Search

Background Coxiella burnetii is a widely distributed pathogen, but data on its epidemiology in livestock, and human populations remain scanty, especially in developing countries such as Kenya. We used the One Health approach to estimate the seroprevalance of C. burnetii in cattle, sheep, goats and human populations in Tana River county, and in humans in Garissa county, Kenya. We also identified potential determinants of exposure among these hosts. Methods Data were collected through a cross-sectional study. Serum samples were taken from 2,727 animals (466 cattle, 1,333 goats, and 928 sheep) and 974 humans and screened for Phase I/II IgG antibodies against C. burnetii using enzyme-linked immunosorbent assay (ELISA). Data on potential factors associated with animal and human exposure were collected using a structured questionnaire. Multivariable analyses were performed with households as a random effect to adjust for the within-household correlation of C. burnetii exposure among animals and humans, respectively. Results The overall apparent seroprevalence estimates of C. burnetii in livestock and humans were 12.80% (95% confidence interval [CI]: 11.57–14.11) and 24.44% (95% CI: 21.77–27.26), respectively. In livestock, the seroprevalence differed significantly by species (p < 0.01). The highest seroprevalence estimates were observed in goats (15.22%, 95% CI: 13.34-17.27) and sheep (14.22%, 95% CI: 12.04–16.64) while cattle (3.00%, 95% CI: 1.65–4.99) had the lowest seroprevalence. Herd-level seropositivity of C. burnetii in livestock was not positively associated with human exposure. Multivariable results showed that female animals had higher odds of seropositivity for C. burnetii than males, while for animal age groups, adult animals had higher odds of seropositivity than calves, kids or lambs. For livestock species, both sheep and goats had significantly higher odds of seropositivity than cattle. In human populations, men had a significantly higher odds of testing positive for C. burnetii than women. Conclusions This study provides evidence of livestock and human exposure to C. burnetii which could have serious economic implications on livestock production and impact on human health. These results also highlight the need to establish active surveillance in the study area to reduce the disease burden associated with this pathogen.

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.

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 hadVibrio choleraeisolated 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 andEscherichia 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 hadEscherichia 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.

