Spatial - Temporal Risk Factors of 2009 – 2019 Cholera Outbreaks among Residents of Nairobi City County Kenya

Abstract

Globally, cholera causes 1.3 to 4 million cases annually, with recurrent outbreaks in Sub-Saharan Africa driven by poor WASH conditions, climate change and urban growth. In Kenya, the disease is among other conditions monitored under the Integrated Disease Surveillance and Response strategy. The risk factors and the trend of cholera outbreaks vary from one place to the other. It is therefore imperative to establish the correlates of the disease, which are not well understood in the Sub-Saharan Africa including Kenya. This study sought to determine spatial-temporal risk factors of cholera outbreaks from 2009 to 2019 among residents of Nairobi City County, Kenya. This study applied a retrospective approach to study the historical cases of cholera recorded in Nairobi. Spatial analysis was applied to map the spatial-temporal variation of environmental and socio-economic factors associated with cholera outbreaks. The study also used a cross-sectional descriptive research design to establish the relationship between WASH conditions and the occurrence of cholera outbreaks in Nairobi City County. The target population was 1,302,325 households in Nairobi City County. The target population also included head of public health in the Ministry of Health in the national government, head of public health in the County government of Nairobi and 8 Disease Surveillance Coordinators from each Sub-County in Nairobi City County. Stratified random sampling techniques was applied to select 399 respondents across the 8 Sub-Counties in Nairobi City County. Proportional sampling was applied to determine the number of target respondents from 8 different Sub-Counties in Nairobi City County. Systematic sampling technique was applied to select the respondents of the study. Purposive sampling was also used in the selection of the key informants. Primary data was collected by use of survey questionnaires and key informants interview guide. Secondary data was gathered from the Ministry of Health, World Health Organization (WHO) bulletins, the Nairobi City County Disease Surveillance department and Survey of Kenya. Quantitative data from the survey questionnaires was analyzed using descriptive and inferential statistics and the results were presented in a prose form. On the other hand, qualitative data was analyzed using thematic analysis and the results were presented in a narrative form. Secondary data was analyzed using geospatial analysis. The study found that frequent cholera outbreaks are likely to occur in the slums and other densely populated areas. This study also established that cholera outbreaks in Nairobi were partly influenced by environmental factors, with most cases linked to densely populated informal settlements and large population sizes. The results indicated that changes in the amount of monthly rainfall in Nairobi showed a significant relationship with variation in the number of cholera cases (p-value<0.05). However, temperature had no significant relationship with changes in the number of cholera cases (p-value>0.05). In addition, the study also established that the top five WASH challenges associated with the spread of Cholera disease included lack of enough water supply (76%); poor personal hygiene (54%); poor waste water management (54%); poor community hygiene and sanitation (55%); and poorly maintained sewage facilities in the residential areas (44%). Also, the findings indicated that areas located within 400m to rivers and sewage lines were more prone to Cholera cases. The study concluded that cholera outbreaks in Nairobi (2009–2019) were influenced by spatial-temporal factors, with dense informal settlements, poor sanitation, rainfall, and proximity to water sources driving the disease's spread. The study recommends strengthening cholera monitoring through early warning systems incorporating environmental data, improving sanitation and hygiene practices in high-risk areas, and enforcing urban planning regulations to prevent development near contamination sources.