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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.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.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).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.

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 aGlobal 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 90thpercentile 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.

Cholera is a severe acute, highly transmissible diarrheal disease which affects many low- and middle-income countries. Outbreaks of cholera are confirmed using microbiological culture, and additional cases during the outbreak are generally identified based on clinical case definitions, rather than laboratory confirmation. Many low-resource areas where cholera occurs lack the capacity to perform culture in an expeditious manner. A simple, reliable, and low-cost rapid diagnostic test (RDT) would improve identification of cases allowing rapid response to outbreaks. Several commercial RDTs are available for cholera testing with two lines to detect either serotypes O1 and O139; however, issues with sensitivity and specificity have not been optimal with these bivalent tests. Here, we report an evaluation of a new commercially available cholera dipstick test which detects only serotype O1. In both laboratory and field studies in Kenya, we demonstrate high sensitivity (97.5%), specificity (100%), and positive predictive value (100%) of this new RDT targeting only serogroup O1. This is the first field evaluation for the new Crystal VC-O1 RDT; however, with these high-performance metrics, this RDT could significantly improve cholera outbreak detection and improve surveillance for better understanding of cholera disease burden.

Background: Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are the main malaria vector control measures. Kenya has employed multiple approaches, including free mass net distribution campaigns, for distributing LLINs to the community that resulted in increased household ownership of one or more nets from 44% in 2010 to 63 % in 2015. Migori and Homa Bay Counties are among the malaria endemic counties in Western Kenya that benefitted from three free mass net distribution campaigns between 2012 and 2018.. Widespread pyrethroid resistance among the primary vectors in Western Kenya has necessitated the re-introduction of IRS using an organophosphate insecticide, pirimiphos-methyl (Actellic® 300CS), as part of a strategy to manage insecticide-resistance. Evaluation of the effectiveness of the combined use of non-pyrethroid IRS and LLINs have yielded varied results. We aimed to evaluate malaria indicators before and after the introduction of IRS in a high malaria transmission area compared with an adjacent area where IRS was not introduced until one year later to estimate the effect of the intervention in an area with pyrethroid resistance.Methods: We reviewed records (MoH 405 A, 405 B, and 706) and tallied monthly aggregate of outpatient department (OPD) attendance, suspected malaria cases, those tested for malaria and those testing positive for malaria at two health facilities, one from Nyatike, an intervention sub-county, and one from Suba, a comparison sub-county, both located in Western Kenya, from February 1, 2016, through March 31, 2018. The first round of IRS was conducted in February – March 2017 in Nyatike sub-county and the second round one year later in both Nyatike and Suba sub-counties while the mass distribution of LLINs has been conducted in both locations. We performed a descriptive analysis and estimated the effect of the interventions and temporal changes of malaria indicators using Poisson regression for a period before and after implementation of the first round of IRS.Results: A higher reduction in the intervention area in total OPD, the proportion of OPD visits due to suspected malaria, testing positivity rate and annual malaria incidences except for the total OPD visits among the under 5 children where 59% decrease was observed in the comparison area while 33% decrease was observed in the intervention area (net change -27%, P Conclusions: Our findings demonstrated a reduced malaria burden among population protected by both non-pyrethroid IRS and LLINs implying a possible additional benefit afforded by the combined intervention in malaria endemic zone.

Studies of the epidemiology of cholera in the Ganges Delta led to understanding cholera's transmission patterns, risk groups, seasonality, and the relationship of cholera with the environment. In Bangladesh and West Bengal cholera is seasonal, transmission occurs consistently every year with only brief periods without cases. By contrast, in most African countries, cholera transmission inconsistent seasonal patterns, and long periods without obvious transmission. Additional differences are observed when molecular methods are used to identify genetic lineages. Transmission patterns of cholera in Africa appear result from intermittent outbreaks followed by elimination of that genetic lineage. Later another outbreak may occur because of reintroduction of new or evolved lineages from adjacent areas, often by human travelers. These then subsequently undergo subsequent elimination. The concept of frequent elimination and reintroduction has several implications when planning for cholera's elimination. These include a) reconsidering concepts regarding the definition of elimination, b) need to enhance methods for rapid detection and response to an outbreak, c) strategies for more effective use of oral cholera vaccine and water-sanitation-hygiene interventions, d) a need to readjust estimates of the disease burden for Africa upon which cost benefit estimates are based, e) re-examination of the role of water as a reservoir for maintaining endemicity of cholera in Africa. This paper will review some of the major features of cholera's epidemiology in most endemic African countries which appear to differ from patterns in the Ganges Delta.

