Hypothetical Intervention Scenarios Research Articles

Speed of environmental change frames relative ecological risk in climate change and climate intervention scenarios

Stratospheric aerosol injection is a potential method of climate intervention to reduce climate risk as decarbonization efforts continue. However, possible ecosystem impacts from the strategic design of hypothetical intervention scenarios are poorly understood. Two recent Earth system model simulations depict policy-relevant stratospheric aerosol injection scenarios with similar global temperature targets, but a 10-year delay in intervention deployment. Here we show this delay leads to distinct ecological risk profiles through climate speeds, which describe the rate of movement of thermal conditions. On a planetary scale, climate speeds in the simulation where the intervention maintains temperature are not statistically distinguishable from preindustrial conditions. In contrast, rapid temperature reduction following delayed deployment produces climate speeds over land beyond either a preindustrial baseline or no-intervention climate change with present policy. The area exposed to threshold climate speeds places different scenarios in context to their relative ecological risks. Our results support discussion of tradeoffs and timescales in future scenario design and decision-making.

Moderate low-cost modifications in diet prevent a substantial number of deaths and mitigate environmental impacts in Brazil.

This study aimed to estimate the health, economic, and environmental impacts of moderate simulated interventions on dietary intake in Brazil. Data on food price and consumption were obtained from three nationwide surveys. Baseline dietary intake was estimated for 33,859 individuals aged 25years and older. Counterfactual intakes were based on six hypothetical intervention scenarios, by changing the weekly frequency and serving size in low or high consumers of fruit and vegetables (FV), milk, whole grains, red and processed meats, and sugar-sweetened beverages. For each scenario, we estimated the attributable number of deaths and disability-adjusted life years (DALY), monetary cost, environmental impacts (14 midpoint indicators), and environmentally-mediated health impacts. Compared with the baseline intake and cost, the most expensive intervention (+ 8.3%) was to increase FV intake (+ 125g), resulting in a 1.2% reduction in all-cause mortality (16,307 deaths/year). The cheapest (- 9.9%) was to reduce red and processed meat intake (- 40g), resulting in a 1.1% reduction in all-cause mortality (14,272 deaths/year). The combined intervention was, on average, 3.7% cheaper than the baseline cost, resulting in an increase in diet cost for 30% of the population (45-22% in the lower- and higher-income groups); all-cause mortality would be reduced by 3.8% (49,488 deaths/year). Interventions targeting red and processed meats would reduce emissions and resource use by 35-55%, in addition to reducing 2300 DALYs/year. A meaningful number of deaths can be avoided and environmental impacts reduced through moderate and potentially affordable diet modifications.

Mortality risk of people living with HIV under hypothetical intervention scenarios of PM2.5 and HIV severity: a prospective cohort study

This study estimated and compared mortality risks among people living with HIV (PLWH) under the real-world and hypothetical scenarios of PM2.5 concentrations and HIV severity. An open cohort from all PLWH receiving antiretroviral therapy in Sichuan during 2010–2019 was constructed, resulting in 541,515 person-years. Annual mean concentrations of PM2.5 were estimated and linked to PLWH by their residential address. The parametric g-formula were used to assess 3- and 5-year mortality risks under the real-world and hypothetical scenarios of PM2.5 (10–35, 35–50, 50–75 μg/m3) and CD4 concentrations (0–200, 200–500, 500–800, 800–1100 counts/μl). The estimated 3- and 5-year mortality risks among the PLWH were 14.43 % and 19.38 %, respectively, which would decrease substantially when annual PM2.5 concentration were reduced to between 10 and 35 μg/m3 (risk difference [RD] = −3.23 % and − 4.06 %) and would increase when PM2.5 concentration were elevated to between 50 and 75 μg/m3 (RD = 3.59 % and 5.04 %). The mortality risk would increase when CD4 concentration were reduced to <200 counts/μl (RD = 15.90 % and 20.27 %) and would decrease when CD4 concentration were ≥ 200 counts/μl, especially to between 800 and 1100 counts/μl (RD = -9.01 % and − 11.75 %). The elevated concentration of PM2.5 may disproportionately affect individuals with immune deficiency, especially those with more severity. The findings would serve as justifications for future intervention design and policy making to alleviate air pollution and improve environmental justice and health equity.

