Abstract
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. In this study, we used retrospective data (2013–2016) at national and district level to characterise 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, and also developed a Typhoid fever 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. In Kasese district, 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 following by seven weeks of precipitation. Our forecasting framework predicted outbreaks better at the district level rather than national. We 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 areas with high incidence of Typhoid fever 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 level.
Highlights
Typhoid fever is caused by Salmonella serovar Typhi and Paratyphi and affects approximately 21 million people annually of whom 222,000 succumb to the disease [1]
Descriptive statistics of typhoid fever at the district and national level There were 210204 Typhoid fever cases reported in Uganda between 2013 and 2016, which gives an incident rate of approximately 160 cases per 100000 people per year
For example; we used a) a time series analysis which identified annual risk periods between the 20th-40th week of each year (May to October), b) and a recorded high incidence of Typhoid fever in Bwera, Kisinga, Kagando Kyarumba and Kilembe sub-counties, c) we showed that incidence of these outbreaks is Epidemiology of Typhoid fever preceded by seven weeks of heavy precipitation occurring between the 15th-20th week (AprilMay) which are usually followed by people displacement due to flooding
Summary
Typhoid fever is caused by Salmonella serovar Typhi and Paratyphi and affects approximately 21 million people annually of whom 222,000 succumb to the disease [1]. It has been estimated that 5.6 billion people are at risk globally [2]. Environmental sanitation, food and water safety as well as limiting bacterial shedding by infectious. Epidemiology of Typhoid fever is no longer active. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding received for this study
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