To the Editor: Dog bites are a serious public health problem because of the associated risk for rabies virus exposure in countries to which the virus is endemic (1,2). Human rabies can be prevented by administration of postexposure prophylaxis (PEP). However, PEP rabies vaccine may be unavailable or prohibitively expensive (3). Delay in or failure to receive PEP after possible rabies virus exposure contributes to increased incidence of human rabies deaths (3). We performed a retrospective investigation of animal bites and postbite treatment in Laikipia North sub-county, Kenya, during January 2013–February 2014. Laikipia North is 1 of 3 sub-counties in Laikipia County and has a population of 32,726 (4). Our investigation was instigated by 3 suspected human rabies deaths that were informally reported to the Kenya Government Zoonotic Disease Unit (ZDU) during early 2014. We reviewed animal bite records from sub-county health facilities and veterinary offices and administered a structured household questionnaire to determine outcomes, knowledge of rabies, bite management, healthcare-seeking behavior, and economic costs. This public health response was government coordinated and approved; no personal identifiers were retained. During January 1, 2013–February 10, 2014, a total of 106 bites were recorded by 6 government-run health facilities in Laikipia North. Median reported bite incidence per month was 24 bites/100,000 persons (range 6–45 bites/100,000 persons). The median age of bite victims was 13 years (range 1–81 years); 61 (58%) bites occurred in males. Of all bites recorded, 94 (88%) were by dogs, 8 (8%) by scorpions, and 4 (4%) by humans. The deaths of 3 humans reported to the ZDU occurred in November and December 2013. To assess whether these cases were part of an exposure cluster, we followed up on bite cases during November 1–December 31, 2013. During this period, 17 additional animal bite cases were recorded. Of these 20 bite cases, we successfully traced the households of 11 (55%) case-patients, including 2 of the 3 who died from rabies. Bites were predominantly received from owned pets (82%), and most bites (82%) were reported to be unprovoked. All bites were inflicted on extremities, and almost all (91%) were single-bite injuries (Table). Table Responses to questionnaire interview of 11 animal bite victims assessed for rabies, Laikipia County, Kenya, 2014* Of 11 animals that bit case-patients, 7 had unknown histories of rabies vaccination and 4 were not vaccinated (Table). Four of the 11 animals were suspected to be rabid, including 1 cat and 3 dogs. All the suspected rabid animals were reported to exhibit aggressive or abnormal behavior, drooling or salivation, vocalization, and roaming tendencies (5; Technical Appendix Table 1). Three of the animals reportedly died; status was unknown for 1. Of the 11 traced bite case-patients, 9 washed their wound before going to a healthcare facility and 8 were prescribed PEP. The median time from bite to reporting to a health facility was 1 day (range 0–3 days). Four respondents delayed in starting PEP: 3 after 3 days, and 1 after 2 days. Reasons given for delay included the high cost of PEP by 3 (including 1 who died); a health facility being too far away by 1, who died; and vaccine unavailable at nearest health facility by 2, 1 of whom died. Of 8 respondents who received PEP, 7 traveled >10 km to reach the nearest health facility. PEP availability was inconsistent at the sub-county hospital and local dispensaries; 6 of 8 respondents seeking PEP visited multiple facilities to receive PEP, including a county referral facility that was >100 km away. The World Health Organization’s 5-dose PEP regimen is recommended in Kenya (1). However, only 3 case-patients were prescribed and received 5 doses. Five respondents were prescribed 3, 4, or 6 doses (Technical Appendix Table 2). This finding indicates large inconsistencies in the PEP prescribing practices in this region of Kenya, a pattern that is similar in other parts of East Africa (6). Respondents bore all medical costs without subsidy. Direct medical costs were ≈$2–$500 (US) per bite victim, and indirect medical costs were ≈$4–$100. The average cost of obtaining a single dose of PEP ranged from $8 to $120 (Table; Technical Appendix Table 2). All respondents had heard of rabies. Nine (82%) knew it was transmitted to humans through a bite from a rabid dog, and 4 (36%) knew that rabies among dogs could be prevented through vaccination. During 2014, at least 3 suspected human rabies deaths and 4 domestic animal deaths were associated with this cluster. Postbite care, including PEP, is a heavy economic burden on this community, moreso because rabies vaccine is not always locally accessible. Dog vaccination rates are low in this region and rabies in suspected animals is rarely definitively diagnosed, increasing risks for human rabies virus exposures and the economic burden of PEP administration. We recommend implementation of regular and comprehensive mass dog vaccination campaigns, in line with Kenya’s National Rabies Elimination Strategy (7), and further detailed studies on the epidemiology of rabies in this ecosystem, which supports human, wildlife, and domestic dog populations. Technical Appendix. Questionnaire for persons bitten by animals to assess rabies status of the animals and discussion of direct and indirect costs related to rabies post-exposure prophylaxis. Click here to view.(151K, pdf)

Introduction : Kenya experienced widespread cholera outbreaks in 1997-1999 and 2007-2010. The re-emergence of cholera in Kenya in 2015 indicates that cholera remains a public health threat. Understanding past outbreaks is important for preventing future outbreaks. This study investigated the relationship between cholera occurrence in Kenya and various environmental and demographic factors related to water, sanitation, socio-economic status, education, urbanization and availability of health facilities during the time period 2008-2013. Methods : The primary outcome analyzed was the number of cholera cases at the district level, obtained from the Kenya Ministry of Health's national cholera surveillance records. Values of independent variables were obtained from the 2009 Kenya Population and Housing Census and other national surveys. The data were analyzed using a zero-inflated negative binomial regression model. Results : Multivariate analysis indicated that the risk of cholera was associated with open defecation, use of unimproved water sources, poverty headcount ratio and the number of health facilities per 100,000 population (p < 0.05). No statistically significant association was found between cholera occurrence and education, percentage of population living in urban areas or population density. Conclusion : The Sustainable Development Goals and Kenya's blueprint for development, Kenya Vision 2030, call for access to sanitation facilities and clean water for all by 2030. Kenya has made important economic strides in recent years but continues to be affected by diseases like cholera that are associated with low socio-economic status. Further expansion of access to sanitation facilities and clean water is necessary for preventing cholera in 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 scaleup., PLOS ONE, 12(6), e0179408; 2017

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.