Homa Bay County in south-western Kenya has a low uptake of antenatal care services and the highest prevalence of HIV in the country. We present the findings of a retrospective review of HIV-exposed infants (HEI) who sought early infant diagnosis services in the county throughout 2015. HEI who were breastfed >6 months, had replacement feeding and did not receive prophylaxis were 2–6 times more likely to be HIV-positive.

Dadaab Refugee camp in Garissa County, Kenya, hosts nearly 340,000 refugees in five subcamps (Dagahaley, Hagadera, Ifo, Ifo2, and Kambioos) (1). On November 18 and 19, 2015, during an ongoing national cholera outbreak (2), two camp residents were evaluated for acute watery diarrhea (three or more stools in ≤24 hours); Vibrio cholerae serogroup O1 serotype Ogawa was isolated from stool specimens collected from both patients. Within 1 week of the report of index cases, an additional 45 cases of acute watery diarrhea were reported. The United Nations High Commissioner for Refugees and their health-sector partners coordinated the cholera response, community outreach and water, sanitation, and hygiene (WASH) activities; Médecins Sans Frontiéres and the International Rescue Committee were involved in management of cholera treatment centers; CDC performed laboratory confirmation of cases and undertook GIS mapping and postoutbreak response assessment; and the Garissa County Government and the Kenya Ministry of Health conducted a case-control study. To prevent future cholera outbreaks, improvements to WASH and enhanced disease surveillance systems in Dadaab camp and the surrounding area are needed.

Background In 2014, Kenya’s field epidemiology and laboratory training program (FELTP) initiated a 3-month-long field-based frontline training (FETP-F) for local public health workers.Methods Between February and April 2017, FELTP conducted a mixed-methods evaluation to examine outcomes achieved among 2014 and 2015 graduates of the trainings. Data quality assessment (DQA) and data consistency assessment (DCA) scores, on-time-reporting (OTR) percentages, and ratings of the training experience were the quantitative measures tracked from baseline and then at 6-month intervals up to 18 months post-completion of the training. The qualitative component consisted of semi-structured face-to-face interviews and observations. Quantitative data were analyzed using one-way analysis of variance (ANOVA). Qualitative data were transcribed and analyzed to identify key themes and dimensions.Results One hundred and three graduates were included. For the qualitative component, we reached saturation after 19 onsite interviews and observation exercises. ANOVA showed that the trainings had small but significant impacts on mean DQA and OTR scores. Results showed an insignificant increase in mean DCA scores. Qualitative analyses showed that 68% of respondents acquired new skills, 83% applied those skills to their day-to-day work, and 91% improved work methods.Conclusion The findings show that FETP-F is effective in improving work methods, facilitating behavior change, and improving key public health competencies.

Objectives The objective of this study was to evaluate the performance of lateral flow immunoassay (LFA) against latex agglutination (LA), India ink and culture in point-of-care diagnosis of cryptococcus meningitis (CM). We conducted cross-sectional study among HIV-positive patients with suspected CM at Mbagathi Hospital, Nairobi, April–July 2017. Results Of 124 capillary blood and serum and 99 cerebrospinal fluid (CSF) samples, LFA and LA had a concurrence on serum of 94.4%, kappa (0.88), sensitivity (100%) and specificity (91%). LFA and LA on CSF, was 97.9%, kappa (0.96), sensitivity (100%) and specificity (96%). LFA and India ink was 96.9%, kappa (0.94), sensitivity (100%) and specificity (94.1%). On CSF culture, concurrence was 72.7%, kappa (0.43), sensitivity (100%) and specificity (64%) and of LFA on capillary blood, serum and CSF was 100% with kappa (1.00), sensitivity and specificity of 100%.

