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BACKGROUND: With coronavirus disease 2019 (COVID-19) vaccination no longer mandated by many businesses/organizations, it is now up to individuals to decide whether to get any new boosters/updated vaccines going forward. METHODS: We developed a Markov model representing the potential clinical/economic outcomes from an individual perspective in the United States of getting versus not getting an annual COVID-19 vaccine. RESULTS: For an 18-49 year old, getting vaccinated at its current price ($60) can save the individual on average $30-$603 if the individual is uninsured and $4-$437 if the individual has private insurance, as long as the starting vaccine efficacy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is ≥50% and the weekly risk of getting infected is ≥0.2%, corresponding to an individual interacting with 9 other people in a day under Winter 2023-2024 Omicron SARS-CoV-2 variant conditions with an average infection prevalence of 10%. For a 50-64 year old, these cost-savings increase to $111-$1278 and $119-$1706 for someone without and with insurance, respectively. The risk threshold increases to ≥0.4% (interacting with 19 people/day), when the individual has 13.4% preexisting protection against infection (eg, vaccinated 9 months earlier). CONCLUSIONS: There is both clinical and economic incentive for the individual to continue to get vaccinated against COVID-19 each year.
Subject(s)
COVID-19 Vaccines , COVID-19 , Cost-Benefit Analysis , Markov Chains , SARS-CoV-2 , Vaccination , Humans , COVID-19/prevention & control , COVID-19/economics , COVID-19/epidemiology , COVID-19 Vaccines/economics , COVID-19 Vaccines/administration & dosage , Middle Aged , Adult , Adolescent , SARS-CoV-2/immunology , Vaccination/economics , Young Adult , United States/epidemiology , Male , FemaleABSTRACT
Over the past sixty years, scientists have been warning about climate change and its impacts on human health, but evidence suggests that many may not be heeding these concerns. This raises the question of whether new communication approaches are needed to overcome the unique challenges of communicating what people can do to slow or reverse climate change. To better elucidate the challenges of communicating about the links between human activity, climate change and its effects, and identify potential solutions, we developed a systems map of the factors and processes involved based on systems mapping sessions with climate change and communication experts. The systems map revealed 27 communication challenges such as "Limited information on how individual actions contribute to collective human activity," "Limited information on how present activity leads to long-term effects," and "Difficult to represent and communicate complex relationships." The systems map also revealed several themes among the identified challenges that exist in communicating about climate change, including a lack of available data and integrated databases, climate change disciplines working in silos, a need for a lexicon that is easily understood by the public, and the need for new communication strategies to describe processes that take time to manifest.
Subject(s)
Climate Change , Health Communication , Humans , Health Communication/methods , Systems Analysis , CommunicationABSTRACT
BACKGROUND: Teaching caregivers to respond to normal infant night awakenings in ways other than feeding is a common obesity prevention effort. Models can simulate caregiver feeding behavior while controlling for variables that are difficult to manipulate or measure in real life. METHODS: We developed a virtual infant model representing an infant with an embedded metabolism and his/her daily sleep, awakenings, and feeds from their caregiver each day as the infant aged from 6 to 12 months (recommended age to introduce solids). We then simulated different night feeding interventions and their impact on infant body mass index (BMI). RESULTS: Reducing the likelihood of feeding during normal night wakings from 79% to 50% to 10% lowered infant BMI from the 84th to the 75th to the 62nd percentile by 12 months, respectively, among caregivers who did not adaptively feed (e.g., adjust portion sizes of solid foods with infant growth). Among caregivers who adaptively feed, all scenarios resulted in relatively stable BMI percentiles, and progressively reducing feeding probability by 10% each month showed the least fluctuations. CONCLUSIONS: Reducing night feeding has the potential to impact infant BMI, (e.g., 10% lower probability can reduce BMI by 20 percentile points) especially among caregivers who do not adaptively feed. IMPACT: Teaching caregivers to respond to infant night waking with other soothing behaviors besides feeding has the potential to reduce infant BMI. When reducing the likelihood of feeding during night wakings from 79% to 50% to 10%, infants dropped from the 84th BMI percentile to the 75th to the 62nd by 12 months, respectively, among caregivers who do not adaptively feed. Night-feeding interventions have a greater impact when caregivers do not adaptively feed their infant based on their growth compared to caregivers who do adaptively feed. Night-feeding interventions should be one of the several tools in a multi-component intervention for childhood obesity prevention.