Background Dengue fever, a mosquito-borne disease, is associated with illness of varying severity in countries in the tropics and sub tropics. Dengue cases continue to be detected more frequently and its geographic range continues to expand. We report the largest documented laboratory confirmed circulation of dengue virus in parts of Kenya since 1982. Methods From September 2011 to December 2014, 868 samples from febrile patients were received from hospitals in Nairobi, northern and coastal Kenya. The immunoglobulin M enzyme linked immunosorbent assay (IgM ELISA) was used to test for the presence of IgM antibodies against dengue, yellow fever, West Nile and Zika. Reverse transcription polymerase chain reaction (RT-PCR) utilizing flavivirus family, yellow fever, West Nile, consensus and sero type dengue primers were used to detect acute arbovirus infections and determine the infecting serotypes. Representative samples of PCR positive samples for each of the three dengue serotypes detected were sequenced to confirm circulation of the various dengue serotypes. Results Forty percent (345/868) of the samples tested positive for dengue by either IgM ELISA (14.6 %) or by RT-PCR (25.1 %). Three dengue serotypes 1–3 (DENV1-3) were detected by serotype specific RT-PCR and sequencing with their numbers varying from year to year and by region. The overall predominant serotype detected from 2011–2014 was DENV1 accounting for 44 % (96/218) of all the serotypes detected, followed by DENV2 accounting for 38.5 % (84/218) and then DENV3 which accounted for 17.4 % (38/218). Yellow fever, West Nile and Zika was not detected in any of the samples tested. Conclusion From 2011–2014 serotypes 1, 2 and 3 were detected in the Northern and Coastal parts of Kenya. This confirmed the occurrence of cases and active circulation of dengue in parts of Kenya. These results have documented three circulating serotypes and highlight the need for the establishment of active dengue surveillance to continuously detect cases, circulating serotypes, and determine dengue fever disease burden in the country and region.

