Dynamic Microsimulation Research Articles

A dynamic microsimulation model for epidemics

A large evidence base demonstrates that the outcomes of COVID-19 and national and local interventions are not distributed equally across different communities. The need to inform policies and mitigation measures aimed at reducing the spread of COVID-19 highlights the need to understand the complex links between our daily activities and COVID-19 transmission that reflect the characteristics of British society. As a result of a partnership between academic and private sector researchers, we introduce a novel data driven modelling framework together with a computationally efficient approach to running complex simulation models of this type. We demonstrate the power and spatial flexibility of the framework to assess the effects of different interventions in a case study where the effects of the first UK national lockdown are estimated for the county of Devon. Here we find that an earlier lockdown is estimated to result in a lower peak in COVID-19 cases and 47% fewer infections overall during the initial COVID-19 outbreak. The framework we outline here will be crucial in gaining a greater understanding of the effects of policy interventions in different areas and within different populations.

A Population Based Regional Dynamic Microsimulation of Germany: The MikroSim Model

Microsimulation models are widely used to evaluate the potential effects of different policies on social indicators. Most microsimulation models in use operate on a national level, disregarding regional variations. We describe the construction of a national microsimulation model for Germany, accounting for local variations in each of the more than 10,000 communities in Germany. The database used and the mechanisms implementing the population dynamics are described. Finally, the further development of the database and microsimulation programs are outlined, which will contribute towards a research lab that will be made available to the wider scientific community.

The future of the elderly population health status: Filling a knowledge gap.

The aging process in OECD countries calls for a better understanding of the future disease prevalence, life expectancy (LE) and patterns of inequalities in health outcomes. In this paper we present the results obtained from several dynamic microsimulation models of the Future Elderly Model family for 12 OECD countries, with the aim of reproducing for the first time comparable long-term projections in individual health status across OECD countries. We provide projections of LE and prevalence of major chronic conditions and disabilities, overall, by gender and by education. We find that the prevalence of main chronic conditions in Europe is catching-up with the United States and significant heterogeneity in the evolution of gender and educational gradients. Our findings represent a contribution to support policymakers in designing and implementing effective interventions in the healthcare sector.

Cost-Effectiveness of Multiple Micronutrients and Balanced-Energy Protein Supplementation During Antenatal Care in India, Pakistan, Mali and Tanzania: A Dynamic Microsimulation

Background: Antenatal energy and micronutrient supplementation can improve birth outcomes and reduce disease burden but no studies have compared their cost-effectiveness. We compared the cost-effectiveness of multiple micronutrient supplementation (MMS), and balanced-energy protein (BEP) with iron and folic acid (IFA) to quantify their benefit in four countries with high prevalence of maternal undernutrition. Methods: Using estimates from the Global Burden of Disease 2017 Study, we simulated birth cohorts for two years in India, Pakistan, Mali, and Tanzania. We compared disability-adjusted life-years (DALYs) and incremental cost-effectiveness ratios (ICERs) in a baseline scenario with existing antenatal IFA coverage with scenarios where 90% of antenatal care attendees receive either MMS, BEP, or targeted-BEP (women with pre-pregnancy BMI <18·5 kg/m2 receive BEP containing MMS while women with BMI ≥18·5 kg/m2 receive MMS). Findings: ICERs for all scenarios were lowest in Pakistan, followed by Mali, India and Tanzania, in line with the baseline trend in attributable burden of low-birthweight. Targeted-BEP averts more DALYs than MMS alone while remaining cost-effective. ICERs for MMS compared to baseline were $9 (95%UI: $5-14) for Pakistan, $13 (95%UI: $7-21) for Mali, $13 (95%UI: $8-20) for India, $44 (95%UI: $20-80) for Tanzania. ICERs for targeted-BEP compared to baseline were $38 (95%UI: 23-54) for Pakistan, $51 (95%UI: 29-80) for Mali, $82 (95%UI: 56-115) for India, and $148 (95%UI: 77-250) for Tanzania. Interpretation: As countries start to invest in replacing IFA with MMS in alignment with recent WHO guidelines, co-implementing targeted-BEP offers a worthwhile and cost-effective strategy that should be considered at the same time to maximise benefits and synergize programme implementation. Funding Statement: Funded by the Bill and Melinda Gates Foundation for this project. Declaration of Interests: ADF has consulted recently for Janssen; SwissRe; Sanofi; Merck for Mothers; and Agathos, Ltd. Other authors have no conflicts of interest to disclose.

