Cholera remains a major public health challenge in Kenya, driven by environmental pollution, poor water, sanitation, and hygiene (WASH) facilities, weak monitoring systems, and climate effects. While there have been improvements in studying the disease, testing, monitoring, and environmental checks, the spread continues, especially in informal settlements, rural areas, and refugee camps. This review looked at 106 peer-reviewed studies published between 1979 and 2024. It aimed to describe the scope, progress, and gaps in cholera research in Kenya. Five databases, including Google Scholar, Web of Science, PubMed, Embase, and Scopus, were searched using the terms "cholera" and "Kenya." Titles and abstracts were reviewed using Rayyan, and data were collected using a standard form that noted study goals, methods, findings, limitations, and geographic coverage. The evidence was analysed thematically, and trends were tracked over time. Among 845 records found, 106 met the criteria for inclusion. The literature consistently connects cholera outbreaks in Kenya to climate events like flooding, drought, and El Niño, with greater vulnerability seen in informal settlements and refugee areas. Surveillance systems are still disconnected, often leading to delays in reporting and limited information at sub-county levels. Assessments of the health system reveal ongoing issues, including a shortage of laboratory resources and necessary tests. Despite innovations such as rapid diagnostic tests, whole-genome sequencing, and spatial modelling that have enhanced outbreak detection and understanding of transmission, their regular use is hindered by cost, infrastructure, and workforce issues. Social and behavioural factors, such as low-risk perception and gaps between knowledge and practice, also contribute to continued transmission. In summary, controlling cholera in Kenya needs a coordinated, multi-faceted approach. This should focus on strengthening surveillance, improving WASH facilities, increasing laboratory and molecular capabilities, expanding vaccine access, and fostering community-led efforts to turn scientific progress into effective public health measures.

The 10-valent pneumococcal conjugate vaccine (PCV-10) has reduced the burden of pneumococcal disease in children. Integrated facility-based sentinel surveillance (IFBS) monitors a range of common causes of febrile illnesses in Kenya. We used this system to assess the real-world vaccine effectiveness (VE) of PCV-10 against hypoxemia among children with suspected pneumonia in Kenya. We analysed IFBS data collected from 13 sites across Kenya from 2017 to 2024. We included children aged 6 weeks to 59 months with reported fever or temperature ≥38.0°C, respiratory features consistent with suspected pneumonia, and a copy of their vaccination records (i.e., child health booklet). We excluded children with a positive test result indicating a non-Pneumococcal aetiology (i.e., positive result on a multiplex PCR, malaria microscopy or rapid diagnostic test, or SARS-CoV-2 PCR). We assessed the association of vaccination status with hypoxemia, defined as an oxygen saturation of ≤90%, adjusting for age, sex, and year. VE was calculated as 1 minus the odds ratio of hypoxemia among children with suspected pneumonia calculated using generalized estimating equations to account for clustering by site. Overall, 3,533 children were analysed, with 94% being up to date with PCV-10 vaccination. The median patient age was 11 months (interquartile range: 6-17). Hypoxemia was observed in 37% of fully vaccinated children, 41% in partially vaccinated children, and 52% in unvaccinated children (χ² test, p = 0.03). The adjusted VE for full vaccination against hypoxemia in children with suspected pneumonia was 39% (95% confidence interval: 6-61%). Among children with suspected pneumonia in Kenya, PCV-10 vaccination was associated with reduced hypoxemia. The PCV-10 coverage in this dataset was high, potentially reflecting a robust routine vaccination effort since PCV-10 was introduced in Kenya in 2011. High-quality surveillance data can be used to provide real-world evidence to support routine immunization programs.