Subject(s)
Body Mass Index , Circadian Rhythm , Feeding Behavior , Caregivers , Humans , Infant , Models, TheoreticalABSTRACT
Finding medications or vaccines that may decrease the infectious period of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could potentially reduce transmission in the broader population. We developed a computational model of the U.S. simulating the spread of SARS-CoV-2 and the potential clinical and economic impact of reducing the infectious period duration. Simulation experiments found that reducing the average infectious period duration could avert a median of 442,852 [treating 25% of symptomatic cases, reducing by 0.5 days, reproductive number (R0) 3.5, and starting treatment when 15% of the population has been exposed] to 44.4 million SARS-CoV-2 cases (treating 75% of all infected cases, reducing by 3.5 days, R0 2.0). With R0 2.5, reducing the average infectious period duration by 0.5 days for 25% of symptomatic cases averted 1.4 million cases and 99,398 hospitalizations; increasing to 75% of symptomatic cases averted 2.8 million cases. At $500/person, treating 25% of symptomatic cases saved $209.5 billion (societal perspective). Further reducing the average infectious period duration by 3.5 days averted 7.4 million cases (treating 25% of symptomatic cases). Expanding treatment to 75% of all infected cases, including asymptomatic infections (R0 2.5), averted 35.9 million cases and 4 million hospitalizations, saving $48.8 billion (societal perspective and starting treatment after 5% of the population has been exposed). Our study quantifies the potential effects of reducing the SARS-CoV-2 infectious period duration.
Subject(s)
COVID-19 Drug Treatment , COVID-19/transmission , Models, Biological , Pandemics , SARS-CoV-2 , COVID-19/epidemiology , COVID-19 Vaccines/therapeutic use , Computational Biology , Computer Simulation , Humans , Pandemics/prevention & control , Pandemics/statistics & numerical data , SARS-CoV-2/drug effects , Time Factors , United States/epidemiology , Virus Shedding/drug effectsABSTRACT
BACKGROUND: The increasing prevalence of smartphone apps to help people find different services raises the question of whether apps to help people find physical activity (PA) locations would help better prevent and control having overweight or obesity. OBJECTIVE: The aim of this paper is to determine and quantify the potential impact of a digital health intervention for African American women prior to allocating financial resources toward implementation. METHODS: We developed our Virtual Population Obesity Prevention, agent-based model of Washington, DC, to simulate the impact of a place-tailored digital health app that provides information about free recreation center classes on PA, BMI, and overweight and obesity prevalence among African American women. RESULTS: When the app is introduced at the beginning of the simulation, with app engagement at 25% (eg, 25% [41,839/167,356] of women aware of the app; 25% [10,460/41,839] of those aware downloading the app; and 25% [2615/10,460] of those who download it receiving regular push notifications), and a 25% (25/100) baseline probability to exercise (eg, without the app), there are no statistically significant increases in PA levels or decreases in BMI or obesity prevalence over 5 years across the population. When 50% (83,678/167,356) of women are aware of the app; 58.23% (48,725/83,678) of those who are aware download it; and 55% (26,799/48,725) of those who download it receive regular push notifications, in line with existing studies on app usage, introducing the app on average increases PA and decreases weight or obesity prevalence, though the changes are not statistically significant. When app engagement increased to 75% (125,517/167,356) of women who were aware, 75% (94,138/125,517) of those who were aware downloading it, and 75% (70,603/94,138) of those who downloaded it opting into the app's push notifications, there were statistically significant changes in PA participation, minutes of PA and obesity prevalence. CONCLUSIONS: Our study shows that a digital health app that helps identify recreation center classes does not result in substantive population-wide health effects at lower levels of app engagement. For the app to result in statistically significant increases in PA and reductions in obesity prevalence over 5 years, there needs to be at least 75% (125,517/167,356) of women aware of the app, 75% (94,138/125,517) of those aware of the app download it, and 75% (70,603/94,138) of those who download it opt into push notifications. Nevertheless, the app cannot fully overcome lack of access to recreation centers; therefore, public health administrators as well as parks and recreation agencies might consider incorporating this type of technology into multilevel interventions that also target the built environment and other social determinants of health.
Subject(s)
Mobile Applications , Black or African American , Exercise , Female , Humans , Obesity/epidemiology , Obesity/prevention & control , OverweightABSTRACT
BACKGROUND: With multiple coronavirus disease 2019 (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 United States population, COVID-19 coronavirus spread (February 2020-December 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% and 50% coverage can prevent 1.5 million cases, 56 240 hospitalizations, and 6660 deaths; gain 77 590 quality-adjusted life-years (QALYs); and 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. CONCLUSIONS: Our study quantifies the potential value of decreasing vaccine hesitancy and increasing vaccination coverage and how this value may decrease with the time it takes to achieve coverage, emphasizing the need to reach high coverage levels as soon as possible, especially before the fall/winter.