Projecting health-ageing trajectories in Europe using a dynamic microsimulation model

The extent of the challenges and opportunities that population ageing presents depends heavily on the population’s health. Hence, for the development of appropriate strategies that enable countries to adopt the emerging demographic and epidemiological realities, information on future health trajectories of elderly population is a natural requirement. This study presents an innovative methodological framework for projecting the health of individuals using a dynamic microsimulation model that considers interactions between sociodemographic characteristics, health, mortality, bio-medical and behavioral risk factors. The model developed, called ATHLOS-Mic, is used to project the health of cohorts born before 1960 for the period 2015–2060 for selected European Countries using SHARE data to illustrate the possible effects of some selected risk factors and education on future health trajectories. Results show that, driven by a better educational attainment, each generation will be healthier than the previous one at same age. Also, we see that, on average, an individual of our base population will live about 18 more years since the start of the projection period, but only 5 years in good health. Finally, we find that a scenario that removes the effect of having a low level of education on individual health has the largest impact on the projected average health, the average number of years lived per person, and the average number of years lived in good health.

The Impact of Health and Education on Labor Force Participation in Aging Societies – Projections for the United States and Germany from a Dynamic Microsimulation

The Impact of Health and Education on Labor Force Participation in Aging Societies – Projections for the United States and Germany from a Dynamic Microsimulation

Developing an Integrated Microsimulation Model for the Impact of Fiscal Policies on Child Health in Europe: The Example of Childhood Obesity in Italy

Background: Welfare policies are generally evaluated for their effects on economic outcomes, and not for their impact on population health. We developed an integrated Microsimulation for Income and Child Health Outcomes (MICHO) model able to forecast the effects of fiscal policies on childhood health in European Countries, and we focused our study on childhood obesity in Italy. Methods: MICHO is based on three integrated modules: M1 simulates the effects of fiscal reforms on disposable household income using the tax-benefit microsimulation program EUROMOD; M2 exploits the data of specific birth cohort studies (the NINFEA birth cohort study for Italy) to estimate the effects of income on child Body Mass Index(BMI) at different ages; and M3 use dynamic microsimulation models to combine the population structure and incomes obtained by M1 with the regression model’s specifications and effect sizes from M2, projecting the simulated distribution of BMI according to different policy scenarios. Findings: Both universal benefits, such as Universal Basic Income (BI), and targeted interventions, such as Child Benefit (CB) for poorer households, have a strong impact on childhood obesity, reaching a Prevalence Ratio (PR) of 0·67 [95%CI: 0·50-0·83] for the simulated BI and 0·64 [95%CI: 0·44-0·84] for CB in 10-years-old children. Focused interventions are also more efficient than universal ones in terms of marginal benefits. Interpretation: A wider use of robust microsimulation models to forecast the effects of fiscal policies on health is desirable, and should be considered as one of the instruments needed to reach the Health in All Policies goals. Funding Statement: European Union’s Horizon 2020 grant No 733206 Declaration of Interests: We declare no competing interests.

IrpetDin. A Dynamic Microsimulation Model for Italy and the Region of Tuscany

IrpetDin. A Dynamic Microsimulation Model for Italy and the Region of Tuscany

The Future of the Elderly Population Health Status: Filling a Knowledge Gap

The ageing process in OECD countries calls for a better understanding of the future disease prevalence, life expectancy and patterns of inequalities in health outcomes. In this paper we present the results obtained from several dynamic microsimulation models of the Future Elderly Model (FEM) family for thirteen OECD countries, with the aim of reproducing for the first time comparable longterm trends in individual health status across OECD. The FEM is a multi-risk multi-morbidity dynamic microsimulation model to project health status and health demand. Given the dynamic structure of the model, we allow individual health status to evolve over time according to individual characteristics. Our model provides forecasts of the evolution of life expectancy and prevalences of major chronic conditions and disabilities, overall, by gender and by education. We find a catch-up of the considered European countries main chronic conditions prevalence with the US and a relevant and persistent educational gradient in the health status of elderly patients. Our findings represent a valid contribution to support policy makers in designing and implementing effective interventions in the healthcare sector.