Visceral leishmaniasis (VL) remains a major public health challenge, disproportionally affecting populations with limited access to timely diagnosis and treatment. National summaries often mask substantial local heterogeneity in disease risk and healthcare access, limiting their usefulness for targeted control and elimination. We analysed ten years (2016–2025) of routine facility-based surveillance data from Kenya using Bayesian small-area estimation and geospatial accessibility modelling to quantify fine-scale variation in disease burden, identify key determinants, and optimise access to treatment services. A total of 11,985 cases were reported, corresponding to an estimated incidence of 10 cases per 100,000 population per year, with marked seasonality and epidemic periods. Disease burden was highly focal: five northern counties accounted for 86% of all cases, with further clustering at sub-county and ward levels. Predicted VL incidence exceeded 100 cases per 100,000 person-years in several wards, predominantly in Turkana and West Pokot counties. Higher temperatures, poverty, and poor housing quality were positively associated with increased probability of VL occurrence and higher case counts, whereas higher precipitation was negatively associated. Under the current configuration of 46 treatment centres, only 45% of the population in need could access care within 120 minutes of motorised travel. Adding five optimally located facilities increased this 120-minute coverage to 76%, with diminishing gains from further expansion. Together, these findings demonstrate how integrating small-area disease modelling with geospatial accessibility analysis can reveal hidden inequities in VL burden and inform more equitable and efficient deployment of treatment services, supporting targeted interventions and accelerating progress towards elimination.

Cholera Priority Areas for Multisectoral Interventions (PAMIs), formerly known as "hotspots", are limited geographical areas where cholera persists or regularly reappears due to cultural, environmental, and socioeconomic conditions. Focusing interventions on PAMIs will help to effectively control and ultimately eliminate cholera among the most at-risk populations. The 2023 GTFCC Methodology was used to identify PAMIs for cholera control in Kenya. The analysis was conducted between February and March 2024, selecting PAMIs based on the previous six years' epidemiological data (Jan 2018 - Dec 2023) at the sub-county level. Epidemiological data was sourced from cholera outbreak line lists. The line list included both confirmed and suspected cholera cases of all ages admitted or reported to health facilities. The numerical priority index was calculated as a sum of four epidemiological indicators: incidence, mortality, persistence, and laboratory testing. Following a validation workshop, stakeholders selected a priority index threshold, identifying 78 sub-counties as initial PAMIs. There were 29 additional PAMIs included in the final list of 107 priority sub-counties based on country-specific vulnerability factors. This evidence-based approach will inform the targeting and implementation of multi-sectoral interventions in line with the Kenya National Cholera Plan.

We report the genome of a case of mpox detected in Kenya involving a truck driver with travel history to Uganda. Whole genome sequencing and phylogenetic analysis of the mpox virus (MPXV) showed that the genome clustered with clade Ib, which was recently identified in the Democratic Republic of Congo.

Cholera continues to cause many outbreaks in low and middle-income countries due to inadequate water, sanitation, and hygiene services. We describe a protracted cholera outbreak in Nairobi City County, Kenya in 2017. We reviewed the cholera outbreak line lists from Nairobi City County in 2017 to determine its extent and factors associated with death. A suspected case of cholera was any person aged >2 years old who had acute watery diarrhea, nausea, or vomiting, whereas a confirmed case was where Vibrio cholerae was isolated from the stool specimen. We summarized cases using means for continuous variables and proportions for categorical variables. Associations between admission status, sex, age, residence, time to care seeking, and outbreak settings; and cholera associated deaths were assessed using odds ratio (OR) with 95% confidence interval (CI). Of the 2,737 cholera cases reported, we analyzed 2,347 (85.7%) cases including 1,364 (58.1%) outpatients, 1,724 (73.5%) not associated with mass gathering events, 1,356 (57.8%) male and 2,202 (93.8%) aged ≥5 years, and 35 deaths (case fatality rate: 1.5%). Cases were reported from all the Sub Counties of Nairobi City County with an overall county attack rate of 50 per 100,000 people. Vibrio cholerae Ogawa serotype was isolated from 78 (34.8%) of the 224 specimens tested and all isolates were sensitive to tetracycline and levofloxacin but resistant to amikacin. The odds of cholera-related deaths was lower among outpatient cases (aOR: 0.35; [95% CI: 0.17-0.72]), age ≥5 years old (aOR: 0.21 [95% CI: 0.09-0.55]), and mass gathering events (aOR: 0.26 [95% CI: 0.07-0.91]) while threefold higher odds among male (aOR: 3.04 [95% CI: 1.30-7.13]). Nairobi City County experienced a protracted and widespread cholera outbreak with a high case fatality rate in 2017.

