This thesis focuses on the application of spatial methods to enhance leprosy control and prevention strategies. Leprosy is a chronic infectious disease affecting the skin and peripheral nerves, and if left untreated can lead to disabilities in hands and feet. Despite global efforts, leprosy remains a public health issue in certain areas, often concentrated in clusters or hotspots. Early case detection and preventive measures in these clusters are important to stop the transmission. Geospatial analysis methods are identified as valuable tools to identify clusters and understand disease patterns.
Chapter 2 to 5 explore various geospatial methods and their practical applications in optimising leprosy control strategies. These include visualising leprosy indicators at different administrative levels, visualising socioeconomic risk factors, identifying clusters with a contextualised approach and standard statistical approach, and a hotspot analysis to determine the population that need to be targeted with prophylactic interventions. In Chapter 6, mathematical modelling is employed to estimate the number of people requiring preventive treatment and predict the impact of interventions. All these methods are found to be valuable in supporting leprosy program managers in targeting interventions, prioritizing resources and developing long-term strategies.
In conclusion, this thesis demonstrates that spatial methods can significantly aid leprosy program managers in optimizing their leprosy control and prevention efforts and efficiently allocating resources. The use of geospatial analysis can identify high-risk areas, assist in the targeting of interventions, and estimate the populations in need of preventive treatment. However, it is crucial to involve leprosy program staff in these analyses and interpret the results carefully. The combination of spatial methods and expert consultation holds the potential to enhance the effectiveness of leprosy control and prevention strategies.
This thesis focuses on the application of spatial methods to enhance leprosy control and prevention strategies. Leprosy is a chronic infectious disease affecting the skin and peripheral nerves, and if left untreated can lead to disabilities in hands and feet. Despite global efforts, leprosy remains a public health issue in certain areas, often concentrated in clusters or hotspots. Early case detection and preventive measures in these clusters are important to stop the transmission. Geospatial analysis methods are identified as valuable tools to identify clusters and understand disease patterns.
Chapter 2 to 5 explore various geospatial methods and their practical applications in optimising leprosy control strategies. These include visualising leprosy indicators at different administrative levels, visualising socioeconomic risk factors, identifying clusters with a contextualised approach and standard statistical approach, and a hotspot analysis to determine the population that need to be targeted with prophylactic interventions. In Chapter 6, mathematical modelling is employed to estimate the number of people requiring preventive treatment and predict the impact of interventions. All these methods are found to be valuable in supporting leprosy program managers in targeting interventions, prioritizing resources and developing long-term strategies.
In conclusion, this thesis demonstrates that spatial methods can significantly aid leprosy program managers in optimizing their leprosy control and prevention efforts and efficiently allocating resources. The use of geospatial analysis can identify high-risk areas, assist in the targeting of interventions, and estimate the populations in need of preventive treatment. However, it is crucial to involve leprosy program staff in these analyses and interpret the results carefully. The combination of spatial methods and expert consultation holds the potential to enhance the effectiveness of leprosy control and prevention strategies.