For most rural households in sub-Saharan Africa, healthy livestock play a key role in averting the burden associated with zoonotic diseases, and in meeting household nutritional and socio-economic ...needs. However, there is limited understanding of the complex nutritional, socio-economic, and zoonotic pathways that link livestock health to human health and welfare. Here we describe a platform for integrated human health, animal health and economic welfare analysis designed to address this challenge. We provide baseline epidemiological data on disease syndromes in humans and the animals they keep, and provide examples of relationships between human health, animal health and household socio-economic status.
We designed a study to obtain syndromic disease data in animals along with economic and behavioral information for 1500 rural households in Western Kenya already participating in a human syndromic disease surveillance study. Data collection started in February 2013, and each household is visited bi-weekly and data on four human syndromes (fever, jaundice, diarrhea and respiratory illness) and nine animal syndromes (death, respiratory, reproductive, musculoskeletal, nervous, urogenital, digestive, udder disorders, and skin disorders in cattle, sheep, goats and chickens) are collected. Additionally, data from a comprehensive socio-economic survey is collected every 3 months in each of the study households.
Data from the first year of study showed 93% of the households owned at least one form of livestock (55%, 19%, 41% and 88% own cattle, sheep, goats and chickens respectively). Digestive disorders, mainly diarrhea episodes, were the most common syndromes observed in cattle, goats and sheep, accounting for 56% of all livestock syndromes, followed by respiratory illnesses (18%). In humans, respiratory illnesses accounted for 54% of all illnesses reported, followed by acute febrile illnesses (40%) and diarrhea illnesses (5%). While controlling for household size, the incidence of human illness increased 1.31-fold for every 10 cases of animal illness or death observed (95% CI 1.16-1.49). Access and utilization of animal source foods such as milk and eggs were positively associated with the number of cattle and chickens owned by the household. Additionally, health care seeking was correlated with household incomes and wealth, which were in turn correlated with livestock herd size.
This study platform provides a unique longitudinal dataset that allows for the determination and quantification of linkages between human and animal health, including the impact of healthy animals on human disease averted, malnutrition, household educational attainment, and income levels.
AbstractHigh seroprevalence of Middle East respiratory syndrome coronavirus (MERS-CoV) among camels has been reported in Kenya and other countries in Africa. To date, the only report of MERS-CoV ...seropositivity among humans in Kenya is of two livestock keepers with no known contact with camels. We assessed whether persons exposed to seropositive camels at household level had serological evidence of infection. In 2013, 760 human and 879 camel sera were collected from 275 and 85 households respectively in Marsabit County. Data on human and animal demographics and type of contact with camels were collected. Human and camel sera were tested for anti-MERS-CoV IgG using a commercial enzyme-linked immunosorbent assay (ELISA) test. Human samples were confirmed by plaque reduction neutralization test (PRNT). Logistic regression was used to identify factors associated with seropositivity. The median age of persons sampled was 30 years (range: 5-90) and 50% were males. A quarter (197/760) of the participants reported having had contact with camels defined as milking, feeding, watering, slaughtering, or herding. Of the human sera, 18 (2.4%) were positive on ELISA but negative by PRNT. Of the camel sera, 791 (90%) were positive on ELISA. On univariate analysis, higher prevalence was observed in female and older camels over 4 years of age (
< 0.05). On multivariate analysis, only age remained significantly associated with increased odds of seropositivity. Despite high seroprevalence among camels, there was no serological confirmation of MERS-CoV infection among camel pastoralists in Marsabit County. The high seropositivity suggests that MERS-CoV or other closely related virus continues to circulate in camels and highlights ongoing potential for animal-to-human transmission.
In mid-2015, the United States' Pandemic Prediction and Forecasting Science and Technical Working Group of the National Science and Technology Council, Food and Agriculture Organization Emergency ...Prevention Systems, and Kenya Meteorological Department issued an alert predicting a high possibility of El-Niño rainfall and Rift Valley Fever (RVF) epidemic in Eastern Africa.
In response to the alert, the Kenya Directorate of Veterinary Services (KDVS) carried out an enhanced syndromic surveillance system between November 2015 and February 2016, targeting 22 RVF high-risk counties in the country as identified previously through risk mapping. The surveillance collected data on RVF-associated syndromes in cattle, sheep, goats, and camels from >1100 farmers through 66 surveillance officers. During the 14-week surveillance period, the KDVS received 10,958 reports from participating farmers and surveillance officers, of which 362 (3.3%) had at least one syndrome. The reported syndromes included 196 (54.1%) deaths in young livestock, 133 (36.7%) abortions, and 33 (9.1%) hemorrhagic diseases, with most occurring in November and December, the period of heaviest rainfall. Of the 69 herds that met the suspect RVF herd definition (abortion in flooded area), 24 (34.8%) were defined as probable (abortions, mortalities in the young ones, and/or hemorrhagic signs) but none were confirmed.
This surveillance activity served as an early warning system that could detect RVF disease in animals before spillover to humans. It was also an excellent pilot for designing and implementing syndromic surveillance in animals in the country, which is now being rolled out using a mobile phone-based data reporting technology as part of the global health security system.
