A tutorial on discrete-event simulation for health policy design and decision making: Optimizing pediatric ultrasound screening for hip dysplasia as an illustration

Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques that serve as options for reaching unique decisions based on personally and individually ranked criteria. These techniques are organized into a taxonomy of ratio assignment and approximate techniques, and the strengths and limitations of each are explored. We compare these techniques potential uses across the Agent-Based Modeling (ABM), System Dynamics (SD), and Discrete Event Simulation (DES) modeling paradigms to inform current researchers, students, and practitioners on the state-of-the-art and to enable new researchers to utilize methods for modeling multi-criteria decisions.

Download Full-text

Managing funerary systems in the pandemic: lessons learned and an application of a scenario simulation in São Paulo City, Brazil

Journal of Humanitarian Logistics and Supply Chain Management ◽

10.1108/jhlscm-09-2020-0078 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Irineu de Brito Jr ◽

Manoel Henrique Capistrano Cunha ◽

Luiz Antonio Tozi ◽

Luiz Augusto Franzese ◽

Márcia Lorena da Silva Frazão ◽

...

Keyword(s):

Decision Making ◽

Discrete Event Simulation ◽

Discrete Event ◽

Sao Paulo ◽

Lessons Learned ◽

São Paulo ◽

Content Type ◽

Event Simulation ◽

Discrete Event Simulation Model ◽

The City

PurposeThis study, a practice forum article, aims to presents the lessons learned and the development of a discrete event simulation model to support the funerary system management of São Paulo City, Brazil, during the COVID-19 pandemic.Design/methodology/approachA discrete event simulation model was developed by the authors as soon as the pandemic affected the city of São Paulo, Brazil. Based on the model, several scenarios with varying minimum, median and peak demands (i.e. the number of deaths) were tested and evaluated. The lessons learned from the scenario analysis and implementation of the decision-making of the city government of São Paulo are discussed in this article.FindingsThe lessons learned about the coordination, inventory management and other operational characteristics in funerary logistics during the pandemic are shared with a model, which quantifies the demand for vehicles, coffins, graves and teams in the cemeteries in different simulated scenarios.Practical implicationsThe São Paulo State Civil Defense used this information during the pandemic to prepare the funerary system of the municipality.Social implicationsThe study presents methods to mitigate the sanitary, environmental and psychosocial problems related to the funerary system.Originality/valueStudies on funerary systems are scarce. This study presents the results that supported the dimensioning of the funerary system during the pandemic and operational lessons about the logistics to support decision-making in future events.

Download Full-text