Measles is a preventable disease that kills thousands of children annually. Vaccine coverage has largely removed this disease from developed countries, but it is still a major public health issue in many developing countries. Transmission patterns are rooted in host mixing behavior at different spatial scales. Classical distance-based measures of interaction ignore social and cultural heterogeneities, leading to clustered contacts that are independent of political boundaries. Identifying the critical behaviors and spatial elements that contribute to recurring epidemics will allow us to define and predict patterns for targeted vaccination. Using historical data from England and Wales, we identified previously undetected host movement biased towards the coastline. Using this information to develop computational disease models with host movement and behavior parameters, we more accurately captured disease dynamics than previous models. Similarly, in many regions, including West Africa, environmental and behavioral heterogeneities drive mixing patterns. Although data are reported with respect to political divisions, these borders do not always govern human behavior. The slightly offset annual rainy season across West Africa dictates land use, labor, and migration across borders. Looking beyond the political divisions within the West African nation of Niger, we investigate regions by language, culture, and livelihood to identify social clusters important in transmission for the development of novel disease models.