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Systems
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System Dynamics Modeling and Simulation for Public Health
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System Dynamics Modeling and Simulation for Public Health

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Theory and Methodology".

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 13625

Special Issue Editor

Dr. Karim J. Chichakly

E-Mail Website
Guest Editor
1. ISEE Systems, Inc., 31 Old Etna Road, Suite 7N, Lebanon, NH 03766, USA
2. Social Science and Policy Studies Department, Worcester Polytechnic Institute, 100 Institute Rd., Worcester, MA 01609, USA
Interests: business strategy; project management; health care; public policy; the environment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

System Dynamics (SD) modeling is a well-established method for addressing public health issues, for example, controlling the spread and harm of epidemics (such as COVID-19). Because SD can model people’s behavior, as well as larger societal forces, it is often more effective than other methods at finding lasting solutions to persistent problems.

This Special Issue invites the submission of papers that examine public health policy issues using stock-flow models that can simulate system behavior and test various interventions to improve health outcomes in a subject population. If possible, these models should be calibrated to real-world data; however, in all cases, they should use parameters derived from established peer-reviewed research and/or subject-matter experts. Novel methods for improving the quality of their results are welcome.

Examinations of any public health issue are acceptable. While not an exhaustive list, possible topics include the following:

  • The spread and control of epidemics;
  • Chronic disease;
  • Cancer;
  • Addiction;
  • Mental health;
  • Suicide prevention;
  • Population health;
  • Health care capacity and delivery;
  • Inequality in health care.

Papers should clearly and concisely describe the issue being addressed, the approach taken, the feedback structure of the model, all policies explored, and the simulation results.

Dr. Karim J. Chichakly
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • system dynamics
  • public health systems
  • thinking disease management
  • population health
  • health care

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Published Papers (6 papers)

