Inclusion of marginalized populations in HPV vaccine modeling: A systematic review

OBJECTIVE

Models simulating the potential impacts of Human Papillomavirus (HPV) vaccine have been used globally to guide vaccination policies and programs. We sought to understand how and why marginalized populations have been incorporated into HPV vaccine simulation models.

METHODS

We conducted a systematic search of PubMed, CINAHL, Scopus, and Embase to identify studies using simulation models of HPV vaccination incorporating one or more marginalized population through stratification or subgroup analysis. We extracted data on study characteristics and described these overall and by included marginalized groups.

RESULTS

We identified 36 studies that met inclusion criteria, which modeled vaccination in 21 countries. Models included men who have sex with men (MSM; k = 16), stratification by HIV status (k = 9), race/ethnicity (k = 6), poverty (k = 5), rurality (k = 4), and female sex workers (k = 1). When evaluating for a marginalized group (k = 10), HPV vaccination was generally found to be cost-effective, including for MSM, individuals living with HIV, and rural populations. In studies evaluating equity in cancer prevention (k = 9), HPV vaccination generally advanced equity, but this was sensitive to differences in HPV vaccine uptake and use of absolute or relative measures of inequities. Only one study assessed the impact of an intervention promoting HPV vaccine uptake.

DISCUSSION

Incorporating marginalized populations into decision models can provide valuable insights to guide decision making and improve equity in cancer prevention. More research is needed to understand the equity impact of HPV vaccination on cancer outcomes among marginalized groups. Research should emphasize implementation - including identifying and evaluating specific interventions to increase HPV vaccine uptake.

Design and study of mine silo drainage method based on fuzzy control and Avoiding Peak Filling Valley strategy

Coal is a non-renewable fossil energy source on which humanity relies heavily, and producing one ton of raw coal requires the discharge of 2-7 tons of mine water from the ground. The huge drainage task increases the cost of coal mining in coal mines significantly, so saving the drainage cost while guaranteeing the safe production of coal mines is a problem that needs to be solved urgently. Most of the fuzzy controllers used in the traditional dynamic planning methods applied to mine drainage are two-dimensional fuzzy controllers with limited control effect, so the traditional two-dimensional fuzzy controllers are improved by introducing the rate of change of gushing water to form a three-dimensional fuzzy controller with three-dimensional control of instantaneous section-water level-rate of change of gushing water, and at the same time, the optimized dynamic planning method is designed by combining the Avoiding Peak Filling Valley strategy and the optimal dy-namic planning method is used in conjunction with the un-optimized dynamic planning method. The optimized dynamic planning method is applied to the same coal mine water silo gushing water experiments; experimental comparison found that the pumping station system before the optimi-zation of the electricity consumed is 52,586 yuan/day, while after the optimization of the electricity consumed is reduced to 41,692 yuan/day, the cost per day consumed compared with the previous reduction of 20.69%, a year can be saved 3,969,730 yuan. Therefore, the mine water bin drainage method based on fuzzy control and Avoiding Peak Filling Valley strategy proposed in this paper can be used as an improvement method of the existing mine drainage method, which can further ex-pand the economic benefits of coal mines and realize safe production while realizing cost savings.

Assessing the properties of patient-specific treatment effect estimates from causal forest algorithms under essential heterogeneity

BACKGROUND

Treatment variation from observational data has been used to estimate patient-specific treatment effects. Causal Forest Algorithms (CFAs) developed for this task have unknown properties when treatment effect heterogeneity from unmeasured patient factors influences treatment choice - essential heterogeneity.

METHODS

We simulated eleven populations with identical treatment effect distributions based on patient factors. The populations varied in the extent that treatment effect heterogeneity influenced treatment choice. We used the generalized random forest application (CFA-GRF) to estimate patient-specific treatment effects for each population. Average differences between true and estimated effects for patient subsets were evaluated.

RESULTS

CFA-GRF performed well across the population when treatment effect heterogeneity did not influence treatment choice. Under essential heterogeneity, however, CFA-GRF yielded treatment effect estimates that reflected true treatment effects only for treated patients and were on average greater than true treatment effects for untreated patients.

CONCLUSIONS

Patient-specific estimates produced by CFAs are sensitive to why patients in real-world practice make different treatment choices. Researchers using CFAs should develop conceptual frameworks of treatment choice prior to estimation to guide estimate interpretation ex post.

Possible mechanisms and simulation modeling of FLASH radiotherapy

FLASH radiotherapy (FLASH-RT) has great potential to improve patient outcomes. It delivers radiation doses at an ultra-high dose rate (UHDR: ≥ 40 Gy/s) in a single instant or a few pulses. Much higher irradiation doses can be administered to tumors with FLASH-RT than with conventional dose rate (0.01-0.40 Gy/s) radiotherapy. UHDR irradiation can suppress toxicity in normal tissues while sustaining antitumor efficiency, which is referred to as the FLASH effect. However, the mechanisms underlying the effects of the FLASH remain unclear. To clarify these mechanisms, the development of simulation models that can contribute to treatment planning for FLASH-RT is still underway. Previous studies indicated that transient oxygen depletion or augmented reactions between secondary reactive species produced by irradiation may be involved in this process. To discuss the possible mechanisms of the FLASH effect and its clinical potential, we summarized the physicochemical, chemical, and biological perspectives as well as the development of simulation modeling for FLASH-RT.

Personalizing age of gastric cancer screening based on comorbidity in China: Model estimates of benefits, affordability and cost-effectiveness optimization

The benefits of gastric cancer screening are related to age and comorbidity status, but reliable estimates are lacking in China. This study aimed to estimate the benefits and affordability of the gastric cancer screening strategy by level of comorbidity to inform decisions to screening age. We assessed six current gastric cancer screening strategies in China using a microsimulation model with different starting and stopping ages and comorbidity profiles, for a total of 378 strategies. 1,000,000 individuals were simulated in the model and followed the alternative strategies. Primary outcomes included gastric cancer incidence, the number of endoscopy and complications, life-years, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. Future costs and QALYs are discounted by 5% per year. Sensitivity analyses were used to evaluate model uncertainty. Strategies with longer screening durations were associated with higher benefits of life-year gained and gastric cancer deaths averted, but were also accompanied by a large number of endoscopy screening, and complication events. Using the threshold of US$18,575 per QALY gained, at the no, moderate, and severe comorbidity level, the leading cost-effectiveness strategies were the new gastric cancer screening scoring system strategy (NGCS) screening from age 40 years to 60 years (40-60), 40-55-NGCS, and 40-55-NGCS strategy, respectively. The results are robust in sensitivity analyses. Our study illustrates the importance of considering comorbidity conditions and age when determining the starting and stopping screening age for gastric cancer and informs the discussion on personalizing decisions. The trade-off between benefits and harms can also be referenced when necessary.

Simulation analysis of high-throughput oyster cryopreservation at three scales of production

Cryopreservation and germplasm repositories offer a variety of potential benefits to aquaculture industries. Despite this, no comprehensive repository systems exist for any prominent aquaculture species. A species that could greatly benefit from the use of cryopreserved sperm and repository storage is the eastern oyster, Crassostrea virginica. High-throughput cryopreservation protocols already exist for this species, and the easy transport of frozen sperm could facilitate selective breeding programs that address pressing challenges currently faced in the industry, such as mortality due to low-salinity conditions. This study addressed the gap between cryopreservation protocols and repository development in the oyster industry by creating simulation models to evaluate cryopreservation needs at three different scales of production. The effects of high-throughput device options and three key parameters (straws per oyster, batch size, and number of operators) on production capacity, time, and cost were evaluated. Recommendations for decisions concerning cryopreservation pathways and repository creation were given at each scale of production. Relative values of broodstock, juvenile oysters, and oyster sperm sold at hatcheries were also discussed. In general, repositories operating at higher production levels benefited from the economy of scale, could use automated high-throughput equipment options, and could hire more labor without drastically increasing production costs.