Background Brucella spp. is a zoonotic bacterial agent of high public health and socio-economic importance. It infects many species of animals including wildlife, and people may get exposed through direct contact with an infected animal or consumption of raw or undercooked animal products. A linked livestock-human cross-sectional study to determine seroprevalences and risk factors of brucellosis in livestock and humans was designed. Estimates were made for intra-cluster correlation coefficients (ICCs) for these observations at the household and village levels. Methodology The study was implemented in Garissa (specifically Ijara and Sangailu areas) and Tana River (Bura and Hola) counties. A household was the unit of analysis and the sample size was derived using the standard procedures. Serum samples were obtained from selected livestock and people from randomly selected households. Humans were sampled in both counties, while livestock could be sampled only in Tana River County. Samples obtained were screened for anti-Brucella IgG antibodies using ELISA kits. Data were analyzed using generalized linear mixed effects logistic regression models with the household (herd) and village being used as random effects. Results The overall Brucella spp. seroprevalences were 3.47% (95% confidence interval [CI]: 2.72–4.36%) and 35.81% (95% CI: 32.87–38.84) in livestock and humans, respectively. In livestock, older animals and those sampled in Hola had significantly higher seroprevalences than younger ones or those sampled in Bura. Herd and village random effects were significant and ICC estimates associated with these variables were 0.40 (95% CI: 0.22–0.60) and 0.24 (95% CI: 0.08–0.52), respectively. In humans, Brucella spp. seroprevalence was significantly higher in older people, males, and people who lived in pastoral areas than younger ones, females or those who lived in irrigated or riverine areas. People from households that had at least one seropositive animal were 3.35 (95% CI: 1.51–7.41) times more likely to be seropositive compared to those that did not. Human exposures significantly clustered at the household level; the ICC estimate obtained was 0.21 (95% CI: 0.06–0.52). Conclusion The presence of a Brucella spp.-seropositive animal in a household significantly increased the odds of Brucella spp. seropositivity in humans in that household. Exposure to Brucella spp. of both livestock and humans clustered significantly at the household level. This suggests that risk-based surveillance measures, guided by locations of primary cases reported, either in humans or livestock, can be used to detect Brucella spp. infections in livestock or humans, respectively., Author summary Brucellosis is an important zoonotic disease that primarily affects livestock and wildlife. In humans, the disease is characterized by prolonged fever, body aches, joint pains and weakness, while in livestock, the disease mainly causes abortions and infertility. We carried out a study in northeastern Kenya (Garissa and Tana River Counties) to identify factors that affect the distribution of the disease in people and livestock. Livestock and people from randomly selected households were recruited and serum samples were obtained and screened using ELISA kits for Brucella IgG antibodies as a measure to determine the level of exposure to Brucella spp. Data obtained were analyzed using mixed effects logistic regression models. Results obtained show that human and animal Brucella spp seroprevalences cluster at the household level. The odds of exposure in humans were at least three times higher in households that had at least one seropositive animal compared to those that had not. These results can be used to design risk-based surveillance systems where each Brucella spp. infection identified in livestock or humans could signal potential locations of additional brucellosis cases in humans and animals.

BACKGROUND Kenya has experienced multiple cholera outbreaks since 1971. Cholera remains an issue of major public health importance and one of the 35 priority diseases under Kenya's updated Integrated Disease Surveillance and Response strategy. METHODS We reviewed the cholera surveillance data reported to the World Health Organization and the Kenya Ministry of Public Health and Sanitation from 1997 through 2010 to determine trends in cholera disease for the 14-year period. RESULTS A total of 68 522 clinically suspected cases of cholera and 2641 deaths were reported (overall case-fatality rate [CFR], 3.9%), affecting all regions of the country. Kenya's largest outbreak occurred during 1997-1999, resulting in 26 901 cases and 1362 deaths (CFR, 5.1%). Following a decline in disease occurrence, the country experienced a resurgence of epidemic cholera during 2007-2009 (16 616 cases and 454 deaths; CFR, 2.7%), which declined rapidly to 0 cases. Cases were reported through July 2010, with no cases reported during the second half of the year. About 42% of cases occurred in children aged

Background Cholera remains endemic in sub-Saharan Africa. We characterized the 2009 cholera outbreaks in Kenya and evaluated the response. Methods We analyzed surveillance data and estimated case fatality rates (CFRs). Households in 2 districts, East Pokot (224 cases; CFR = 11.7%) and Turkana South (1493 cases; CFR = 1.0%), were surveyed. We randomly selected 15 villages and 8 households per village in each district. Healthcare workers at 27 health facilities (HFs) were surveyed in both districts. Results In 2009, cholera outbreaks caused a reported 11 425 cases and 264 deaths in Kenya. Data were available from 44 districts for 6893 (60%) cases. District CFRs ranged from 0% to 14.3%. Surveyed household respondents (n = 240) were aware of cholera (97.5%) and oral rehydration solution (ORS) (87.9%). Cholera deaths were reported more frequently from East Pokot (n = 120) than Turkana South (n = 120) households (20.7% vs. 12.3%). The average travel time to a HF was 31 hours in East Pokot compared with 2 hours in Turkana South. Fewer respondents in East Pokot (9.8%) than in Turkana South (33.9%) stated that ORS was available in their village. ORS or intravenous fluid shortages occurred in 20 (76.9%) surveyed HFs. Conclusions High CFRs in Kenya are related to healthcare access disparities, including availability of rehydration supplies.