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Research

33 pages, 4124 KB  
Article
Reimagining Commercial Health Insurance in India: A System-Dynamics Approach to Complex Stakeholder Incentives and Policy Outcomes
by Nachiket Mor, Aakriti Gupta and Rahul Roy
Systems 2025, 13(12), 1104; https://doi.org/10.3390/systems13121104 - 8 Dec 2025
Viewed by 956
Abstract
Most low- and middle-income governments are unwilling and unable to adequately fund their health systems using tax resources. Despite this route’s popularity in public discourse, it is neither a feasible nor a desirable route for financing Universal Health Coverage (UHC), given competing public [...] Read more.
Most low- and middle-income governments are unwilling and unable to adequately fund their health systems using tax resources. Despite this route’s popularity in public discourse, it is neither a feasible nor a desirable route for financing Universal Health Coverage (UHC), given competing public finance priorities and limited citizen demand, among other challenges. It thus becomes essential to study the underlying mechanisms behind commercial health insurance and offer citizens the best possible product, which ensures that they not only receive a high degree of protection from health and financial risk on a sustained basis but also find reasonable access and support to improve their health outcomes. In this paper, we build a system-dynamics model that simulates the aggregate behavior of the Indian health-insurance industry, with interacting feedbacks between decisions by stakeholders such as the insurer, healthy and chronically ill populations, and the regulator to outcomes like insurance penetration among segments, overall coverage, health status over the long run, a mechanism of market-discovered premium, and financial viability of the private insurer. We then investigate policy choices and scenarios to explore contrast between design choices and ideal or targeted states of this market, such as a market with 100% enrollment, risk selection by insurers, group insurance models, and managed care, and study the impact on our outcomes of interest, i.e., insurance penetration and pricing, the financial sustainability of the insurers, and the population’s health outcomes. The simulations show that even while insurers and the different population segments optimize for their respective near-term objectives, the best outcomes for all come from the managed-care policy option, which has greater insurance penetration, lower premiums, higher profitability for insurers, and better long-term health outcomes. All other choices and scenarios yield suboptimal, imbalanced systemic outcomes. We thus recommend managed care as a desirable policy alternative for low-income countries intending to improve UHC by leveraging commercial health insurance. Full article
(This article belongs to the Special Issue System Dynamics Modeling and Simulation for Public Health)
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23 pages, 3005 KB  
Article
Wastewater Infrastructure as a Public Health Tool: Agent-Based Modeling of Surveillance Strategies in a COVID-19 Context
by Lin Xiang, James W. Keck, James Gallimore, Amirmohammad Sakhaei, Elizabeth Loh and Scott M. Berry
Systems 2025, 13(12), 1093; https://doi.org/10.3390/systems13121093 - 3 Dec 2025
Cited by 1 | Viewed by 634
Abstract
Wastewater-based epidemiology (WBE) played a vital role during the COVID-19 pandemic by providing early warnings of outbreaks through SARS-CoV-2 RNA detection in sewage. Many rural communities did not benefit from WBE because limited centralized sewer infrastructure challenged conventional WBE surveillance strategies. We present [...] Read more.
Wastewater-based epidemiology (WBE) played a vital role during the COVID-19 pandemic by providing early warnings of outbreaks through SARS-CoV-2 RNA detection in sewage. Many rural communities did not benefit from WBE because limited centralized sewer infrastructure challenged conventional WBE surveillance strategies. We present a multi-agent computer model simulating COVID-19 spread in a U.S. county with both sewered and non-sewered zones to assess the performance of WBE in this setting. We evaluate how the sewage service status of the first SARS-CoV-2 carrier, cross-zone community mobility, and WBE detection thresholds influence outbreak detection timing at the county’s wastewater treatment plant under basic reproduction numbers (R0) of 4 and 8. Our key findings include that (1) a detection threshold of 10 gc/mL can identify outbreaks up to six days earlier than a threshold of 50 gc/mL; (2) outbreaks originating in non-sewered zones are detected 1–2 days later, compared with outbreaks in sewered zones; and (3) cross-zone community mobility impacts detection timing only when outbreaks begin in non-sewered zones. Furthermore, once detected, disease prevalence can increase by five- to eleven-fold within the following week. These results underscore the importance of WBE sensitivity and tailored surveillance strategies in both sewered and non-sewered zones of a community. Strengthening WBE capabilities at local treatment facilities can improve early outbreak detection, thereby supporting timely public health interventions. Full article
(This article belongs to the Special Issue System Dynamics Modeling and Simulation for Public Health)
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27 pages, 1761 KB  
Article
Veteran Suicide Prevention in the USA: Evaluating Strategies and Outcomes Within Face the Fight
by Karim J. Chichakly, Katherine A. Dondanville, Brooke A. Fina, Hannah C. Tyler and David C. Rozek
Systems 2025, 13(11), 1039; https://doi.org/10.3390/systems13111039 - 19 Nov 2025
Viewed by 1159
Abstract
Veteran suicide remains a critical public health crisis in the United States, with rates nearly twice those of the general population. Addressing this challenge requires multiple evidence-based interventions across settings. This paper presents a system dynamics model developed within the Face the Fight™ [...] Read more.
Veteran suicide remains a critical public health crisis in the United States, with rates nearly twice those of the general population. Addressing this challenge requires multiple evidence-based interventions across settings. This paper presents a system dynamics model developed within the Face the Fight™ veteran suicide prevention initiative to evaluate and optimize strategies from 2022 to 2032. The model integrates peer-reviewed evidence on intervention effectiveness, subject-matter expert calibration, and annual updates from Veterans Affairs and grantee data to estimate the potential population-level impact of suicide prevention. The model organizes veterans by levels of suicide distress and estimates the impact of interventions in an initial three target areas aligned with a public health approach to suicide prevention: creating protective environments (e.g., secure firearm storage), strengthening access and delivery of suicide care (e.g., suicide-specific clinical programs), and identifying and supporting people at risk (e.g., suicide screening). Model results indicate that focusing solely on high-distress veterans is insufficient to reduce suicide rates to those of the general population, while balanced portfolios combining clinical, community, and firearm-safety approaches yield the greatest projected benefit. Sensitivity analyses demonstrate the model’s responsiveness to population distress distributions and intervention capacities, underscoring the need for a balanced, scalable strategy. Evaluating suicide-prevention impact is inherently challenging, but the model provides a dynamic and transparent framework for assessing investment effectiveness, refining strategies, and forecasting long-term outcomes. Its adaptability ensures ongoing insights to guide funding priorities, informs data-driven policy, and extends to other populations and public health challenges where multiple interventions interact to influence outcomes. Full article