How to use machine learning and fuzzy cognitive maps to test hypothetical scenarios in health behavior change interventions: a case study on fruit intake

BackgroundIntervention planners use logic models to design evidence-based health behavior interventions. Logic models that capture the complexity of health behavior necessitate additional computational techniques to inform decisions with respect to the design of interventions.ObjectiveUsing empirical data from a real intervention, the present paper demonstrates how machine learning can be used together with fuzzy cognitive maps to assist in designing health behavior change interventions.MethodsA modified Real Coded Genetic algorithm was applied on longitudinal data from a real intervention study. The dataset contained information about 15 determinants of fruit intake among 257 adults in the Netherlands. Fuzzy cognitive maps were used to analyze the effect of two hypothetical intervention scenarios designed by domain experts.ResultsSimulations showed that the specified hypothetical interventions would have small impact on fruit intake. The results are consistent with the empirical evidence used in this paper.ConclusionsMachine learning together with fuzzy cognitive maps can assist in building health behavior interventions with complex logic models. The testing of hypothetical scenarios may help interventionists finetune the intervention components thus increasing their potential effectiveness.

Analysis of the different interventions scenario for programmatic measles control in Bangladesh: A modelling study.

In recent years measles has been one of the most critical public health problem in Bangladesh. Although the Ministry of Health in Bangladesh employs a broad extension of measles control policies, logistical challenges exist, and there is significant doubt regarding the disease burden. Mathematical modelling of measles is considered one of the most effective ways to understand infection transmission and estimate parameters in different countries, such as Bangladesh. In this study, a mathematical modelling framework is presented to explore the dynamics of measles in Bangladesh. We calibrated the model using cumulative measles incidence data from 2000 to 2019. Also, we performed a sensitivity analysis of the model parameters and found that the contact rate had the most significant influence on the basic reproduction number R0. Four hypothetical intervention scenarios were developed and simulated for the period from 2020 to 2035. The results show that the scenario which combines enhanced treatment for exposed and infected population, first and second doses of vaccine is the most effective at rapidly reducing the total number of measles incidence and mortality in Bangladesh. Our findings also suggest that strategies that focus on a single interventions do not dramatically affect the decline in measles incidence cases; instead, those that combine two or more interventions simultaneously are the most effective in decreasing the burden of measles incidence and mortality. In addition, we also evaluated the cost-effectiveness of varying combinations of three basic control strategies including distancing, vaccination and treatment, all within the optimal control framework. Our finding suggested that combines distancing, vaccination and treatment control strategy is the most cost-effective for reducing the burden of measles in Bangladesh. Other strategies can be comprised to measles depending on the availability of funds and policymakers' choices.

Decolonization of hospital patients may aid efforts to reduce transmission of carbapenem-resistant Enterobacterales

Background: Multimodal approaches are often used to prevent transmission of antimicrobial-resistant pathogens among patients in healthcare settings; understanding the effect of individual interventions is challenging. We designed a model to compare the effectiveness of hand hygiene (HH) with or without decolonization in reducing patient colonization with carbapenem-resistant Enterobacterales (CRE). Methods: We developed an agent-based model to represent transmission of CRE in an acute-care hospital comprising 3 general wards and 2 ICUs, each with 20 single-occupancy rooms, located in a community of 85,000 people. The model accounted for the movement of healthcare personnel (HCP), including their visits to patients. CRE dynamics were modeled using a susceptible–infectious–susceptible framework with transmission occurring via HCP–patient contacts. The mean time to clearance of CRE colonization without intervention was 387 days (Zimmerman et al, 2013). Our baseline included a facility-level HH compliance of 30%, with an assumed efficacy of 50%. Contact precautions were employed for patients with CRE-positive cultures with assumed adherence and efficacy of 80% and 50%, respectively. Intervention scenarios included decolonization of culture-positive CRE patients, with a mean time to decolonization of 3 days. We considered 2 hypothetical intervention scenarios: (A) decolonization of patients with the baseline HH compliance and (B) decolonization with a slightly improved HH compliance of 35%. The hospital-level CRE incidence rate was used to compare the results from these intervention scenarios. Results: CRE incidence rates were lower in intervention scenarios than the baseline scenario (Fig. 1). The baseline mean incidence rate was 29.1 per 10,000 patient days. For decolonization with the baseline HH, the mean incidence rate decreased to 14.5 per 10,000 patient days, which is a 50.2% decrease relative to the baseline incidence (Table 1). The decolonization scenario with a slightly improved HH compliance of 35% produced a relative reduction of 71.9% relative to the baseline incidence. Conclusions: Our analysis shows that decolonization, combined with modest improvement in HH compliance, could lead to large decreases in pathogen transmission. In turn, this model implies that efforts to identify and improve decolonization strategies for better patient safety in health care may be needed and are worth exploring.Disclosures: None