Subject(s)
COVID-19 Vaccines/economics , Cost-Benefit Analysis , Vaccination/economics , COVID-19/prevention & control , COVID-19 Vaccines/administration & dosage , Humans , Models, Economic , SARS-CoV-2 , United States , Vaccination/statistics & numerical dataABSTRACT
BACKGROUND: Although norovirus outbreaks periodically make headlines, it is unclear how much attention norovirus may receive otherwise. A better understanding of the burden could help determine how to prioritize norovirus prevention and control. METHODS: We developed a computational simulation model to quantify the clinical and economic burden of norovirus in the United States. RESULTS: A symptomatic case generated $48 in direct medical costs, $416 in productivity losses ($464 total). The median yearly cost of outbreaks was $7.6 million (range across years, $7.5-$8.2 million) in direct medical costs, and $165.3 million ($161.1-$176.4 million) in productivity losses ($173.5 million total). Sporadic illnesses in the community (incidence, 10-150/1000 population) resulted in 14 118-211 705 hospitalizations, 8.2-122.9 million missed school/work days, $0.2-$2.3 billion in direct medical costs, and $1.4-$20.7 billion in productivity losses ($1.5-$23.1 billion total). The total cost was $10.6 billion based on the current incidence estimate (68.9/1000). CONCLUSION: Our study quantified norovirus' burden. Of the total burden, sporadic cases constituted >90% (thus, annual burden may vary depending on incidence) and productivity losses represented 89%. More than half the economic burden is in adults ≥45, more than half occurs in winter months, and >90% of outbreak costs are due to person-to-person transmission, offering insights into where and when prevention/control efforts may yield returns.
Subject(s)
Cost of Illness , Gastroenteritis/economics , Gastroenteritis/epidemiology , Norovirus , Adolescent , Adult , Aged , Child , Child, Preschool , Disease Outbreaks/economics , Gastroenteritis/virology , Health Care Costs , Hospitalization , Humans , Incidence , Infant , Infant, Newborn , Middle Aged , United States/epidemiology , Young AdultABSTRACT
BACKGROUND: The protection that an influenza vaccine offers can vary significantly from person to person due to differences in immune systems, body types, and other factors. The question, then, is what is the value of efforts to reduce this variability such as making vaccines more personalized and tailored to individuals. METHODS: We developed a compartment model of the United States to simulate different influenza seasons and the impact of reducing the variability in responses to the influenza vaccine across the population. RESULTS: Going from a vaccine that varied in efficacy (0-30%) to one that had a uniform 30% efficacy for everyone averted 16.0-31.2 million cases, $1.9-$3.6 billion in direct medical costs, and $16.1-$42.7 billion in productivity losses. Going from 0-50% in efficacy to just 50% for everyone averted 27.7-38.6 million cases, $3.3-$4.6 billion in direct medical costs, and $28.8-$57.4 billion in productivity losses. Going from 0-70% to 70% averted 33.6-54.1 million cases, $4.0-$6.5 billion in direct medical costs, and $44.8-$64.7 billion in productivity losses. CONCLUSIONS: This study quantifies for policy makers, funders, and vaccine developers and manufacturers the potential impact of efforts to reduce variability in the protection that influenza vaccines offer (eg, developing vaccines that are more personalized to different individual factors).
