Sequential Multiple Assignment Randomized Trial (SMART) to identify optimal sequences of telemedicine interventions for improving initiation of insulin therapy: A simulation study.

BACKGROUND: To examine the value of a Sequential Multiple Assignment Randomized Trial (SMART) design compared to a conventional randomized control trial (RCT) for telemedicine strategies to support titration of insulin therapy for Type 2 Diabetes Mellitus (T2DM) patients new to insulin. METHODS: Microsimulation models were created in R using a synthetic sample based on primary data from 63 subjects enrolled in a pilot study of a smartphone application (App), Diabetes Pal compared to a nurse-based telemedicine strategy (Nurse). For comparability, the SMART and an RCT design were constructed to allow comparison of four (embedded) adaptive interventions (AIs). RESULTS: In the base case scenario, the SMART has similar overall mean expected HbA1c and cost per subject compared with RCT, for sample size of n = 100 over 10,000 simulations. SMART has lower (better) standard deviations of the mean expected HbA1c per AI, and higher efficiency of choosing the correct AI across various sample sizes. The differences between SMART and RCT become apparent as sample size decreases. For both trial designs, the threshold value at which a subject was deemed to have been responsive at an intermediate point in the trial had an optimal choice (i.e., the sensitivity curve had a U-shape). SMART design dominates the RCT, in the overall mean HbA1c (lower value) when the threshold value is close to optimal. CONCLUSIONS: SMART is suited to evaluating the efficacy of different sequences of treatment options, in addition to the advantage of providing information on optimal treatment sequences.

Trends in functional disability and cognitive impairment among the older adult in China up to 2060: estimates from a dynamic multi-state population model.

BACKGROUND: Available evidence suggests that cognitive impairment (CI), which leads to deficits in episodic memory, executive functions, visual attention, and language, is associated with difficulties in the capacity to perform activities of daily living. Hence any forecast of the future prevalence of functional disability should account for the likely impact of cognitive impairment on the onset of functional disability. Thus, this research aims to address this gap in literature by projecting the number of older adults in China with functional disability and cognitive impairment while accounting for the impact of cognitive impairment on the onset of functional disability. METHODS: We developed and validated a dynamic multi-state population model which simulates the population of China and tracks the transition of Chinese older adults (65 years and older) from 2010 to 2060, to and from six health states-(i) active older adults without cognitive impairment, (ii) active older adults with cognitive impairment, (iii) older adults with 1 to 2 ADL limitations, (iv) older adults with cognitive impairment and 1 to 2 ADL limitations, (v) older adults with 3 or more ADL limitations, and (vi) older adults with cognitive impairment and 3 or more ADL limitations. RESULTS: From 2015 to 2060, the number of older adults 65 years and older in China is projected to increase, of which the number with impairment (herein referred to as individuals with cognitive impairment and/or activity of daily living limitations) is projected to increase more than fourfold from 17·9 million (17·8-18·0) million in 2015 to 96·2 (95·3-97·1) million by 2060. Among the older adults with impairment, those with ADL limitations only is projected to increase from 3·7 million (3·6-3·7 million) in 2015 to 23·9 million (23·4-24·6 million) by 2060, with an estimated annual increase of 12·2% (12·1-12·3); while that for cognitive impairment only is estimated to increase from 11·4 million (11·3-11·5 million) in 2015 to 47·8 million (47·5-48·2 million) by 2060-this representing an annual growth of 7·07% (7·05-7·09). CONCLUSION: Our findings suggest there will be an increase in demand for intermediate and long-term care services among the older adults with functional disability and cognitive impairment.

Systems modelling as an approach for understanding and building consensus on non-communicable diseases (NCD) management in Cambodia.

BACKGROUND: This paper aims to demonstrate how systems modeling methodology of Group Model Building (GMD) can be applied for exploring and reaching consensus on non-communicable disease (NCD) management. This exercise was undertaken as a first step for developing a quantitative simulation model for generating credible estimates to make an investment case for the prevention and management of NCDs. METHODS: Stakeholder engagement was facilitated through the use of a Group Model Building (GMB) approach. This approach combines various techniques in order to gain a whole system perspective. RESULTS: A conceptual qualitative model framework that connects prevention-via risk factors reduction-screening and treatment of non-communicable diseases (NCDs) was developed with stakeholders that draws on stakeholders personal experiences, beliefs, and perceptions through a moderated interactions to gain in-depth understanding of NCDs management. CONCLUSION: Managing NCDs in Cambodia will require concerted effort to tackle NCD risk factors, identifying individuals with NCDs through screening and providing adequate and affordable consistent care to improve health and outcomes of NCDs.