Background Shigellosis is the major cause of bloody diarrhoea worldwide and is endemic in most developing countries. In Kenya, bloody diarrhoea is reported weekly as part of priority diseases under Integrated Disease Surveillance and Response System (IDSR) in the Ministry of Health. Methods We conducted a case control study with 805 participants (284 cases and 521 controls) between January and December 2012 in Kilifi and Nairobi Counties. Kilifi County is largely a rural population whereas Nairobi County is largely urban. A case was defined as a person of any age who presented to outpatient clinic with acute diarrhoea with visible blood in the stool in six selected health facilities in the two counties within the study period. A control was defined as a healthy person of similar age group and sex with the case and lived in the neighbourhood of the case. Results The main presenting clinical features for bloody diarrhoea cases were; abdominal pain (69 %), mucous in stool (61 %), abdominal discomfort (54 %) and anorexia (50 %). Pathogen isolation rate was 40.5 % with bacterial and protozoal pathogens accounting for 28.2 % and 12.3 % respectively. Shigella was the most prevalent bacterial pathogen isolated in 23.6 % of the cases while Entamoeba histolytica was the most prevalent protozoal pathogen isolated in 10.2 % of the cases. On binary logistic regression, three variables were found to be independently and significantly associated with acute bloody diarrhoea at 5 % significance level; storage of drinking water separate from water for other use (OR = 0.41, 95 % CI 0.20–0.87, p = 0.021), washing hands after last defecation (OR = 0.24, 95 % CI 0.08–.076, p = 0.015) and presence of coliforms in main source water (OR = 2.56, CI 1.21–5.4, p = 0.014). Rainfall and temperature had strong positive correlation with bloody diarrhoea. Conclusion The main etiologic agents for bloody diarrhoea were Shigella and E. histolytica. Good personal hygiene practices such as washing hands after defecation and storing drinking water separate from water for other use were found to be the key protective factors for the disease while presence of coliform in main water source was found to be a risk factor. Implementation of water, sanitation and hygiene (WASH) interventions is therefore key in prevention and control of bloody diarrhoea.

Introduction: Polio eradication is now feasible after removal of Nigeria from the list of endemic countries and global reduction of cases of wild polio virus in 2015 by more than 80%. However, all countries must remain focused to achieve eradication. In August 2015, the Catholic bishops in Kenya called for boycott of a polio vaccination campaign citing safety concerns with the polio vaccine. We conducted a survey to establish if the coverage was affected by the boycott. Methods: A cross sectional survey was conducted in all the 32 counties that participated in the campaign. A total of 90,157 children and 37,732 parents/guardians were sampled to determine the vaccination coverage and reasons for missed vaccination. Results: The national vaccination coverage was 93% compared to 94% in the November 2014 campaign. The proportion of parents/guardians that belonged to Catholic Church was 31% compared to 7% of the children who were missed. Reasons for missed vaccination included house not being visited (44%), children not being at home at time of visit (38%), refusal by parents (12%), children being asleep (1%), and various other reasons (5%). Compared to the November 2014 campaign, the proportion of children who were not vaccinated due to parent’s refusal significantly increased from 6% to 12% in August 2015. Conclusion: The call for boycott did not affect the campaign significantly. However, if the call for boycott is repeated in future it could have some significant negative implication to polio eradication. It is therefore important to ensure that any vaccine safety issues are addressed accordingly. Pan African Medical Journal 2016; 24

