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1. Impact of Vaccination and Nonpharmaceutical Interventions With Possible COVID-19 Viral Evolutions Using an Agent-Based Simulation

   https://doi.org/10.1016/j.focus.2023.100155  

   Lee, Serin; Zabinsky, Zelda B.; Wasserheit, Judith N.; Ross, Jennifer M.; Chen, Shi; Liu, Shan (February 2024, AJPM Focus)

   The objective is to understand the role of emerging variants, vaccination, and NPI policies on COVID-19 infections and deaths. We aim to identify scenarios in which COVID-19 can be managed such that the death rate from COVID-19 becomes comparable with the combined annual mortality rate from influenza and pneumonia. As a case study for a large urban area, we simulate COVID-19 transmission in King County, Washington, (greater Seattle) using an agent- based simulation model. Calibrated to local epidemiological data, our study uses detailed synthetic population data and includes interactions between vaccination and specific NPIs while considering waning immunity and emergence of variants. Virus mutation scenarios include 12 combinations of infectivity, disease severity, and immune evasiveness. A highly effective pancoronavirus vaccine that works against all strains is considered an optimistic scenario. Our findings highlight the potential benefits of pancoronavirus vaccines that offer enhanced and longer-lasting immunity. We emphasize the crucial role of nonpharmaceutical interventions in reducing COVID-19 deaths regardless of virus mutation scenarios. Owing to highly immune evasive and contagious SARS-CoV-2 variants, most scenarios in this study fail to reduce the mortality of COVID-19 to the level of influenza and pneumonia. However, our findings indicate that periodic vaccinations and a threshold nonpharmaceutical intervention policy may succeed in achieving this goal. This indicates the need for caution and vigilance in managing a continuing COVID-19 epidemic. 

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2. Evaluation of COVID-19 vaccination strategies with a delayed second dose

   https://doi.org/10.1371/journal.pbio.3001211  

   Moghadas, Seyed M.; Vilches, Thomas N.; Zhang, Kevin; Nourbakhsh, Shokoofeh; Sah, Pratha; Fitzpatrick, Meagan C.; Galvani, Alison P. (April 2021, PLOS Biology)

   Read, Andrew Fraser (Ed.)

   Two of the Coronavirus Disease 2019 (COVID-19) vaccines currently approved in the United States require 2 doses, administered 3 to 4 weeks apart. Constraints in vaccine supply and distribution capacity, together with a deadly wave of COVID-19 from November 2020 to January 2021 and the emergence of highly contagious Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants, sparked a policy debate on whether to vaccinate more individuals with the first dose of available vaccines and delay the second dose or to continue with the recommended 2-dose series as tested in clinical trials. We developed an agent-based model of COVID-19 transmission to compare the impact of these 2 vaccination strategies, while varying the temporal waning of vaccine efficacy following the first dose and the level of preexisting immunity in the population. Our results show that for Moderna vaccines, a delay of at least 9 weeks could maximize vaccination program effectiveness and avert at least an additional 17.3 (95% credible interval [CrI]: 7.8–29.7) infections, 0.69 (95% CrI: 0.52–0.97) hospitalizations, and 0.34 (95% CrI: 0.25–0.44) deaths per 10,000 population compared to the recommended 4-week interval between the 2 doses. Pfizer-BioNTech vaccines also averted an additional 0.60 (95% CrI: 0.37–0.89) hospitalizations and 0.32 (95% CrI: 0.23–0.45) deaths per 10,000 population in a 9-week delayed second dose (DSD) strategy compared to the 3-week recommended schedule between doses. However, there was no clear advantage of delaying the second dose with Pfizer-BioNTech vaccines in reducing infections, unless the efficacy of the first dose did not wane over time. Our findings underscore the importance of quantifying the characteristics and durability of vaccine-induced protection after the first dose in order to determine the optimal time interval between the 2 doses. 

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3. Phased Implementation of COVID-19 Vaccination: Rapid Assessment of Policy Adoption, Reach and Effectiveness to Protect the Most Vulnerable in the US

   https://doi.org/10.3390/ijerph18147665  

   Li, Yun; Li, Moming; Rice, Megan; Su, Yanfang; Yang, Chaowei (July 2021, International Journal of Environmental Research and Public Health)

   The US and the rest of the world have suffered from the COVID-19 pandemic for over a year. The high transmissibility and severity of this virus have provoked governments to adopt a variety of mitigation strategies. Some of these previous measures, such as social distancing and mask mandates, were effective in reducing the case growth rate yet became economically and administratively difficult to enforce as the pandemic continued. In late December 2020, COVID-19 vaccines were first approved in the US and states began a phased implementation of COVID-19 vaccination. However, there is limited quantitative evidence regarding the effectiveness of the phased COVID-19 vaccination. This study aims to provide a rapid assessment of the adoption, reach, and effectiveness of the phased implementation of COVID-19 vaccination. We utilize an event-study analysis to evaluate the effect of vaccination on the state-level daily COVID-19 case growth rate. Through this analysis, we assert that vaccination was effective in reducing the spread of COVID-19 shortly after the first shots were given. Specifically, the case growth rate declined by 0.124, 0.347, 0.345, 0.464, 0.490, and 0.756 percentage points corresponding to the 1–5, 6–10, 11–15, 16–20, 21–25, and 26 or more day periods after the initial shots. The findings could be insightful for policymakers as they work to optimize vaccine distribution in later phases, and also for the public as the COVID-19 related health risk is a contentious issue. 