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.

Future requirements for and supply of ophthalmologists for an aging population in Singapore.

BACKGROUND: Singapore's population, as that of many other countries, is aging; this is likely to lead to an increase in eye diseases and the demand for eye care. Since ophthalmologist training is long and expensive, early planning is essential. This paper forecasts workforce and training requirements for Singapore up to the year 2040 under several plausible future scenarios. METHODS: The Singapore Eye Care Workforce Model was created as a continuous time compartment model with explicit workforce stocks using system dynamics. The model has three modules: prevalence of eye disease, demand, and workforce requirements. The model is used to simulate the prevalence of eye diseases, patient visits, and workforce requirements for the public sector under different scenarios in order to determine training requirements. RESULTS: Four scenarios were constructed. Under the baseline business-as-usual scenario, the required number of ophthalmologists is projected to increase by 117% from 2015 to 2040. Under the current policy scenario (assuming an increase of service uptake due to increased awareness, availability, and accessibility of eye care services), the increase will be 175%, while under the new model of care scenario (considering the additional effect of providing some services by non-ophthalmologists) the increase will only be 150%. The moderated workload scenario (assuming in addition a reduction of the clinical workload) projects an increase in the required number of ophthalmologists of 192% by 2040. Considering the uncertainties in the projected demand for eye care services, under the business-as-usual scenario, a residency intake of 8-22 residents per year is required, 17-21 under the current policy scenario, 14-18 under the new model of care scenario, and, under the moderated workload scenario, an intake of 18-23 residents per year is required. CONCLUSIONS: The results show that under all scenarios considered, Singapore's aging and growing population will result in an almost doubling of the number of Singaporeans with eye conditions, a significant increase in public sector eye care demand and, consequently, a greater requirement for ophthalmologists.

Projecting the burden of dental caries and periodontal diseases among the adult population in the United Kingdom using a multi-state population model.

Objectives: With the aging United Kingdom population, oral diseases are expected to increase. Exploring credible projections is fundamental to understanding the likely impact of emerging population-level interventions on oral disease burden. This study aims at providing a credible, evidence-based projection of the adult population in the United Kingdom with dental caries and periodontal diseases. Methods: We developed a multi-state population model using system dynamics that disaggregates the adult population in the United Kingdom into different oral health states. The caries population was divided into three states: no caries, treated caries, and untreated caries. The periodontal disease population was disaggregated into no periodontal disease, pocketing between 4 and < 6 mm, 6 and < 9 mm, and 9 mm or more. Data from the 2009 dental health survey in the United Kingdom was used to estimate age and gender-specific prevalence rates as input to the multi-state population model. Results: Of the population 16 years and older, the number with carious teeth is projected to decrease from 15.742 million in the year 2020 to 15.504 million by the year 2050, representing a decrease of 1.5%. For individuals with carious teeth, the older adult population is estimated to constitute 62.06% by 2050 and is projected to increase 89.4% from 5.079 million in 2020 to 9.623 million by 2050. The adult population with periodontal pocketing is estimated to increase from 25.751 million in 2020 to 27.980 million by 2050, while those with periodontal loss of attachment are projected to increase from 18.667 million in 2020 to 20.898 million by 2050. The burden of carious teeth and periodontal diseases is anticipated to shift from the adult population (16-59 years) to the older adult population. The older adult population with carious teeth is estimated to rise from 32.26% in 2020 to 62.06% by 2050, while that for periodontal disease is expected to increase from 42.44% in 2020 to 54.57% by 2050. Conclusion: This model provides evidence-based plausible future demand for oral health conditions, allowing policymakers to plan for oral health capacity to address growing needs. Because of the significant delay involved in educating and training oral health personnel, such projections offer policymakers the opportunity to be proactive in planning for future capacity needs instead of being reactive.

Projecting the chronic disease burden among the adult population in the United States using a multi-state population model.