Subject(s)
Disease Transmission, Infectious/prevention & control , Epidemics , Influenza Vaccines/administration & dosage , Influenza, Human/epidemiology , Influenza, Human/prevention & control , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Cost-Benefit Analysis , Female , Humans , Infant , Infant, Newborn , Influenza Vaccines/economics , Influenza Vaccines/immunology , Influenza, Human/economics , Male , Middle Aged , Models, Statistical , Pharmacies , Seasons , Treatment Outcome , United States/epidemiology , Vaccination/economics , Vaccination Coverage , Young AdultABSTRACT
BACKGROUND: Studies show that by 3 months, over half of US infants receive formula, and guidelines play a key role in formula feeding. The question then is, what might happen if caregivers follow guidelines and, more specifically, are there situations where following guidelines can result in infants who are overweight/have obesity? METHODS: We used our "Virtual Infant" agent-based model representing infant-caregiver pairs that allowed caregivers to feed infants each day according to guidelines put forth by Johns Hopkins Medicine (JHM), Children's Hospital of Philadelphia (CHOP), Children's Hospital of the King's Daughters (CHKD), and Women, Infants, and Children (WIC). The model simulated the resulting development of the infants from birth to 6 months. The two sets of guidelines vary in their recommendations, and do not provide studies that support amounts at given ages. RESULTS: Simulations identified several scenarios where caregivers followed JHM/CHOP/CHKD and WIC guidelines, but infants still became overweight/with obesity by 6 months. For JHM/CHOP/CHKD guidelines, this occurred even when caregivers adjusted feeding based on infant's weight. For WIC guidelines, when caregivers adjusted formula amounts, infants maintained healthy weight. CONCLUSIONS: WIC guidelines may be a good starting point for caregivers who adjust as their infant grows, but the minimum amounts for JHM/CHKD/CHOP recommendations may be too high. IMPACT: Our virtual infant simulation study answers the question: can caregivers follow current formula-feeding guidelines and still end up with an infant who is overweight or has obesity? Our study identified several situations in which unhealthy weight gain and/or weight loss could result from following established formula-feeding recommendations. Our study also suggests that the minimum recommended amount of daily formula feeding should be lower for JHM/CHOP/CHKD guidelines to give caregivers more flexibility in adjusting daily feeding levels in response to infant weight. WIC guidelines may be a good starting point for caregivers who adjust as their infant grows. In order to understand how to adjust guidelines, we can use computational simulation models, which serve as "virtual laboratories" to help overcome the logistical and ethical issues of clinical trials.
Subject(s)
Infant Formula , Infant Nutritional Physiological Phenomena , Overweight/prevention & control , Pediatric Obesity/prevention & control , Body Weight , Caregivers , Computer Simulation , Feeding Behavior/physiology , Female , Guidelines as Topic , Humans , Infant , Infant Food , Infant, Newborn , Male , Time Factors , United States , Weight GainABSTRACT
Background: With efforts underway to develop a universal coronavirus vaccine, otherwise known as a pan-coronavirus vaccine, this is the time to offer potential funders, researchers, and manufacturers guidance on the potential value of such a vaccine and how this value may change with differing vaccine and vaccination characteristics. Methods: Using a computational model representing the United States (U.S.) population, the spread of SARS-CoV-2 and the various clinical and economic outcomes of COVID-19 such as hospitalisations, deaths, quality-adjusted life years (QALYs) lost, productivity losses, direct medical costs, and total societal costs, we explored the impact of a universal vaccine under different circumstances. We developed and populated this model using data reported by the CDC as well as observational studies conducted during the COVID-19 pandemic. Findings: A pan-coronavirus vaccine would be cost saving in the U.S. as a standalone intervention as long as its vaccine efficacy is ≥10% and vaccination coverage is ≥10%. Every 1% increase in efficacy between 10% and 50% could avert an additional 395,000 infections and save $1.0 billion in total societal costs ($45.3 million in productivity losses, $1.1 billion in direct medical costs). It would remain cost saving even when a strain-specific coronavirus vaccine would be subsequently available, as long as it takes at least 2-3 months to develop, test, and bring that more specific vaccine to the market. Interpretation: Our results provide support for the development and stockpiling of a pan-coronavirus vaccine and help delineate the vaccine characteristics to aim for in development of such a vaccine. Funding: The National Science Foundation, the Agency for Healthcare Research and Quality, the National Institute of General Medical Sciences, the National Center for Advancing Translational Sciences, and the City University of New York.