Objectives: The objective of this study was to evaluate the performance of lateral flow immunoassay (LFA) against latex agglutination (LA), India ink and culture in point-of-care diagnosis of CM. We conducted a cross-sectional study among patients with suspected CM at Mbagathi Hospital, Nairobi, April-July 2017. Results: Of 124 capillary blood and serum and 99 cerebrospinal fluid (CSF) samples, the agreement between LFA and LA on serum was 94.4%, kappa (0.88), sensitivity (100%) and specificity (91%). LFA and LA on CSF, was 97.9%, kappa (0.96), sensitivity (100%) and specificity (96%). LFA and India ink was 96.9%, kappa (0.94), sensitivity (100%) and specificity (94.1%). On CSF culture, the agreement was 72.7%, kappa (0.43), sensitivity (100%) and specificity (64%). The agreement of LFA on capillary blood, serum and CSF was 100% with kappa (1.00), sensitivity and specificity of 100%

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.

Late diagnosis of HIV and enrolment to care are global public health challenges. This study aimed to characterise late HIV diagnoses and initiation of treatment among patients at Juba Teaching Hospital (JTH) in South Sudan. We conducted a retrospective review of lab-confirmed HIV patients at JTH, 2013–2016. Demographic, clinical, and laboratory data were entered into and descriptive statistics were calculated using Microsoft Excel. We identified 401 patients, with mean age 33.71±4.54 years, 235 (59%) were female, 307 (77%) were late entry, 64 (16%) were lost to follow-up, and 57 (14%) died within 12 months of diagnosis. Among patients who presented late, 122 (57%) were female, and 112 (53%) were 2 at diagnosis. Late diagnosis of HIV infection is a significant public health problem in South Sudan, particularly for younger and female patients.Keywords: antiretroviral therapy, insecurity, late diagnosis, mortality, women

Aim Typhoid fever is a vaccine-preventable bacterial disease that causes significant morbidity and mortality throughout Africa. This paper describes an upsurge of typhoid fever cases in Moyale Sub-County (MSC), Kenya, 2014–2015. Methods We conducted active hospital and health facility surveillance and laboratory and antimicrobial sensitivity testing for all patients presenting with headache, fever, stomach pains, diarrhea, or constipation at five MSC health facilities between December 2014 and January 2015. We also conducted direct observation of the residential areas of the suspected cases to assess potential environmental exposures and transmission mechanisms. Demographic, clinical, and laboratory data were entered into, and descriptive statistics were calculated with, MS Excel. Results A total of 317 patients were included in the study, with mean age 24 ± 8.1 years, and 51% female. Of the 317 suspect cases, 155 (49%) were positive by Widal antigen reaction test. A total of 188 (59%) specimens were subjected to culture and sensitivity testing, with 71 (38%) culture positive and 54 (76%), 43 (60%), and 33 (46%) sensitive to ceftriaxone, cefuroxime, and ciprofloxacin, respectively. Environmental assessments through direct observations showed that commercial and residential areas had limited (1) clean water sources, (2) latrines, and (3) hygiene stations for street food hawkers and their customers. Conclusions Typhoid fever is endemic in MSC and causes significant disease across age and sex groups. The local health department should develop policies to (1) assure community access to potable water and hygiene stations and (2) vaccinate specific occupations, such as food and drink handlers, against typhoid.

Introduction in February 2015, an outbreak of acute watery diarrhea was reported in two sub counties in western Kenya. Vibrio cholerae 01 serotype Ogawa was isolated from 26 cases and from water samples collected from a river mainly used by residents of the two sub-counties for domestic purposes. We carried out an investigation to determine factors associated with the outbreak. Methods we conducted a frequency matched case control study in the community. We defined cases as episodes of watery diarrhea (at least three motions in 24 hours) in persons ≥ 2 years who were residents of Rongo or Ndhiwa sub-counties from January 23-February 25, 2015. Cases were systematically recruited from a cholera line list and matched to two controls (persons without diarrhea since January 23, 2015) by age category and residence. A structured questionnaire was administered to evaluate exposures in cases and controls and multivariable logistic regression done to determine independent factors associated with the outbreak. Results we recruited 52 cases and 104 controls. Females constituted 61% (95/156) of all participants. Overall latrine coverage was 58% (90/156). Latrine coverage was 44% (23/52) for cases and 64% (67/104) for controls. Having no latrine at home (aOR = 10.9; 95% CI: 3.02-39.21), practicing communal hand washing in a basin (aOR = 6.5; 95% CI: 2.30-18.11) and vending of food as an occupation (aOR = 3.4; 95% CI: 1.06-10.74) were independently associated with the outbreak. Conclusion poor latrine coverage and personal hygiene practices were identified as the main drivers of the outbreak. We recommended improved public health education on latrine usage and promotion of hand washing with soap and water in the community.