Mpox is a zoonotic disease caused by the Monkeypox virus (MPXV) in the family: Poxviridae, genus: Orthopoxvirus. Historically, the disease was restricted mostly to Africa with cases being reported in Central Africa (mostly caused by clade I) and in West Africa (caused by clade II). However, there has been a recent shift in the virus range with outbreaks being reported in Europe and America, and in countries where the virus was initially not endemic. This multi-country outbreak was driven mostly by clade IIb lineage of MPXV. Since December 2023, there has been an ongoing mpox outbreak in the Democratic Republic of Congo (DRC), driven by a new clade I lineage of the virus, designated clade Ib. The DRC outbreak has persisted, with an increase in cases being reported over the past few months. Spillover of these outbreak-related cases to the neighbouring countries have also been reported in multiple countries including Uganda and Rwanda. Here, we report the rapid application of unbiased metagenomic next generation sequencing (mNGS) to reconstruct the genome sequence of the first reported case of MPXV in Kenya. Our findings show that the Kenyan case clusters together with clade Ib MPXV strains, associated with the sustained outbreak in the DRC. Clade Ib lineage has been associated with continuing geographical expansion of the virus to previously unaffected areas, high incidence of the disease as well as high case fatality (CFR 4.9-6.7%). Similar to other clade Ib strains, the Kenyan strain carries predominant APOBEC3-type mutations which is characteristic feature of human-to-human transmission, highlighting the need for surveillance to curtail any potential expansion of this MPXV strain. The lack of information on genomes associated with cases reported in different East African countries, is a gap that urgently needs to be addressed to aid in the monitoring of this MPXV strain. This case investigation, therefore, underscores the need for sequencing efforts to be enhanced across the continent to help improve our understanding of the geographical range and diversity of the MPXV strains, especially those belonging to clade I which is currently under-represented. ### Competing Interest Statement The authors have declared no competing interest.

Cholera is an issue of major public health importance. It was first reported in Kenya in 1971, with the country experiencing outbreaks through the years, most recently in 2021. Factors associated with the outbreaks in Kenya include open defecation, population growth with inadequate expansion of safe drinking water and sanitation infrastructure, population movement from neighboring countries, crowded settings such as refugee camps coupled with massive displacement of persons, mass gathering events, and changes in rainfall patterns. The Ministry of Health, together with other ministries and partners, revised the national cholera control plan to a multisectoral cholera elimination plan that is aligned with the Global Roadmap for Ending Cholera. One of the key features in the revised plan is the identification of hotspots. The hotspot identification exercise followed guidance and tools provided by the Global Task Force on Cholera Control (GTFCC). Two epidemiological indicators were used to identify the sub-counties with the highest cholera burden: incidence per population and persistence. Additionally, two indicators were used to identify sub-counties with poor WASH coverage due to low proportions of households accessing improved water sources and improved sanitation facilities. The country reported over 25,000 cholera cases between 2015 and 2019. Of 290 sub-counties, 25 (8.6%) sub-counties were identified as a high epidemiological priority; 78 (26.9%) sub-counties were identified as high WASH priority; and 30 (10.3%) sub-counties were considered high priority based on a combination of epidemiological and WASH indicators. About 10% of the Kenyan population (4.89 million) is living in these 30-combination high-priority sub-counties. The novel method used to identify cholera hotspots in Kenya provides useful information to better target interventions in smaller geographical areas given resource constraints. Kenya plans to deploy oral cholera vaccines in addition to WASH interventions to the populations living in cholera hotspots as it targets cholera elimination by 2030.