Using neural networks to calibrate agent based models enables improved regional evidence for vaccine strategy and policy

Distribution and administration strategy are critical to successful population immunization efforts. Agent-based modeling (ABM) can reflect the complexity of real-world populations and can experimentally evaluate vaccine strategy and policy. However, ABMs historically have been limited in their time-to-development, long runtime, and difficulty calibrating. Our team had several technical advances in the development of our GradABMs: a novel class of scalable, fast and differentiable simulations. GradABMs can simulate million-size populations in a few seconds on commodity hardware, integrate with deep neural networks and ingest heterogeneous sources. This allows for rapid and real-world sensitivity analyses. Our first epidemiological GradABM (EpiABMv1) enabled simulation interventions over real million-scale populations and was used in vaccine strategy and policy during the COVID-19 pandemic. Literature suggests decisions aided by evidence from these models saved thousands of lives. Our most recent model (EpiABMv2) extends EpiABMv1 to allow improved regional calibration using deep neural networks to incorporate local population data, and in some cases different policy recommendations versus our prior models. This is an important advance for our model to be more effective at vaccine strategy and policy decisions at the local public health level.

Mortality, incarceration and cost implications of fentanyl felonization laws: A modeling study

BACKGROUND

Opioid overdose continues to be a major cause of death in the United States. One effort to control opioid use has been to implement policies that enhance criminalization of opioid possession. Laws to further criminalize possession of fentanyl have been enacted or are under consideration across the country, including at the national level.

OBJECTIVE

Estimate the long-term effects on opioid death and incarceration resulting from increasingly strict fentanyl possession laws .

DESIGN

We built a Markov simulation model to explore the potential outcomes of a 2022 Colorado law which made possession of >1 g of drug with any amount of fentanyl a Level 4 drug felony (and escalation of the previous law, where >4 g of any drug with any amount of fentanyl in possession was considered a felony). The model simulates a cohort of people with fentanyl possession moving through the criminal justice system, exploring the probability of overdose and incarceration under different scenarios, including various fentanyl possession policies and potential interventions.

SETTING

Colorado PARTICIPANTS: A simulated cohort of people in possession of fentanyl.

MEASUREMENTS

Number of opioid overdose deaths, people incarcerated, and associated costs over 5 years.

RESULTS

When >4 g of a drug containing any amount of fentanyl is considered a felony in Colorado, the model predicts 5460 overdose deaths (95% CrI 410-9260) and 2,740 incarcerations for fentanyl possession (95% CrI: 230-10,500) over 5 years. When the policy changes so that >1 g possession of drug with fentanyl is considered a felony, opioid overdose deaths increase by 19% (95% CRI: 16-38%) and incarcerations for possession increase by 98% (CrI: 85-98%). Diversion programs and MOUD in prison help alleviate some of the increases in death and incarceration, but do not completely offset them.

LIMITATIONS

The mathematical model is meant to offer broad assessment of the impact of these policies, not forecast specific and exact numerical outcomes.

CONCLUSIONS

Our model shows that lowering thresholds for felony possession of fentanyl containing drugs can lead to more opioid overdose deaths and incarceration.

Dynamics of colorectal cancer screening in low and middle-income countries: A modeling analysis from Thailand

BACKGROUND

Low and middle-income countries face constraints for early colorectal cancer (CRC) detection, including restricted access to care and low colonoscopy capacity. Considering these constraints, we studied strategies for increasing access to early CRC detection and reducing CRC progression and mortality rates in Thailand.

METHODS

We developed a system dynamics model to simulate CRC death and progression trends. We analyzed the impacts of increased access to screening via fecal immunochemical test and colonoscopy, improving access to CRC diagnosis among symptomatic individuals, and their combination.

RESULTS

Projecting the status quo (2023-2032), deaths per 100K people increase from 87.5 to 115.4, and CRC progressions per 100K people rise from 131.8 to 159.8. In 2032, improved screening access prevents 2.5 CRC deaths and 2.5 progressions per 100K people, with cumulative prevented 7K deaths and 9K progressions, respectively. Improved symptom evaluation access prevents 7.5 CRC deaths per 100K with no effect on progression, totaling 35K saved lives. A combined approach prevents 9.3 deaths and 1.8 progressions per 100K, or 41K and 7K cumulatively. The combined strategy prevents most deaths; however, there is a tradeoff: It prevents fewer CRC progressions than screening access improvement. Increasing the current annual colonoscopy capacity (200K) to sufficient capacity (681K), the combined strategy achieves the best results, preventing 15.0 CRC deaths and 10.3 CRC progressions per 100K people, or 54K and 30K cumulatively.

CONCLUSION

Until colonoscopy capacity increases, enhanced screening and symptom evaluation are needed simultaneously to curb CRC deaths, albeit not the best strategy for CRC progression prevention.

'Drive the doctor' for endovascular thrombectomy in a rural area: a simulation study

BACKGROUND

Patients who present in a primary stroke center (PSC) with ischemic stroke are usually transferred to a comprehensive stroke center (CSC) in case of a large vessel occlusion (LVO) for endovascular thrombectomy (EVT) treatment, the so-called 'drip-and-ship' (DS) model. The 'drive-the-doctor' (DD) model modifies the DS model by allowing mobile interventionalists (MIs) to transfer to an upgraded PSC acting as a thrombectomy capable stroke center (TSC), instead of transferring patients to a CSC. Using simulation we estimated time savings and impact on clinical outcome of DD in a rural region.

METHODS

Data from EVT patients in northern Netherlands was prospectively collected in the MR CLEAN Registry between July 2014 - November 2017. A Monte Carlo simulation model of DS patients served as baseline model. Scenarios included regional spread of TSCs, pre-hospital patient routing to 'the nearest PSC' or 'nearest TSC', MI's notification after LVO confirmation or earlier prehospital, and MI's transport modalities. Primary outcomes are onset to groin puncture (OTG) and predicted probability of favorable outcome (PPFO) (mRS 0-2).

RESULTS

Combining all scenarios OTG would be reduced by 28-58 min and PPFO would be increased by 3.4-7.1%. Best performing and acceptable scenario was a combination of 3 TSCs, prehospital patient routing based on the RACE scale, MI notification after LVO confirmation and MI's transfer by ambulance. OTG would reduce by 48 min and PPFO would increase by 5.9%.

CONCLUSIONS

A DD model is a feasible scenario to optimize acute stroke services for EVT eligible patients in rural regions. Key design decisions in implementing the DD model for a specific region are regional spread of TSCs, patient routing strategy, and MI's notification moment and transport modality.

The health and economic benefits of sugar taxation and vegetables and fruit subsidy scenarios in Canada

A tax on sugar-sweetened beverages (SSB) has been implemented in various jurisdictions. Though research confirmed this tax to reduce sugar consumption and to prevent chronic diseases, it also revealed concerns: one concern relates to the small proportion of sugar in the diet coming from SSBs; and another concern relates to the disproportional tax burden to low-income groups. To inform public health decision makers on alternatives, we examined three 'real world' taxation and subsidy scenarios in Canada: 1) a CAD$0.75/100 g tax on SSBs; 2) a CAD$0.75/100 g tax on free sugar in all foods; and 3) a 20% subsidy on vegetables and fruit (V&F). Using national survey data and a proportional multi-state life table-based Markov model, we simulated the changes in disability-adjusted life years, healthcare costs, tax revenue, intervention costs, and incremental cost-effectiveness ratio for five income quintiles after implementing the three scenarios, over a lifetime of the 2015 Canadian adult population. The first, second and third scenario would prevent 28,921, 262,348 and 551 cases of type 2 diabetes, respectively. They would avert 752,353, 12,167,113, and 29,447 disability-adjusted life years and save CAD$12,942 million, 149,927 million, and 442 million in health care costs, respectively, over a lifetime. Combining the second and third scenarios would lead to the largest health and economic benefits. Although the lowest income quintile would bear a higher sugar tax burden (0.81% of income, CAD$120/person/year), this would be compensated by a coinciding subsidy on V&F (1.30% of income, CAD$194/person/year). These findings support policies that include a tax on all free sugar in foods and a subsidy on V&F as an effective means to reduce chronic diseases and health care costs. Although the sugar tax was financially regressive, the V&F subsidy could compensate for the tax burden of the disadvantaged groups and improve health and economic equity.

Cost-effectiveness of office-based buprenorphine treatment for opioid use disorder

AIM

To assess the effectiveness and cost-effectiveness of office-based buprenorphine treatment (OBBT) in the U.S.

DESIGN SETTING AND PARTICIPANTS

We performed a model-based analysis of buprenorphine treatment provided in a primary care setting for the U.S. population with OUD.

INTERVENTION

Buprenorphine treatment provided in a primary care setting.

MEASUREMENTS

Fatal and nonfatal overdoses and deaths over five years, discounted lifetime quality-adjusted life years (QALYs), costs.