Introduction: As the United States population ages, the adult population with chronic diseases is expected to increase. Exploring credible, evidence-based projections of the future burden of chronic diseases is fundamental to understanding the likely impact of established and emerging interventions on the incidence and prevalence of chronic disease. Projections of chronic disease often involve cross-sectional data that fails to account for the transition of individuals across different health states. Thus, this research aims to address this gap by projecting the number of adult Americans with chronic disease based on empirically estimated age, gender, and race-specific transition rates across predetermined health states. Methods: We developed a multi-state population model that disaggregates the adult population in the United States into three health states, i.e., (a) healthy, (b) one chronic condition, and (c) multimorbidity. Data from the 1998 to 2018 Health and Retirement Study was used to estimate age, gender, and race-specific transition rates across the three health states, as input to the multi-state population model to project future chronic disease burden. Results: The number of people in the United States aged 50 years and older will increase by 61.11% from 137.25 million in 2020 to 221.13 million in 2050. Of the population 50 years and older, the number with at least one chronic disease is estimated to increase by 99.5% from 71.522 million in 2020 to 142.66 million by 2050. At the same time, those with multimorbidity are projected to increase 91.16% from 7.8304 million in 2020 to 14.968 million in 2050. By race by 2050, 64.6% of non-Hispanic whites will likely have one or more chronic conditions, while for non-Hispanic black, 61.47%, and Hispanic and other races 64.5%. Conclusion: The evidence-based projections provide the foundation for policymakers to explore the impact of interventions on targeted population groups and plan for the health workforce required to provide adequate care for current and future individuals with chronic diseases.

The effectiveness of public health interventions against COVID-19: Lessons from the Singapore experience.

BACKGROUND: In dealing with community spread of COVID-19, two active interventions have been attempted or advocated-containment, and mitigation. Given the extensive impact of COVID-19 globally, there is international interest to learn from best practices that have been shown to work in controlling community spread to inform future outbreaks. This study explores the trajectory of COVID-19 infection in Singapore had the government intervention not focused on containment, but rather on mitigation. In addition, we estimate the actual COVID-19 infection cases in Singapore, given that confirmed cases are publicly available. METHODS AND FINDINGS: We developed a COVID-19 infection model, which is a modified SIR model that differentiate between detected (diagnosed) and undetected (undiagnosed) individuals and segments total population into seven health states: susceptible (S), infected asymptomatic undiagnosed (A), infected asymptomatic diagnosed (I), infected symptomatic undiagnosed (U), infected symptomatic diagnosed (E), recovered (R), and dead (D). To account for the infection stages of the asymptomatic and symptomatic infected individuals, the asymptomatic infected individuals were further disaggregated into three infection stages: (a) latent (b) infectious and (c) non-infectious; while the symptomatic infected were disaggregated into two stages: (a) infectious and (b) non-infectious. The simulation result shows that by the end of the current epidemic cycle without considering the possibility of a second wave, under the containment intervention implemented in Singapore, the confirmed number of Singaporeans infected with COVID-19 (diagnosed asymptomatic and symptomatic cases) is projected to be 52,053 (with 95% confidence range of 49,370-54,735) representing 0.87% (0.83%-0.92%) of the total population; while the actual number of Singaporeans infected with COVID-19 (diagnosed and undiagnosed asymptomatic and symptomatic infected cases) is projected to be 86,041 (81,097-90,986), which is 1.65 times the confirmed cases and represents 1.45% (1.36%-1.53%) of the total population. A peak in infected cases is projected to have occurred on around day 125 (27/05/2020) for the confirmed infected cases and around day 115 (17/05/2020) for the actual infected cases. The number of deaths is estimated to be 37 (34-39) among those infected with COVID-19 by the end of the epidemic cycle; consequently, the perceived case fatality rate is projected to be 0.07%, while the actual case fatality rate is estimated to be 0.043%. Importantly, our simulation model results suggest that there about 65% more COVID-19 infection cases in Singapore that have not been captured in the official reported numbers which could be uncovered via a serological study. Compared to the containment intervention, a mitigation intervention would have resulted in early peak infection, and increase both the cumulative confirmed and actual infection cases and deaths. CONCLUSION: Early public health measures in the context of targeted, aggressive containment including swift and effective contact tracing and quarantine, was likely responsible for suppressing the number of COVID-19 infections in Singapore.

