Scientific modelling is a way of thinking about complex systems in order to make sense of them.
For example, we might want to know how seasonality will influence the impact of releasing male mosquitoes that have been genetically modified to produce only male offspring. To address this question, the modeller will first construct a mathematical representation of the mosquito population and how it depends on seasonal factors such as rainfall. The model will also need to represent the modified mosquitoes by how they are expected to interact with the wild mosquitoes. By studying the equations of the model, the modeller can try to determine how the nature of seasonality will influence the outcome of a release.
Many kinds of models are used in Target Malaria to address different kinds of questions. These range from ‘big-picture’ questions, such as “how much could gene drive technology reduce malaria at the scale of a country?”, to detailed questions such as “how the population of a cage depends on the number of eggs a typical female lays per day?”. Depending on the nature of the model, a wide variety of inputs might be used – from lab measurements to satellite data!
Within Target Malaria, we often find modelling is most helpful when done in collaboration with other researchers with an interest in the questions being addressed, such as field entomologists, molecular biologists, and risk and regulatory experts.