The majority of Kenya’s > 3 million camels have antibodies against Middle East respiratory syndrome coronavirus (MERS-CoV), although human infection in Africa is rare. We enrolled 243 camels aged 0–24 months from 33 homesteads in Northern Kenya and followed them between April 2018 to March 2020. We collected and tested camel nasal swabs for MERS-CoV RNA by RT-PCR followed by virus isolation and whole genome sequencing of positive samples. We also documented illnesses (respiratory or other) among the camels. Human camel handlers were also swabbed, screened for respiratory signs, and samples were tested for MERS-CoV by RT-PCR. We recorded 68 illnesses among 58 camels, of which 76.5% (52/68) were respiratory signs and the majority of illnesses (73.5% or 50/68) were recorded in 2019. Overall, 124/4692 (2.6%) camel swabs collected from 83 (34.2%) calves in 15 (45.5%) homesteads between April–September 2019 screened positive, while 22 calves (26.5%) recorded reinfections (second positive swab following ≥ 2 consecutive negative tests). Sequencing revealed a distinct Clade C2 virus that lacked the signature ORF4b deletions of other Clade C viruses. Three previously reported human PCR positive cases clustered with the camel infections in time and place, strongly suggesting sporadic transmission to humans during intense camel outbreaks in Northern Kenya.

Introduction: The Ministry of Health, Kenya (MOH) investigated a report on acute watery diarrhea (AWD) cases at a city hotel to confirm the cause, characterize, and identify associated factors. Methods: A suspected case of cholera was defined as AWD in any person aged >2 years at the hotel from August 31, 2017, to September 6, 2017. We took rectal swabs for laboratory confirmation and summarized the AWD data by person, place, and time. We defined a cohort of hotel staff with those who ate dinner on August 31, 2017, considered exposed and conducted a retrospective cohort study. We calculated attack rates (AR) and risk ratios (RR) with 95% confidence interval. Variables with p<0.1 at bivariate analysis were entered into a multivariate model and those with p<0.05 in the final model considered independently associated with the AWD. Results: Vibrio cholera was isolated from seven (10.1%) out of 69 samples. Line listed 139 cases with a median age of 32 years (Range: 20–58 years) included 127 (91.4%) male and 127 (91.4%) guests. Index case was reported on August 31, 2017, cases peaked at 95 cases on September 3, 2017, and declined to three on September 6, 2017. A total of 30 (81.1%) of 37 hotel staff were exposed with 17 (56.7%) cases. Food specific ARs were: steamed spinach 78.6% and pineapples 26.3%. Spinach (RR: 3.0 (95%CI: 1.76-72.97)) was a risk factor while pineapples (RR: 0.4 (95%CI: 0.01-0.58)) was protective. Conclusion: This was a point source cholera outbreak likely due to eating contaminated spinach.

