The potential epidemiologic, clinical, and economic impact of requiring schools to offer Physical Education (PE) classes in Mexico City.

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.

Maintaining face mask use before and after achieving different COVID-19 vaccination coverage levels: a modelling study.

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.

The impact of reducing the frequency of night feeding on infant BMI.

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.

Should countries switch to using five- or ten-dose rotavirus vaccines now that they are available?

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.

Lives and Costs Saved by Expanding and Expediting Coronavirus Disease 2019 Vaccination.

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.

The Benefits of Vaccinating With the First Available COVID-19 Coronavirus Vaccine.

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.

Estimated number of N95 respirators needed for healthcare workers in acute-care hospitals during the coronavirus disease 2019 (COVID-19) pandemic.

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.

The value of decreasing the duration of the infectious period of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

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.

Potential Clinical and Economic Value of Norovirus Vaccination in the Community Setting.

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.

Vaccine Efficacy Needed for a COVID-19 Coronavirus Vaccine to Prevent or Stop an Epidemic as the Sole Intervention.

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 number=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).

How Efficacious Must a COVID-19 Coronavirus Vaccine be to Prevent or Stop an Epidemic by Itself.

BACKGROUND: Given the continuing coronavirus disease 2019 (COVID-19) pandemic and much of the U.S. implementing social distancing due to the lack of alternatives, there has been a push to develop a vaccine to eliminate the need for social distancing. METHODS: In 2020, we developed a computational model of the U.S. simulating the spread of COVID-19 coronavirus and vaccination. RESULTS: Simulation experiments revealed that when vaccine efficacy exceeded 70%, coverage exceeded 60%, and vaccination occurred on day 1, the attack rate dropped to 22% with daily cases not exceeding 3.2 million (reproductive rate, R0, 2.5). When R0 was 3.5, the attack rate dropped to 41% with daily cases not exceeding 14.4 million. Increasing coverage to 75% when vaccination occurred by day 90 resulted in 5% attack rate and daily cases not exceeding 258,029when R0 was 2.5 and a 26% attack rate and maximum daily cases of 22.6 million when R0 was 3.5. When vaccination did not occur until day 180, coverage (i.e., those vaccinated plus those otherwise immune) had to reach 100%. A vaccine with an efficacy between 40% and 70% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages. CONCLUSION: Our study found that to either prevent or largely extinguish an epidemic without any other measures (e.g., social distancing), the vaccine has to have an efficacy of at least 70%.

Using Simulation Modeling to Guide the Design of the Girl Scouts Fierce & Fit Program.

OBJECTIVE: The study aim was to help the Girl Scouts of Central Maryland evaluate, quantify, and potentially modify the Girl Scouts Fierce & Fit program. METHODS: From 2018 to 2019, our Public Health Informatics, Computational, and Operations Research team developed a computational simulation model representing the 250 adolescent girls participating in the Fierce & Fit program and how their diets and physical activity affected their BMI and subsequent outcomes, including costs. RESULTS: Changing the Fierce & Fit program from a 6-week program meeting twice a week, with 5 minutes of physical activity each session, to a 12-week program meeting twice a week with 30 minutes of physical activity saved an additional $84,828 ($80,130-$89,526) in lifetime direct medical costs, $81,365 ($76,528-$86,184) in lifetime productivity losses, and 7.85 (7.38-8.31) quality-adjusted life-years. The cost-benefit of implementing this program was $95,943. Based on these results, the Girl Scouts of Central Maryland then implemented these changes in the program. CONCLUSIONS: This is an example of using computational modeling to help evaluate and revise the design of a program aimed at increasing physical activity among girls.

The Potential Health Care Costs And Resource Use Associated With COVID-19 In The United States.

With the coronavirus disease 2019 (COVID-19) pandemic, one of the major concerns is the direct medical cost and resource use burden imposed on the US health care system. We developed a Monte Carlo simulation model that represented the US population and what could happen to each person who got infected. We estimated resource use and direct medical costs per symptomatic 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 case could incur a median direct medical cost of $3,045 during the course of the infection alone. If 80 percent of the US population were to get infected, the result could be a median of 44.6 million hospitalizations, 10.7 million intensive care unit (ICU) admissions, 6.5 million patients requiring a ventilator, 249.5 million hospital bed days, and $654.0 billion in direct medical costs over the course of the pandemic. If 20 percent of the US population were to get infected, there could be a median of 11.2 million hospitalizations, 2.7 million ICU admissions, 1.6 million patients requiring a ventilator, 62.3 million hospital bed days, and $163.4 billion in direct medical costs over the course of the pandemic.