FINDINGS

For a cohort of 100,000 untreated individuals who enter OBBT, approximately 9350 overdoses would be averted over five years; of these, approximately 900 would have been fatal. OBBT compared to no treatment would yield 1.07 incremental lifetime QALYs per person at an incremental cost of $17,000 per QALY gained when using a healthcare perspective. If OBBT is half as effective and twice as expensive as assumed in the base case, the incremental cost when using a healthcare perspective is $25,500 per QALY gained. Using a limited societal perspective that additionally includes patient costs and criminal justice costs, OBBT is cost-saving compared to no treatment even under pessimistic assumptions about efficacy and cost.

CONCLUSIONS

Expansion of OBBT would be highly cost-effective compared to no treatment when considered from a healthcare perspective, and cost-saving when reduced criminal justice costs are included. Given the continuing opioid crisis in the U.S., expansion of this care option should be a high priority.

A new mixed agent-based network and compartmental simulation framework for joint modeling of related infectious diseases- application to sexually transmitted infections

Background

A model that jointly simulates infectious diseases with common modes of transmission can serve as a decision-analytic tool to identify optimal intervention combinations for overall disease prevention. In the United States, sexually transmitted infections (STIs) are a huge economic burden, with a large fraction of the burden attributed to HIV. Data also show interactions between HIV and other sexually transmitted infections (STIs), such as higher risk of acquisition and progression of co-infections among persons with HIV compared to persons without. However, given the wide range in prevalence and incidence burdens of STIs, current compartmental or agent-based network simulation methods alone are insufficient or computationally burdensome for joint disease modeling. Further, causal factors for higher risk of coinfection could be both behavioral (i.e., compounding effects of individual behaviors, network structures, and care behaviors) and biological (i.e., presence of one disease can biologically increase the risk of another). However, the data on the fraction attributed to each are limited.

Methods

We present a new mixed agent-based compartmental (MAC) framework for jointly modeling STIs. It uses a combination of a new agent-based evolving network modeling (ABENM) technique for lower-prevalence diseases and compartmental modeling for higher-prevalence diseases. As a demonstration, we applied MAC to simulate lower-prevalence HIV in the United States and a higher-prevalence hypothetical Disease 2, using a range of transmission and progression rates to generate burdens replicative of the wide range of STIs. We simulated sexual transmissions among heterosexual males, heterosexual females, and men who have sex with men (men only and men and women). Setting the biological risk of co-infection to zero, we conducted numerical analyses to evaluate the influence of behavioral factors alone on disease dynamics.

Results

The contribution of behavioral factors to risk of coinfection was sensitive to disease burden, care access, and population heterogeneity and mixing. The contribution of behavioral factors was generally lower than observed risk of coinfections for the range of hypothetical prevalence studied here, suggesting potential role of biological factors, that should be investigated further specific to an STI.

Conclusions

The purpose of this study is to present a new simulation technique for jointly modeling infectious diseases that have common modes of transmission but varying epidemiological features. The numerical analysis serves as proof-of-concept for the application to STIs. Interactions between diseases are influenced by behavioral factors, are sensitive to care access and population features, and are likely exacerbated by biological factors. Social and economic conditions are among key drivers of behaviors that increase STI transmission, and thus, structural interventions are a key part of behavioral interventions. Joint modeling of diseases helps comprehensively simulate behavioral and biological factors of disease interactions to evaluate the true impact of common structural interventions on overall disease prevention. The new simulation framework is especially suited to simulate behavior as a function of social determinants, and further, to identify optimal combinations of common structural and disease-specific interventions.

Genetic testing to guide screening for pancreatic ductal adenocarcinoma: Results of a microsimulation model

BACKGROUND

First-degree relatives (FDRs) of patients with pancreatic ductal adenocarcinoma (PDAC) have elevated PDAC risk, partially due to germline genetic variants. We evaluated the potential effectiveness of genetic testing to target MRI-based screening among FDRs.

METHODS

We used a microsimulation model of PDAC, calibrated to Surveillance, Epidemiology, and End Results (SEER) data, to estimate the potential life expectancy (LE) gain of screening for each of the following groups of FDRs: individuals who test positive for each of eight variants associated with elevated PDAC risk (e.g., BRCA2, CDKN2A); individuals who test negative; and individuals who do not test. Screening was assumed to take place if LE gains were achievable. We simulated multiple screening approaches, defined by starting age and frequency. Sensitivity analysis evaluated changes in results given varying model assumptions.

RESULTS

For women, 92% of mutation carriers had projected LE gains from screening for PDAC, if screening strategies (start age, frequency) were optimized. Among carriers, LE gains ranged from 0.1 days (ATM+ women screened once at age 70) to 510 days (STK11+ women screened annually from age 40). For men, LE gains were projected for all mutation carriers, ranging from 0.2 days (BRCA1+ men screened once at age 70) to 620 days (STK11+ men screened annually from age 40). For men and women who did not undergo genetic testing, or for whom testing showed no variant, screening yielded small LE benefit (0-2.1 days).

CONCLUSIONS

Genetic testing of FDRs can inform targeted PDAC screening by identifying which FDRs may benefit.

Defining minimum volume thresholds to increase quality of care: a new patient-oriented approach using mixed integer programming

A positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so-called volume-outcome relationship into minimum volume regulation (MVR) to increase the quality of care-yet with limited success. Until today, the effect of strict MVR application remains unclear as outcome quality gains cannot be estimated adequately and restrictions to application such as patient travel time and utilization of remaining hospital capacity are not considered sufficiently. Accordingly, when defining MVR, its effectiveness cannot be assessed. Thus, we developed a mixed integer programming model to define minimum volume thresholds balancing utility in terms of outcome quality gain and feasibility in terms of restricted patient travel time and utilization of hospital capacity. We applied our model to the German hospital sector and to four surgical procedures. Results showed that effective MVR needs a minimum volume threshold of 125 treatments for cholecystectomy, of 45 and 25 treatments for colon and rectum resection, respectively, of 32 treatments for radical prostatectomy and of 60 treatments for total knee arthroplasty. Depending on procedure type and incidence as well as the procedure's complication rate, outcome quality gain ranged between 287 (radical prostatectomy) and 977 (colon resection) avoidable complications (11.7% and 11.9% of all complications). Ultimately, policy makers can use our model to leverage MVR's intended benefit: concentrating treatment delivery to improve the quality of care.

Effects of habitat fragmentation and hunting activities on African swine fever dynamics among wild boar populations

African Swine Fever (ASF) has been slowly but steadily increasing its endemic range throughout Europe, posing an imminent risk to the pig industry. ASF transmission among wild boar occurs mainly through wild boar population movements, hence wild boar presence and density are important risk factors for introducing, maintaining, and spreading the disease. The understanding of wild boar population dynamics and their role in ASF transmission and persistence remains limited. It is crucial to gain knowledge in this area to improve wildlife management while minimizing the risks for ASF introduction and spread. We adapted an individual-based spatio-temporal stochastic model developed by Halasa et al. (2019) and tailored it to two regions in France. The model assessed yearly hunting activity, the carcass persistence seasonality, and the specific landscape characteristics of the Franco-Belgian border region and the Pyrénées-Atlantiques department. Following the establishment of local population dynamics through preliminary runs of the model, the model was run 100 iterations over 8 years in the two study areas where ASF was randomly seeded after the 2nd year of simulation. For each scenario, the model was initiated with 500 wild boar groups randomly spread across the study areas. Hunting activities were included and excluded to assess the impact on population growth and ASF spread. Results showed an ever-growing wild boar population for all scenarios, which was balanced when hunting activities were included. When introducing ASF, the wild boar populations were dramatically impacted in both areas with a decrease of 63 % of the population at the Franco-Belgian border and 86 % in the Pyrénées-Atlantiques department. Habitat fragmentation and landscape connectivity were highlighted as important factors shaping ASF propagation. The Franco-Belgian border, which had the most fragmented habitat with unsuitable areas for wild boars, was shown to limit wild boar movements, reducing the probability, and spread of ASF across the landscape. The lack of connectivity was reflected in a less effective transmission and lower number of infected groups (406 versus 467). In contrast, the epidemic duration was lengthened in the fragmented habitat compared to the homogenous area (2.6 years vs 1.6 years). This study provided information on defining and implementing control measures in case of an ASF incursion, since delimitation of the area via fences artificially induces landscape fragmentation, which is important for controlling ASF outbreaks.