College Campuses and COVID-19 Mitigation: Clinical and Economic Value.

Colleges in the United States are determining how to operate safely amid the coronavirus disease 2019 (COVID-19) pandemic. To examine the clinical outcomes, cost, and cost-effectiveness of COVID-19 mitigation strategies on college campuses. The Clinical and Economic Analysis of COVID-19 interventions (CEACOV) model, a dynamic microsimulation model, was used to examine alternative mitigation strategies. The CEACOV model tracks infections accrued by students and faculty, accounting for community transmissions. Data from published literature were used to obtain parameters related to COVID-19 and contact-hours. Undergraduate students and faculty at U.S. colleges. One semester (105 days). Modified societal. COVID-19 mitigation strategies, including social distancing, masks, and routine laboratory screening. Infections among students and faculty per 5000 students and per 1000 faculty, isolation days, tests, costs, cost per infection prevented, and cost per quality-adjusted life-year (QALY). Among students, mitigation strategies reduced COVID-19 cases from 3746 with no mitigation to 493 with extensive social distancing and masks, and further to 151 when laboratory testing was added among asymptomatic persons every 3 days. Among faculty, these values were 164, 28, and 25 cases, respectively. Costs ranged from about $0.4 million for minimal social distancing to about $0.9 million to $2.1 million for strategies involving laboratory testing ($10 per test), depending on testing frequency. Extensive social distancing with masks cost $170 per infection prevented ($49 200 per QALY) compared with masks alone. Adding routine laboratory testing increased cost per infection prevented to between $2010 and $17 210 (cost per QALY gained, $811 400 to $2 804 600). Results were most sensitive to test costs. Data are from multiple sources. Extensive social distancing with a mandatory mask-wearing policy can prevent most COVID-19 cases on college campuses and is very cost-effective. Routine laboratory testing would prevent 96% of infections and require low-cost tests to be economically attractive. National Institutes of Health.

Disability and Long-Term Care in Singapore

Public systems for long term care (LTC) redistribute resources between generations. Population aging is one of the most significant transformations in the 21st century, where the number of older persons aged 60 years and above is expected to double by 2050, rising to 2.1 billion. We used the Future Elderly Model (FEM) to project the impact of population aging in Singapore up to the year 2050. The FEM is a dynamic economic and demographic microsimulation model. By 2050, the total number of older adults with potential limitation in activities of daily living (ADL) was projected to increase to 275 thousand (18.9%). With the increasing prevalence of disability and chronic diseases, older adults might not have sufficient savings to meet future needs sustainably, despite the expansion of disability insurance from ElderShield to CareShield Life. Lessons and best practices for LTC could be transferred from our experiences to other aging cities globally. Part of a symposium sponsored by International Comparisons of Healthy Aging Interest Group.

PDB39 Assessing the IMPACT of New ANTI Diabetics Drugs: A Dynamic Microsimulation Approach

Assess the impact of SGLT-2i and DPP-4i type drugs on mortality and cardiovascular diseases. In this study a cohort of 63,812 diabetic Italians in 2016, drawn from the Health Search database of general practitioners, was studied to assess the impact of a greater diffusion of new anti-diabetes drugs (SGLT-2i or DPP-4i), in terms of mortality, incidence of cardiovascular diseases and costs, using the dynamic Italian micro-simulation model Future Italian Model.The use of modern dynamic micro-simulation techniques allowed us to model the individual transitions to cardiovascular diseases (angina, heart attack, stroke, ischemic heart disease, heart failure and hypertension), death and drug therapies. Furthermore, we were able to construct policy relevant “what-if'' scenarios about the usage of the new anti-diabetes drugs, building on the effects reported by the relevant literature. Preliminary results indicate that an increase in the prevalence of Dual therapy with SGLT-2i or DPP-4i would have positive effects in terms of reducing the prevalence of cardiovascular events, the number of deaths and the total costs associated with diabetes. Being a cohort of elderly patients (the average age is 71), the greatest benefits in terms of reduced mortality and increased life expectancy at 65 are concentrated between 2017 and 2020, when up to 3 months of life expectancy at 65 could be gained. An increase in the share of Dual therapy with SGLT2 or Dpp-4 up to 80% of all dual therapies, albeit associated with higher pharmaceutical expenditure, could induce up to 100,000 fewer deaths by 2035 compared to the baseline scenario and it would lead to savings of almost € 4 billion.

