No abstract

Camels are increasingly becoming the livestock of choice for pastoralists reeling from effects of climate change in semi-arid and arid parts of Kenya. As the population of camels rises, better understanding of their role in the epidemiology of zoonotic diseases in Kenya is a public health priority. Rift Valley fever (RVF), brucellosis and Q fever are three of the top priority diseases in the country but the involvement of camels in the transmission dynamics of these diseases is poorly understood. We analyzed 120 camel serum samples from northern Kenya to establish seropositivity rates of the three pathogens and to characterize the infecting Brucella species using molecular assays. We found seropositivity of 24.2% (95% confidence interval [CI]: 16.5–31.8%) for Brucella, 20.8% (95% CI: 13.6–28.1%) and 14.2% (95% CI: 7.9–20.4%) for Coxiella burnetii and Rift valley fever virus respectively. We found 27.5% (95% CI: 19.5–35.5%) of the animals were seropositive for at least one pathogen and 13.3% (95% CI: 7.2–19.4%) were seropositive for at least two pathogens. B. melitensis was the only Brucella spp. detected. The high sero-positivity rates are indicative of the endemicity of these pathogens among camel populations and the possible role the species has in the epidemiology of zoonotic diseases. Considering the strong association between human infection and contact with livestock for most zoonotic infections in Kenya, there is immediate need to conduct further research to determine the role of camels in transmission of these zoonoses to other livestock species and humans. This information will be useful for designing more effective surveillance systems and intervention measures.

Background To improve early detection of emerging infectious diseases in sub-Saharan Africa (SSA), many of them zoonotic, numerous electronic animal disease-reporting systems have been piloted but not implemented because of cost, lack of user friendliness, and data insecurity. In Kenya, we developed and rolled out an open-source mobile phone-based domestic and wild animal disease reporting system and collected data over two years to investigate its robustness and ability to track disease trends. Methods The Kenya Animal Biosurveillance System (KABS) application was built on the Java® platform, freely downloadable for android compatible mobile phones, and supported by web-based account management, form editing and data monitoring. The application was integrated into the surveillance systems of Kenya’s domestic and wild animal sectors by adopting their existing data collection tools, and targeting disease syndromes prioritized by national, regional and international animal and human health agencies. Smartphone-owning government and private domestic and wild animal health officers were recruited and trained on the application, and reports received and analyzed by Kenya Directorate of Veterinary Services. The KABS application performed automatic basic analyses (frequencies, spatial distribution), which were immediately relayed to reporting officers as feedback. Results Of 697 trained domestic animal officers, 662 (95%) downloaded the application, and >72% of them started reporting using the application within three months. Introduction of the application resulted in 2- to 14-fold increase in number of disease reports when compared to the previous year (relative risk = 14, CI 13.8–14.2, p<0.001), and reports were more widely distributed. Among domestic animals, food animals (cattle, sheep, goats, camels, and chicken) accounted for >90% of the reports, with respiratory, gastrointestinal and skin diseases constituting >85% of the reports. Herbivore wildlife (zebra, buffalo, elephant, giraffe, antelopes) accounted for >60% of the wildlife disease reports, followed by carnivores (lions, cheetah, hyenas, jackals, and wild dogs). Deaths, traumatic injuries, and skin diseases were most reported in wildlife. Conclusions This open-source system was user friendly and secure, ideal for rolling out in other countries in SSA to improve disease reporting and enhance preparedness for epidemics of zoonotic diseases.

Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic disease transmitted from dromedary camels to people, which can result in outbreaks with human-to-human transmission. Because it is a subclinical infection in camels, epidemiological measures other than prevalence are challenging to assess. This study estimated the force of infection (FOI) of MERS-CoV in camel populations from age-stratified serological data. A cross-sectional study of MERS-CoV was conducted in Kenya from July 2016 to July 2017. Seroprevalence was stratified into four age groups: <1, 1–2, 2–3 and >3 years old. Age-independent and age-dependent linear and quadratic generalised linear models were used to estimate FOI in pastoral and ranching camel herds. Models were compared based on computed AIC values. Among pastoral herds, the age-dependent quadratic FOI was the best fit model, while the age-independent FOI was the best fit for the ranching herd data. FOI provides an indirect estimate of infection risk, which is especially valuable where direct estimates of incidence and other measures of infection are challenging to obtain. The FOIs estimated in this study provide important insight about MERS-CoV dynamics in the reservoir species, and contribute to our understanding of the zoonotic risks of this important public health threat.

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is an emerging viral disease and dromedary camels are known to be the source of human spill over events. A cross-sectional epidemiological surveillance study was carried out in Kenya in 2017 to, 1) estimate MERS-CoV antibody seropositivity in the camel-dense counties of Turkana, Marsabit, Isiolo, Laikipia and Nakuru to identify, and 2) determine the risk factors associated with seropositivity in camels. Blood samples were collected from a total of 1421 camels selected using a multi-stage sampling method. Data were also collected from camel owners or herders using a pre-tested structured questionnaire. The sera from camel samples were tested for the presence circulating antibodies to MERS-CoV using the anti-MERS-CoV IgG ELISA test. Univariate and multivariable statistical analysis were used to investigate factors potentially associated with MERS-CoV seropositivity in camels. The overall seropositivity in camel sera was 62.9 %, with the highest seropositivity recorded in Isiolo County (77.7 %), and the lowest seropositivity was recorded in Nakuru County (14.0 %). When risk factors for seropositivity were assessed, the “ Type of camel production system ” {(aOR = 5.40(95 %CI: 1.67–17.49)}, “ Age between 1–2 years, 2–3 years and above 3 years ” {(aOR = 1.64 (95 %CI: 1.04–2.59}”, {(aOR = 3.27 (95 %CI: 3.66–5.61)}” and {(aOR = 6.12 (95 %CI: 4.04–9.30)} respectively and “ Sex of camels ” {(aOR = 1.75 (95 %CI: 1.27–2.41)} were identified as significant predictors of MERS-CoV seropositivity. Our studies indicate a high level of seropositivity to MERS-CoV in camels in the counties surveyed, and highlights the important risk factors associated with MERS-CoV seropositivity in camels. Given that MERS-CoV is a zoonosis, and Kenya possesses the fourth largest camel population in Africa, these findings are important to inform the development of efficient and risk-based prevention and mitigation strategies against MERS-CoV transmission to humans.