Health and Environmental Impacts of Replacing Kerosene-Based Lighting with Renewable Electricity in Eastern Africa

BACKGROUND AND AIM: Lighting sources have been overlooked in previous estimates of the health burden attributable to household air pollution (HAP). However, lighting sources can be an important predictor of personal exposure to HAP in countries with limited access to electricity. We modeled the health and environmental impacts of hypothetical intervention scenarios that replace kerosene-based lighting with renewable electricity in Eastern Africa. METHODS: We used comparative risk assessment methods to quantify the ischemic heart disease-, stroke-, lung cancer-, chronic obstructive pulmonary disease- and lower respiratory infection-related mortality attributable to personal fine particulate matter (PM2.5) exposure due to kerosene-based lighting for residents of Eastern Africa in 2015. We used health and demographic data from the Global Burden of Disease; PM2.5 exposure estimates from a previous study replacing kerosene-based lighting with solar lighting; and exposure-response functions from the literature to estimate the number of deaths that could be avoided with increased scaling-up of the lighting source intervention. We estimated avoided black carbon emissions using emission factors from published literature. RESULTS:We estimated that 6,218, 10,092, 12,723 deaths could be avoided if 33%, 66%, and 100% respectively of households using kerosene-based lighting replaced it with electricity in Eastern Africa in 2015. Including lighting fuel in estimates of deaths due to PM2.5 from household air pollution in the region would add a further 9% in addition to those from cooking with solid fuel. Full replacement of kerosene-based lighting with renewable electricity would have reduced black carbon emissions by 4.4 Gg/year or 3,957 CO2eq Gg in 2015, with the largest emission reductions in Uganda and Kenya. CONCLUSIONS:Kerosene-based lighting is a non-negligible source of HAP in the region and should be included in assessments of the mortality burden attributable to HAP. KEYWORDS: Household Air Pollution, Mortality, Particulate Matter.

Health and environmental impacts of replacing kerosene-based lighting with renewable electricity in East Africa

BackgroundLighting sources have been overlooked in previous estimates of the health burden attributable to household air pollution (HAP). However, lighting sources can be an important predictor of personal exposure to HAP in countries with limited access to electricity. We modeled the health and environmental impacts of hypothetical intervention scenarios that replace kerosene-based lighting with renewable electricity in East Africa. MethodsWe used comparative risk assessment methods to quantify the ischemic heart disease-, stroke-, lung cancer-, chronic obstructive pulmonary disease- and lower respiratory infection-related morbidity and mortality attributable to personal fine particulate matter (PM2.5) exposure due to kerosene-based lighting for residents of East Africa in 2015. We used health and demographic data from the Global Burden of Disease; PM2.5 exposure estimates from a previous study replacing kerosene-based lighting with solar lighting; and exposure-response functions from the literature to estimate the number of deaths and DALYs that could be avoided with increased scaling-up of the lighting source intervention. We estimated avoided black carbon emissions using emission factors from published literature. ResultsWe estimated that 6218, 10,092, 12,723 deaths and 409, 654, 814 hundred thousand DALYs could be avoided if 33%, 66%, and 100% respectively of households using kerosene-based lighting replaced it with electricity in East Africa in 2015. Including lighting fuel in estimates of deaths due to PM2.5 from household air pollution in the region would add a further 9% in addition to those from cooking with solid fuel. Full replacement of kerosene-based lighting with renewable electricity would have reduced black carbon emissions by 4.4 Gg/year or 3957 CO2eq Gg in 2015, with the largest emission reductions in Uganda and Kenya. ConclusionKerosene-based lighting is a non-negligible source of HAP in the region and should be included in assessments of the health burden attributable to HAP.

Resource allocation for depression management in general practice: A simple data-based filter model.

BackgroundThis study aimed to illustrate the potential utility of a simple filter model in understanding the patient outcome and cost-effectiveness implications for depression interventions in primary care.MethodsModelling of hypothetical intervention scenarios during different stages of the treatment pathway was conducted.ResultsThree scenarios were developed for depression related to increasing detection, treatment response and treatment uptake. The incremental costs, incremental number of successes (i.e., depression remission) and the incremental costs-effectiveness ratio (ICER) were calculated. In the modelled scenarios, increasing provider treatment response resulted in the greatest number of incremental successes above baseline, however, it was also associated with the greatest ICER. Increasing detection rates was associated with the second greatest increase to incremental successes above baseline and had the lowest ICER.ConclusionsThe authors recommend utility of the filter model to guide the identification of areas where policy stakeholders and/or researchers should invest their efforts in depression management.

