A model-driven software development platform for Climate-Sensitive Infectious Disease Modelling

Grant number: 226107/Z/22/Z

Grant search

Key facts

  • Disease

    Disease X
  • Start & end year

    2023
    2028
  • Known Financial Commitments (USD)

    $331,118.97
  • Funder

    Wellcome Trust
  • Principal Investigator

    Prof Marios Fokaefs
  • Research Location

    Canada
  • Lead Research Institution

    York University (Canada)
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies

  • Research Subcategory

    N/A

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

The COVID-19 pandemic demonstrated the value of epidemiological models in battling against the disease. However, modelling is not a trivial task. It requires time, effort and continuous maintenance to address the evolution of the disease and of the countermeasures. On one hand, this requires a systematic and robust development process to ensure the effectiveness and the quality of the produced models. On the other hand, it also implies the need for a change management process that will handle the maintenance and the evolution of the models. Furthermore, infectious diseases have to be studied in conjunction with other affecting parameters, include climate and sociodemographics. Therefore, modellers need to be able to consider multidimensional and hybrid models to better study the phenomenon. In this project, we propose the application of software engineering and model-driven engineering principles to aid the design, development and simulation of climate-sensitive infectious disease models. More specifically, we propose a integrated development platform that will support (a) the definition and design of models, (b) the simulation of scenarios based on these models, (c) the automatic validation and verification of models and code generation, (d) the control of model versions, and (e) the merging of models from different domains.