Simone De Reggi (University of Trento) – Modelling information-dependent protective behaviour in response to mosquito-borne epidemic outbreaks

Recent rises in cases of several mosquito-borne diseases--such as dengue, Chikungunya, and West Nile virus--in both endemic and non-endemic areas, have increased the interest in the use of mathematical models to understand the spread of vector-borne infections, and the potential effects of control strategies. The classical Ross-–Macdonald framework provides the foundation for much of the mathematical modelling of such diseases. In this talk, I will present a model for a mosquito-borne epidemic outbreak in which human hosts may adopt protective behaviours against mosquito bites. First, I will introduce the basics of the Ross–Macdonald framework. Then, I will extend the model by allowing individuals within the host population to adopt protective behaviours (e.g., using repellents) according to information they receive about disease prevalence. I will show that, in the early phase of an epidemic, behaviour-driven protection may either decrease or increase the reproduction number of the epidemic, depending on several factors. In addition, I will show that, in the long run, behavioural responses may facilitate epidemic control, but may also prolong disease persistence, potentially generating recurrent epidemic waves.

Acknowledgements
This work was supported by the project "One Health Basic and Translational Actions Addressing Unmet Needs on Emerging Infectious Diseases" (INF-ACT), BaC "Behaviour and sentiment monitoring and modelling for outbreak control/BEHAVE-MOD" (No. PE00000007, CUP I83C22001810007) funded by the NextGenerationEU. The author is member of the UMI research group MSE, and of the INdAM research group GNCS.