ABSTRACT
Importance: There are considerable socioeconomic status (SES) disparities in youth physical activity (PA) levels. For example, studies show that lower-SES youth are less active, have lower participation in organized sports and physical education classes, and have more limited access to PA equipment. Objective: To determine the potential public health and economic effects of eliminating disparities in PA levels among US youth SES groups. Design and Setting: An agent-based model representing all 6- to 17-year-old children in the US was used to simulate the epidemiological, clinical, and economic effects of disparities in PA levels among different SES groups and the effect of reducing these disparities. Main Outcomes and Measures: Anthropometric measures (eg, body mass index) and the presence and severity of risk factors associated with weight (stroke, coronary heart disease, type 2 diabetes, or cancer), as well as direct and indirect cost savings. Results: This model, representing all 50 million US children and adolescents 6 to 17 years old, found that if the US eliminates the disparity in youth PA levels across SES groups, absolute overweight and obesity prevalence would decrease by 0.826% (95% CI, 0.821%-0.832%), resulting in approximately 383â¯000 (95% CI, 368â¯000-399â¯000) fewer cases of overweight and obesity and 101â¯000 (95% CI, 98â¯000-105â¯000) fewer cases of weight-related diseases (stroke and coronary heart disease events, type 2 diabetes, or cancer). This would result in more than $15.60 (95% CI, $15.01-$16.10) billion in cost savings over the youth cohort's lifetime. There are meaningful benefits even when reducing the disparity by just 25%, which would result in $1.85 (95% CI, $1.70-$2.00) billion in direct medical costs averted and $2.48 (95% CI, $2.04-$2.92) billion in productivity losses averted. For every 1% in disparity reduction, total productivity losses would decrease by about $83.8 million, and total direct medical costs would decrease by about $68.7 million. Conclusions and Relevance: This study quantified the potential savings from eliminating or reducing PA disparities, which can help policymakers, health care systems, schools, funders, sports organizations, and other businesses better prioritize investments toward addressing these disparities.
Subject(s)
Coronary Disease , Diabetes Mellitus, Type 2 , Neoplasms , Stroke , Child , Humans , Adolescent , Overweight , Socioeconomic Disparities in Health , Exercise , ObesityABSTRACT
OBJECTIVES: To evaluate the epidemiologic, clinical, and economic value of an annual nursing home (NH) COVID-19 vaccine campaign and the impact of when vaccination starts. DESIGN: Agent-based model representing a typical NH. SETTING AND PARTICIPANTS: NH residents and staff. METHODS: We used the model representing an NH with 100 residents, its staff, their interactions, COVID-19 spread, and its health and economic outcomes to evaluate the epidemiologic, clinical, and economic value of varying schedules of annual COVID-19 vaccine campaigns. RESULTS: Across a range of scenarios with a 60% vaccine efficacy that wanes starting 4 months after protection onset, vaccination was cost saving or cost-effective when initiated in the late summer or early fall. Annual vaccination averted 102 to 105 COVID-19 cases when 30-day vaccination campaigns began between July and October (varying with vaccination start), decreasing to 97 and 85 cases when starting in November and December, respectively. Starting vaccination between July and December saved $3340 to $4363 and $64,375 to $77,548 from the Centers for Medicare & Medicaid Services and societal perspectives, respectively (varying with vaccination start). Vaccination's value did not change when varying the COVID-19 peak between December and February. The ideal vaccine campaign timing was not affected by reducing COVID-19 levels in the community, or varying transmission probability, preexisting immunity, or COVID-19 severity. However, if vaccine efficacy wanes more quickly (over 1 month), earlier vaccination in July resulted in more cases compared with vaccinating later in October. CONCLUSIONS AND IMPLICATIONS: Annual vaccination of NH staff and residents averted the most cases when initiated in the late summer through early fall, at least 2 months before the COVID-19 winter peak but remained cost saving or cost-effective when it starts in the same month as the peak. This supports tethering COVID vaccination to seasonal influenza campaigns (typically in September-October) for providing protection against SARS-CoV-2 winter surges in NHs.
Subject(s)
COVID-19 Vaccines , COVID-19 , Aged , Humans , United States/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2 , Medicare , Vaccination , Nursing HomesABSTRACT