Background This study was conducted in Bura irrigation scheme in Tana River County and the pastoral area in Ijara, Garissa County in the eastern Kenya to establish the knowledge, attitude and practices on malaria transmission, control and management, and determine malaria prevalence and the associated risk factors. Methods A cross sectional survey design that involved 493 randomly selected people from 334 households was used between November and December 2013. All the randomly selected people were screened for malaria parasites using rapid diagnostic test (RDT)—Carestart™ malaria HRP2 (pf) kit. A questionnaire was administered to determine potential risk factors and perceptions on malaria exposure within a period of 2 months prior to the survey. Two logistic regression models were fitted to the data; one used the RDT results while the other used data from the questionnaire survey. Results Using RDT, the prevalence of malaria was 4.68 % (95 % CI: 1.48–7.88 %) and 0.31 % (−0.30 to 0.92 %) in irrigated and non-irrigated areas, respectively. From the questionnaires, 14.62 % (9.27–19.97 %) and 23.91 % (19.23–28.60 %) of the participants perceived to have had malaria in the irrigated and pastoral areas, respectively. The main malaria control measure was the use of bed nets: average of three nets per household in Bura irrigation scheme and one in Ijara. Artemether–lumefantrine was the main drug of choice mainly in the irrigated area while sulfadoxine–pyrimethamine was likely to be used in the non-irrigated area. Households located >5 km from the nearest health facility had higher prevalence of Plasmodium infection than those located ≤5 km. Conclusion The residents of Bura irrigation scheme were more likely to be infected compared to those living in the non-irrigated area of Ijara. However, those in the non-irrigated area were more likely to be treated or use over-the-counter medication for perceived malaria illnesses compared to those in the irrigated area. There is a need, therefore, to formulate effective ways of managing malaria especially in irrigated areas and build capacity on differential diagnosis for malaria, especially in the pastoral areas.

Introduction: Kenya adopted the Integrated Disease Surveillance and Response (IDSR) strategy in 1998 to strengthen disease surveillance and epidemic response. However, the goal of weekly surveillance reporting among health facilities has not been achieved. We conducted a crosssectional study to determine the prevalence of adequate reporting and factors associated with IDSR reporting among health facilities in one Kenyan County. Methods: Health facilities (public and private) were enrolled using stratified random sampling from 348 facilities prioritized for routine surveillance reporting. Adequately-reporting facilities were defined as those which submitted >10 weekly reports during a twelve-week period and a poor reporting facilities were those which submitted

Background Rubella infection has been identified as a leading cause of birth defects commonly known as Congenital Rubella Syndrome (CRS). Kenya does not currently have a rubella immunization program nor a CRS surveillance system. In 2014, a rubella outbreak was reported in a rural district in Kenya. We investigated the outbreak to determine its magnitude and describe the outbreak in time, place and person. We also analyzed the laboratory-confirmed rubella cases from 2010 to 2014 to understand the burden of the disease in the country. Methods The Rubella outbreak was detected using the case-based measles surveillance system. A suspected case was a person with generalized rash and fever while a confirmed case was a person who tested positive for rubella IgM. All laboratory-confirmed and epidemiologically linked cases were line listed. The measles case-based surveillance database was used to identify rubella cases from 2010 to 2014. Results A total of 125 rubella cases were line listed. Fifty four percent of cases were female. Case age ranged from 3 months to 32 years with a median of 4 years. Fifty-one percent were aged less than 5 years, while 82 % were aged less than 10 years. Six percent of the cases were women of reproductive age. All cases were treated as outpatients and there were no deaths. The number of confirmed rubella cases was 473 in 2010, 604 in 2011, 300 in 2012, 336 in 2013 and 646 in 2014. Conclusions Analysis of Kenya rubella data shows that rubella is endemic throughout the country, and many outbreaks may be underestimated or undocumented. Six percent of all the cases in this outbreak were women of reproductive age indicating that the threat of CRS is real. The country should consider initiating a CRS surveillance system to quantify the burden with the goal of introducing rubella vaccine in the future.

