flepiMoP: The evolution of a flexible infectious disease modeling pipeline during the COVID-19 pandemic

• Published in: Epidemics 2024-06, Vol.47, p.100753, Article 100753
• Main Authors: Lemaitre, Joseph C., Loo, Sara L., Kaminsky, Joshua, Lee, Elizabeth C., McKee, Clifton, Smith, Claire, Jung, Sung-mok, Sato, Koji, Carcelen, Erica, Hill, Alison, Lessler, Justin, Truelove, Shaun
• Format: Article
• Language: English
• Subjects: Compartmental model; COVID-19; COVID-19 - epidemiology; COVID-19 - prevention & control; COVID-19 - transmission; Epidemiological Models; Forecasting; Humans; Influenza; Open-source Software; Pandemics - prevention & control; Pipeline; Respiratory syncytial virus; SARS-CoV-2; Scenario Planning; Software
• ISSN: 1755-4365; 1878-0067; 1878-0067
• DOI: 10.1016/j.epidem.2024.100753

The COVID-19 pandemic led to an unprecedented demand for projections of disease burden and healthcare utilization under scenarios ranging from unmitigated spread to strict social distancing policies. In response, members of the Johns Hopkins Infectious Disease Dynamics Group developed flepiMoP (formerly called the COVID Scenario Modeling Pipeline), a comprehensive open-source software pipeline designed for creating and simulating compartmental models of infectious disease transmission and inferring parameters through these models. The framework has been used extensively to produce short-term forecasts and longer-term scenario projections of COVID-19 at the state and county level in the US, for COVID-19 in other countries at various geographic scales, and more recently for seasonal influenza. In this paper, we highlight how the flepiMoP has evolved throughout the COVID-19 pandemic to address changing epidemiological dynamics, new interventions, and shifts in policy-relevant model outputs. As the framework has reached a mature state, we provide a detailed overview of flepiMoP’s key features and remaining limitations, thereby distributing flepiMoP and its documentation as a flexible and powerful tool for researchers and public health professionals to rapidly build and deploy large-scale complex infectious disease models for any pathogen and demographic setup. •flepiMoP is an open-source infectious dynamics modeling software framework.•It enables researchers and public health professionals to build complex models without coding.•flepiMoP can simulate hundreds of compartments on thousands of connected populations.•And infer parameters from observed data with a powerful distributed inference engine.•Producing forecasts and scenario projections of COVID-19 and influenza in different countries.