Equity impacts of interventions to increase physical activity: A health impact assessment

Abstract Background Behavioural interventions may increase social inequalities in health. This study aimed to project the equity impact of physical activity interventions that have differential effectiveness across education groups on the long-term health inequalities among older adults in Germany. Methods We created six hypothetical intervention scenarios targeting adults aged 55 years and above: Scenarios #1 to #4 applied realistic intervention effects that varied by education. Under scenario #5, the lower and medium educated group adapted the physical activity pattern of the higher educated. Under scenario #6, all persons increased their physical activity level to the recommended 300 minutes weekly. The number of incident ischemic heart disease, stroke and diabetes cases as well as deaths from all causes was simulated under each of these six intervention scenarios for males and females over a 10-year projection period using the DYNAMO-HIA tool, and compared against a reference scenario with unchanged physical activity pattern. Results For males, the highest reduction of disease cases and deaths would be achieved under scenario #4 (most effective in higher educated persons), while increasing inequalities between education groups. For females, the highest reduction would be achieved under scenario #3 (most effective in lower educated persons), while decreasing inequalities between education groups. Scenarios #1 to #4 would prevent only a fraction of the disease cases and deaths that would be avoided under scenario #5 or scenario #6. Conclusions This modelling study shows how the overall population health impact varies, depending on how intervention-induced physical activity changes differ across education groups. For decision-makers, both the assessment of health impacts overall as well as within a population is relevant, as interventions with the greatest population health gain might be accompanied by an unintended increase in health inequalities. Key messages Health impact assessments with a focus on equity are essential for decision-makers. In order to correctly project population health effects, and choose between options of intervention types from a public health perspective, data on subgroup-specific intervention effects are needed.

Estimates of the current and future burden of cancer attributable to excess body weight and abdominal adiposity in Canada

The increasing prevalence of obesity among Canadians has important implications for newly diagnosed cases of cancer given that excess body weight and abdominal adiposity are known to increase the risk of several cancers. The purpose of this analysis was to estimate the current attributable and future avoidable burden of cancer related to excess body weight and abdominal adiposity among Canadian adults. We estimated the population attributable risk (PAR) for all cancers associated with excess body weight and abdominal adiposity using contemporary cancer incidence, relative risk and exposure prevalence data for body mass index (BMI), waist circumference and waist-to-hip-ratio. Using the partial impact fraction (PIF), we also estimated the future avoidable burden of cancer from 2015 to 2042 in Canada, and by province, through various hypothetical intervention scenarios. In 2003, approximately half (50.5%) of the Canadian population was estimated to be overweight (BMI 25.0–29.9) or obese (BMI ≥30.0), 56.5% to have excess abdominal adiposity and 56.8% with a high waist-to-hip ratio. In 2015, the estimated PARs of all incident cancers associated with excess body weight, excess abdominal adiposity and high waist-to-hip ratio were 7.2%, 8.9% and 10.0%, respectively. If the population BMI could revert to its 1994 distribution, 72,157 associated cancer cases could be prevented cumulatively by 2042. A reduction in excess body weight and abdominal adiposity has the potential to decrease the future cancer burden in Canada substantially, and hence efforts to reverse increasing trends in obesity should be prioritized.

The impact of reducing alcohol consumption in Australia: An estimate of the proportion of potentially avoidable cancers 2013-2037.

The International Agency for Research on Cancer first concluded that alcohol causes cancer in humans in 1988. The World Cancer Research Fund has declared that alcohol causes cancer of the oral cavity, pharynx, larynx, oesophagus (squamous cell carcinoma), female breast, colon, rectum, stomach and liver. It recommended that alcohol be avoided altogether to prevent cancer. We aimed to quantify the impact of reducing alcohol consumption on future cancer incidence in Australia. We used PREVENT 3.01 simulation modelling software to estimate the proportion of cancers that could potentially be prevented over a 25-year period under two hypothetical intervention scenarios and two latency periods (20 and 30 years). Under a scenario where alcohol consumption abruptly ceases, we estimated up to 4% of alcohol-related cancers could be avoided over a 25-year period (~49,500 cancers, depending on assumed latency). If the maximum consumption of all Australian adults was ≤20 g/day (~two Australian standard drinks), up to 2% of alcohol-related cancers could be avoided (~29,600 cancers). The maximum proportions were higher for men (6% for no alcohol consumption; 5% for ≤20 g/day) than women (3%; 1%). The proportion avoidable was highest for oesophageal squamous cell carcinoma (17% no alcohol consumption; 9% ≤20 g/day), followed by cancers of the oral cavity (12%; 5%) and pharynx (11%; 5%). The cancer sites with the highest numbers of potentially avoidable cases were colon in men (11,500; 9,900) and breast in women (14,400; 4,100). Successful interventions to reduce alcohol intake could lead to significant reductions in cancer incidence.