Simulation modeling the effects of peels on pesticide removal from potatoes during household food processing

The impact of crop peels on reducing pesticide residue levels in crops during household food processing was evaluated in this study. We proposed a series of pesticide fate models to simulate the removal efficiency of residues in crop peels and medullas (i.e., pulps) via soaking and washing. The simulated results indicated that the variation in the peel thickness had a significant impact on residue removal from the peel compartment. However, the peel compartment had a low impact on the removal efficiency of pesticide residues from the medulla compartment, as demonstrated by the simulated results from the non-peel model (i.e., already peeled crops). In addition, we observed that even though systemic pesticides have a higher potential to penetrate from the peel into the medulla, the increasing residue level caused by the mass transfer from the peel into the medulla is too low to cause human health damage, because the absolute mass of residues in the peel is considerably small. Based on the simulation results, we concluded that washing or soaking crops with or without peels using water is not effective in reducing residue levels in crop medullas. Modifying crops into slices, instead of directly washing or soaking crops, could significantly improve the removal efficiency of pesticide residues inside the medulla. The models proposed in this study can improve our understanding on the fate of pesticides in crops during household food processing.

Long-term impact of HPV vaccination and COVID-19 pandemic on oropharyngeal cancer incidence and burden among men in the USA: A modeling study

BACKGROUND

Oropharyngeal cancer (OPC) incidence is rising rapidly among men in the United States of America (USA). We aimed to project the impact of maintaining the current HPV vaccination uptake and achieving 80% national (Healthy People) goal on OPC incidence and burden.

METHODS

We developed an open-cohort micro-simulation model of OPC natural history among contemporary and future birth cohorts of men, accounting for sexual behaviors, population growth, aging, and herd immunity. We used data from nationally representative databases, cancer registries from all 50 states, large clinical trials, and literature. We evaluated the status quo scenario (the current HPV vaccination uptake remained stable) and alternative scenarios of improvements in uptake rates in adolescents (aged 9-17 years) and young adults (aged 18-26 years) by 2025 to achieve and maintain the 80% goal. The primary outcome was to project OPC incidence and burden from 2009 to 2100. We also assessed the impact of disruption in HPV vaccine uptake during the COVID-19 pandemic.

FINDINGS

OPC incidence is projected to rise until the mid-2030s, reaching the age-standardized incidence rate of 9·8 (95% uncertainty interval [UI] 9·5-10·1) per 100 000 men, with the peak annual burden of 23 850 (UI, 23 200-24 500) cases. Under the status quo scenario, HPV vaccination could prevent 124 000 (UI, 117 000-131 000) by 2060, 400 000 (UI, 384 000-416 000) by 2080, and 792 000 (UI, 763 000-821 000) by 2100 OPC cases among men. Achievement and maintenance of 80% coverage among adolescent girls only, adolescent girls and boys, and adolescents plus young adults could prevent an additional number of 100 000 (UI, 95 000-105 000), 118 000 (UI, 113 000-123 000), and 142 000 (UI, 136 000-148 000) male OPC cases by 2100. Delayed recovery of the HPV vaccine uptake during the COVID-19 pandemic could lead to 600 (UI, 580-620) to 6200 (UI, 5940-6460) additional male OPC cases by 2100, conditional on the decline in the extent of the national HPV vaccination coverage and potential delay in rebounding.

INTERPRETATION

Oropharyngeal cancer burden is projected to rise among men in the USA. Nationwide efforts to achieve the HPV vaccination goal of 80% coverage should be a public health priority. Rapid recovery of the declined HPV vaccination uptake during the COVID-19 pandemic is also crucial to prevent future excess OPC burden.

FUNDING

National Cancer Institute and National Institute on Minority Health and Health Disparities of the USA.

Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities

BACKGROUND

Simulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities. We aim to disaggregate one type of Markov macro-simulation model, the proportional multistate lifetable, ensuring that under business-as-usual (BAU) the sum of deaths across disaggregated strata in each time step returns the same as the initial non-disaggregated model. We then demonstrate the application by deprivation quintiles for New Zealand (NZ), for: hypothetical interventions (50% lower all-cause mortality, 50% lower coronary heart disease mortality) and a dietary intervention to substitute 59% of sodium with potassium chloride in the food supply.

METHODS

We developed a disaggregation algorithm that iteratively rescales mortality, incidence and case-fatality rates by time-step of the model to ensure correct total population counts were retained at each step. To demonstrate the algorithm on deprivation quintiles in NZ, we used the following inputs: overall (non-disaggregated) all-cause mortality & morbidity rates, coronary heart disease incidence & case fatality rates; stroke incidence & case fatality rates. We also obtained rate ratios by deprivation for these same measures. Given all-cause and cause-specific mortality rates by deprivation quintile, we derived values for the incidence, case fatality and mortality rates for each quintile, ensuring rate ratios across quintiles and the total population mortality and morbidity rates were returned when averaged across groups. The three interventions were then run on top of these scaled BAU scenarios.

RESULTS

The algorithm exactly disaggregated populations by strata in BAU. The intervention scenario life years and health adjusted life years (HALYs) gained differed slightly when summed over the deprivation quintile compared to the aggregated model, due to the stratified model (appropriately) allowing for differential background mortality rates by strata. Modest differences in health gains (HALYs) resulted from rescaling of sub-population mortality and incidence rates to ensure consistency with the aggregate population.

CONCLUSION

Policy makers ideally need to know the effect of population interventions estimated both overall, and by socioeconomic and other strata. We demonstrate a method and provide code to do this routinely within proportional multistate lifetable simulation models and similar Markov models.

Impact of Joint Lung Cancer Screening and Cessation Interventions Under the New Recommendations of the U.S. Preventive Services Task Force

INTRODUCTION

In 2021, the U.S. Preventive Services Task Force (USPSTF) revised its lung cancer screening recommendations expanding its eligibility. As more smokers become eligible, cessation interventions at the point of screening could enhance the benefits. Here, we evaluate the effects of joint screening and cessation interventions under the new recommendations.

METHODS

A validated lung cancer natural history model was used to estimate lifetime number of low-dose computed tomography screens, percentage ever screened, lung cancer deaths, lung cancer deaths averted, and life-years gained for the 1960 U.S. birth cohort aged 45 to 90 years (4.5 million individuals). Screening occurred according to the USPSTF 2013 and 2021 recommendations with varying uptake (0%, 30%, 100%), with or without a cessation intervention at the point of screening with varying effectiveness (15%, 100%).

RESULTS

Screening 30% of the eligible population according to the 2021 criteria with no cessation intervention (USPSTF 2021, 30% uptake, without cessation intervention) was estimated to result in 6845 lung cancer deaths averted and 103,725 life-years gained. These represent 28% and 34% increases, respectively, relative to screening according to the 2013 guidelines (USPSTF 2013, 30% uptake, without cessation intervention). Adding a cessation intervention at the time of the first screen with 15% effectiveness (USPSTF 2021, 30% uptake, with cessation intervention with 15% effectiveness) was estimated to result in 2422 additional lung cancer deaths averted (9267 total, ∼73% increase versus USPSTF 2013, 30% uptake, without cessation intervention) and 322,785 life-years gained (∼318% increase). Screening 100% of the eligible according to the 2021 guidelines with no cessation intervention (USPSTF 2021, 100% uptake, without cessation intervention) was estimated to result in 23,444 lung cancer deaths averted (∼337% increase versus USPSTF 2013, 30% uptake, without cessation intervention) and 354,330 life-years gained (∼359% increase). Adding a cessation intervention with 15% effectiveness (USPSTF 2021, 100% uptake, with cessation intervention with 15% effectiveness) would result in 31,998 lung cancer deaths averted (∼497% increase versus USPSTF 2013, 30% uptake, without cessation intervention) and 1,086,840 life-years gained (∼1309% increase).

CONCLUSIONS

Joint screening and cessation interventions would result in considerable lung cancer deaths averted and life-years gained. Adding a one-time cessation intervention of modest effectiveness (15%) results in comparable life-years gained as increasing screening uptake from 30% to 100% because while cessation decreases mortality from many causes, screening only reduces lung cancer mortality. This simulation indicates that incorporating cessation programs into screening practice should be a priority as it can maximize overall benefits.