Modelling solid waste management solutions: The case of Campania, Italy.

The waste crisis in Campania has inspired a huge body of literature that has described its complex nature. Quantitative analysis in this regard provides useful insight into single aspects of the problem but from a static perspective. In this work, a dynamic model has been developed to analyse the interactions between the main elements of the waste system in Campania and their evolution over the critical time horizon. The model considers the process of capacity construction that has been developed to deal with the crisis and the flow of waste through the treatment options available, showing how the waste system behaves if such infrastructures are not able to cope with the amounts expected. The model also provides the analytical framework to explore the effects of alternative waste policies.

Trajectories of functional ability over the life course: a conceptual model of the interaction of stressor-induced functional loss and resilience.

Understanding the factors that influence functional ability over the life course is integral to identifying clinical and public health policies to facilitate successful aging. The World Health Organization has advocated a conceptual framework to clarify the policy discussion. We have sought to translate this general framework into an explicit system dynamics model of the interaction of physiological loss, stressors and endogenous responses to produce a familiar variety of trajectories of functional ability over the life courses. Simulation experiments were implemented for both a 30-month duration with only one major stressor; and for the life course with an initial major stressor and subsequent stressors determined by the level of functional ability. For both contexts, variations in the few parameters in the scenarios led to a realistic range of trajectories of function over time.

Projection of Eye Disease Burden in Singapore.

INTRODUCTION: Singapore's ageing population is likely to see an increase in chronic eye conditions in the future. This study aimed to estimate the burden of eye diseases among resident Singaporeans stratified for age and ethnicity by 2040. MATERIALS AND METHODS: Prevalence data on myopia, epiretinal membrane (ERM), retinal vein occlusion (RVO), age macular degeneration (AMD), diabetic retinopathy (DR), cataract, glaucoma and refractive error (RE) by age cohorts and educational attainment from the Singapore Epidemiology of Eye Diseases (SEED) study were applied to population estimates from the Singapore population model. RESULTS: All eye conditions are projected to increase by 2040. Myopia and RE will remain the most prevalent condition, at 2.393 million (2.32 to 2.41 million) cases, representing a 58% increase from 2015. It is followed by cataract and ERM, with 1.33 million (1.31 to 1.35 million), representing an 81% increase, and 0.54 million (0.53 to 0.549 million) cases representing a 97% increase, respectively. Eye conditions that will see the greatest increase from 2015 to 2040 in the Chinese are: DR (112%), glaucoma (100%) and ERM (91.4%). For Malays, DR (154%), ERM (136%), and cataract (122%) cases are expected to increase the most while for Indians, ERM (112%), AMD (101%), and cataract (87%) are estimated to increase the most in the same period. CONCLUSION: Results indicate that the burden for all eye diseases is expected to increase significantly into the future, but at different rates. These projections can facilitate the planning efforts of both policymakers and healthcare providers in the development and provision of infrastructure and resources to adequately meet the eye care needs of the population. By stratifying for age and ethnicity, high risk groups may be identified and targeted interventions may be implemented.

Emergency department crowding in Singapore: Insights from a systems thinking approach.

OBJECTIVES: Emergency Department crowding is a serious and international health care problem that seems to be resistant to most well intended but often reductionist policy approaches. In this study, we examine Emergency Department crowding in Singapore from a systems thinking perspective using causal loop diagramming to visualize the systemic structure underlying this complex phenomenon. Furthermore, we evaluate the relative impact of three different policies in reducing Emergency Department crowding in Singapore: introduction of geriatric emergency medicine, expansion of emergency medicine training, and implementation of enhanced primary care. METHODS: The construction of the qualitative causal loop diagram is based on consultations with Emergency Department experts, direct observation, and a thorough literature review. For the purpose of policy analysis, a novel approach, the path analysis, is applied. RESULTS: The path analysis revealed that both the introduction of geriatric emergency medicine and the expansion of emergency medicine training may be associated with undesirable consequences contributing to Emergency Department crowding. In contrast, enhancing primary care was found to be germane in reducing Emergency Department crowding; in addition, it has apparently no negative side effects, considering the boundary of the model created. CONCLUSION: Causal loop diagramming was a powerful tool for eliciting the systemic structure of Emergency Department crowding in Singapore. Additionally, the developed model was valuable in testing different policy options.

