Cystic echinococcosis (CE) is a zoonotic disease of global relevance that leads to significant morbidity and economic losses in the livestock industry. Effective intervention and surveillance strategies are essential and available for controlling and preventing the spread of this disease. As a Neglected Tropical Disease (NTD), one of the main obstacles to control and surveillance is resource constraints and lack of sustainable investments. This

thesis aims to address these issues by utilising an interdisciplinary approach that combines spatial analysis, individual-based transmission modelling, and stakeholder elicitation techniques. In Chapter 1, the research delves into the extensive academic literature, shedding light on the transmission of CE and the various modelling approaches that have been previously explored.

In Chapter 2, A spatial model was designed to investigate the spatial heterogeneity of CE infection in different livestock species across farms was implemented in central and southern Italy. The model allowed the identification of disease “hot spots” at high spatial resolution between multiple Italian provinces, while also highlighting species-specific infection risk. A total of 3141 animal samples from abattoirs were collected and used to predict the probability of infection in farms. Areas of high infection rates were found in the regions of Sardinia, Sicily and Salerno province. The resulting maps of infection risk will be valuable for targeted intervention efforts and further surveillance programmes, enabling optimal distribution of resources for future surveillance and control efforts. This study was published as part of the Neglected Tropical Diseases section of Frontiers in Tropical Diseases.

Chapter 3 presents an individual-based CE transmission model in a single farm setting that was developed and implemented in the context of a resource-constrained setting using the province of Rio Negro, Argentina as a case study. The model captures key aspects of the parasite life cycle and host interactions, allowing for the evaluation of intervention strategies such as anthelmintic treatment and vaccination, while accounting for individual-level heterogeneities. The results contribute to the increase in insights into the effectiveness of these strategies in reducing disease prevalence, assisting policymakers in making evidence-based decisions for CE management. The models developed in the previous two chapters are integrated in Chapter 4 to build a profile of disease transmission and intervention for 121 farms in the vaccination area of Rio Negro, Argentina. Utilising sampling data collected during the vaccination programme between the years 2009 - 2019, a profile of disease prevalence was established using the spatial model developed. The transmission model was then fitted to these prevalences post-intervention, and new

intervention scenarios were carried out beyond 2023. Dosage costs were also analysed between different intervention scenarios. These outputs highlight the difference in cost-effectiveness between increasing coverage of dog deworming and sheep vaccination.

Chapter 5 introduces a socio-economic study carried out involving an elicitation survey to assess stakeholders’ willingness to invest/disinvest in surveillance sensitivity for infectious diseases in a One Health context. The survey explored this at different levels of surveillance sensitivity and with different uncertainties as to the outcomes of the decisions being made. Understanding these priorities and financial constraints is key to identifying the most acceptable and cost-effective surveillance strategies. The findings will contribute to the development of tailored intervention plans that balance the need for sensitivity and cost-effectiveness.

This integrated approach of this thesis, combining spatial analysis, transmission modelling, and socio-economic elicitations offers a comprehensive framework for understanding the complex dynamics of CE transmission and control. These findings will be instrumental in guiding the development and implementation of effective intervention and surveillance strategies, ultimately contributing to the reduction of disease burden and economic impact

of CE on affected communities. The research thesis represents a development in the field of zoonotic disease management, laying the ground to improve both human and animal welfare in regions affected by cystic echinococcosis. Through innovative modelling techniques and stakeholder engagement, the project provides a solid foundation for evidence-based decision-making in designing and implementing targeted intervention and

surveillance strategies.

Throughout my doctoral research, I made significant contributions to several published projects that closely relate to the themes of this thesis, both in terms of the disease under study and the methodologies employed. For a detailed summary of these projects, please refer to Appendix E.