CityGML urban model generation using national public datasets for flood damage simulations: A case study in Korea

Managing information at city level has become increasingly important owing to the introduction of smart cities and the increasing severity of disasters due to climate change. A data collection framework, model construction, and information management must be established to systematically manage information at the city level. This study developed an urban model generation method using detailed attributes within the City Geography Markup Language (CityGML), a standard data schema for 3D representation of cities based on different types of publicly available information within Korea. The generated model was used to develop a method for simulating flooding status, degree of flooding, and level of building damage after heavy rainfall, in Korea. Furthermore, we developed a method to estimate the loss of human life and property damage by combining the results of the flood analysis with the city model. The proposed methodology supports the creation of standard-based models for flood analysis and exhibits strong interoperability for application to different areas of analysis.

Stroke care networks and the impact on quality of care

Lack of rapidly available neurological expertise, especially in rural areas, is one of the key obstacles in stroke care. Stroke care networks attempt to address this challenge by connecting hospitals with specialized stroke centers, stroke units, and hospitals of lower levels of care. While the benefits of stroke care networks are well-documented, travel distances are likely to increase when patients are transferred almost exclusively between members of the same network. This is particularly important for patients who require mechanical thrombectomy, an increasingly employed treatment method that requires equipment and expertise available in specialized stroke centers. This study aims to analyze the performance of the current design of stroke care networks in Bavaria, Germany, and to evaluate the improvement potential when the networks are redesigned to minimize travel distances. To this end, we define three fundamental criteria for assessing network design performance: 1) average travel distances, 2) the populace in the catchment area relative to the number of stroke units, and 3) the ratio of stroke units to lower-care hospitals. We generate several alternative stroke network designs using an analytical approach based on mathematical programming and clustering. Finally, we evaluate the performance of the existing networks in Bavaria via simulation. The results show that the current network design could be significantly improved concerning the average travel distances. Moreover, the existing networks are unnecessarily imbalanced when it comes to their number of stroke units per capita and the ratio of stroke units to lower-care hospitals.

Participatory simulation modeling to inform colorectal cancer screening in a complex remote northern health system: Canada's Northwest Territories

BACKGROUND & AIMS

Colorectal cancer (CRC) mortality in the Northwest Territories (NWT), a northern region of Canada, could be reduced by implementing a CRC screening program. However, this may require additional colonoscopy resources. We used participatory simulation modeling to predict colonoscopy demand and to develop strategies for implementing a feasible and effective CRC screening program in this complex remote northern health system.

METHODS

Using a participatory simulation modeling approach, we first developed a conceptual model of CRC screening with local collaborators. This approach informed our parameter adjustments of an existing microsimulation model, OncoSim-CRC, using data from a retrospective cohort review of CRC screening between 2014-2019 and secondary data. Model scenarios reflecting program implementation were run for 500 million cases. Validity was assessed, and outputs analyzed with collaborators. Alternative scenarios were developed to reduce colonoscopy demand and results were presented to end-users.

RESULTS

We estimated that colonoscopy demand with a CRC screening program phased-in over 5 years would surpass capacity within 2 years. If demand is met, screen-detected cancers would increase by 110 %, and clinically-detected cases would reduce by 26 % over the next 30 years. We also found that prolonging the phase-in period, or revising adenoma follow-up guidelines would reduce colonoscopy demand while still improving cancer detection. Both strategies were considered feasible by collaborators. The adjusted model was valid, and the projections informed local end-users plans for CRC screening delivery.

CONCLUSIONS

Using participatory simulation modeling, we projected that a screening program would improve CRC detection but surpass current colonoscopy capacity. Phasing-in the screening program and reducing endoscopic adenoma follow-up would enhance feasibility of a CRC screening program in the NWT and help maintain its effectiveness.

Reducing the smoking-related health burden in the USA through diversion to electronic cigarettes: a system dynamics simulation study

BACKGROUND

Electronic cigarettes ("e-cigarettes") have altered tobacco smoking trends, and their impacts are controversial. Given their lower risk relative to combustible tobacco, e-cigarettes have potential for harm reduction. This study presents a simulation-based analysis of an e-cigarette harm reduction policy set in the USA.

METHODS

A system dynamics simulation model was constructed, with separate aging chains representing people in different stages of use (both of combustible cigarettes and e-cigarettes). These structures interact with a policy module to close the gap between actual (simulated) and goal numbers of individuals who smoke, chosen to reduce the tobacco-attributable death rate (i.e., mostly combustible cigarette-attributable, but conservatively allowing e-cigarette-attributable deaths) to that due to all accidents in the general population. The policy is two-fold, removing existing e-liquid flavor bans and providing an informational campaign promoting e-cigarettes as a lower-risk alternative. Realistic practical implementation challenges are modeled in the policy sector, including time delays, political resistance, and budgetary limitations. Effects of e-cigarettes on tobacco smoking occur through three mechanisms: (1) diversion from ever initiating smoking; (2) reducing progression to established smoking; and (3) increasing smoking cessation. An important unintended effect of possible death from e-cigarettes was conservatively included.

RESULTS

The base-case model replicated the historical exponential decline in smoking and the exponential increase in e-cigarette use since 2010. Simulations suggest tobacco smoking could be reduced to the goal level approximately 40 years after implementation. Implementation obstacles (time delays, political resistance, and budgetary constraints) could delay and weaken the effect of the policy by up to 62% in the worst case, relative to the ideal-case scenario; however, these discrepancies substantially decreased over time in dampened oscillations as negative feedback loops stabilize the system after the one-time "shock" introduced by policy changes.

CONCLUSIONS

The simulation suggests that the promotion of e-cigarettes as a harm-reduction policy is a viable strategy, given current evidence that e-cigarettes offset or divert from smoking. Given the strong effects of implementation challenges on policy effectiveness in the short term, accurately modeling such obstacles can usefully inform policy design. Ongoing research is needed, given continuing changes in e-cigarette use prevalence, new policies being enacted for e-cigarettes, and emerging evidence for substitution effects between combustible cigarettes and e-cigarettes.

Cost-Effectiveness Analysis in Implementation Science: a Research Agenda and Call for Wider Application

Purpose of Review

Cost-effectiveness analysis (CEA) can help identify the trade-offs decision makers face when confronted with alternative courses of action for the implementation of public health strategies. Application of CEA alongside implementation scientific studies remains limited. We aimed to identify areas for future development in order to enhance the uptake and impact of model-based CEA in implementation scientific research.

Recent Findings

Important questions remain about how to broadly implement evidence-based public health interventions in routine practice. Establishing population-level implementation strategy components and distinct implementation phases, including planning for implementation, the time required to scale-up programs, and sustainment efforts required to maintain them, can help determine the data needed to quantify each of these elements. Model-based CEA can use these data to determine the added value associated with each of these elements across systems, settings, population subgroups, and levels of implementation to provide tailored guidance for evidence-based public health action. There is a need to integrate implementation science explicitly into CEA to adequately capture diverse real-world delivery contexts and make detailed, informed recommendations on the aspects of the implementation process that provide good value.

Summary

We describe examples of how model-based CEA can integrate implementation scientific concepts and evidence to help tailor evaluations to local context. We also propose six distinct domains for methodological advancement in order to enhance the uptake and impact of model-based cost-effectiveness analysis in implementation scientific research.

Spatial planning of fire-agency stations as a function of wildfire likelihood in Thasos, Greece

Even though wildfires constitute a natural phenomenon, they may have severe implications with respect to the socioeconomic structure of the affected population and the ecological wealth of a territory, especially when they burn under high intensities. Timing of the initial attack is thus crucial to fire control in areas that fires are considered to be under high threat of burning. The aim of this paper is to investigate the combined use of simulation modeling and spatial optimization to assess the pre-positioning of fire-management resources on a small Greek island, Thasos, based on the current and desired fire agency capabilities, maximization of environmental protection, and rationalization of financial resources. The estimation of burn probability (BP) depicted specific areas of high fire hazard in the southern, central, and western part of the island, where essential preventive measures should be undertaken. Based on this result, BP was then used as a primary input for the assessment of optimal locations of fire operation agencies in order to achieve the maximal coverage under certain (already available) and minimum number of fire-fighting vehicles in different time windows. The results generated three differentiated optimal location schemes [8 available vehicles within either 10 (immediate response time) or 31 min (average response time) with the current fire resources; 19 and 2 required vehicles within 10 and 31 min, respectively, based on a minimum number of fire resources]. This type of information enables us to propose a relocation of the current fire agency in a southern town of the island. The flexibility and interaction of the models provide a framework for appropriate decision making under a set of political and financial constraints.

