Introduction: Given the continuing COVID-19 pandemic and much of the U.S. implementing social distancing owing to the lack of alternatives, there has been a push to develop a vaccine to eliminate the need for social distancing. Methods: In 2020, the team developed a computational model of the U.S. simulating the spread of COVID-19 coronavirus and vaccination. Results: Simulation experiments revealed that to prevent an epidemic (reduce the peak by >99%), the vaccine efficacy has to be at least 60% when vaccination coverage is 100% (reproduction num-ber=2.5−3.5). This vaccine efficacy threshold rises to 70% when coverage drops to 75% and up to 80% when coverage drops to 60% when reproduction number is 2.5, rising to 80% when coverage drops to 75% when the reproduction number is 3.5. To extinguish an ongoing epidemic, the vaccine efficacy has to be at least 60% when coverage is 100% and at least 80% when coverage drops to 75% to reduce the peak by 85%−86%, 61%−62%, and 32% when vaccination occurs after 5%, 15%, and 30% of the population, respectively, have already been exposed to COVID-19 coronavirus. A vaccine with an efficacy between 60% and 80% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages. Conclusions: This study found that the vaccine has to have an efficacy of at least 70% to prevent an epidemic and of at least 80% to largely extinguish an epidemic without any other measures (e.g., social distancing).

With the coronavirus disease 2019 pandemic, one of the major concerns is the burden COVID-19 will impose on the United States (U.S.) health care system. We developed a Monte Carlo simulation model representing the U.S. population and what can happen to each person who gets infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV2). We estimate resource use and direct medical costs per infection and at the national level, with various "attack rates" (infection rates) to understand the potential economic benefits of reducing the burden of the disease. A single symptomatic COVID-19 infection would cost a median of $3,045 in direct medical costs incurred only during the course of the infection. Eighty percent of the U.S. population getting infected could result in a median of 44.6 million hospitalizations, 10.7 million ICU admissions, 6.5 million ventilators used, and 249.5 million hospital bed days, costing $654.0 billion in direct costs over the course of the pandemic. If 20% were to become infected, there would be a median of 11.2 million hospitalizations, 62.3 million hospital bed days, and 1.6 million ventilators used, costing $163.4 billion.

Background With multiple COVID-19 vaccines available, understanding the epidemiologic, clinical, and economic value of increasing coverage levels and expediting vaccination is important. Methods We developed a computational model (transmission and age-stratified clinical and economics outcome model) representing the US population, COVID-19 coronavirus spread (02/2020-12/2022), and vaccination to determine the impact of increasing coverage and expediting time to achieve coverage. Results When achieving a given vaccination coverage in 270 days (70% vaccine efficacy), every 1% increase in coverage can avert an average of 876,800 (217,000–2,398,000) cases, varying with the number of people already vaccinated. For example, each 1% increase between 40%-50% coverage can prevent 1.5million cases, 56,240 hospitalizations, 6,660 deaths, gain 77,590 QALYs, save $602.8 million in direct medical costs and $1.3 billion in productivity losses . Expediting to 180 days could save an additional 5.8 million cases, 215,790 hospitalizations, 26,370 deaths, 206,520 QALYs, $3.5 billion in direct medical costs, and $4.3 billion in productivity losses. Conclusion Our study quantifies the potential value of decreasing vaccine hesitancy and increasing vaccination coverage and how this value may decrease with time it takes to achieve coverage, emphasizing the need to reach high coverage levels as soon as possible, especially before the Fall/Winter.

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Increasing physical activity among children is a potentially important public health intervention. Quantifying the economic and health effects of the intervention would help decision makers understand its impact and priority. Using a computational simulation model that we developed to represent all US children ages 8–11 years, we estimated that maintaining the current physical activity levels (only 31.9 percent of children get twenty-five minutes of high-calorie-burning physical activity three times a week) would result each year in a net present value of $1.1 trillion in direct medical costs and $1.7 trillion in lost productivity over the course of their lifetimes. If 50 percent of children would exercise, the number of obese and overweight youth would decrease by 4.18 percent, averting $8.1 billion in direct medical costs and $13.8 billion in lost productivity. Increasing the proportion of children who exercised to 75 percent would avert $16.6 billion and $23.6 billion, respectively.