Background Kenya detected the first case of COVID-19 on March 13, 2020, and as of July 30, 2020, 17 975 cases with 285 deaths (case fatality rate (CFR) = 1.6%) had been reported. This study described the cases during the early phase of the pandemic to provide information for monitoring and response planning in the local context. Methods We reviewed COVID-19 case records from isolation centres while considering national representation and the WHO sampling guideline for clinical characterization of the COVID-19 pandemic within a country. Socio-demographic, clinical, and exposure data were summarized using median and mean for continuous variables and proportions for categorical variables. We assigned exposure variables to socio-demographics, exposure, and contact data, while the clinical spectrum was assigned outcome variables and their associations were assessed. Results A total of 2796 case records were reviewed including 2049 (73.3%) male, 852 (30.5%) aged 30-39 years, 2730 (97.6%) Kenyans, 636 (22.7%) transporters, and 743 (26.6%) residents of Nairobi City County. Up to 609 (21.8%) cases had underlying medical conditions, including hypertension (n = 285 (46.8%)), diabetes (n = 211 (34.6%)), and multiple conditions (n = 129 (21.2%)). Out of 1893 (67.7%) cases with likely sources of exposure, 601 (31.8%) were due to international travel. There were 2340 contacts listed for 577 (20.6%) cases, with 632 contacts (27.0%) being traced. The odds of developing COVID-19 symptoms were higher among case who were aged above 60 years (odds ratio (OR) = 1.99, P = 0.007) or had underlying conditions (OR = 2.73, P < 0.001) and lower among transport sector employees (OR = 0.31, P < 0.001). The odds of developing severe COVID-19 disease were higher among cases who had underlying medical conditions (OR = 1.56, P < 0.001) and lower among cases exposed through community gatherings (OR = 0.27, P < 0.001). The odds of survival of cases from COVID-19 disease were higher among transport sector employees (OR = 3.35, P = 0.004); but lower among cases who were aged >= 60 years (OR = 0.58, P = 0.034) and those with underlying conditions (OR = 0.58, P = 0.025). Conclusion The early phase of the COVID-19 pandemic demonstrated a need to target the elderly and comorbid cases with prevention and control strategies while closely monitoring asymptomatic cases.

Rapid detection and response to infectious disease outbreaks requires a robust surveillance system with a sufficient number of trained public health workforce personnel. The Frontline Field Epidemiology Training Program (Frontline) is a focused 3-month program targeting local ministries of health to strengthen local disease surveillance and reporting capacities. Limited literature exists on the impact of Frontline graduates on disease surveillance completeness and timeliness reporting. Using routinely collected Ministry of Health data, we mapped the distribution of graduates between 2014 and 2017 across 47 Kenyan counties. Completeness was defined as the proportion of complete reports received from health facilities in a county compared with the total number of health facilities in that county. Timeliness was defined as the proportion of health facilities submitting surveillance reports on time to the county. Using a panel analysis and controlling for county-fixed effects, we evaluated the relationship between the number of Frontline graduates and priority disease reporting of measles. We found that Frontline training was correlated with improved completeness and timeliness of weekly reporting for priority diseases. The number of Frontline graduates increased by 700%, from 57 graduates in 2014 to 456 graduates in 2017. The annual average rates of reporting completeness increased from 0.8% in 2014 to 55.1% in 2017. The annual average timeliness reporting rates increased from 0.1% in 2014 to 40.5% in 2017. These findings demonstrate how global health security implementation progress in workforce development may influence surveillance and disease reporting.

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.

Introduction in 2015, a cholera outbreak was confirmed in Nairobi county, Kenya, which we investigated to identify risk factors for infection and recommend control measures. Methods we analyzed national cholera surveillance data to describe epidemiological patterns and carried out a case-control study to find reasons for the Nairobi county outbreak. Suspected cholera cases were Nairobi residents aged >2 years with acute watery diarrhea (>4 stools/≤12 hours) and illness onset 1-14 May 2015. Confirmed cases had Vibrio cholerae isolated from stool. Case-patients were frequency-matched to persons without diarrhea (1:2 by age group, residence), interviewed using standardized questionaires. Logistic regression identified factors associated with case status. Household water was analyzed for fecal coliforms and Escherichia coli. Results during December 2014-June 2015, 4,218 cholera cases including 282 (6.7%) confirmed cases and 79 deaths (case-fatality rate [CFR] 1.9%) were reported from 14 of 47 Kenyan counties. Nairobi county reported 781 (19.0 %) cases (attack rate, 18/100,000 persons), including 607 (78%) hospitalisations, 20 deaths (CFR 2.6%) and 55 laboratory-confirmed cases (7.0%). Seven (70%) of 10 water samples from communal water points had coliforms; one had Escherichia coli. Factors associated with cholera in Nairobi were drinking untreated water (adjusted odds ratio [aOR] 6.5, 95% confidence interval [CI] 2.3-18.8), lacking health education (aOR 2.4, CI 1.1-7.9) and eating food outside home (aOR 2.4, 95% CI 1.2-5.7). Conclusion we recommend safe water, health education, avoiding eating foods prepared outside home and improved sanitation in Nairobi county. Adherence to these practices could have prevented this protacted cholera outbreak.

