Epidemiological modelling with behavioural considerations and to inform policy making

Many problems in epidemiology are impacted by behavioural dynamics, whilst in response to health emergencies prompt analysis and communication of findings is required to be of use to decision makers. Both instances are likely to benefit from interdisciplinary approaches. This talk will feature two examples, one with a public health focus and one with a veterinary health focus.

In the first part, I will summarise work originally conducted in late 2020 that was contributed to Scientific Pandemic Influenza Group on Modelling, Operational sub-group (SPI-M-O) of SAGE (Scientific Advisory Group for Emergencies) on Christmas household bubbles in England. This was carried out in response to a policy involving a planned easing of restrictions in England between 23–27 December 2020, with Christmas bubbles allowing people from up to three households to meet throughout the holiday period. Using a household model and computational simulation, we estimated the epidemiological impact of both this and alternative bubble strategies that allowed extending contacts beyond the immediate household.

(Associated paper: Modelling the epidemiological implications for SARS-CoV-2 of Christmas household bubbles in England in December 2020. doi.org/10.1016/j.jtbi.2022.111331)

In the second part, I will present a methodological pipeline developed to generate novel quantitative data on farmer beliefs with respect to disease management, process the data into a form amenable for use in mathematical models of livestock disease transmission and then refine said mathematical models according to the findings of the data. Such an approach is motivated by livestock disease models traditionally omitting variation in farmer disease management behaviours. I will discuss our application of this methodology for a fast, spatially spreading disease outbreak scenario amongst cattle herds in Great Britain, for which we elicited when farmers would use an available vaccine and then used the attained behavioural groups within a livestock disease model to make epidemiological and health economic assessments.

(Associated paper: Incorporating heterogeneity in farmer disease control behaviour into a livestock disease transmission model. doi.org/10.1016/j.prevetmed.2023.106019)