To investigate the effects of irrigation on land cover changes and the risk of selected zoonotic pathogens, we carried out a study in irrigated, pastoral and riverine areas in the eastern Kenya. Activities implemented included secondary data analyses to determine land use and land cover (LULC) changes as well as human, livestock and wildlife population trends; entomological surveys to characterize mosquitoes population densities and species distribution by habitat and season; and serological surveys in people to determine the risk of Rift Valley fever virus (RVFV), West Nile fever virus (WNV), dengue fever virus (DFV), Leptospira spp. and Brucella spp. Results demonstrate a drastic decline in vegetation cover over R approximate to 25 years particularly in the irrigated areas where cropland increased by about 1,400% and non-farm land (under closed trees, open to closed herbaceous vegetation, bushlands and open trees) reduced by 30-100%. The irrigated areas had high densities of Aedes mcintoshi, Culexspp. and Mansonia spp. (important vectors for multiple arboviruses) during the wet and dry season while pastoral areas had high densities of Ae. tricholabis specifically in the wet season. The seroprevalences of RVFV, WNV and DFV were higher in the irrigated compared to the pastoral areas while those for Leptospira spp and Brucella spp. were higher in the pastoral compared to the irrigated areas. It is likely that people in the pastoral areas get exposed to Leptospira spp by using water fetched from reservoirs that are shared with livestock and wildlife, and to Brucella spp. by consuming raw or partially cooked animal source foods such as milk and meat. This study suggests that irrigation increases the risk of mosquito-borne infections while at the same time providing a protective effect against zoonotic pathogens that thrive in areas with high livestock population densities.

Indigenous wild poliovirus has been eliminated in 98% of endemic countries since 1988, with a decrease from 350 000 cases in 1988 to 223 confirmed cases in 2012 [1]. The success of polio eradication efforts has been dependent on increasing population immunity through routine immunization and supplementary immunization activities and by improving surveillance for acute flaccid paralysis (AFP). AFP surveillance systems are expected to annually identify ≥2 nonpolio AFP (NPAFP) cases per 100 000 population under 15 years of age to demonstrate that their systems are sensitive enough to detect paralytic polio cases [2]. All countries within the Horn of Africa region have successfully eliminated endemic poliovirus circulation, with Kenya successfully presenting in 2005 their complete country documentation outlining polio-free status. However, the region has remained at high risk for reintroduction and has had multiple outbreaks in recent years. An outbreak of 19 cases of wild poliovirus occurred in Turkana, Kenya, in 2009, and was followed by an outbreak of 22 cases in Uganda in 2010. In 2011, another wild poliovirus case was detected in western Kenya and was found to be genetically related to the 2010 outbreak in Uganda. These outbreaks indicated missed circulation within the region over a 3-year period. As of 31 December, 203 confirmed cases of WPV had been confirmed in the Horn of Africa in 2013. All of these outbreaks underscore the regional struggle to achieve the surveillance sensitivity and population immunity necessary to prevent transmission of imported poliovirus. In the midst of these outbreaks, the health system in Kenya has been decentralized, with both increased administrative autonomy at the district level and an increase in number of districts. Following a risk analysis performed in January 2012, which showed that 121 of 159 (77%) of districts in Kenya were at high or medium risk for a polio outbreak, the Kenya Ministry of Public Health and Sanitation (MoPHS) engaged the US Centers for Disease Control and Prevention (CDC), World Health Organization (WHO), United Nations Children’s Fund (UNICEF), and other international partners to assist in a review of the national surveillance and routine immunization systems. The purpose of the review was to identify gaps in the programs, as well as to provide recommendations toward improving detection of imported poliovirus and preventing poliovirus circulation during this period of health system decentralization [3].

A One Health (OH) approach that integrates human,animal and environmental approaches to management of zoonotic diseases has gained momentum in the last decadeas part of a strategy to prevent and control emerging infectious diseases. However, there are few examples of howan OH approach can be established in a country. Kenya establishment of an OH office, referred to asthe Zoonotic Disease Unit (ZDU) in 2011. The ZDU bridges theanimal and human health sectors with a senior epidemiologist deployed from each ministry; and agoal of maintaining collaboration at the animal and human health interface towards better prevention and control of zoonoses. The country is adding an ecologist to the ZDU to ensure that environmental risks are adequately addressed in emerging disease control.