Abstract

Malaria is the leading cause of morbidity and mortality in Uganda, with nearly half of the population becoming infected in any given year. Uganda relies on analyzing high-quality surveillance data to help detect outbreaks, determine which areas or population groups are most affected, and help target resources to where they are most needed. In March 2019, over 300 health facilities from different districts in Uganda reported substantially higher malaria cases than usual. In 13 districts, health facilities reported that the number of malaria cases was so high that they were experiencing stock outs of antimalarial drugs. Although seasonal increases in cases had been expected, districts reported that the number of cases being identified were overwhelming the capacity of the health facilities. Uganda´s National Malaria Control Division tasked a team of epidemiologists to investigate this unprecedented increase in malaria cases. National Malaria Control Division were interested in how malaria epidemiology had been changing in recent years, and whether they had missed something that would have predicted the situation they were facing in 2019. This case study describes the steps taken to conduct a descriptive analysis of routine malaria surveillance data and demonstrates how to detect malaria outbreaks using historical data. It is useful for training Field Epidemiologists and public health officers involved in analysis of surveillance data.

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