Simulation models for transmission of health care-associated infection: A systematic review

BACKGROUND

Health care-associated infections (HAIs) are a global health burden because of their significant impact on patient health and health care systems. Mechanistic simulation modeling that captures the dynamics between patients, pathogens, and the environment is increasingly being used to improve understanding of epidemiological patterns of HAIs and to facilitate decisions on infection prevention and control (IPC). The purpose of this review is to present a systematic review to establish (1) how simulation models have been used to investigate HAIs and their mitigation and (2) how these models have evolved over time, as well as identify (3) gaps in their adoption and (4) useful directions for their future development.

METHODS

The review involved a systematic search and identification of studies using system dynamics, discrete event simulation, and agent-based model to study HAIs.

RESULTS

The complexity of simulation models developed for HAIs significantly increased but heavily concentrated on transmission dynamics of methicillin-resistant Staphylococcus aureus in the hospitals of high-income countries. Neither HAIs in other health care settings, the influence of contact networks within a health care facility, nor patient sharing and referring networks across health care settings were sufficiently understood.

CONCLUSIONS

This systematic review provides a broader overview of existing simulation models in HAIs to identify the gaps and to direct and facilitate further development of appropriate models in this emerging field.

A hybrid simulation model approach to examine bacterial genome sequencing during a hospital outbreak

Background

Hospital infection control requires timely detection and identification of organisms, and their antimicrobial susceptibility. We describe a hybrid modeling approach to evaluate whole genome sequencing of pathogens for improving clinical decisions during a 2017 hospital outbreak of OXA-181 carbapenemase-producing Escherichia coli and the associated economic effects.

Methods

Combining agent-based and discrete-event paradigms, we built a hybrid simulation model to assess hospital ward dynamics, pathogen transmission and colonizations. The model was calibrated to exactly replicate the real-life outcomes of the outbreak at the ward-level. Seven scenarios were assessed including genome sequencing (early or late) and no sequencing (usual care). Model inputs included extent of microbiology and sequencing tests, patient-level data on length of stay, hospital ward movement, cost data and local clinical knowledge. The main outcomes were outbreak size and hospital costs. Model validation and sensitivity analyses were performed to address uncertainty around data inputs and calibration.

Results

An estimated 197 patients were colonized during the outbreak with 75 patients detected. The total outbreak cost was US$318,654 with 6.1% of total costs spent on sequencing. Without sequencing, the outbreak was estimated to result in 352 colonized patients costing US$531,109. Microbiology tests were the largest cost component across all scenarios.

Conclusion

A hybrid simulation approach using the advantages of both agent-based and discrete-event modeling successfully replicated a real-life bacterial hospital outbreak as a foundation for evaluating clinical outcomes and efficiency of outbreak management. Whole genome sequencing of a potentially serious pathogen appears effective in containing an outbreak and minimizing hospital costs.

Presenting models to policymakers: intention and perception

The Seifu et al. article is a start to a timely inquiry on policymakers' perceptions of mathematical modeling and simulations aimed to guide obesity prevention programs. These computational tools have the potential to transform the fields of public health policy. Yet, to be effective, a broad Data and Information Literacy Initiative is needed to instill policymakers with the willingness to become life-long learners, to adapt and accept new technologies, attitudes, information, and creative ways of thinking.

Improving logistic efficiency of WEEE collection through dynamic scheduling using simulation modeling

The complexity of collection systems for Waste from Electric and Electronic Equipment (WEEE) in the EU is increasing, due to the latest directive that sets new collection targets and modes. The high variability and the uncertainty of reverse flows require innovative logistic approaches. One recent option for increasing efficiency and responsiveness in waste collection services, boosted by new technological solutions for waste level monitoring, is to adopt a dynamic collection scheme, where the collection frequency is not established a priori (based on a fixed plan), but it is based on the actual filling levels of waste bins. This option can allow the service provider to plan the collection service following the actual demand, resulting in a more responsive service, while improving the logistic efficiency. This paper evaluates the implementation of dynamic scheduling schemes for the collection of WEEE. A hybrid simulation model has been developed in order to support researchers and practitioners in assessing quantitative impacts of adopting dynamic scheduling in WEEE collection. Three logistic alternatives (a fixed collection schedule scheme, a pure dynamic scheme and a mixed one) have been compared in a test case based on data of an Italian municipality; collection services for different types of WEEE (i.e. large appliances and small items) have been analyzed. Results show a promising performance of dynamic schedules compared to the fixed one, revealing, for the specific test case, how a mixed solution can combine the advantages of dynamic and fixed scheduling, gaining flexibility towards customer demand while improving truck resource utilization.

Staffs' and managers' perceptions of how and when discrete event simulation modelling can be used as a decision support in quality improvement: a focus group discussion study at two hospital settings in Sweden

OBJECTIVE

To explore healthcare staffs' and managers' perceptions of how and when discrete event simulation modelling can be used as a decision support in improvement efforts.

DESIGN

Two focus group discussions were performed.

SETTING

Two settings were included: a rheumatology department and an orthopaedic section both situated in Sweden.

PARTICIPANTS

Healthcare staff and managers (n=13) from the two settings.

INTERVENTIONS

Two workshops were performed, one at each setting. Workshops were initiated by a short introduction to simulation modelling. Results from the respective simulation model were then presented and discussed in the following focus group discussion.

RESULTS

Categories from the content analysis are presented according to the following research questions: how and when simulation modelling can assist healthcare improvement? Regarding how, the participants mentioned that simulation modelling could act as a tool for support and a way to visualise problems, potential solutions and their effects. Regarding when, simulation modelling could be used both locally and by management, as well as a pedagogical tool to develop and test innovative ideas and to involve everyone in the improvement work.

CONCLUSIONS

Its potential as an information and communication tool and as an instrument for pedagogic work within healthcare improvement render a broader application and value of simulation modelling than previously reported.

Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models

PURPOSE

Interaction of the programmed death-1 (PD-1) co-receptor on T cells with the programmed death-ligand 1 (PD-L1) on tumor cells can lead to immunosuppression, a key event in the pathogenesis of many tumors. Thus, determining the amount of PD-L1 in tumors by immunohistochemistry (IHC) is important as both a diagnostic aid and a clinical predictor of immunotherapy treatment success. Because IHC reactivity can vary, we developed computational simulation models to accurately predict PD-L1 expression as a complementary assay to affirm IHC reactivity.

METHODS

Multiple myeloma (MM) and oral squamous cell carcinoma (SCC) cell lines were modeled as examples of our approach. Non-transformed cell models were first simulated to establish non-tumorigenic control baselines. Cell line genomic aberration profiles, from next-generation sequencing (NGS) information for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines, were introduced into the workflow to create cancer cell line-specific simulation models. Percentage changes of PD-L1 expression with respect to control baselines were determined and verified against observed PD-L1 expression by ELISA, IHC, and flow cytometry on the same cells grown in culture.

RESULT

The observed PD-L1 expression matched the predicted PD-L1 expression for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines and clearly demonstrated that cell genomics play an integral role by influencing cell signaling and downstream effects on PD-L1 expression.

CONCLUSION

This concept can easily be extended to cancer patient cells where an accurate method to predict PD-L1 expression would affirm IHC results and improve its potential as a biomarker and a clinical predictor of treatment success.

Simulation Modeling to Interpret the Captures of Moths in Pheromone-Baited Traps Used for Surveillance of Invasive Species: the Gypsy Moth as a Model Case

When pheromone traps are used for detection of an invasive pest and then delimitation of its distribution, an unresolved issue is the interpretation of failure to capture any target insects. Is a population present but not detected, a so-called false negative? Using the gypsy moth (Lymantria dispar) as an exemplar, we modeled the probability of males being captured in traps deployed at densities typical for surveillance (1 per 2.6 km² or 1 per mi²) and delimitation (up to 49 per 2.6 km²). The simulations used a dynamic wind model generating a turbulent plume structure and varying wind direction, and a behavior model based on the documented maneuvers of gypsy moths during plume acquisition and along-plume navigation. Several strategies of plume acquisition using Correlated Random Walks were compared to ensure that the generated dispersions over three days were not either overly clumped or ranged many km. Virtual moths were released into virtual space with patterns mimicking prior releases of gypsy moth males in Massachusetts at varying distance from a baited trap. In general, capture rates of virtual and real moths at varying trap densities were similar. One application of this approach was to estimate through bootstrapping the probabilities of not detecting populations having densities ranging from 1 to 100 moths per 2.6 km² and using traps that varied from 25 to 100 % in their efficiencies of capture. Low-level populations (e.g., 20-30 per 2.6 km²) often were not detected with one trap per 2.6 km², especially when traps had low efficiencies.

