Why is it so hard to model the COVID-19 epidemic? In this guest blog Ignacio Brottier and Patricio Pipp look at how agent-based simulation modeling goes beyond traditional SEIR and its shortfalls.
The first step to understanding any system is asking ourselves what it is we are trying to understand and, as the team of FiveThirtyEight well explains in their very recommended article, understanding COVID-19’s evolution is no easy task...
The webinar Hybrid Dynamic Models in COVID-19 Planning and Beyond drew in a record number of attendees and prompted some great questions around the theme of simulation modeling and healthcare planning.
Dr. Nathaniel Osgood, a Professor in the Department of Computer Science and Associate Faculty in the Department of Community Health & Epidemiology at the University of Saskatchewan, provided great insight into simulation modeling related to healthcare. Read on for the webinar details, recording, and Dr. Nathaniel Osgood’s Q&A answers.
Our AnyLogic partners in China obtained a paper relating to COVID-19 and permission to publish a translation.
Writing this now, there is obviously a lot of interest surrounding the spread of the COVID-19, the coronavirus disease. The paper studies the prevalence of infection in a population using agent-based simulation and looks at the importance of factors such as the frequency of close contact among a population.
Timothy E. Hoffman, Katherine J. Barnett, Lyle Wallis and William H. Hanneman of the Center for Environmental Medicine, Colorado State University are to be published in the October 2017 issue of the peer-reviewed Aging Cell journal of the Anatomical Society.
The aim of their investigation was to assess recent significant and unusual research observations regarding aging.
In cancer patients, an inability to access the surgical system can be lethal, but accessing it can be impoverishing, especially in low- and middle-income countries (LMICs). A group from the Global Surgery and Social Change, Department of Global Health and Social Medicine, Harvard Medical, supported by National Cancer Institute used AnyLogic Software to evaluate the health, financial, and equity impacts of governmental and charitable policies for surgical oncology in a resource-limited setting.
Indiana University Health Arnett (IUHA) is an integrated healthcare system which consists of a full service acute care hospital and a multispecialty clinic with approximately 200 providers at numerous locations. In the past, provider schedules were driven by individual preference which led to increased variation in scheduling rules that failed to meet employer or patient expectations. To better serve patients and maintain provider approval, IUHA sought to develop a scheduling methodology that provides same day access for a designated patient population while allowing acceptable access to the remaining patient population.
Traditional Marketing Mix models attempt to explore the tradeoffs amongst different marketing channels and the spends associated with them. The weaknesses of these models are, generally, their static nature and the restrictive assumptions required to apply their results. For these reasons, an American pharmaceutical company, one of the largest in the world, engaged with Sterling Simulation to explore the benefits of agent-based modeling, prior to launching a new product. The use-case was presented by Scott Hebert, Vice President of Sterling Simulation at the AnyLogic Conference 2015.
The Children’s Hospital of Philadelphia (CHOP) is well known as one the best places in the world for a child to come and get medical care. Less known, is the behind-the-scenes work of Dr. T. Eugene Day, Program Manager for Health Systems in the Office of Safety and Medical Operations to improve quality, safety, and overall patient care. Like many hospitals, CHOP is met with a multitude of challenges beyond the daily task of performing life-saving procedures and providing care for patients. Dr. Day utilizes simulation modeling with AnyLogic software to identify opportunities and aid planning for systemic improvements versus typical approaches.
A multi-national pharmaceutical company recently launched a new non-generic drug. Since the company already owned the leading non-generic drug in that market, cannibalization was a concern. The goal was to create market share for the new drug, while maintaining or increasing market share for the well-established drug by modifying types of promotional spend. Traditionally, the Analytics Department would employ a Marketing-Mix Model (MMM) to determine the impact of promotional spend, but the company was looking for further insight into the mechanics behind the MMM. After exploring multiple options, they determined agent-based modeling, and ultimately AnyLogic would allow for the greatest flexibility and visualization.
Alexander Doroshenko, Weicheng Qian and Nathaniel D. Osgood from the Division of Preventive Medicine at the University of Alberta in Canada were recently published in PeerJ, an Open Access, peer-reviewed, scholarly journal. It considers and publishes Research Articles in Biological and Medical Sciences. The objective of the University of Alberta project was to investigate the effect of outbreak response immunization (ORI) among adolescents as an emergency public health intervention in light of a recent re-emergence of pertussis outbreaks. ORI is supplementary immunization given over and above the routine vaccination schedule, including to those who may be fully immunized or those who did not receive their scheduled vaccines.