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.

Background: Infectious diseases remain one of the greatest threats to public health globally. Effective public health surveillance systems are therefore needed to provide timely and accurate information for early detection and response. 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 completeness of reporting increased significantly after the training by 17 percentage points (from 45% to 62%) for the intervention group compared to 3 percentage points (49% to 52%) for the comparison group. Timeliness of reporting increased significantly by 21 percentage points (from 30% to 51%) for the intervention group compared to 7 percentage points (from 31% to 38%) for the comparison group. Major challenges identified 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 being given 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.

Kenya is endemic for cholera with different waves of outbreaks having been documented since 1971. In recent years, new variants of Vibrio cholerae O1 have emerged and have replaced most of the traditional El Tor biotype globally. These strains also appear to have increased virulence, and it is important to describe and document their phenotypic and genotypic traits. This study characterized 146 V. cholerae O1 isolates from cholera outbreaks that occurred in Kenya between 1975 and 2017. Our study reports that the 1975-1984 strains had typical classical or El Tor biotype characters. New variants of V. cholerae O1 having traits of both classical and El Tor biotypes were observed from 2007 with all strains isolated between 2015 and 2017 being sensitive to polymyxin B and carrying both classical and El Tor type ctxB. All strains were resistant to Phage IV and harbored rstR, rtxC, hlyA, rtxA and tcpA genes specific for El Tor biotype indicating that the strains had an El Tor backbone. Pulsed field gel electrophoresis (PFGE) genotyping differentiated the isolates into 14 pulsotypes. The clustering also corresponded with the year of isolation signifying that the cholera outbreaks occurred as separate waves of different genetic fingerprints exhibiting different genotypic and phenotypic characteristics. The emergence and prevalence of V. cholerae O1 strains carrying El Tor type and classical type ctxB in Kenya are reported. These strains have replaced the typical El Tor biotype in Kenya and are potentially more virulent and easily transmitted within the population.

Chikungunya is a reemerging vector borne pathogen associated with severe morbidity in affected populations. Lamu, along the Kenyan coast was affected by a major chikungunya outbreak in 2004. Twelve years later, we report on entomologic investigations and laboratory confirmed chikungunya cases in northeastern Kenya. Patient blood samples were received at the Kenya Medical Research Institute (KEMRI) viral hemorrhagic fever laboratory and the immunoglobulin M enzyme linked immunosorbent assay (IgM ELISA) was used to test for the presence of IgM antibodies against chikungunya and dengue. Reverse transcription polymerase chain reaction (RT-PCR) utilizing flavivirus, alphavirus and chikungunya specific primers were used to detect acute infections and representative PCR positive samples sequenced to confirm the circulating strain. Immature mosquitoes were collected from water-holding containers indoors and outdoors in the affected areas in northeastern Kenya. A total of 189 human samples were tested; 126 from Kenya and 63 from Somalia. 52.9% (100/189) tested positive for Chikungunya virus (CHIKV) by either IgM ELISA or RT-PCR. Sequence analysis of selected samples revealed that the virus was closely related to that from China (2010). 29% (55/189) of the samples, almost all from northeastern Kenya or with a history of travel to northern Kenya, tested positive for dengue IgM antibodies. Entomologic risk assessment revealed high house, container and Breteau indices of, 14.5, 41.9 and 17.1% respectively. Underground water storage tanks were the most abundant, 30.1%, of which 77.4% were infested with Aedes aegypti mosquitoes. These findings confirm the presence of active chikungunya infections in the northeastern parts of Kenya. The detection of dengue IgM antibodies concurrently with chikungunya virus circulation emphasizes on the need for improved surveillance systems and diagnostic algorithms with the capacity to capture multiple causes of arbovirus infections as these two viruses share common vectors and eco-systems. In addition sustained entomological surveillance and vector control programs targeting most productive containers are needed to monitor changes in vector densities, for early detection of the viruses and initiate vector control efforts to prevent possible outbreaks.

