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Prioritizing interventions for cholera control in Kenya, 2015-2020
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Abstract
Kenya has experienced cholera outbreaks since 1971, with the most recent wave beginning in late 2014. Between 2015-2020, 32 of 47 counties reported 30,431 suspected cholera cases. The Global Task Force for Cholera Control (GTFCC) developed a
Global Roadmap for Ending Cholera by 2030
, which emphasizes the need to target multi-sectoral interventions to priority areas known as “cholera burden hotspots.” This study utilizes the GTFCC’s hotspot method to identify hotspots in Kenya at the county and sub-county administrative levels from 2015 through 2020. 32 of 47 (68.1%) counties reported cholera cases during this time while only 149 of 301 (49.5%) sub-counties reported cholera cases. The analysis identifies hotspots based on the mean annual incidence (MAI) over the past five-year period and cholera’s persistence in the area. Applying a MAI threshold of 90
th
percentile and the median persistence at both the county and sub-county levels, we identified 13 high risk sub-counties from 8 counties, including the 3 high risk counties of Garissa, Tana River and Wajir. This demonstrates that several sub-counties are high level hotspots while their counties are not. In addition, when cases reported by county versus sub-county hotspot risk are compared, 1.4 million people overlapped in the areas identified as both high-risk county and high-risk sub-county. However, assuming that finer scale data is more accurate, 1.6 million high risk sub-county people would have been misclassified as medium risk with a county-level analysis. Furthermore, an additional 1.6 million people would have been classified as living in high-risk in a county-level analysis when at the sub-county level, they were medium, low or no-risk sub-counties. This results in 3.2 million people being misclassified when county level analysis is utilized rather than a more-focused sub-county level analysis. This analysis highlights the need for more localized risk analyses to target cholera intervention and prevention efforts towards the populations most vulnerable.
Title: Prioritizing interventions for cholera control in Kenya, 2015-2020
Description:
Abstract
Kenya has experienced cholera outbreaks since 1971, with the most recent wave beginning in late 2014.
Between 2015-2020, 32 of 47 counties reported 30,431 suspected cholera cases.
The Global Task Force for Cholera Control (GTFCC) developed a
Global Roadmap for Ending Cholera by 2030
, which emphasizes the need to target multi-sectoral interventions to priority areas known as “cholera burden hotspots.
” This study utilizes the GTFCC’s hotspot method to identify hotspots in Kenya at the county and sub-county administrative levels from 2015 through 2020.
32 of 47 (68.
1%) counties reported cholera cases during this time while only 149 of 301 (49.
5%) sub-counties reported cholera cases.
The analysis identifies hotspots based on the mean annual incidence (MAI) over the past five-year period and cholera’s persistence in the area.
Applying a MAI threshold of 90
th
percentile and the median persistence at both the county and sub-county levels, we identified 13 high risk sub-counties from 8 counties, including the 3 high risk counties of Garissa, Tana River and Wajir.
This demonstrates that several sub-counties are high level hotspots while their counties are not.
In addition, when cases reported by county versus sub-county hotspot risk are compared, 1.
4 million people overlapped in the areas identified as both high-risk county and high-risk sub-county.
However, assuming that finer scale data is more accurate, 1.
6 million high risk sub-county people would have been misclassified as medium risk with a county-level analysis.
Furthermore, an additional 1.
6 million people would have been classified as living in high-risk in a county-level analysis when at the sub-county level, they were medium, low or no-risk sub-counties.
This results in 3.
2 million people being misclassified when county level analysis is utilized rather than a more-focused sub-county level analysis.
This analysis highlights the need for more localized risk analyses to target cholera intervention and prevention efforts towards the populations most vulnerable.
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