I like that you raise a point about methodological complexity. Epidemiology in place variable, known as spatial epidemiology, contains a lot of complex statistical methods computed from either frequentism or Bayesianism (belief and probability) approach.
Spatial epidemiology allows us to display maps of disease risk that are leveraged for the decision-making process. These risk maps help identify areas with higher or lower disease risks, enabling policymakers to target interventions.
However, not all knowledge users, even decision-makers may fully realize and adopt the importance of statistical methods that work behind the map. When comparing different areas to find out high-risk distribution, people might use two or more common epidemiological measurements such as absolute numbers, rates, or proportions, then exhibit the number on a map to make assumption.