In a context of escalating public health challenges, including the rise of chronic diseases, the impact of climate change, and the COVID-19 pandemic, certain populations bear a disproportionate burden. As a result, there is an urgent need to develop public health strategies that not only promote overall well-being but also mitigate these health inequities. Addressing these issues through a geographic lens is essential because health status is strongly influenced by the social determinants of health, i.e., the conditions under which individuals are born, grow, live, work, and age. Such spatial epidemiology studies could facilitate the prioritization of public health interventions, and the design of initiatives tailored to the characteristics of populations and their environments. In recent decades, the research field of spatial epidemiology has been boosted by the increasing availability of high-resolution spatial data and advances in computational techniques. However, academic findings are rarely translated into population health interventions. This thesis aims to bridge this gap by exploring the potential of spatial epidemiology in supporting public health policies. To this end, the research was structured around case studies aligned with the challenges faced by the Public Health Department of the canton of Vaud. First, indicators related to social determinants of health were developed and mapped at a fine spatial scale (hectare level) to address the challenges of a national health promotion program engaged with municipalities. These indicators were then associated with individual health data to investigate the influence of the physical and social environments on the spatial distribution of cardiovascular risk factors. By identifying a pronounced geographic pattern of hypertension, obesity, and diabetes in the adult population of the city of Lausanne, the results provided insights for prioritizing and adapting future prevention campaigns. The role of spatial epidemiology in infectious disease surveillance was then explored in the context of the COVID-19 pandemic. Spatio-temporal approaches were applied to individual RT-PCR test data to identify emerging clusters of COVID-19 cases. Subsequent genomic analysis of these clusters demonstrated that incorporating geographic approaches could improve the effectiveness of current surveillance systems by guiding prioritization strategies for contact tracing and virus tracking. In the final case study, spatial approaches were used to design the COVID-19 mobile vaccination campaign in the canton of Vaud, illustrating the translation of research into practice. This thesis demonstrates that fine-scale spatial epidemiology can inform strategic decision-making for various health challenges, and concludes with practical recommendations for adopting a geographic lens within public health departments.