS-CoV-2, in comparison to the baseline, but it has significant impact in reducing daily hospitalizations. Furthermore, while treatment significantly reduces daily hospitalizations (and, consequently, deaths), the prospects of COVID-19 elimination in the United States are significantly enhanced if investments in control resources are focused on mask usage and vaccination rather than on treatment. [ABSTRACT FROM AUTHOR]

COVID-19 is the most devastating pandemic that affected humanity and the world economy. This paper aimed to study the time-varying connectedness between the COVID-19 vaccination, infection rate (INFR), and the case fatality ratio (CFR) in the United States and the stock market returns. We used COVID-19 daily confirmed number of infections, deaths, and vaccinations and the daily US stock market index return. A wavelet coherence approach was used to assess the co-movement of the US stock market with the COVID-19 vaccination, INFR, and the CFR. The COVID-19 vaccination, INFR, and CFR have a positive and significant influence on S&P 500 returns at the majority of business cycle frequencies with an in-phase relation. The wavelet coherence analysis uncovers strong and significant connectedness between COVID-19 vaccination rate and S&P 500 return. From an economic perspective, the US government should continue its intervention with their vaccination strategy, as it is beneficial for fighting the pandemic. This may lead to the recovery of the stock market as well as to the whole economy. [ABSTRACT FROM AUTHOR]

The Delta-Omicron wave of the COVID-19 pandemic (Wave 4) in the United States occurred in Fall of 2021 through Spring of 2022. Although vaccinations were widely available, this was the deadliest period to date in the U.S., and the toll was especially high in rural areas, exacerbating an existing rural mortality penalty. This paper uses county-level multilevel regression models and publicly available data for 47 U.S. states and the District of Columbia. We describe differences in COVID-19 case and mortality rates across the rural-urban continuum during Wave 4 of the COVID-19 pandemic. Using a progressive modeling approach, we evaluate the relative contribution of a range of explanatory factors for the rural disadvantage we observe, including: pre-pandemic population health composition, vaccination rates, political partisanship, socioeconomic composition, access to broadband internet rate, and primary care physicians per capita. Results show that rural counties had higher observed burdens of cases and deaths in Wave 4 compared to more urban counties. The most remote rural counties had Wave 4 COVID-19 mortality rates 52% higher than the most urban counties. Older age composition, worse pre-pandemic population health, lower vaccination rates, higher share of votes cast for Donald Trump in the 2020 Presidential election, and lower socioeconomic composition completely explained the rural disadvantage in reported COVID-19 case rates in Wave 4, and accounting for these factors reversed the observed rural disadvantage in COVID-19 mortality. In models of mortality rate, Trump vote share had the largest effect size, followed by the percentage of the population age 50 or older, the poverty rate, the pre-pandemic mortality rate, the share of residents with a 4-year college degree, and the vaccination rate. These findings add to a growing literature describing the disproportionate toll of the COVID-19 pandemic on rural America, highlighting the combined effect of multiple sources of rural disadvantage. • Rural counties had higher case and death rates in the Delta-Omicron wave. • Rural counties had up to 51% more deaths per capita than the most urban counties. • Age, health, and SES composition partially explained the rural disadvantage. • Vaccination and Trump vote share were separate factors in the rural disadvantage. • Multiple sources of disadvantage combined in rural areas to produce poor outcomes. [ABSTRACT FROM AUTHOR]

Research in several countries shows higher Covid-19 vaccination willingness and uptake among physicians than nurses. Our paper aims to characterize and explain this difference. In early 2021, we surveyed 1047 U.S. primary care professionals who served adolescents, ages 11–17. The national sample included physicians (71%) as well as nurses and advanced practice providers. The survey assessed the three domains of the Increasing Vaccination Model: thinking and feeling , social processes , and direct behavior change. Covid-19 vaccine uptake was higher among physicians than among nurses and advanced practice providers (91% vs. 76%, p <.05). Overall, in the thinking and feeling domain, higher confidence in Covid-19 vaccination, higher perceived susceptibility to the disease, and stronger anticipated regret were associated with higher vaccine uptake (all p <.05). In the social processes domain, perceiving more positive social norms for Covid-19 vaccination, receiving recommendations to get the vaccine, and wanting to help others were associated with higher vaccine uptake (all p <.05). In the direct behavior change domain, receiving an invitation to get the vaccine and better access to vaccination were associated with higher uptake (both p <.05). Of these variables, most of the thinking and feeling and social processes variables mediated the association of training with vaccine uptake. Physicians had higher Covid-19 vaccine uptake than nurses and advanced practice providers, corresponding with their more supportive vaccine beliefs and social experiences. Efforts to reach the remaining unvaccinated cohort can build on these findings. • Covid-19 vaccine uptake among advanced practice providers and nurses was lower than in physicians. • Vaccine confidence and social norms explained the difference in Covid-19 vaccine uptake. • Recommendations from employers and providers suppressed some differences in vaccination. • Behavioral nudges – invitation and incentives – were associated with more vaccine uptake. • Offers directions and contexts for future vaccination interventions and programs in the U.S. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) has been shown to have more severe health outcomes in older people specifically in relation to mortality and disability. Vaccination seems to be efficacious and safe for preventing the negative consequences of COVID-19, but vaccine hesitancy seems to be high in older adults. We therefore aimed to investigate the prevalence of unwillingness and the uncertainty to vaccinate against COVID-19 in older people and the factors that can be associated with the unwillingness to vaccinate. For this work, we searched several databases until 18th June 2021 for studies reporting the prevalence of unwillingness and the uncertainty to vaccinate against COVID-19 in people aged >60 years. A meta-analysis of the prevalence, with the correspondent 95% confidence intervals (CIs), was proposed. Factors that can be associated with the unwillingness to vaccinate against COVID-19 were explored through multivariable analyses and reported as odds ratios (ORs). Among 662 papers initially screened, we included 15 studies for a total of 9753 older adults. The prevalence of unwillingness to vaccinate against COVID-19 in older people was 27.03% (95%CI: 15.10–38.95%), whilst the correspondent figure of uncertainty was 19.33% (95%CI: 12.28–26.39). The risk of being unvaccinated was significantly higher in Hispanics (OR=1.197; 95%CI: 1.010–1.418) and in case of low education (OR=1.678; 95%CI: 1.170–2.408) and low income (OR=1.287; 95%CI: 1.127–1.469). In conclusion, the hesitancy for COVID-19 vaccination is a relevant problem in older people, particularly in those with a low income, a low level of education, and in Hispanics living in the United States. • COVID-19 is considered a geriatric syndrome people. • vaccine hesitancy in older people can affect vaccine uptake. • The prevalence of unwillingness and uncertainty seems to be higher in older adults compared to younger persons. • The risk of being unvaccinated was significantly higher in Hispanics and in case of low education and low income. [ABSTRACT FROM AUTHOR]