The economic and operational value of using drones to transport vaccines

BACKGROUND

Immunization programs in low and middle income countries (LMICs) face numerous challenges in getting life-saving vaccines to the people who need them. As unmanned aerial vehicle (UAV) technology has progressed in recent years, potential use cases for UAVs have proliferated due to their ability to traverse difficult terrains, reduce labor, and replace fleets of vehicles that require costly maintenance.

METHODS

Using a HERMES-generated simulation model, we performed sensitivity analyses to assess the impact of using an unmanned aerial system (UAS) for routine vaccine distribution under a range of circumstances reflecting variations in geography, population, road conditions, and vaccine schedules. We also identified the UAV payload and UAS costs necessary for a UAS to be favorable over a traditional multi-tiered land transport system (TMLTS).

RESULTS

Implementing the UAS in the baseline scenario improved vaccine availability (96% versus 94%) and produced logistics cost savings of $0.08 per dose administered as compared to the TMLTS. The UAS maintained cost savings in all sensitivity analyses, ranging from $0.05 to $0.21 per dose administered. The minimum UAV payloads necessary to achieve cost savings over the TMLTS, for the various vaccine schedules and UAS costs and lifetimes tested, were substantially smaller (up to 0.40L) than the currently assumed UAV payload of 1.5L. Similarly, the maximum UAS costs that could achieve savings over the TMLTS were greater than the currently assumed costs under realistic flight conditions.

CONCLUSION

Implementing a UAS could increase vaccine availability and decrease costs in a wide range of settings and circumstances if the drones are used frequently enough to overcome the capital costs of installing and maintaining the system. Our computational model showed that major drivers of costs savings from using UAS are road speed of traditional land vehicles, the number of people needing to be vaccinated, and the distance that needs to be traveled.

The role of public policies in reducing smoking prevalence: results from the Michigan SimSmoke tobacco policy simulation model

INTRODUCTION

Michigan has implemented several of the tobacco control policies recommended by the World Health Organization MPOWER goals. We consider the effect of those policies and additional policies consistent with MPOWER goals on smoking prevalence and smoking-attributable deaths (SADs).

METHODS

The SimSmoke tobacco control policy simulation model is used to examine the effect of past policies and a set of additional policies to meet the MPOWER goals. The model is adapted to Michigan using state population, smoking, and policy data starting in 1993. SADs are estimated using standard attribution methods. Upon validating the model, SimSmoke is used to distinguish the effect of policies implemented since 1993 against a counterfactual with policies kept at their 1993 levels. The model is then used to project the effect of implementing stronger policies beginning in 2014.

RESULTS

SimSmoke predicts smoking prevalence accurately between 1993 and 2010. Since 1993, a relative reduction in smoking rates of 22 % by 2013 and of 30 % by 2054 can be attributed to tobacco control policies. Of the 22 % reduction, 44 % is due to taxes, 28 % to smoke-free air laws, 26 % to cessation treatment policies, and 2 % to youth access. Moreover, 234,000 SADs are projected to be averted by 2054. With additional policies consistent with MPOWER goals, the model projects that, by 2054, smoking prevalence can be further reduced by 17 % with 80,000 deaths averted relative to the absence of those policies.

CONCLUSIONS

Michigan SimSmoke shows that tobacco control policies, including cigarette taxes, smoke-free air laws, and cessation treatment policies, have substantially reduced smoking and SADs. Higher taxes, strong mass media campaigns, and cessation treatment policies would further reduce smoking prevalence and SADs.

Preventing dementia by promoting physical activity and the long-term impact on health and social care expenditures

BACKGROUND

Preventing dementia has been proposed to increase population health as well as reduce the demand for health and social care. Our aim was to evaluate whether preventing dementia by promoting physical activity (PA) a) improves population health or b) reduces expenditure for both health and social care if one takes into account the additional demand in health and social care caused by increased life expectancy.

METHODS

A simulation model was developed that models the relation between PA, dementia, mortality, and the use of health care and social care in England. With this model, scenarios were evaluated in which different assumptions were made about the increase in PA level in (part of) the population.

RESULTS

Lifetime spending on health and social care related to dementia was highest for the physically inactive (£28,100/£28,900 for 40-year-old males/females), but spending on other diseases was highest for those that meet PA recommendations (£55,200/£43,300 for 40-year-old males/females) due to their longer life expectancies. If the English population aged 40-65 were to increase their PA by one level, life expectancy would increase by 0.23years and health and social care expenditures would decrease by £400 per person.

CONCLUSIONS

Preventing dementia by increasing PA increases life expectancy and can result in decreased spending overall on health and social care, even after additional spending during life years gained has been taken into account. If prevention is targeted at the physically inactive, savings in dementia-related costs outweigh the additional spending in life years gained.

Projecting the effects of long-term care policy on the labor market participation of primary informal family caregivers of elderly with disability: insights from a dynamic simulation model

Background

Using Singapore as a case study, this paper aims to understand the effects of the current long-term care policy and various alternative policy options on the labor market participation of primary informal family caregivers of elderly with disability.

Methods

A model of the long-term care system in Singapore was developed using System Dynamics methodology.

Results

Under the current long-term care policy, by 2030, 6.9 percent of primary informal family caregivers (0.34 percent of the domestic labor supply) are expected to withdraw from the labor market. Alternative policy options reduce primary informal family caregiver labor market withdrawal; however, the number of workers required to scale up long-term care services is greater than the number of caregivers who can be expected to return to the labor market.

Conclusions

Policymakers may face a dilemma between admitting more foreign workers to provide long-term care services and depending on primary informal family caregivers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12877-016-0243-0) contains supplementary material, which is available to authorized users.

Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model

Drybeans (Phaseolus vulgaris L.) are an important subsistence crop in Central America. Future climate change may threaten drybean production and jeopardize smallholder farmers' food security. We estimated yield changes in drybeans due to changing climate in these countries using downscaled data from global circulation models (GCMs) in El Salvador, Guatemala, Honduras, and Nicaragua. We generated daily weather data, which we used in the Decision Support System for Agrotechnology Transfer (DSSAT) drybean submodel. We compared different cultivars, soils, and fertilizer options in three planting seasons. We analyzed the simulated yields to spatially classify high-impact spots of climate change across the four countries. The results show a corridor of reduced yields from Lake Nicaragua to central Honduras (10-38 % decrease). Yields increased in the Guatemalan highlands, towards the Atlantic coast, and in southern Nicaragua (10-41 % increase). Some farmers will be able to adapt to climate change, but others will have to change crops, which will require external support. Research institutions will need to devise technologies that allow farmers to adapt and provide policy makers with feasible strategies to implement them.

Nanoscopic fuel-rich thermobaric formulations: Chemical composition optimization and sustained secondary combustion shock wave modulation

Advanced thermobaric explosives have become one of the urgent requirements when targeting caves, fortified structures, and bunkers. Highly metal-based systems are designed to exploit the secondary combustion resulted from active metal particles; thus sustained overpressure and additional thermal loadings can be achieved. This study, reports on a novel approach for chemical composition optimization using thermochemical calculations in an attempt to achieve the highest explosion power. Shock wave resulted from thermobaric explosives (TBX) was simulated using ANSYS(®) AUTODYN(®) 2D hydrocode. Nanoscopic fuel-rich thermobaric charge was prepared by pressing technique; static field test was conducted. Comparative studies of modeled pressure-time histories to practical measurements were conducted. Good agreement between numerical modeling and experimental measurements was observed, particularly in terms of the prediction of wider overpressure profile which is the main characteristics of TBX. The TBX wider overpressure profile was ascribed to the secondary shock wave resulted from fuel combustion. The shock wave duration time and its decay pattern were acceptably predicted. Effective lethal fire-ball duration up to 50ms was achieved and evaluated using image analysis technique. The extended fire-ball duration was correlated to the additional thermal loading due to active metal fuel combustion. The tailored thermobaric charge exhibited an increase in the total impulse by 40-45% compared with reference charge.