More than 75% of emerging infectious diseases are zoonotic in origin and a transdisciplinary, multi-sectoral One Health approach is a key strategy for their effective prevention and control. In 2004, ...US Centers for Disease Control and Prevention office in Kenya (CDC Kenya) established the Global Disease Detection Division of which one core component was to support, with other partners, the One Health approach to public health science. After catalytic events such as the global expansion of highly pathogenic H5N1 and the 2006 East African multi-country outbreaks of Rift Valley Fever, CDC Kenya supported key Kenya government institutions including the Ministry of Health and the Ministry of Agriculture, Livestock, and Fisheries to establish a framework for multi-sectoral collaboration at national and county level and a coordination office referred to as the Zoonotic Disease Unit (ZDU). The ZDU has provided Kenya with an institutional framework to highlight the public health importance of endemic and epidemic zoonoses including RVF, rabies, brucellosis, Middle East Respiratory Syndrome Coronavirus, anthrax and other emerging issues such as anti-microbial resistance through capacity building programs, surveillance, workforce development, research, coordinated investigation and outbreak response. This has led to improved outbreak response, and generated data (including discovery of new pathogens) that has informed disease control programs to reduce burden of and enhance preparedness for endemic and epidemic zoonotic diseases, thereby enhancing global health security. Since 2014, the Global Health Security Agenda implemented through CDC Kenya and other partners in the country has provided additional impetus to maintain this effort and Kenya's achievement now serves as a model for other countries in the region.Significant gaps remain in implementation of the One Health approach at subnational administrative levels; there are sustainability concerns, competing priorities and funding deficiencies.
To-date, Rift Valley fever (RVF) outbreaks have occurred in 38 of the 69 administrative districts in Kenya. Using surveillance records collected between 1951 and 2007, we determined the risk of ...exposure and outcome of an RVF outbreak, examined the ecological and climatic factors associated with the outbreaks, and used these data to develop an RVF risk map for Kenya.
Exposure to RVF was evaluated as the proportion of the total outbreak years that each district was involved in prior epizootics, whereas risk of outcome was assessed as severity of observed disease in humans and animals for each district. A probability-impact weighted score (1 to 9) of the combined exposure and outcome risks was used to classify a district as high (score ≥ 5) or medium (score ≥2 - <5) risk, a classification that was subsequently subjected to expert group analysis for final risk level determination at the division levels (total = 391 divisions). Divisions that never reported RVF disease (score < 2) were classified as low risk. Using data from the 2006/07 RVF outbreak, the predictive risk factors for an RVF outbreak were identified. The predictive probabilities from the model were further used to develop an RVF risk map for Kenya.
The final output was a RVF risk map that classified 101 of 391 divisions (26%) located in 21 districts as high risk, and 100 of 391 divisions (26%) located in 35 districts as medium risk and 190 divisions (48%) as low risk, including all 97 divisions in Nyanza and Western provinces. The risk of RVF was positively associated with Normalized Difference Vegetation Index (NDVI), low altitude below 1000m and high precipitation in areas with solonertz, luvisols and vertisols soil types (p <0.05).
RVF risk map serves as an important tool for developing and deploying prevention and control measures against the disease.
Although seroprevalence of Middle East respiratory coronavirus syndrome is high among camels in Africa, researchers have not detected zoonotic transmission in Kenya. We followed a cohort of 262 camel ...handlers in Kenya during April 2018-March 2020. We report PCR-confirmed Middle East respiratory coronavirus syndrome in 3 asymptomatic handlers.
Zoonotic diseases have varying public health burden and socio-economic impact across time and geographical settings making their prioritization for prevention and control important at the national ...level. We conducted systematic prioritization of zoonotic diseases and developed a ranked list of these diseases that would guide allocation of resources to enhance their surveillance, prevention, and control.
A group of 36 medical, veterinary, and wildlife experts in zoonoses from government, research institutions and universities in Kenya prioritized 36 diseases using a semi-quantitative One Health Zoonotic Disease Prioritization tool developed by Centers for Disease Control and Prevention with slight adaptations. The tool comprises five steps: listing of zoonotic diseases to be prioritized, development of ranking criteria, weighting criteria by pairwise comparison through analytical hierarchical process, scoring each zoonotic disease based on the criteria, and aggregation of scores.
In order of importance, the participants identified severity of illness in humans, epidemic/pandemic potential in humans, socio-economic burden, prevalence/incidence and availability of interventions (weighted scores assigned to each criteria were 0.23, 0.22, 0.21, 0.17 and 0.17 respectively), as the criteria to define the relative importance of the diseases. The top five priority diseases in descending order of ranking were anthrax, trypanosomiasis, rabies, brucellosis and Rift Valley fever.
Although less prominently mentioned, neglected zoonotic diseases ranked highly compared to those with epidemic potential suggesting these endemic diseases cause substantial public health burden. The list of priority zoonotic disease is crucial for the targeted allocation of resources and informing disease prevention and control programs for zoonoses in Kenya.