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4. Investigating associations between COVID-19 mortality and population-level health and socioeconomic indicators in the United States: A modeling study

   https://doi.org/10.1371/journal.pmed.1003693  

   Kandula, Sasikiran; Shaman, Jeffrey (July 2021, PLOS Medicine)

   Turner, Richard (Ed.)

   Background With the availability of multiple Coronavirus Disease 2019 (COVID-19) vaccines and the predicted shortages in supply for the near future, it is necessary to allocate vaccines in a manner that minimizes severe outcomes, particularly deaths. To date, vaccination strategies in the United States have focused on individual characteristics such as age and occupation. Here, we assess the utility of population-level health and socioeconomic indicators as additional criteria for geographical allocation of vaccines. Methods and findings County-level estimates of 14 indicators associated with COVID-19 mortality were extracted from public data sources. Effect estimates of the individual indicators were calculated with univariate models. Presence of spatial autocorrelation was established using Moran’s I statistic. Spatial simultaneous autoregressive (SAR) models that account for spatial autocorrelation in response and predictors were used to assess (i) the proportion of variance in county-level COVID-19 mortality that can explained by identified health/socioeconomic indicators (R 2 ); and (ii) effect estimates of each predictor. Adjusting for case rates, the selected indicators individually explain 24%–29% of the variability in mortality. Prevalence of chronic kidney disease and proportion of population residing in nursing homes have the highest R 2 . Mortality is estimated to increase by 43 per thousand residents (95% CI: 37–49; p < 0.001) with a 1% increase in the prevalence of chronic kidney disease and by 39 deaths per thousand (95% CI: 34–44; p < 0.001) with 1% increase in population living in nursing homes. SAR models using multiple health/socioeconomic indicators explain 43% of the variability in COVID-19 mortality in US counties, adjusting for case rates. R 2 was found to be not sensitive to the choice of SAR model form. Study limitations include the use of mortality rates that are not age standardized, a spatial adjacency matrix that does not capture human flows among counties, and insufficient accounting for interaction among predictors. Conclusions Significant spatial autocorrelation exists in COVID-19 mortality in the US, and population health/socioeconomic indicators account for a considerable variability in county-level mortality. In the context of vaccine rollout in the US and globally, national and subnational estimates of burden of disease could inform optimal geographical allocation of vaccines. 

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5. “Better to die trying”: Vaccine perceptions and COVID-19 experiences in rural Namibian pastoralists

   https://doi.org/10.1016/j.vaccine.2025.127061  

   Prall, Sean; Lopes, Aparicio (May 2025, Vaccine)

   Substantial research indicates that local explanatory models of disease shape heath behaviors. However, less is known regarding how cultural models of disease influence interpretations of vaccines. Vaccination decisions are based around a plethora of social and cultural factors, including beliefs about disease, cultural-historical experiences with healthcare, and recent vaccination experiences. To understand how local interpretations of vaccination influence vaccination-decision making, we explore cultural models of health, vaccine norms, and COVID-19 beliefs and experiences in Himba and Herero pastoralists of the Kunene region of northern Namibia. Mixed sex focus groups were conducted in July and August of 2024 in communities across a rural and peri-urban gradient. Discussion prompts were designed to elicit dialogue on vaccination beliefs, norms, and experiences, as well as their recent experience with COVID-19. Results from these focus groups indicate that there was substantial confusion differentiating vaccinations from other types of injections. For childhood vaccines, immunization is normative and expected. Women were the primary decision-makers for childhood immunization, reflecting the matrilineal bias of Himba and Herero kinship. For adults, while local leaders had some influence interfacing with public health outreach, the decision to get vaccinated was largely a personal one. Beliefs about COVID-19 were interpreted through pre-existing cultural models of illness, and beliefs about the origins of COVID-19 reflected mistrust in international actors. Fears about COVID-19 vaccines were common, particularly concerns about vaccine safety. However, fears of the illness typically overrode fears of the vaccine, and most report receiving the vaccine despite these worries. These results highlight the importance of extending research beyond a knowledge, attitude, practice framework to incorporate local explanatory models and cultural-historical experiences in understanding vaccine-decision making. These features are particularly important in more traditional, rural, and marginalized populations where medical mistrust is common and local explanatory models of disease drive healthcare decision-making. 

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