(This article belongs to the Special Issue System Dynamics Modeling and Simulation for Public Health)
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18 pages, 1583 KB  
Article
Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve Analysis
by Sandra Usaquén-Perilla, Laura Valentina Bocanegra-Villegas and Jose Isidro García-Melo
Systems 2025, 13(7), 591; https://doi.org/10.3390/systems13070591 - 16 Jul 2025
Viewed by 1025
Abstract
The development of new diagnostic technologies is accelerating, and budgetary constraints in the health sector necessitate a systematic decision-making process to acquire emerging technologies. Health Technology Assessment methodologies integrate technology, clinical efficacy, patient safety, and organizational and financial factors in this context. However, [...] Read more.
The development of new diagnostic technologies is accelerating, and budgetary constraints in the health sector necessitate a systematic decision-making process to acquire emerging technologies. Health Technology Assessment methodologies integrate technology, clinical efficacy, patient safety, and organizational and financial factors in this context. However, these methodologies do not include the learning curve, a critical factor in operator-dependent technologies. This study presents an evaluation model incorporating the learning curve, developed from the domains of the AdHopHTA project. Using System Dynamics (SD), the model was validated and calibrated as a case study to evaluate the use of Point-of-Care Ultrasound (POCUS) in identifying dengue. This approach allowed for the analysis of the impact of the learning curve and patient demand on the revenues and costs of the healthcare system and the cost–benefit indicator associated with dengue detection. The model assesses physician competency and how different training strategies and frequencies of use affect POCUS adoption. The findings underscore the importance of integrating the learning curve into decision-making. This study highlights the need for further investigation into the barriers that limit the effective use of POCUS, particularly in resource-limited settings. It proposes a framework to improve the integration of this technology into clinical practice for early dengue detection. Full article
(This article belongs to the Special Issue System Dynamics Modeling and Simulation for Public Health)
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19 pages, 1312 KB  
Article
The Population Health Impacts of Changes to the National Health Service Health Check Programme: A System Dynamics Modelling Approach in a Local Authority in England
by Abraham George, Padmanabhan Badrinath, Stephanie Newton, Amy Hooper, Aaron Bhavsar, Mark Chambers, Peter Lacey, Rutuja Kulkarni-Johnston and Harry Whitlow
Systems 2025, 13(2), 101; https://doi.org/10.3390/systems13020101 - 7 Feb 2025
Cited by 1 | Viewed by 2991
Abstract
Health checks aim to improve the health of the population by identifying individuals with risk factors earlier and intervening to prevent disease. The role of commissioners is to ensure health checks provide as much benefit as possible for taxpayer funds invested into them. [...] Read more.
Health checks aim to improve the health of the population by identifying individuals with risk factors earlier and intervening to prevent disease. The role of commissioners is to ensure health checks provide as much benefit as possible for taxpayer funds invested into them. As such, evidence of the potential impacts of different commissioning choices is beneficial in this decision-making process. System dynamics modelling can be used to provide this evidence by modelling the health check programme using a pre-existing cohort model of a given population. This modelling considers local data, literature findings, and stakeholder views, from which nine different scenarios of a local health check programme have been tested. These scenarios found that extending the duration of health checks to 20 years and improving treatment uptake for those with high blood pressure or high cholesterol reduced rates of cardiovascular disease, improved healthy life expectancy and reduced years lived in ill health. In contrast, improving attendance in the most deprived quintile of the population made very little change to the health of the population overall, although a larger effect was observed in the most deprived areas. These findings helped guide local commissioning decisions by showing the long-term impact of different health check scenarios. Full article
(This article belongs to the Special Issue System Dynamics Modeling and Simulation for Public Health)
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22 pages, 3325 KB  
Article
Health and Economic Effects of Salt Reduction Interventions for Preventing Noncommunicable Diseases in Japan: A System Dynamics Simulation Study
by Fatin Aminah Hassan, Nobuo Nishi, Nobuaki Minato, Takehiro Sugiyama and Nayu Ikeda
Systems 2024, 12(11), 478; https://doi.org/10.3390/systems12110478 - 8 Nov 2024
Viewed by 4898
Abstract
Reducing salt intake is a vital public health measure for combating noncommunicable diseases and mitigating rising social security expenditures in Japan. We developed a system dynamics model to analyze the potential health and cost effects of salt reduction interventions among the Japanese population [...] Read more.
Reducing salt intake is a vital public health measure for combating noncommunicable diseases and mitigating rising social security expenditures in Japan. We developed a system dynamics model to analyze the potential health and cost effects of salt reduction interventions among the Japanese population aged 40 years and above from 2012 to 2040. The simulation findings derived from the model indicate that, in the base run, the disability-adjusted life years (DALYs) for cardiovascular disease (CVD) and chronic kidney disease (CKD) are projected to be approximately 55 and 9.5 per 100,000 people, respectively, contributing approximately 40 trillion yen in social security expenditures by 2040. The model predicts that implementing mandatory reformulation could decrease DALYs for CVD and CKD by 5.7% and 6.2%, respectively, resulting in an approximately 6.7% reduction in social security expenditure. Additionally, voluntary reformulation is estimated to reduce the DALYs for CVD and CKD by 4.7% and 5.2%, leading to a 5.6% decrease in social security expenditure. Finally, accelerating the adoption of a low-salt diet is expected to lower the DALYs for CVD by 2.8% and CKD by 3.2%, thereby reducing social security expenditures by 3.4%. Thus, product reformulation initiatives have a greater impact on health and economic outcomes. Full article
(This article belongs to the Special Issue System Dynamics Modeling and Simulation for Public Health)
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