The impact of gastrointestinal nematodes on health and production of goat was investigated in a low potential area (Ecozone 3) of Kenya. The study involved 44 Small East African goat kids aged 4–5 ...months divided into two replicate groups (treated and control) and set stocked on pasture for 7 months through a dry season and a short rainy season from May to December 1998.
The treated group received fortnightly albendazole treatment while the control group were untreated. Live weight, packed cell volume (PCV), faecal egg counts and pasture larval counts were measured every 2 weeks. Half of the animals from each group were randomly selected for slaughter, total worm counts and identification at the end of December.
The faecal egg counts for the treated group remained low while those of the control group rose gradually through the study period. The counts were higher during the short rainy season. The control group lost weight during the dry season and underwent compensatory growth during the short rainy season. The treated group maintained their weight during the dry season and also showed compensatory growth during the short rainy season. Comparing the weight at the start and end of the study, the treated group gained an average of 3.1±0.3
kg while the control group gained 1.1±0.2
kg. Two goats in the control group died at the end of the dry season after showing clinical signs of parasitic gastroenteritis. Two others in the same group were given salvage treatments during the same period. The PCV (%) values were reduced during the dry season in both groups. The values were higher in the treated group. At slaughter the mean group worm counts for the control group was 1133±387 while that for the treated group was 123±56. In all the animals
Haemonchus contortus was the main nematode recovered. Hypobiotic larvae were recovered in the abomasum.
The pasture larval counts were significantly lower in the paddocks grazed by the treated group in both the dry and short rainy season compared to that grazed by the control group.
It was concluded that gastrointestinal helminths cause production losses, weight loss and mortalities in goats.
H. contortus was the main nematode infecting the goats in this area. The albendazole treatment prevented parasitic gastroenteritis, weight loss and mortalities.
Although livestock vaccination is effective in preventing Rift Valley fever (RVF) epidemics, there are concerns about safety and effectiveness of the only commercially available RVF Smithburn ...vaccine. We conducted a randomized controlled field trial to evaluate the immunogenicity and safety of the new RVF Clone 13 vaccine, recently registered in South Africa.
In a blinded randomized controlled field trial, 404 animals (85 cattle, 168 sheep, and 151 goats) in three farms in Kenya were divided into three groups. Group A included males and non-pregnant females that were randomized and assigned to two groups; one vaccinated with RVF Clone 13 and the other given placebo. Groups B included animals in 1st half of pregnancy, and group C animals in 2nd half of pregnancy, which were also randomized and either vaccinated and given placebo. Animals were monitored for one year and virus antibodies titers assessed on days 14, 28, 56, 183 and 365.
In vaccinated goats (N = 72), 72% developed anti-RVF virus IgM antibodies and 97% neutralizing IgG antibodies. In vaccinated sheep (N = 77), 84% developed IgM and 91% neutralizing IgG antibodies. Vaccinated cattle (N = 42) did not develop IgM antibodies but 67% developed neutralizing IgG antibodies. At day 14 post-vaccination, the odds of being seropositive for IgG in the vaccine group was 3.6 (95% CI, 1.5 - 9.2) in cattle, 90.0 (95% CI, 25.1 - 579.2) in goats, and 40.0 (95% CI, 16.5 - 110.5) in sheep. Abortion was observed in one vaccinated goat but histopathologic analysis did not indicate RVF virus infection. There was no evidence of teratogenicity in vaccinated or placebo animals.
The results suggest RVF Clone 13 vaccine is safe to use and has high (>90%) immunogenicity in sheep and goats but moderate (> 65%) immunogenicity in cattle.
Developing disease risk maps for priority endemic and episodic diseases is becoming increasingly important for more effective disease management, particularly in resource limited countries. For ...endemic and easily diagnosed diseases such as anthrax, using historical data to identify hotspots and start to define ecological risk factors of its occurrence is a plausible approach. Using 666 livestock anthrax events reported in Kenya over 60 years (1957-2017), we determined the temporal and spatial patterns of the disease as a step towards identifying and characterizing anthrax hotspots in the region.
Data were initially aggregated by administrative unit and later analyzed by agro-ecological zones (AEZ) to reveal anthrax spatio-temporal trends and patterns. Variations in the occurrence of anthrax events were estimated by fitting Poisson generalized linear mixed-effects models to the data with AEZs and calendar months as fixed effects and sub-counties as random effects.
The country reported approximately 10 anthrax events annually, with the number increasing to as many as 50 annually by the year 2005. Spatial classification of the events in eight counties that reported the highest numbers revealed spatial clustering in certain administrative sub-counties, with 12% of the sub-counties responsible for over 30% of anthrax events, whereas 36% did not report any anthrax disease over the 60-year period. When segregated by AEZs, there was significantly greater risk of anthrax disease occurring in agro-alpine, high, and medium potential AEZs when compared to the agriculturally low potential arid and semi-arid AEZs of the country (p < 0.05). Interestingly, cattle were > 10 times more likely to be infected by B. anthracis than sheep, goats, or camels. There was lower risk of anthrax events in August (P = 0.034) and December (P = 0.061), months that follow long and short rain periods, respectively.
Taken together, these findings suggest existence of certain geographic, ecological, and demographic risk factors that promote B. anthracis persistence and trasmission in the disease hotspots.
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