Background Cutaneous leishmaniasis is a neglected disease known to cause significant morbidity among the poor. We investigated a suspected outbreak to determine the magnitude of cases, characterize the cases and identify risk factors of cutaneous leishmaniasis in Gilgil, a peri-urban settlement in Central Kenya. Methods Hospital records for the period 2010-2016 were reviewed and additional cases were identified through active case search. Clinical diagnosis of cutaneous leishmaniasis was made based on presence of ulcerative, nodular or papular skin lesion. The study enrolled 58 cases matched by age and neighbourhood to 116 controls in a case control study. Data was collected using structured questionnaires and simple proportions, means and medians were computed, and logistic regression models were constructed for analysis of individual, indoor and outdoor risk factors. Results Of the 255 suspected cases of cutaneous leishmaniasis identified, females constituted 56% (142/255) and the median age was 7 years (IQR 7-21). Cases occurred in clusters and up to 43% of cases originated from Gitare (73/255) and Kambi-Turkana (36/255) villages. A continuous transmission pattern was depicted throughout the period under review. Individual risk factors included staying outside the residence in the evening after sunset (OR 4.1, CI 1.2-16.2) and visiting forests (OR 4.56, CI 2.04-10.22). Sharing residence with a case (OR 14.4, CI 3.8-79.3), residing in a thatched house (OR 7.9, CI 1.9-45.7) and cracked walls (OR 2.3, CI 1.0-4.9) were identified among indoor factors while sighting rock hyraxes near residence (OR 5.3, CI 2.2-12.7), residing near a forest (OR 7.8, CI 2.8-26.4) and having a close neighbour with cutaneous leishmaniasis (OR 6.8, CI 2.8-16.0) were identified among outdoor factors. Conclusions We identify a large burden of cutaneous leishmaniasis in Gilgil with evidence of individual, indoor and outdoor factors of disease spread. The role of environmental factors and rodents in disease transmission should be investigated further.

Cholera is among the re-emerging diseases in Kenya. Beginning in December 2014, a persistent outbreak occurred involving 29 out of the 47 countries. Homa Bay County in Western Kenya was among the first counties to report cholera cases from January to April 2015. This case study is based on an outbreak investigation conducted by FELTP residents in Homa Bay County in February 2015. It simulates an outbreak investigation including laboratory confirmation, active case finding, descriptive epidemiology and implementation of control measures. This case study is designed for the training of basic level field epidemiology trainees or any other health care workers working in public health-related fields. It can be administered in 2-3 hours. Used as adjunct training material, the case study provides the trainees with competencies in investigating an outbreak in preparation for the actual real-life experience of such outbreaks.

Introduction health care workers (HCWs) have an increased risk of M. tuberculosis infection and tuberculosis (TB) disease compared to the general population. We evaluated the magnitude of TB disease among HCWs in two District Hospitals in Kenya. Methods retrospective review of TB laboratory registers was performed at Makindu and Kiambu district hospitals. Cases were HCWs with confirmed TB diagnosis working at either hospital from 2010 to 2013. Cases were interviewed using structured questionnaire to collect clinical and epidemiologic information. Infection prevention (IP) practices were observed and recorded. Results Makindu and Kiambu had 91 and 450 HCWs respectively. As from the registers, 6,275 sputum smears were examined with 1,122 (18%) acid alcohol fast bacilli smear positive. Kiambu and Makindu reported 11 and five cases of TB among HCWs respectively. Of the 16, 57% were male; mean age was 45 (SD 5.32) years. HCWs affected were: four (25%) laboratory technicians, four (25%) nurses, two (13%) occupation therapists, two (13%) clinical officers and one pharmacist, telephone operator, driver and casual worker. Mean working time lost recuperating was 14 (range: 0-28) weeks. Both facilities lacked high-efficiency particulate air filters and Kiambu hospital lacked a biosafety cabinet too. Windows at both facilities were often closed and suspected TB patients shared common crowded outpatient waiting area where sputum was also collected. No standard reporting tool for TB disease among HCWs was in place at both facilities. Conclusion TB disease was distributed across professional cadres with long working time lost recuperating. Inadequate IP measures exposed HCWs to occupational risk of acquiring TB disease.