Importance: Current guidance to furlough health care staff with mild COVID-19 illness may prevent the spread of COVID-19 but may worsen nursing home staffing shortages as well as health outcomes that are unrelated to COVID-19. Objective: To compare COVID-19-related with non-COVID-19-related harms associated with allowing staff who are mildly ill with COVID-19 to work while masked. Design, Setting, and Participants: This modeling study, conducted from November 2023 to June 2024, used an agent-based model representing a 100-bed nursing home and its residents, staff, and their interactions; care tasks; and resident and staff health outcomes to simulate the impact of different COVID-19 furlough policies over 1 postpandemic year. Exposures: Simulating increasing proportions of staff who are mildly ill and are allowed to work while wearing N95 respirators under various vaccination coverage, SARS-CoV-2 transmissibility and severity, and masking adherence. Main Outcomes and Measures: The main outcomes were staff and resident COVID-19 cases, staff furlough days, missed care tasks, nursing home resident hospitalizations (related and unrelated to COVID-19), deaths, and costs. Results: In the absence of SARS-CoV-2 infection in the study's 100-bed agent-based model, nursing home understaffing resulted in an annual mean (SD) 93.7 (0.7) missed care tasks daily (22.1%), 38.0 (7.6) resident hospitalizations (5.2%), 4.6 (2.2) deaths (0.6%), and 39.7 (19.8) quality-adjusted life years lost from non-COVID-19-related harms, costing $1 071 950 ($217 200) from the Centers for Medicare & Medicaid Services (CMS) perspective and $1 112 800 ($225 450) from the societal perspective. Under the SARS-CoV-2 Omicron variant conditions from 2023 to 2024, furloughing all staff who tested positive for SARS-CoV-2 was associated with a mean (SD) 326.5 (69.1) annual furlough days and 649.5 (95% CI, 593.4-705.6) additional missed care tasks, resulting in 4.3 (95% CI, 2.9-5.9) non-COVID-19-related resident hospitalizations and 0.7 (95% CI, 0.2-1.1) deaths, costing an additional $247 090 (95% CI, $203â¯160-$291â¯020) from the CMS perspective and $405â¯250 (95% CI, $358â¯550-$451â¯950) from the societal perspective. Allowing 75% of staff who were mildly ill to work while masked was associated with 5 additional staff and 5 additional resident COVID-19 cases without added COVID-19-related hospitalizations but mitigated staffing shortages, with 475.9 additional care tasks being performed annually, 3.5 fewer non-COVID-19-related hospitalizations, and 0.4 fewer non-COVID-19-related deaths. Allowing staff who were mildly ill to work ultimately saved an annual mean $85â¯470 (95% CI, $41â¯210-$129â¯730) from the CMS perspective and $134â¯450 (95% CI, $86â¯370-$182â¯540) from the societal perspective. These results were robust to increased vaccination coverage, increased nursing home transmission, increased importation of COVID-19 from the community, and failure to mask while working ill. Conclusion and Relevance: In this modeling study of staff COVID-19 furlough policies, allowing nursing home staff to work with mild COVID-19 illness was associated with fewer resident harms from staffing shortages and missed care tasks than harms from increased COVID-19 transmission, ultimately saving substantial direct medical and societal costs.
Subject(s)
COVID-19 , Nursing Homes , SARS-CoV-2 , Humans , COVID-19/epidemiology , Nursing Homes/statistics & numerical data , Masks/statistics & numerical data , Health Personnel , United States/epidemiologyABSTRACT
BACKGROUND: Face mask wearing has been an important part of the response to the COVID-19 pandemic. As vaccination coverage progresses in countries, relaxation of such practices is increasing. Subsequent COVID-19 surges have raised the questions of whether face masks should be encouraged or required and for how long. Here, we aim to assess the value of maintaining face masks use indoors according to different COVID-19 vaccination coverage levels in the USA. METHODS: In this computational simulation-model study, we developed and used a Monte Carlo simulation model representing the US population and SARS-CoV-2 spread. Simulation experiments compared what would happen if face masks were used versus not used until given final vaccination coverages were achieved. Different scenarios varied the target vaccination coverage (70-90%), the date these coverages were achieved (Jan 1, 2022, to July 1, 2022), and the date the population discontinued wearing face masks. FINDINGS: Simulation experiments revealed that maintaining face mask use (at the coverage seen in the USA from March, 2020, to July, 2020) until target vaccination coverages were achieved was cost-effective and in many cases cost saving from both the societal and third-party payer perspectives across nearly all scenarios explored. Face mask use was estimated to be cost-effective and usually cost saving when the cost of face masks per person per day was ≤US$1·25. In all scenarios, it was estimated to be cost-effective to maintain face mask use for about 2-10 weeks beyond the date that target vaccination coverage (70-90%) was achieved, with this added duration being longer when the target coverage was achieved during winter versus summer. Factors that might increase the transmissibility of the virus (eg, emergence of the delta [B.1.617.2] and omicron [B.1.1.529] variants), or decrease vaccine effectiveness (eg, waning immunity or escape variants), or increase social interactions among certain segments of the population, only increased the cost savings or cost-effectiveness provided by maintaining face mask use. INTERPRETATION: Our study provides strong support for maintaining face mask use until and a short time after achieving various final vaccination coverage levels, given that maintaining face mask use can be not just cost-effective, but even cost saving. The emergence of the omicron variant and the prospect of future variants that might be more transmissible and reduce vaccine effectiveness only increases the value of face masks. FUNDING: The Agency for Healthcare Research and Quality, the National Institute of General Medical Sciences, the National Science Foundation, the National Center for Advancing Translational Sciences, and the City University of New York.