Modelling foreign labour inflows using a dynamic microsimulation model of an ageing country - Slovakia

Modelling foreign labour inflows using a dynamic microsimulation model of an ageing country - Slovakia

A generic business process model for conducting microsimulation studies

Abstract Microsimulations make use of quantitative methods to analyze complex phenomena in populations. They allow modeling socioeconomic systems based on micro-level units such as individuals, households, or institutional entities. However, conducting a microsimulation study can be challenging. It often requires the choice of appropriate data sources, micro-level modeling of multivariate processes, and the sound analysis of their outcomes. These work stages have to be conducted carefully to obtain reliable results. We present a generic business process model for conducting microsimulation studies based on an international statistics process model. This simplifies the comprehensive understanding of dynamic microsimulation models. A nine-step procedure that covers all relevant work stages from data selection to output analysis is presented. Further, we address technical problems that typically occur in the process and provide sketches as well as references of solutions.

Estimation of regional transition probabilities for spatial dynamic microsimulations from survey data lacking in regional detail

Spatial dynamic microsimulations allow for the multivariate analysis of complex systems with geographic segmentation. A synthetic replica of the system is stochastically projected into future periods using micro-level transition probabilities. These should accurately represent the dynamics of the system to allow for reliable simulation outcomes. In practice, transition probabilities are unknown and must be estimated from suitable survey data. This can be challenging when the dynamics vary locally. Survey data often lacks in regional detail due to confidentiality restrictions and limited sampling resources. In that case, transition probability estimates may misrepresent regional dynamics due to insufficient local observations and coverage problems. The simulation process subsequently fails to provide an authentic evolution of the system. A constrained maximum likelihood approach for probability alignment to solve these issues is proposed. It accounts for regional heterogeneity in transition dynamics through the consideration of external benchmarks from administrative records. It is proven that the method is consistent. A parametric bootstrap for uncertainty estimation is presented. Simulation experiments are conducted to compare the approach with an existing method for probability alignment. Furthermore, an empirical application to labor force estimation based on the German Microcensus is provided.

Lifetime Burden of Adult Congenital Heart Disease in the USA Using a Microsimulation Model.

Congenital heart defects (CHD) represent a growing burden of illness among adults. We estimated the lifetime health, education, labor, and social outcomes of adults with CHD in the USA using the Future Adult Model, a dynamic microsimulation model that has been used to study the lifetime impacts of a variety of chronic diseases. We simulated a cohort of adult heads of households > 25years old derived from the Panel Survey of Income Dynamics who reported a childhood heart problem as a proxy for CHD and calculated life expectancy, disability-free and quality-adjusted life years, lifetime earnings, education attainment, employment, development of chronic disease, medical spending, and disability insurance claiming status. Total burden of disease was estimated by comparing to a healthy cohort with no childhood heart problem. Eighty-seven individuals reporting a childhood heart problem were identified from the PSID and were used to generate the synthetic cohort simulated in the model. Life expectancy, disability-free, quality-adjusted, and discounted quality-adjusted life years were an average 4.6, 6.7, 5.3, and 1.4years lower than in healthy adults. Lung disease, cancer, and severe mental distress were more common compared to healthy individuals. The CHD cohort earned $237,800 less in lifetime earnings and incurred higher average total medical spend by $66,600 compared to healthy individuals. Compared to healthy adults, the total burden of CHD is over $500K per adult. Despite being among the healthiest adults with CHD, there are significant decrements in life expectancy, employment, and lifetime earnings, with concomitant increases in medical spend.