Introduction bacterial meningitis, responsible for childhood morbidity and mortality, can also lead to permanent neurological disability among survivors. This study conducted from January to December, 2015 used standard bacteriological and molecular methods to investigate the etiology of three common causes of bacterial meningitis among hospitalized patients admitted at a semi-urban hospital in Nairobi, Kenya. Methods a total of 196 patients admitted at Mama Lucy Kibaki with clinically diagnosed meningitis were recruited into this cross-sectional study. Participants' information was collected through patient interviews and abstraction of health records. Bacterial culture, gram stains and multiplex polymerase chain reaction (PCR) were used to investigate causes of bacterial meningitis from cerebrospinal fluid (CSF) samples. Characteristics such as age, gender, occupation, underlying conditions of patients with laboratory confirmed bacterial meningitis infection are described. Results among the 196 patients diagnosed with bacterial meningitis, the median age was 1 year (range 1 to 36 years) with 87.2% aged 1 to 4 years; 54.6% were males. Using PCR, 22 out of 196 (11.2%) samples had evidence suggesting a bacterial infection. These included 12/22 (54.5%) S. pneumonia, 7/22 (31.8%) N. meningitides and 3/22 (13.6%) H. influenza. From bacterial culture, four of 196 (2.1%) samples grew S. pneumonia. All three samples found positive for H. influenza were from male patients aged between 1 to 4 years. Conclusion of the three common causes evaluated, S. pneumonia was the most common cause of bacterial meningitis among patients from this region, particularly among infants. One older patient was diabetic, thereby highlighting the importance of pre-existing conditions. Although serotyping of bacteria was not done, under-vaccination might have played a role in the cases identified and ensuring complete and timely vaccination may prevent further cases of bacterial meningitis.

Introduction male partner involvement in elimination of mother-to-child transmission (eMTCT) of HIV activities remains low in Western Kenya, despite its importance in reducing rates of child HIV transmission. We sought to identify factors associated with male partner involvement in eMTCT in Kisumu East sub-County, Western Kenya. Methods we conducted a cross-sectional study among women aged ≥ 18 years who had children aged ≤ 12 months and were attending a child health clinic for immunization services in one of four Western Kenya health centers between February and April, 2015. We assessed male involvement using an "involvement index" of five factors of equal weight: partner antenatal care (ANC) attendance, partner HIV testing, partner financial support to the woman during ANC, partner awareness of ANC services and partner participation in decision making on contraception including condom use. Male involvement was classified as high or low based on their index score. We calculated odds ratios (OR) and 95% confidence intervals (CI) to identify factors associated with high male partner involvement. Results we recruited 216 female participants. Mean age was 26.1 years (± 5.5 years), 189 (87.5%) were married. The majority (94.4%) had attended ANC in public health facilities. Nineteen percent of women had high male involvement. Having > 8 years of formal education (AOR 3.9, CI = 1.51-10.08), having male partner who was employed, history of previous couple testing (AOR = 3.2, CI = 1.42-7.22) and reports of partner having read the mother-child booklet during ANC (AOR = 2.9, CI = 1.30-6.49), were associated with high male involvement. Conclusion based on our findings, we recommend targeted strategies to actively sensitize men and encourage their involvement in eMTCT, particularly among partners of women with fewer years of education and among partners who are not employed.

On January 6, 2015, a man aged 40 years was admitted to Kenyatta National Hospital in Nairobi, Kenya, with acute watery diarrhea. The patient was found to be infected with toxigenic Vibrio cholerae serogroup O1, serotype Inaba. A subsequent review of surveillance reports identified four patients in Nairobi County during the preceding month who met either of the Kenya Ministry of Health suspected cholera case definitions: 1) severe dehydration or death from acute watery diarrhea (more than four episodes in 12 hours) in a patient aged ≥5 years, or 2) acute watery diarrhea in a patient aged ≥2 years in an area where there was an outbreak of cholera. An outbreak investigation was immediately initiated. A confirmed cholera case was defined as isolation of V. cholerae O1 or O139 from the stool of a patient with suspected cholera or a suspected cholera case that was epidemiologically linked to a confirmed case. By January 15, 2016, a total of 11,033 suspected or confirmed cases had been reported from 22 of Kenya's 47 counties (Table). The outbreak is ongoing.

