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Background and aim: Routine surveillance is increasingly recognised as central to multi-dimensional malaria control efforts, especially for programme planning and impact assessment. Whilst it is global strategy to transform surveillance into a core programmatic component, essential in-depth interpretation of routine surveillance data remains limited, especially in higher transmission settings. I therefore aimed to explore utility of indicators of uncomplicated malaria burden from routine health facility surveillance data in identifying and mapping high-risk areas for malaria in Uganda. Methods and data sources: To examine routine surveillance indicators of malaria burden, I first evaluated internal consistency between measures from three national reference health facilities, comparing incidence and test positivity rates over time and space. In addition, I examined impacts of control interventions on the age associated burden of malaria, stratified by endemicity and intervention. I then extended this to compare routine reporting data with concurrent community cohort incidence estimates across three sub-counties to evaluate potential sources of bias. Finally, using four years of national health management information system (HMIS)-reported confirmed malaria data in a Bayesian autoregressive analytical framework, I explored the space-time distribution of malaria, and estimated adjusted national and local HMIS-based incidence rates. Primary findings: At the health facility level, HMIS-based incidence and test positivity rates showed similar trends and predicable relationships, with reduced transmission associated with increasing age of test confirmed malaria cases. Comparison of HMIS and cohort data suggested that HMIS data could provide a relatively unbiased proxy for true incidence - especially in lower-transmission, better performing surveillance systems settings. Lastly, space-time modelling of national HMIS data revealed high-burden and high-risk areas within health facility catchments, districts, and regions, highlighting the utility of routine surveillance data in identifying programmatically relevant heterogeneities in malaria burden in Uganda. Conclusion: This thesis highlights the potential viability of routine data in evaluating endemic malaria risk with improved routine HMIS. This is shown by: similar trends of HMIS-based incidence with other measures; its unbiased relationship with community cohort incidence; and, its capacity to identify high case rate locations. To realize the potential of these data, coordinated efforts are needed towards high testing rates, complete and timely recording and reporting, and multilevel feedback within national malaria control programme systems. Further research opportunities include treatment or non-care seeking and non-reporting care alternatives impacts on surveillance-based indicators of malaria burden.

Prolonged conjunctival infection with Chlamydia trachomatis leads to an inflammatory response, trachomatous inflammation follicular (TF). Over time, repeat infection can progress to scarring of the conjunctiva causing the eyelid to turn inward, resulting in lashes rubbing against the cornea. This painful stage of the disease is called trachomatous trichiasis (TT). TT can damage the cornea, leading to vision impairment or blindness. Trachoma is targeted for elimination as a public health problem by the year 2020, which for TT is defined as less than 1 TT-positive person, who is not already known to the health system, per 1,000 population. For trachoma to meet the elimination targets, massive resources are required for both mapping and intervention. A particularly large knowledge gap exists around identifying areas where TT is likely to be found. To better align resources and plan for elimination, the trachoma community needs to understand how much TT currently exists and requires management, how to accurately measure TT prevalence, and where TT cases are mostly likely to be located. Understanding these elements will help position trachoma control programs to meet the TT elimination targets. In my thesis I first calculate an updated global estimate of TT cases and describe the methods involved. Second, I provide a survey design for measuring TT with adequate precision for control activities, along with validation exercise results and a brief time-cost analysis. I then examine the spatial structure of TF and TT and identify areas of spatial autocorrelation. Finally, I identify environmental factors associated with higher than expected TT prevalence to identify TT hot spots. The outcomes of these activities provide an updated global estimate of existing TT cases, a validated tool for measuring TT prevalence at the implementation unit (district) level, and insight on where to begin case finding activities in the context of the "end game". These outputs are critical to the continued effort of trachoma elimination as a public health problem, specifically providing targeted direction for TT resources.