On October 5, Dahdaleh postdoctoral research fellow Mohammadali Tofighi introduced computer modelling approaches and applications for modelling health impacts caused by climate change in Malawi.

The modelling process can be abstract. Mohammadali discussed a few modelling approaches that can be used based on the level of abstraction and the information available. For example, dynamic systems modelling works best for low abstraction data because it is numerical with analysis of physical state variables and algebraic differential equations. Whereas system dynamics modelling can work well with high-abstraction ideas and uses feedback loops to gather data. Next, agent-based modelling can account for and measure individual behaviour, direct and indirect interaction, and a wide range of abstractions.

The research team were able to map out their data to find patterns, and correlations, and apply real-world solutions that address the spread of disease or food insecurity caused by climate change. They used a combination of these modelling techniques, but he especially highlighted agent-based modelling, which allows for flexible, expandable, and sharable data collection. It can depict how environments and agents interact. For instance, the level of rainfall can inform the rate of malaria being spread. Ultimately, these models can simulate rapidly changing weather patterns and prepare local communities for these challenges.