Subject(s)
COVID-19 , Vaccination Coverage , COVID-19/prevention & control , COVID-19 Vaccines , Humans , Masks , Pandemics/prevention & control , SARS-CoV-2ABSTRACT
BACKGROUND: Many schools have been cutting physical education (PE) classes due to budget constraints, which raises the question of whether policymakers should require schools to offer PE classes. Evidence suggests that PE classes can help address rising physical inactivity and obesity prevalence. However, it would be helpful to determine if requiring PE is cost-effective. METHODS: We developed an agent-based model of youth in Mexico City and the impact of all schools offering PE classes on changes in weight, weight-associated health conditions and the corresponding direct and indirect costs over their lifetime. RESULTS: If schools offer PE without meeting guidelines and instead followed currently observed class length and time active during class, overweight and obesity prevalence decreased by 1.3% (95% CI: 1.0%-1.6%) and was cost-effective from the third-party payer and societal perspectives ($5,058 per disability-adjusted life year [DALY] averted and $5,786/DALY averted, respectively, assuming PE cost $50.3 million). When all schools offered PE classes meeting international guidelines for PE classes, overweight and obesity prevalence decreased by 3.9% (95% CI: 3.7%-4.3%) in the cohort at the end of five years compared to no PE. Long-term, this averted 3,183 and 1,081 obesity-related health conditions and deaths, respectively and averted ≥$31.5 million in direct medical costs and ≥$39.7 million in societal costs, assuming PE classes cost ≤$50.3 million over the five-year period. PE classes could cost up to $185.5 million and $89.9 million over the course of five years and still remain cost-effective and cost saving respectively, from the societal perspective. CONCLUSION: Requiring PE in all schools could be cost-effective when PE class costs, on average, up to $10,340 per school annually. Further, the amount of time students are active during class is a driver of PE classes' value (e.g., it is cost saving when PE classes meet international guidelines) suggesting the need for specific recommendations.
Subject(s)
Overweight , Physical Education and Training , Adolescent , Cost-Benefit Analysis , Humans , Mexico/epidemiology , Obesity/epidemiology , Obesity/prevention & control , Overweight/epidemiology , Overweight/prevention & control , SchoolsABSTRACT
INTRODUCTION: With norovirus vaccine candidates currently under development, now is the time to identify the vaccine characteristics and implementation thresholds at which vaccination becomes cost effective and cost saving in a community setting. METHODS: In 2020, a norovirus transmission, clinical, and economics computational simulation model representing different U.S. population segments was developed to simulate the spread of norovirus and the potential impact of vaccinating children aged <5 years and older adults (aged ≥65 years). RESULTS: Compared with no vaccination, vaccinating preschool-aged children averted 8%-72% of symptomatic norovirus cases in a community, whereas vaccinating older adults averted 2%-29% of symptomatic cases (varying with vaccine efficacy [25%-75%] and vaccination coverage [10%-80%]). Vaccination with a 25% vaccine efficacy was cost effective (incremental cost-effectiveness ratio ≤$50,000 per quality-adjusted life year) when vaccination cost ≤$445 and cost saving at ≤$370 when vaccinating preschool-aged children and ≤$42 and ≤$30, respectively, when vaccinating older adults. With a 50% vaccine efficacy, vaccination was cost effective when it cost ≤$1,190 and cost saving at ≤$930 when vaccinating preschool-aged children and ≤$110 and ≤$64, respectively, when vaccinating older adults. These cost thresholds (cost effective and cost saving, respectively) further increased with a 75% vaccine efficacy to ≤$1,600 and ≤$1,300 for preschool-aged children and ≤$165 and ≤$100 for older adults. CONCLUSIONS: This study outlines thresholds at which a norovirus vaccine would be cost effective and cost saving in the community when vaccinating children aged <5 years and older adults. Establishing these thresholds can help provide decision makers with targets to consider when developing and implementing a norovirus vaccine.