Forecasting fish biomasses, densities, productions, and bioaccumulation potentials of mid-atlantic wadeable streams

Regional fishery conditions of Mid-Atlantic wadeable streams in the eastern United States are estimated using the Bioaccumulation and Aquatic System Simulator (BASS) bioaccumulation and fish community model and data collected by the US Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP). Average annual biomasses and population densities and annual productions are estimated for 352 randomly selected streams. Realized bioaccumulation factors (BAF) and biomagnification factors (BMF), which are dependent on these forecasted biomasses, population densities, and productions, are also estimated by assuming constant water exposures to methylmercury and tetra-, penta-, hexa-, and hepta-chlorinated biphenyls. Using observed biomasses, observed densities, and estimated annual productions of total fish from 3 regions assumed to support healthy fisheries as benchmarks (eastern Tennessee and Catskill Mountain trout streams and Ozark Mountains smallmouth bass streams), 58% of the region's wadeable streams are estimated to be in marginal or poor condition (i.e., not healthy). Using simulated BAFs and EMAP Hg fish concentrations, we also estimate that approximately 24% of the game fish and subsistence fishing species that are found in streams having detectable Hg concentrations would exceed an acceptable human consumption criterion of 0.185 μg/g wet wt. Importantly, such streams have been estimated to represent 78.2% to 84.4% of the Mid-Atlantic's wadeable stream lengths. Our results demonstrate how a dynamic simulation model can support regional assessment and trends analysis for fisheries.

Projecting the direct cost burden of osteoarthritis in Canada using a microsimulation model

OBJECTIVES

To estimate the future direct cost of OA in Canada using a population-based health microsimulation model of osteoarthritis (POHEM-OA).

METHODS

We used administrative health data from the province of British Columbia (BC), Canada, a survey of a random sample of BC residents diagnosed with OA (Ministry of Health of BC data), Canadian Institute of Health Information (CIHI) cost data and literature estimates to populate a microsimulation model. Cost components associated with pharmacological and non-pharmacological treatments, total joint replacement (TJR) surgery, as well as use of hospital resources and management of complications arising from the treatment of osteoarthritis (OA) were included. Future costs were then simulated using the POHEM-OA model to construct profiles for each adult Canadian.

RESULTS

From 2010 to 2031, as the prevalence of OA is projected to increase from 13.8% to 18.6%, the total direct cost of OA is projected to increase from $2.9 billion to $7.6 billion, an almost 2.6-fold increase (in 2010 $CAD). From the highest to the lowest, the cost components that will constitute the total direct cost of OA in 2031 are hospitalization cost ($2.9 billion), outpatient services ($1.2 billion), alternative care and out-of-pocket cost categories ($1.2 billion), drugs ($1 billion), rehabilitation ($0.7 billion) and side-effect of drugs ($0.6 billion).

CONCLUSIONS

Projecting the future trends in the cost of OA enables policy makers to anticipate the significant shifts in its distribution of burden in the future.

One size does not fit all: The impact of primary vaccine container size on vaccine distribution and delivery

BACKGROUND

While the size and type of a vaccine container (i.e., primary container) can have many implications on the safety and convenience of a vaccination session, another important but potentially overlooked consideration is how the design of the primary container may affect the distribution of the vaccine, its resulting cost, and whether the vial is ultimately opened.

METHODS

Using our HERMES software platform, we developed a simulation model of the World Health Organization Expanded Program on Immunization supply chain for the Republic of Benin and used the model to explore the effects of different primary containers for various vaccine antigens.

RESULTS

Replacing vaccines with presentations containing fewer doses per vial reduced vaccine availability (proportion of people arriving for vaccines who are successfully immunized) by as much as 13% (from 73% at baseline) and raised logistics costs by up to $0.06 per dose administered (from $0.25 at baseline) due to increased bottlenecks, while reducing total costs by as much as $0.15 per dose administered (from $2.52 at baseline) due to lower open vial wastage. Primary containers with a greater number of doses per vial each improved vaccine availability by 19% and reduced logistics costs by $0.05 per dose administered, while reducing the total costs by up to $0.25 per dose administered. Changes in supply chain performance were more extreme in departments with greater constraints. Implementing a vial opening threshold reversed the direction of many of these effects.

CONCLUSIONS

Our results show that one size may not fit all when choosing a primary vaccine container. Rather, the choice depends on characteristics of the vaccine, the vaccine supply chain, immunization session size, and goals of decision makers. In fact, the optimal vial size may vary among locations within a country. Simulation modeling can help identify tailored approaches to improve availability and efficiency.

Effects of dispersal on total biomass in a patchy, heterogeneous system: Analysis and experiment

An intriguing recent result from mathematics is that a population diffusing at an intermediate rate in an environment in which resources vary spatially will reach a higher total equilibrium biomass than the population in an environment in which the same total resources are distributed homogeneously. We extended the current mathematical theory to apply to logistic growth and also showed that the result applies to patchy systems with dispersal among patches, both for continuous and discrete time. This allowed us to make specific predictions, through simulations, concerning the biomass dynamics, which were verified by a laboratory experiment. The experiment was a study of biomass growth of duckweed (Lemna minor Linn.), where the resources (nutrients added to water) were distributed homogeneously among a discrete series of water-filled containers in one treatment, and distributed heterogeneously in another treatment. The experimental results showed that total biomass peaked at an intermediate, relatively low, diffusion rate, higher than the total carrying capacity of the system and agreeing with the simulation model. The implications of the experiment to dynamics of source, sink, and pseudo-sink dynamics are discussed.

An alternative methodology for planning baggage carousel capacity expansion: A case study of Incheon International Airport

Intensifying competition for air transportation passengers has led airports to research optimal designs and determine the infrastructure expansion capacities of their terminals. As a result, many researchers have studied this subject from a variety of perspectives. In this study, we propose an alternative methodology of determining the expansion of baggage carousel capacity over a series of steps that includes both a simulation and a cost-benefit analysis. The methodology consists of three stages. In the first stage, we forecast the volume of arriving passengers (excluding transfer passengers) and aircraft traffic with an autoregressive integrated moving average (ARIMA) model. Next, we conduct an elaborate analysis to estimate passenger delay using a discrete event simulation model in which we consider the conveyor load and the baggage carousel allocation to aircraft rates. Finally, we determine a plan to expand baggage carousel capacity that accounts for expansion costs and passenger benefits. Construction and conveyor costs were applied to expansion costs, and capacity expansion leads to passenger benefits due to reduced waiting time. Using a real case with 23 candidate baggage carousels at Incheon International Airport during 2013-2015, our experiments demonstrate the strength of the proposed methodology in planning appropriate capacity expansion that reflect the operational flow of passengers within the airport based on the future trend of passenger demand. In particular, our results show that carousel no. 18 should be expanded during the first quarter of 2013, carousels no. 17 and no. 19 should be expanded in 2014, and carousel no. 5 should be expanded in 2015 to obtain optimal benefit-cost ratios of 1.65, 1.79, and 1.76 for each year, respectively.

Groundwater resources management through the applications of simulation modeling: a review

The global population is increasing rapidly and expected to touch the 9.5 billion mark by 2050 from the current 7.2 billion. The management of the groundwater resources is a challenging task worldwide against the backdrop of the growing water demand for industrial, agricultural, and domestic uses and shrinking resources. Moreover, this task has been hampered significantly due to declining/rising groundwater levels and associated contamination. A broad range of solutions could be considered to address the aforementioned problems of groundwater management, but the effectiveness of all the solutions and their combinations cannot be verified with field experiments. Given their predictive capability, simulation models are often the only viable means of providing input to management decisions, as they can forecast the likely impacts of a particular water management strategy. This paper presents a comprehensive review on the simulation modeling applications for the management of groundwater resources. The past papers on the overview of groundwater simulation models, use of remote sensing and GIS in groundwater modeling, and application of simulation models in arid and semiarid regions are described in detail. Conclusions are drawn where gaps exist and more research needs to be focused.

What do the screening trials really tell us and where do we go from here?

Publication of apparently conflicting results from 2 large trials of prostate cancer screening has intensified the debate about prostate-specific antigen (PSA) testing and has led to a recommendation against screening from the US Preventive Services Task Force. This article reviews the trials and discusses the limitations of their empirical results in informing public health policy. In particular, the authors explain why harm-benefit trade-offs based on empirical results may not accurately reflect the trade-offs expected under long-term population screening. This information should be useful to clinicians in understanding the implications of these studies regarding the value of PSA screening.