Cameroon’s Bilateral Economic Partnership Agreement: A Microsimulation Approach

This article studies the impact of the bilateral economic partnership agreement between Cameroon and the European Union on microeconomic indicators including poverty and inequality. The analyses are based on a dynamic microsimulation model on which the scenario of the complete cancellation of customs tariffs on imports of the EU origin products is applied. This is based on a social accounting matrix that we have implemented for 2016 and the ECAM 4 household data survey collected in 2014. The results show that: The Cameroon’s EPA on the macroeconomic aspect leads to an increase of imports against a decrease of exports and production; the increasing of imports is going through a decreasing of market price for domestic market against an increase of imported price. This leads to an elevation of the exchange rate and then discourages the imports of agricultural products; contrary, there is a decreasing of industrial price for imported products on domestic market. This break the local industries efforts since their indirect taxes are increasing. There are also GDP loses of about 0.14% per year. On the microeconomic aspect, it undermines and even exacerbates poverty reduction efforts through indicators of incidence, depth and severity of poverty. This impact increases from 2016 to 2040, period of our simulations, and is more pronounced in rural than in urban areas. For inequality, our results show that the agreement leads to an increase in inequalities ranging from 0.43 to 0.46 during the period 2016-2023. However, the impact is vanished between the period 2033-2040.

Dynamic microsimulation modelling of potential pension reforms in North Macedonia

AbstractDue to structural and policy shifts, pension deficit in North Macedonia doubled over a decade and significantly outpaced the central budget deficit. The objective of the paper is to examine fiscal and development effects of few pension-reform designs. We constructed MK-PENS Dynamic Microsimulation Pension Model and simulated the effects of few reforms affecting one stakeholder and few combined reforms. Results robustly suggest that without reform and assuming only statutory pension adjustment, the deficit will remain as is. Simulated scenarios suggest that proposed pension reforms significantly reduce the pension deficit, with the most favourable results obtained within the combined scenarios of shared burden. Gradual introduction of reform's elements should come into play in case large political cost is envisaged.

The COVID-19 Resilience of a Continental Welfare Regime - Nowcasting the Distributional Impact of the Crisis

We evaluate the COVID-19 resilience of a Continental welfare regime by nowcasting the implications of the shock and its associated policy responses on the distribution of household incomes. Our approach relies on a dynamic microsimulation approach that combines a household income generation model estimated on the latest EU-SILC wave with novel nowcasting techniques to calibrate the simulations using external macro controls reflecting the macroeconomic climate during the crisis. We focus on Luxembourg, a country that introduced minor tweaks to the existing tax-benefit system which already contained instruments with a strong social insurance focus that gave certainty during the crisis. The income-support policy changes were effective in cushioning household incomes and mitigating an increase in income inequality in the early stages of the pandemic. The share of labour incomes dropped, but was compensated by an increase in benefits, reflecting the cushioning effect of the transfer system.Overall market incomes dropped and became more unequal. Their disequalizing evolution was, however, overpowered by an increase in tax-benefit redistribution. Net redistribution increased, driven by an increase in the generosity of benefits and larger access to benefits.These changes are mainly explained by the labour market shock, signalling the automatic stabilizers embedded in the pre-COVID system. The system was well-equipped ahead of the crisis to cushion household incomes against job losses. The methodology is scalable to other countries and well-designed to explore the impact of later stages in the COVID crisis, both economy-wide and sector-specific. The model is a real-time analysis and decision support tool to monitor the recovery, with high applicability for policymakers.

Projections of care for older people with dementia in England: 2015 to 2040.

BackgroundThe number of older people with dementia and the cost of caring for them, already substantial, are expected to rise due to population ageing.ObjectiveThis study makes projections of the number of older people with dementia receiving unpaid care or using care services and associated costs in England.MethodsThe study drew on up-to-date information for England from multiple sources including data from the CFASII study, output from the PACSim dynamic microsimulation model, Office for National Statistics population projections and data from the MODEM cohort study. A simulation model was built to make the projections.ResultsWe project that the number of older people with dementia will more than double in the next 25 years. The number receiving unpaid or formal care is projected to rise by 124%, from 530,000 in 2015 to 1,183,000 in 2040. Total cost of dementia is projected to increase from £23.0 billion in 2015 to £80.1 billion in 2040, and average cost is projected to increase from £35,100 per person per year in 2015 to £58,900 per person per year in 2040. Total and average costs of social care are projected to increase much faster than those of healthcare and unpaid care.ConclusionThe numbers of people with dementia and associated costs of care will rise substantially in the coming decades, unless new treatments enable the progression of the condition to be prevented or slowed. Care and support for people with dementia and their family carers will need to be increased.