Subject(s)
Norovirus , Vaccines , Aged , Child , Child, Preschool , Cost-Benefit Analysis , Humans , Quality-Adjusted Life Years , VaccinationABSTRACT
INTRODUCTION: Single-dose rotavirus vaccines, which are used by a majority of countries, are some of the largest-sized vaccines in immunization programs, and have been shown to constrain supply chains and cause bottlenecks. Efforts have been made to reduce the size of the single-dose vaccines; however, with two-dose, five-dose and ten-dose options available, the question then is whether using multi-dose instead of single-dose rotavirus vaccines will improve vaccine availability. METHODS: We used HERMES-generated simulation models of the vaccine supply chains of the Republic of Benin, Mozambique, and Bihar, a state in India, to evaluate the operational and economic impact of implementing each of the nine different rotavirus vaccine presentations. RESULTS: Among single-dose rotavirus vaccines, using Rotarix RV1 MMP (multi-monodose presentation) led to the highest rotavirus vaccine availability (49-80%) and total vaccine availability (56-79%), and decreased total costs per dose administered ($0.02-$0.10) compared to using any other single-dose rotavirus vaccine. Using two-dose ROTASIIL decreased rotavirus vaccine availability by 3-6% across each supply chain compared to Rotarix RV1 MMP, the smallest single-dose vaccine. Using a five-dose rotavirus vaccine improved rotavirus vaccine availability (52-92%) and total vaccine availability (60-85%) compared to single-dose and two-dose vaccines. Further, using the ten-dose vaccine led to the highest rotavirus vaccine availability compared to all other rotavirus vaccines in both Benin and Bihar. CONCLUSION: Our results show that countries that implement five-dose or ten-dose rotavirus vaccines consistently reduce cold chain constraints and achieve higher rotavirus and total vaccine availability compared to using either single-dose or two-dose rotavirus vaccines.
Subject(s)
Rotavirus Infections , Rotavirus Vaccines , Rotavirus , Benin , Humans , Immunization Programs , India , Infant , Mozambique , Rotavirus Infections/prevention & control , Vaccines, AttenuatedABSTRACT
INTRODUCTION: During a pandemic, there are many situations in which the first available vaccines may not have as high effectiveness as vaccines that are still under development or vaccines that are not yet ready for distribution, raising the question of whether it is better to go with what is available now or wait. METHODS: In 2020, the team developed a computational model that represents the U.S. population, COVID-19 coronavirus spread, and vaccines with different possible efficacies (to prevent infection or to reduce severe disease) and vaccination timings to estimate the clinical and economic value of vaccination. RESULTS: Except for a limited number of situations, mainly early on in a pandemic and for a vaccine that prevents infection, when an initial vaccine is available, waiting for a vaccine with a higher efficacy results in additional hospitalizations and costs over the course of the pandemic. For example, if a vaccine with a 50% efficacy in preventing infection becomes available when 10% of the population has already been infected, waiting until 40% of the population are infected for a vaccine with 80% efficacy in preventing infection results in 15.6 million additional cases and 1.5 million additional hospitalizations, costing $20.6 billion more in direct medical costs and $12.4 billion more in productivity losses. CONCLUSIONS: This study shows that there are relatively few situations in which it is worth foregoing the first COVID-19 vaccine available in favor of a vaccine that becomes available later on in the pandemic even if the latter vaccine has a substantially higher efficacy.
Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , COVID-19/epidemiology , Computer Simulation , Humans , Pandemics , United States/epidemiology , VaccinationABSTRACT
OBJECTIVE: Due to shortages of N95 respirators during the coronavirus disease 2019 (COVID-19) pandemic, it is necessary to estimate the number of N95s required for healthcare workers (HCWs) to inform manufacturing targets and resource allocation. METHODS: We developed a model to determine the number of N95 respirators needed for HCWs both in a single acute-care hospital and the United States. RESULTS: For an acute-care hospital with 400 all-cause monthly admissions, the number of N95 respirators needed to manage COVID-19 patients admitted during a month ranges from 113 (95% interpercentile range [IPR], 50-229) if 0.5% of admissions are COVID-19 patients to 22,101 (95% IPR, 5,904-25,881) if 100% of admissions are COVID-19 patients (assuming single use per respirator, and 10 encounters between HCWs and each COVID-19 patient per day). The number of N95s needed decreases to a range of 22 (95% IPR, 10-43) to 4,445 (95% IPR, 1,975-8,684) if each N95 is used for 5 patient encounters. Varying monthly all-cause admissions to 2,000 requires 6,645-13,404 respirators with a 60% COVID-19 admission prevalence, 10 HCW-patient encounters, and reusing N95s 5-10 times. Nationally, the number of N95 respirators needed over the course of the pandemic ranges from 86 million (95% IPR, 37.1-200.6 million) to 1.6 billion (95% IPR, 0.7-3.6 billion) as 5%-90% of the population is exposed (single-use). This number ranges from 17.4 million (95% IPR, 7.3-41 million) to 312.3 million (95% IPR, 131.5-737.3 million) using each respirator for 5 encounters. CONCLUSIONS: We quantified the number of N95 respirators needed for a given acute-care hospital and nationally during the COVID-19 pandemic under varying conditions.