Introduction Measles is targeted for elimination in the World Health Organization African Region by the year 2020. In 2011, Kenya was off track in attaining the 2012 pre-elimination goal. We describe the epidemiology of measles in Kenya and assess progress made towards elimination. Methods We reviewed national case-based measles surveillance and immunization data from January 2003 to December 2016. A case was confirmed if serum was positive for anti-measles IgM antibody, was epidemiologically linked to a laboratory-confirmed case or clinically compatible. Data on case-patient demographics, vaccination status, and clinical outcome and measles containing vaccine (MCV) coverage were analyzed. We calculated measles surveillance indicators and incidence, using population estimates for the respective years. Results The coverage of first dose MCV (MCV1) increased from 65% to 86% from 2003-2012, then declined to 75% in 2016. Coverage of second dose MCV (MCV2) remained < 50% since introduction in 2013. During 2003-2016, there were 26,188 suspected measles cases were reported, with 9043(35%) confirmed cases, and 165 deaths (case fatality rate, 1.8%). The non-measles febrile rash illness rate was consistently > 2/100,000 population, and “80% of the sub-national level investigated a case in 11 of the 14 years. National incidence ranged from 4 to 62/million in 2003-2006 and decreased to 3/million in 2016. The age specific incidence ranged from 1 to 364/million population and was highest among children aged < 1 year. Conclusion Kenya has made progress towards measles elimination. However, this progress remains at risk and the recent declines in MCV1 coverage and the low uptake in MCV2 could reverse these gains.

Background: From December 2014 to September 2016, a cholera outbreak in Kenya, the largest since 2010, caused 16,840 reported cases and 256 deaths. The outbreak affected 30 of Kenya's 47 counties and occurred shortly after the decentralization of many healthcare services to the county level. This mixed-methods study, conducted June-July 2015, assessed cholera preparedness in Homa Bay, Nairobi, and Mombasa counties and explored clinic-and community-based health care workers' (HCW) experiences during outbreak response. Methods: Counties were selected based on cumulative cholera burden and geographic characteristics. We conducted 44 health facility cholera preparedness checklists (according to national guidelines) and 8 focus group discussions (FGDs). Frequencies from preparedness checklists were generated. To determine key themes from FGDs, inductive and deductive codes were applied; MAX software for qualitative data analysis (MAXQDA) was used to identify patterns. Results: Some facilities lacked key materials for treating cholera patients, diagnosing cases, and maintaining infection control. Overall, 82% (36/44) of health facilities had oral rehydration salts, 65% (28/43) had IV fluids, 27% (12/44) had rectal swabs, 11% (5/44) had Cary-Blair transport media, and 86% (38/44) had gloves. A considerable number of facilities lacked disease reporting forms (34%, 14/41) and cholera treatment guidelines (37%, 16/43). In FDGs, HCWs described confusion regarding roles and reporting during the outbreak, which highlighted issues in coordination and management structures within the health system. Similar to checklist findings, FGD participants described supply challenges affecting laboratory preparedness and infection prevention and control. Perceived successes included community engagement, health education, strong collaboration between clinic and community HCWs, and HCWs' personal passion to help others. Conclusions: The confusion over roles, reporting, and management found in this evaluation highlights a need to adapt, implement, and communicate health strategies at the county level, in order to inform and train HCWs during health system transformations. International, national, and county stakeholders could strengthen preparedness and response for cholera and other public health emergencies in Kenya, and thereby strengthen global health security, through further investment in the existing Integrated Disease Surveillance and Response structure and national cholera prevention and control plan, and the adoption of county-specific cholera control plans.