Prioritizing interventions for cholera control in Kenya, 2015-2020.

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 in priority 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 90th 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.

An epidemiological analysis of Acute Flaccid Paralysis (AFP) surveillance in Kenya, 2016 to 2018.

BACKGROUND: The poliovirus has been targeted for eradication since 1988. Kenya reported its last case of indigenous Wild Poliovirus (WPV) in 1984 but suffered from an outbreak of circulating Vaccine-derived Poliovirus type 2 (cVDPV2) in 2018. We aimed to describe Kenya's polio surveillance performance 2016-2018 using WHO recommended polio surveillance standards. METHODS: Retrospective secondary data analysis was conducted using Kenyan AFP surveillance case-based database from 2016 to 2018. Analyses were carried out using Epi-Info statistical software (version 7) and mapping was done using Quantum Geographic Information System (GIS) (version 3.4.1). RESULTS: Kenya reported 1706 cases of AFP from 2016 to 2018. None of the cases were confirmed as poliomyelitis. However, 23 (1.35%) were classified as polio compatible. Children under 5 years accounted for 1085 (63.6%) cases, 937 (55.0%) cases were boys, and 1503 (88.1%) cases had received three or more doses of Oral Polio Vaccine (OPV). AFP detection rate substantially increased over the years; however, the prolonged health workers strike in 2017 negatively affected key surveillance activities. The mean Non-Polio (NP-AFP) rate during the study period was 2.87/ 100,000 children under 15 years, and two adequate specimens were collected for 1512 (88.6%) AFP cases. Cumulatively, 31 (66.0%) counties surpassed target for both WHO recommended AFP quality indicators. CONCLUSIONS: The performance of Kenya's AFP surveillance system surpassed the minimum WHO recommended targets for both non-polio AFP rate and stool adequacy during the period studied. In order to strengthen the country's polio free status, health worker's awareness on AFP surveillance and active case search should be strengthened in least performing counties to improve case detection. Similar analyses should be done at the sub-county level to uncover underperformance that might have been hidden by county level analysis.

Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya.

BACKGROUND: Effective public health surveillance systems are crucial for early detection and response to outbreaks. In 2016, Kenya transitioned its surveillance system from a standalone web-based surveillance system to the more sustainable and integrated District Health Information System 2 (DHIS2). As part of Global Health Security Agenda (GHSA) initiatives in Kenya, training on use of the new system was conducted among surveillance officers. We evaluated the surveillance indicators during the transition period in order to assess the impact of this training on surveillance metrics and identify challenges affecting reporting rates. METHODS: From February to May 2017, we analysed surveillance data for 13 intervention and 13 comparison counties. An intervention county was defined as one that had received refresher training on DHIS2 while a comparison county was one that had not received training. We evaluated the impact of the training by analysing completeness and timeliness of reporting 15 weeks before and 12 weeks after the training. A chi-square test of independence was used to compare the reporting rates between the two groups. A structured questionnaire was administered to the training participants to assess the challenges affecting surveillance reporting. RESULTS: The average completeness of reporting for the intervention counties increased from 45 to 62%, i.e. by 17 percentage points (95% CI 16.14-17.86) compared to an increase from 49 to 52% for the comparison group, i.e. by 3 percentage points (95% CI 2.23-3.77). The timeliness of reporting increased from 30 to 51%, i.e. by 21 percentage points (95% CI 20.16-21.84) for the intervention group, compared to an increase from 31 to 38% for the comparison group, i.e.by 7 percentage points (95% CI 6.27-7.73). Major challenges for the low reporting rates included lack of budget support from government, lack of airtime for reporting, health workers strike, health facilities not sending surveillance data, use of wrong denominator to calculate reporting rates and surveillance officers having other competing tasks. CONCLUSIONS: Training plays an important role in improving public health surveillance reporting. However, to improve surveillance reporting rates to the desired national targets, other challenges affecting reporting must be identified and addressed accordingly.