Can following formula-feeding recommendations still result in infants who are overweight or have obesity?

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.

The Impact of Following Solid Food Feeding Guides on BMI Among Infants: A Simulation Study.

INTRODUCTION: There are several recommendations advising caregivers when and how to introduce solid food to infants. These complementary feeding guides vary in terms of the recommendations for timing and portions. The objective of this study is to determine the impact of following different guidelines on weight trajectories of infants. METHODS: In 2018, the study team developed a computational simulation model to capture feeding behaviors, activity levels, metabolism, and body size of infants from 6 months to 1 year. Daily food intake of virtual infants based on feeding recommendations translated to changes in body weight. Next, simulations tested the impact of the following complementary feeding recommendations that provided amount, type, and timing of foods: Children's Hospital of Philadelphia, Johns Hopkins Medicine, Enfamil, and Similac. RESULTS: When virtual caregivers fed infants according to the four different guides, none of the simulated situations resulted in normal weight at 12 months when infants were also being breastfed along average observed patterns. Reducing breast milk portions in half while caregivers fed infants according to complementary feeding guidelines resulted in overweight BMIs between 9 and 11 months for Children's Hospital of Philadelphia, Johns Hopkins Medicine, and Enfamil guidelines. Cutting breast milk portions in half also led to infants reaching unhealthy underweight BMI percentiles between 7 and 11 months for female and male infants when caregivers followed Children's Hospital of Philadelphia, Johns Hopkins Medicine, and Similac guidelines. CONCLUSIONS: This study identified situations in which infants could reach unhealthy weights, even while following complementary feeding guidelines, suggesting that current recommended portion sizes should be tightened.

Simulating the Impact of Sugar-Sweetened Beverage Warning Labels in Three Cities.

INTRODUCTION: A number of locations have been considering sugar-sweetened beverage point-of-purchase warning label policies to help address rising adolescent overweight and obesity prevalence. METHODS: To explore the impact of such policies, in 2016 detailed agent-based models of Baltimore, Philadelphia, and San Francisco were developed, representing their populations, school locations, and food sources, using data from various sources collected between 2005 and 2014. The model simulated, over a 7-year period, the mean change in BMI and obesity prevalence in each of the cities from sugar-sweetened beverage warning label policies. RESULTS: Data analysis conducted between 2016 and 2017 found that implementing sugar-sweetened beverage warning labels at all sugar-sweetened beverage retailers lowered obesity prevalence among adolescents in all three cities. Point-of-purchase labels with 8% efficacy (i.e., labels reducing probability of sugar-sweetened beverage consumption by 8%) resulted in the following percentage changes in obesity prevalence: Baltimore: -1.69% (95% CI= -2.75%, -0.97%, p<0.001); San Francisco: -4.08% (95% CI= -5.96%, -2.2%, p<0.001); Philadelphia: -2.17% (95% CI= -3.07%, -1.42%, p<0.001). CONCLUSIONS: Agent-based simulations showed how warning labels may decrease overweight and obesity prevalence in a variety of circumstances with label efficacy and literacy rate identified as potential drivers. Implementing a warning label policy may lead to a reduction in obesity prevalence. Focusing on warning label design and store compliance, especially at supermarkets, may further increase the health impact.

Simulating the Impact of Crime on African American Women's Physical Activity and Obesity.

OBJECTIVE: The objective of this study was to quantify the impact of crime on physical activity location accessibility, leisure-time physical activity (LTPA), and obesity among African American women. METHODS: An agent-based model was developed in 2016 to represent resource-limited Washington, DC, communities and their populations to simulate the impact of crime on LTPA and obesity among African American women under different circumstances. RESULTS: Data analysis conducted between 2016 and 2017 found that in the baseline scenario, African American women had a 25% probability of exercising. Reducing crime so more physical activity locations were accessible (increasing from 10% to 50%) decreased the annual rise in obesity prevalence by 2.69%. Increasing the probability of African American women to exercise to 37.5% further increased the impact of reducing crime on obesity (2.91% annual decrease in obesity prevalence). CONCLUSIONS: These simulations showed that crime may serve as a barrier to LTPA. Reducing crime and increasing propensity to exercise through multilevel interventions (i.e., economic development initiatives to increase time available for physical activity and subsidized health care) may promote greater than linear declines in obesity prevalence. Crime prevention strategies alone can help prevent obesity, but combining such efforts with other ways to encourage physical activity can yield even greater benefits.

Modeling The Economic And Health Impact Of Increasing Children's Physical Activity In The United States.

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.