Data from: Temporal, spatial and household dynamics of typhoid fever in Kasese district, Uganda

Typhoid fever affects 21 million people globally, 1% of whom succumb to the disease. The social, economic and public health consequences of this disease disproportionately affect people in Africa and Asia. In order to design context specific prevention strategies, we need to holistically characterise outbreaks in these settings. Here we used retrospective data (2013-2016) at national and district level to characterize temporal and spatial dynamics of typhoid fever outbreaks using time series and spatial analysis. We then selected cases matched with controls to investigate household socio-economic drivers using a conditional logistic regression model, in addition to develop a typhoid outbreak-forecasting framework. The incidence rate of typhoid fever at national and district level was ~ 160 and 60 cases per 100,000 persons per year, respectively, predominantly in urban areas. Bwera sub-county registered the highest incidence rate, followed by Kisinga, Kitholhu and Nyakiyumbu sub-counties. The male-female case ratio at district level was at 1.68 and outbreaks occurred between the 20th and 40th week (May and October) each year preceded by seven weeks of precipitation. Our forecasting framework predicts outbreaks better at the district rather than at the national level. We have identified a temporal window associated with typhoid fever outbreaks in Kasese district, which is preceded by precipitation, flooding and displacement of people. We also observed that high typhoid incidence areas also had high environmental contamination with limited water treatment. Taken together with the forecasting framework, this knowledge can inform the development of specific control and preparedness strategies at district and national levels. NATIONAL_DATASET.csv - Ministry of Health surveillance database (2013-2015) with corresponding weather used in the retrospective study HOSPITAL DATASET.csv - Health records of Typhoid fever patients from the three hospitals in Kasese district HOUSEHOLD DATASET.csv - Database from the Case-Control study FORECAST DATASET.csv - Ministry of Health Surveillance Database (2016-2017) used for validation of the forecast framework HOUSEHOLD DATASET.RData TYPHOID_ANALYSIS_RCODE.html TYPHOID_ANALYSIS_RCODE.Rmd KASESE_WEATHER_FORCASTING.csv