Grant: Team Grant: Mpox and zoonotic threats - Social and behavioural science

We will design and analyze epidemiological and geospatial models including artificial intelligence-based and mathematical models to study the epidemiology, transmission dynamics, and immunology and intervention strategies of mpox, and other zoonotic threats. These models will be used to generate valuable insights; predict the effectiveness of control strategies; identify modifiable risk factors which could be targeted for intervention, as well as other possible intervention strategies and inform public health decision-making; analyze public health interventions and risk management strategies; investigate the effectiveness of public health interventions, and thus provide rapid evidence to inform decision-making in Canada and/or globally. We will use biobehavioral data from PubMed data, and the recent survey by CDC/ECDC on the MSM community and modelling to study the different aspects and forecast the control interventions, risk factors; impact of mpox virus on sexually transmitted and blood-borne infections (STBBIs) by considering and examining Sex-and Gender-Based Analysis Plus (SGBA+). The host immune response to mpox plays an essential role in disease pathogenesis and clinical manifestations, even though it is little understood. Thus, our models will also provide insight into the factors that shape the virus' within-host dynamics in the presence of infection-induced and vaccination-induced immunity. We plan to use risk-map assessment and geospatial analysis to identify hotspots for (re)emergence of zoonotic threats that will be used by countries' decision-makers and health units in pandemic surveillance and response to improve preparedness. This will explore the complete scope of potential health and other impacts of proposed public health interventions, and capture the broad range of risks and benefits tied to different mpox and other zoonotic threats prevention and control strategies in Canada and/or globally.