Mapping malaria incidence using routine health facility surveillance data in Uganda

Area of Science:

• Epidemiology
• Public Health
• Geographic Information Systems

Background:

• Malaria risk mapping is crucial for resource allocation and progress tracking.
• Traditional maps rely on parasite prevalence surveys, but health facility data is an underutilized resource.
• Accurate malaria incidence mapping is needed for effective control strategies in Uganda.

Purpose of the Study:

• To model and map malaria incidence in Uganda using health facility data.
• To assess the impact of indoor residual spraying (IRS) on malaria incidence.
• To compare health facility data-based estimates with routine surveillance data.

Main Methods:

• Utilized 24 months of individual-level outpatient data from 74 health facilities in Uganda (n=445,648 confirmed cases).
• Estimated monthly malaria incidence at the parish level by calculating care-seeking population denominators.
• Applied spatio-temporal models incorporating environmental, sociodemographic, and intervention variables to predict incidence across Uganda.

Main Results:

• Malaria incidence averaged 705 cases per 1000 person-years, with high burden in northern and northeastern Uganda.
• Health facility data indicated considerably higher malaria cases than Ministry of Health reports, suggesting underreporting.
• Indoor residual spraying (IRS) was associated with lower incidence, averting an estimated 6.2 million cases in 14 districts.

Conclusions:

• Routinely collected health system outpatient data is a valuable resource for malaria burden mapping.
• Investing in robust surveillance systems within public health facilities offers a low-cost, high-benefit tool for malaria control.
• Health facility data can effectively identify vulnerable regions and track the impact of interventions like IRS.