The United Nations Sustainable Development Goals (UN SDGs) for 2030 emphasize the importance of improving health and well-being around the world, especially in less developed regions. This requires reliable health data, but accurately tracking infectious diseases in these areas can be challenging due to underreporting and limited resources. This is particularly problematic when dealing with small populations, where a lack of reported cases can distort our understanding of the spread of disease.

This project aims to develop new statistical methods to address this challenge. We will build models that account for “zero inflation,” a common problem in these contexts where many regions may report zero cases of disease. These models will also consider how disease patterns vary over space and time. By providing more accurate estimates of disease incidence, these new methods will help us better understand the progress of health indicators, tailor public health interventions to specific regions, and guide resource allocation to effectively combat infectious diseases and achieve the UN SDGs.