Introduction:antimicrobial resistance is neglected in developing countries; associated with limited surveillance and unregulated use of antimicrobials. Consequently, delayed patient recoveries, deaths and further antimicrobial resistance occur. Recent gastroenteritis outbreak at a children's home associated with multidrug resistant non-typhoidalSalmonellaspp, raised concerns about the magnitude of the problem in Kenya, prompting antimicrobial resistance assessment preceding surveillance system establishment. Methods:eight public medical laboratories were conveniently selected. Questionnaires were administered to key informants to evaluate capacity, practice and utilization of antimicrobial susceptibility tests. Retrospective review of laboratory records determined antimicrobial resistance to isolates. Antimicrobial resistance was defined as resistance of a microorganism to an antimicrobial agent to which it was previously sensitive and multidrug resistance as non-susceptibility to at least one agent in three or more antimicrobial categories. Results:the laboratories comprised; 2(25%) national, 4(50%) sub-national and 2(25%) district. Overall, antimicrobial susceptibility testing capacity was inadequate in all. Seven (88%) had basic capacity for stool cultures, 3(38%) had capacity for blood culture. Resistance to enteric organisms was observed with the following and other commonly prescribed antimicrobials, ampicillin: 40(91%)Salmonellaspp isolates; Tetracycline: 16(84%)Shigella flexineriisolates; cotrimoxazole: 20(100%)Shigellaspp isolates, 24(91%)Salmonellaspp isolates. Comparable patterns of multidrug resistance were evident withShigellaflexineri andSalmonella typhimurium. Ten (100%) clinicians reported not using laboratory results for patient management, for various reasons. Conclusion:antimicrobial susceptibility testing capacity was inadequate and the available approved guidelines for this in Kenya were adhered to by one laboratory. The resistance patterns indicated potential resistance to commonly prescribed antimicrobials.

Introduction: Kenya is home to over 400 000 refugees from neighbouring countries. There is scanty information about diarrhoea amongst urban refugees in Kenya.Objectives: We investigated the enteric bacteria causing diarrhoea amongst urban refugee children and described the associated factors.Method: During the period of August–December 2010, urban refugee children between the ages of two and five who attended Eastleigh County Council Health Centre were enrolled into the study. Diarrhoeal cases were compared with age-matched children with no diarrhoea (controls). Stool specimens were collected and enteric bacteria isolated. A questionnaire was administered to identify risk factors.Results: A total of 41 cases and 41 controls were enrolled in the study. The age and country of origin were similar for cases and controls. The bacterial isolation rates amongst the cases were: non-pathogenic Escherichia coli 71%, Shigella dysenteriae 2.4%, Shigella flexneri 2.4%, Salmonella paratyphi 5%. For the controls, non-pathogenic E. coli 90% and enterotoxigenic E. coli (ETEC)2.4% were amongst the organisms isolated. All isolates were resistant to amoxicillin; resistance to other antibiotics varied by isolate type. Factors associated independently with diarrhoea included children not washing their hands with soap (aOR 5.9, p < 0.05), neighbour(s) having diarrhoea (aOR 39.8, p < 0.05), children not exclusively breastfed for their first 6 months (aOR 7.6, p < 0.05) and children eating food cooked the previous day (aOR 23.8, p = 0.002).Conclusions: Shigella species, Salmonella species and ETEC were found to be responsible for diarrhoea amongst the urban refugee children. Measures to control and guide the use of antibiotics are critical for the prevention of antibiotic resistance. Efforts to improve personal and domestic hygiene, including educational campaigns to promote appropriate handwashing, should be encouraged.

Additional file 1. Microscopist questionnaire.

Additional file 1. Microscopist questionnaire.

Additional file 2. Health facility information and slide collection form.

Additional file 2. Health facility information and slide collection form.