System dynamics (SD) modelling employs systems thinking to understand complex systems’ behaviors over time. SD is among the most popular modelling methods in health policy and healthcare research. But unlike agent-based models that aim to capture micro-level system behaviors such as human decision-making and heterogeneous interactions between individuals, SD models address macro-level system behaviors such as changes or movement of resources in complex systems over time.
Using differential equations to model changing variables over time while allowing for feedback and various interactions and delays, SD models also address the issues of simultaneity or the mutual causation of systems behaviors. The method allows for the model breadth to explore long-term effects of strategic changes in our complex health systems.
The George Institute for Global Health India is pleased to invite you to a webinar on “System dynamics modelling for health systems strengthening: Applications before and during the COVID-19 pandemic in Thailand”
Mark your calendars for 12th November 2021 | 13:30 PM IST
- Introducing the concept of systems thinking in the context of health systems strengthening
- Clarifying how ‘systems dynamics modeling’ can be used as an applied system thinking methodology in health policy process
- Presenting an example of health policy and systems research using SD methodology in context of COVID – 19.
- Expanding the scope of SYSTAC – A global systems thinking accelerator launched by the Alliance for Health Policy and Systems Research
- Borwornsom Leerapan – Faculty of Medicine Ramathibodi Hospital, Mahidol University
- Dr. Sohana Safique – Deputy Project Coordinator, Urban Health, icddr,b, Bangladesh Moderator
- Dr. Devaki Nambair – Program Head – Health Systems and Equity, The George Institute for Global Health
- Mr. Siddharth Srivastava – Research Assistant, The George Institute for Global Health
Use and impact of SD in the contexts of Thailand’ UHC and the COVID-19 pandemic
In the context of the COVID-19 pandemic, SD can be used for epidemiological modelling of the COVID-19 pandemic. In addition, the massive demands for COVID-19 vaccination by both vulnerable and general populations as well as rapid adoption of digital health solutions in care delivery models can also be modelled. This has implications for the demands and supply of the health workforce, both in the short and long term. Hence, updated policy options of workforce planning in new care delivery models can be simulated to keep the modelling relevant to the current policy process.