Health worker knowledge of Integrated Disease Surveillance and Response standard case definitions: a cross-sectional survey at rural health facilities in Kenya.

BACKGROUND: The correct knowledge of standard case definition is necessary for frontline health workers to diagnose suspected diseases across Africa. However, surveillance evaluations commonly assume this prerequisite. This study assessed the knowledge of case definitions for health workers and their supervisors for disease surveillance activities in rural Kenya. METHODS: A cross-sectional survey including 131 health workers and their 11 supervisors was undertaken in two counties in Kenya. Descriptive analysis was conducted to classify the correctness of knowledge into four categories for three tracer diseases (dysentery, measles, and dengue). We conducted a univariate and multivariable logistic regression analyses to explore factors influencing knowledge of the case definition for dysentery. RESULTS: Among supervisors, 81.8% knew the correct definition for dysentery, 27.3% for measles, and no correct responses were provided for dengue. Correct knowledge was observed for 50.4% of the health workers for dysentery, only 12.2% for measles, and none for dengue. Of 10 examined factors, the following were significantly associated with health workers' correct knowledge of the case definition for dysentery: health workers' cadre (aOR 2.71; 95% CI 1.20-6.12; p = 0.017), and display of case definition poster (aOR 2.24; 95% CI 1.01-4.98; p = 0.048). Health workers' exposure to the surveillance refresher training, supportive supervision and guidelines were not significantly associated with the knowledge. CONCLUSION: The correct knowledge of standard case definitions was sub-optimal among health workers and their supervisors, which is likely to impact the reliability of routine surveillance reports generated from health facilities.

Understanding mSOS: A qualitative study examining the implementation of a text-messaging outbreak alert system in rural Kenya.

Outbreaks of epidemic diseases pose serious public health risks. To overcome the hurdles of sub-optimal disease surveillance reporting from the health facilities to relevant authorities, the Ministry of Health in Kenya piloted mSOS (mobile SMS-based disease outbreak alert system) in 2013-2014. In this paper, we report the results of the qualitative study, which examined factors that influence the performances of mSOS implementation. In-depth interviews were conducted with 11 disease surveillance coordinators and 32 in-charges of rural health facilities that took part in the mSOS intervention. Drawing from the framework analysis, dominant themes that emerged from the interviews are presented. All participants voiced their excitement in using mSOS. The results showed that the technology was well accepted, easy to use, and both health workers and managers unanimously recommended the scale-up of the system despite challenges encountered in the implementation processes. The most challenging components were the context in which mSOS was implemented, including the lack of strong existing structure for continuous support supervision, feedback and response action related to disease surveillance. The study revealed broader health systems issues that should be addressed prior to and during the intervention scale-up.

Effectiveness of a Mobile Short-Message-Service-Based Disease Outbreak Alert System in Kenya.

We conducted a randomized, controlled trial to test the effectiveness of a text-messaging system used for notification of disease outbreaks in Kenya. Health facilities that used the system had more timely notifications than those that did not (19.2% vs. 2.6%), indicating that technology can enhance disease surveillance in resource-limited settings.

Molecular epidemiology of geographically dispersed Vibrio cholerae, Kenya, January 2009-May 2010.

Numerous outbreaks of cholera have occurred in Kenya since 1971. To more fully understand the epidemiology of cholera in Kenya, we analyzed the genetic relationships among 170 Vibrio cholerae O1 isolates at 5 loci containing variable tandem repeats. The isolates were collected during January 2009-May 2010 from various geographic areas throughout the country. The isolates grouped genetically into 5 clonal complexes, each comprising a series of genotypes that differed by an allelic change at a single locus. No obvious correlation between the geographic locations of the isolates and their genotypes was observed. Nevertheless, geographic differentiation of the clonal complexes occurred. Our analyses showed that multiple genetic lineages of V. cholerae were simultaneously infecting persons in Kenya. This finding is consistent with the simultaneous emergence of multiple distinct genetic lineages of V. cholerae from endemic environmental reservoirs rather than recent introduction and spread by travelers.