Catalog of Regulatory Science Tools to Help Assess New Medical Devices
This regulatory science tool comprises a model for conducting a retrospective analysis of COVID-19 intervention strategies.
Technical Description
This tool provides a graphical user interface frontend for the "dynamic-spread" Susceptible-Infected-Removed (SIR) model or Highly Adaptive Risk Assessment Model (HARAM) that enables users to estimate the change in risk of infection associated with different intervention strategies (including facemask choices) to epidemics.
This interface allows for the selection of 4 different scenarios and 3 different intervention strategies based on COVID-19 case data. It also allows the users to change the infection characteristics, baseline mask effectiveness, and different values characterizing the mitigation strategies featured in the model. This flexibility in adjusting the input parameters allow the user to see how different parameters can affect case data. The user has the option to either view the output data in one of 3 plot windows showing the number of new cases, active cases, and the normalized spread function over time. They also have the option to change how the bounds of the data are displayed, and the ability to export the data. A detailed explanation of how to use the model interface, all the different options, parameters, and exports along with their meanings are found on the model’s GitHub page.
Intended Purpose
The graphical user interface allows users to execute the model for the purpose of informing decisions regarding countermeasures to the spread of infections, specifically COVID-19. Countermeasures include the use of facemasks by infected persons specifically the facemasks’ filtration efficiency, compliance in the population, and social distancing.
Testing
The data output from the graphical user interface was compared to values produced by research versions of the computer code, and the outputs were identical (within the bounds of uncertainty quantification). The graphical user interface provides a simplified and intuitive method for implementing the epidemiological model.
The credibility of the model was evaluated in the following publications:
- Jenna Osborn, Shayna Berman, Sara Bender-Bier, Gavin D'Souza, Matthew Myers. Retrospective analysis of interventions to epidemics using dynamic simulation of population behavior. Mathematical Biosciences, 2021, 341: 108712. doi: 10.1016/j.mbs.2021.108712.
- Gavin D'Souza, Jenna Osborn, Shayna Berman, Matthew Myers. Comparison of effectiveness of enhanced infection countermeasures in different scenarios, using a dynamic-spread-function model. Mathematical Biosciences and Engineering, 2022, 19(9): 9571-9589. doi: 10.3934/mbe.2022445.
- Shayna Berman, Gavin D'Souza, Jenna Osborn, Matthew Myers. Comparison of homemade mask designs based on calculated infection risk, using actual COVID-19 infection scenarios. Mathematical Biosciences and Engineering, 2023, 20(8): 14811-14826. doi: 10.3934/mbe.2023663.
Limitations
This model is only valid for the four COVID-19 scenarios specified in the testing section. Only the default parameters for each scenario and their corresponding inputs are representative of the data.
Supporting Documentation
- Jenna Osborn, Shayna Berman, Sara Bender-Bier, Gavin D'Souza, Matthew Myers. Retrospective analysis of interventions to epidemics using dynamic simulation of population behavior. Mathematical Biosciences, 2021, 341: 108712. doi: 10.1016/j.mbs.2021.108712.
- Gavin D'Souza, Jenna Osborn, Shayna Berman, Matthew Myers. Comparison of effectiveness of enhanced infection countermeasures in different scenarios, using a dynamic-spread-function model. Mathematical Biosciences and Engineering, 2022, 19(9): 9571-9589. doi: 10.3934/mbe.2022445.
- Shayna Berman, Gavin D'Souza, Jenna Osborn, Matthew Myers. Comparison of homemade mask designs based on calculated infection risk, using actual COVID-19 infection scenarios. Mathematical Biosciences and Engineering, 2023, 20(8): 14811-14826. doi: 10.3934/mbe.2023663.
- Highly Adaptive Risk Assessment Mode (HARAM) Graphical User Interface (GUI) GitHub Repository.
Contact
Tool Reference
- In addition to citing relevant publications please reference the use of this tool using RST24EP04.1