Reducing alcohol-related harm in Australia: a simple data-based tool to assist prioritization of research and health care delivery in primary care.

The detection of harmful alcohol use and the delivery of brief advice in primary care are less than optimal. Given limited health care resources, deciding where best to allocate funding to optimize health outcomes is imperative. A simple data-based tool could be useful when access to specialist health economic advice is unavailable. This study aimed to examine the utility of a simple data-based calculator to facilitate priority setting in general practice for reducing alcohol-related harm. A simple algorithm was developed within Microsoft Excel to allow comparison of hypothetical intervention scenarios that aimed to increase detection and brief advice for harmful alcohol use in general practice. The calculator accommodated varying implementation costs, size of effect and reach for each scenario created. The incremental costs of the intervention scenarios, the incremental number of successes (i.e. abstinence or drinking at safe levels) and the incremental costs-effectiveness ratio (ICER) were calculated for each hypothetical scenario and compared with a usual care scenario. In the hypothetical scenarios modelled, increasing both the detection of harmful alcohol consumption and the provision of brief advice produced the greatest number of incremental successes above baseline. Increasing detection alone produced fewer incremental successes but was the most cost-effective approach, as indicated by the lowest ICER. The data-based calculator provides a simple method of exploring reach and cost-effectiveness outcomes without the need for any specific skills. Although this approach has limitations, the calculator can be used by decision makers to guide intervention planning.

The relation of the road environment and bicycling attitudes to usual travel mode to school in teenagers

Although active travel to school for primary school students has been widely studied, research into the determinants of teenage active travel to school is noticeably lacking. Understanding the determinants of teen active travel to school is important given that teenage travel may have implications for the formation of habits that carry over to adulthood. We present evidence linking travel to school with bicycling attitudes and with road environments on plausible paths to school using data from a large cross-sectional survey of students at three high schools in Northern California. Results suggest that the relationship between attitudes and bicycling are stronger than the relationship between road environments and bicycling. Students’ perceived social pressure to bicycle has a particularly strong association with bicycling. Hypothetical intervention scenarios suggest that students would walk and bicycle to school at substantially greater rates if they had better road environments for walking and bicycling, shorter distances to school, and more positive bicycling attitudes.

Preventing HIV Transmission Among Partners of HIV-Positive Male Sex Workers in Mexico City: A Modeling Study.

Mexico has a concentrated HIV epidemic, with male sex workers constituting a key affected population. We estimated annual HIV cumulative incidence among male sex workers' partners, and then compared incidence under three hypothetical intervention scenarios: improving condom use; and scaling up HIV treatment as prevention, considering current viral suppression rates (CVS, 60.7%) or full viral suppression among those treated (FVS, 100%). Clinical and behavioral data to inform model parameterization were derived from a sample (n=79) of male sex workers recruited from street locations and Clínica Condesa, an HIV clinic in Mexico City. We estimated annual HIV incidence among male sex workers' partners to be 8.0% (95% CI: 7.3-8.7). Simulation models demonstrated that increasing condom use by 10%, and scaling up HIV treatment initiation by 50% (from baseline values) would decrease the male sex workers-attributable annual incidence to 5.2, 4.4% (CVS) and 3.2% (FVS), respectively. Scaling up the number of male sex workers on ART and implementing interventions to ensure adherence is urgently required to decrease HIV incidence among male sex workers' partners in Mexico City.

In silico modeling of the effects of alpha-synuclein oligomerization on dopaminergic neuronal homeostasis.