Projection of young-old and old-old with functional disability: does accounting for the changing educational composition of the elderly population make a difference?

This study compares projections, up to year 2040, of young-old (aged 60-79) and old-old (aged 80+) with functional disability in Singapore with and without accounting for the changing educational composition of the Singaporean elderly. Two multi-state population models, with and without accounting for educational composition respectively, were developed, parameterized with age-gender-(education)-specific transition probabilities (between active, functional disability and death states) estimated from two waves (2009 and 2011) of a nationally representative survey of community-dwelling Singaporeans aged ≥ 60 years (N=4,990). Probabilistic sensitivity analysis with the bootstrap method was used to obtain the 95% confidence interval of the transition probabilities. Not accounting for educational composition overestimated the young-old with functional disability by 65 percent and underestimated the old-old by 20 percent in 2040. Accounting for educational composition, the proportion of old-old with functional disability increased from 40.8 percent in 2000 to 64.4 percent by 2040; not accounting for educational composition, the proportion in 2040 was 49.4 percent. Since the health profiles, and hence care needs, of the old-old differ from those of the young-old, health care service utilization and expenditure and the demand for formal and informal caregiving will be affected, impacting health and long-term care policy.

Implications of long-term care capacity response policies for an aging population: a simulation analysis.

INTRODUCTION: The demand for long-term care (LTC) services is likely to increase as a population ages. Keeping pace with rising demand for LTC poses a key challenge for health systems and policymakers, who may be slow to scale up capacity. Given that Singapore is likely to face increasing demand for both acute and LTC services, this paper examines the dynamic impact of different LTC capacity response policies, which differ in the amount of time over which LTC capacity is increased, on acute care utilization and the demand for LTC and acute care professionals. METHODS: The modeling methodology of System Dynamics (SD) was applied to create a simplified, aggregate, computer simulation model for policy exploration. This model stimulates the interaction between persons with LTC needs (i.e., elderly individuals aged 65 years and older who have functional limitations that require human assistance) and the capacity of the healthcare system (i.e., acute and LTC services, including community-based and institutional care) to provide care. Because the model is intended for policy exploration, stylized numbers were used as model inputs. To discern policy effects, the model was initialized in a steady state. The steady state was disturbed by doubling the number of people needing LTC over the 30-year simulation time. Under this demand change scenario, the effects of various LTC capacity response policies were studied and sensitivity analyses were performed. RESULTS: Compared to proactive and quick adjustment LTC capacity response policies, slower adjustment LTC capacity response policies (i.e., those for which the time to change LTC capacity is longer) tend to shift care demands to the acute care sector and increase total care needs. CONCLUSIONS: Greater attention to demand in the acute care sector relative to demand for LTC may result in over-building acute care facilities and filling them with individuals whose needs are better suited for LTC. Policymakers must be equally proactive in expanding LTC capacity, lest unsustainable acute care utilization and significant deficits in the number of healthcare professionals arise. Delaying LTC expansion could, for example, lead to increased healthcare expenditure and longer wait lists for LTC and acute care patients.

Simulating the impact of long-term care policy on family eldercare hours.

OBJECTIVE: To understand the effect of current and future long-term care (LTC) policies on family eldercare hours for older adults (60 years of age and older) in Singapore. DATA SOURCES: The Social Isolation Health and Lifestyles Survey, the Survey on Informal Caregiving, and the Singapore Government's Ministry of Health and Department of Statistics. STUDY DESIGN: An LTC Model was created using system dynamics methodology and parameterized using available reports and data as well as informal consultation with LTC experts. PRINCIPAL FINDINGS: In the absence of policy change, among the elderly living at home with limitations in their activities of daily living (ADLs), the proportion of those with greater ADL limitations will increase. In addition, by 2030, average family eldercare hours per week are projected to increase by 41 percent from 29 to 41 hours. All policy levers considered would moderate or significantly reduce family eldercare hours. CONCLUSION: System dynamics modeling was useful in providing policy makers with an overview of the levers available to them and in demonstrating the interdependence of policies and system components.