BackgroundAlpha-synuclein (ASYN) is central in Parkinson’s disease (PD) pathogenesis. Converging pieces of evidence suggest that the levels of ASYN expression play a critical role in both familial and sporadic Parkinson’s disease. ASYN fibrils are the main component of inclusions called Lewy Bodies (LBs) which are found mainly in the surviving neurons of the substantia nigra. Despite the accumulated knowledge regarding the involvement of ASYN in molecular mechanisms underlying the development of PD, there is much information missing which prevents understanding the causes of the disease and how to stop its progression.ResultsUsing a Systems Biology approach, we develop a biomolecular reactions model that describes the intracellular ASYN dynamics in relation to overexpression, post-translational modification, oligomerization and degradation of the protein. Especially for the proteolysis of ASYN, the model takes into account the biological knowledge regarding the contribution of Chaperone Mediated Autophagy (CMA), macro-autophagic and proteasome pathways in the protein’s degradation. Importantly, inhibitory phenomena, caused by ASYN, concerning CMA (more specifically the lysosomal-associated membrane protein 2a, abbreviated as Lamp2a receptor, which is the rate limiting step of CMA) and the proteasome are carefully modeled. The model is validated by simulation studies of known experimental overexpression data from SH-SY5Y cells and the unknown model parameters are estimated either computationally or by experimental fitting. The calibrated model is then tested under three hypothetical intervention scenarios and in all cases predicts increased cell viability that agrees with experimental evidence. The biomodel has been annotated and is made available in SBML format.ConclusionsThe mathematical model presented here successfully simulates the dynamic phenomena of ASYN overexpression and oligomerization and predicts the biological system’s behavior in a number of scenarios not used for model calibration. It allows, for the first time, to qualitatively estimate the protein levels that are capable of deregulating proteolytic homeostasis. In addition, it can help form new hypotheses for intervention that could be tested experimentally.

Health and Economic Burden of Obesity in Brazil

IntroductionHigher and lower-middle income countries are increasingly affected by obesity. Obesity-related diseases are placing a substantial health and economic burden on Brazil. Our aim is to measure the future consequences of these trends on the associated disease burden and health care costs.MethodA previously developed micro-simulation model is used to project the extent of obesity, obesity-related diseases and associated healthcare costs to 2050. In total, thirteen diseases were considered: coronary heart disease, stroke, hypertension, diabetes, osteoarthritis, and eight cancers. We simulated three hypothetical intervention scenarios: no intervention, 1% and 5% reduction in body mass index (BMI).ResultsIn 2010, nearly 57% of the Brazilian male population was overweight or obese (BMI ≥25 kg/m2), but the model projects rates as high as 95% by 2050. A slightly less pessimistic picture is predicted for females, increasing from 43% in 2010 to 52% in 2050. Coronary heart disease, stroke, hypertension, cancers, osteoarthritis and diabetes prevalence cases are projected to at least double by 2050, reaching nearly 34,000 cases of hypertension by 2050 (per 100,000). 1% and 5% reduction in mean BMI will save over 800 prevalence cases and nearly 3,000 cases of hypertension by 2050 respectively (per 100,000). The health care costs will double from 2010 ($5.8 billion) in 2050 alone ($10.1 billion). Over 40 years costs will reach $330 billion. However, with effective interventions the costs can be reduced to $302 billion by 1% and to $273 billion by 5% reduction in mean BMI across the population.ConclusionObesity rates are rapidly increasing creating a high burden of disease and associated costs. However, an effective intervention to decrease obesity by just 1% will substantially reduce obesity burden and will have a significant effect on health care expenditure.

Mental disorders as risk factors for later substance dependence: estimates of optimal prevention and treatment benefits

Although mental disorders have been shown to predict subsequent substance disorders, it is not known whether substance disorders could be cost-effectively prevented by large-scale interventions aimed at prior mental disorders. Although experimental intervention is the only way to resolve this uncertainty, a logically prior question is whether the associations of mental disorders with subsequent substance disorders are strong enough to justify mounting such an intervention. We investigated this question in this study using simulations to estimate the number of substance disorders that might be prevented under several hypothetical intervention scenarios focused on mental disorders. Data came from the National Comorbidity Survey Replication (NCS-R), a nationally representative US household survey that retrospectively assessed lifetime history and age of onset of DSM-IV mental and substance disorders. Survival analysis using retrospective age-of-onset reports was used to estimate associations of mental disorders with subsequent substance dependence. Simulations based on the models estimated effect sizes in several hypothetical intervention scenarios. Although successful intervention aimed at mental disorders might prevent some proportion of substance dependence, the number of cases of mental disorder that would have to be treated to prevent a single case of substance dependence is estimated to be so high that this would not be a cost-effective way to prevent substance dependence (in the range 76-177 for anxiety-mood disorders and 40-47 for externalizing disorders). Treatment of prior mental disorders would not be a cost-effective way to prevent substance dependence. However, prevention of substance dependence might be considered an important secondary outcome of interventions for early-onset mental disorders.