The evolution of Kenya's animal health surveillance system and its potential for efficient detection of zoonoses.

Introduction: Animal health surveillance systems in Kenya have undergone significant changes and faced various challenges throughout the years. Methods: In this article, we present a comprehensive overview of the Kenya animal health surveillance system (1944 to 2024), based on a review of archived documents, a scoping literature review, and an examination of past surveillance assessments and evaluation reports. Results: The review of archived documents revealed key historical events that have shaped the surveillance system. These include the establishment of the Directorate of Veterinary Services in 1895, advancements in livestock farming, the implementation of mandatory disease control interventions in 1944, the growth of veterinary services from a section to a ministry in 1954, the disruption caused by the Mau Mau insurrection from 1952 to 1954, which led to the temporary halt of agriculture in certain regions until 1955, the transition of veterinary clinical services from public to private, and the progressive privatization plan for veterinary services starting in 1976. Additionally, we highlight the development of electronic surveillance from 2003 to 2024. The scoping literature review, assessments and evaluation reports uncovered several strengths and weaknesses of the surveillance system. Among the strengths are a robust legislative framework, the adoption of technology in surveillance practices, the existence of a formal intersectoral coordination platform, the implementation of syndromic, sentinel, and community-based surveillance methods, and the presence of a feedback mechanism. On the other hand, the system's weaknesses include the inadequate implementation of strategies and enforcement of laws, the lack of standard case definitions for priority diseases, underutilization of laboratory services, the absence of formal mechanisms for data sharing across sectors, insufficient resources for surveillance and response, limited integration of surveillance and laboratory systems, inadequate involvement of private actors and communities in disease surveillance, and the absence of a direct supervisory role between the national and county veterinary services. Discussion and recommendations: To establish an effective early warning system, we propose the integration of surveillance systems and the establishment of formal data sharing mechanisms. Furthermore, we recommend enhancing technological advancements and adopting artificial intelligence in surveillance practices, as well as implementing risk-based surveillance to optimize the allocation of surveillance resources.

Molecular and serological diagnosis of multiple bacterial zoonoses in febrile outpatients in Garissa County, north-eastern Kenya.

Bacterial zoonoses are diseases caused by bacterial pathogens that can be naturally transmitted between humans and vertebrate animals. They are important causes of non-malarial fevers in Kenya, yet their epidemiology remains unclear. We investigated brucellosis, Q-fever and leptospirosis in the venous blood of 216 malaria-negative febrile patients recruited in two health centres (98 from Ijara and 118 from Sangailu health centres) in Garissa County in north-eastern Kenya. We determined exposure to the three zoonoses using serological (Rose Bengal test for Brucella spp., ELISA for C. burnetti and microscopic agglutination test for Leptospira spp.) and real-time PCR testing and identified risk factors for exposure. We also used non-targeted metagenomic sequencing on nine selected patients to assess the presence of other possible bacterial causes of non-malarial fevers. Considerable PCR positivity was found for Brucella (19.4%, 95% confidence intervals [CI] 14.2-25.5) and Leptospira spp. (1.7%, 95% CI 0.4-4.9), and high endpoint titres were observed against leptospiral serovar Grippotyphosa from the serological testing. Patients aged 5-17 years old had 4.02 (95% CI 1.18-13.70, p-value = 0.03) and 2.42 (95% CI 1.09-5.34, p-value = 0.03) times higher odds of infection with Brucella spp. and Coxiella burnetii than those of ages 35-80. Additionally, patients who sourced water from dams/springs, and other sources (protected wells, boreholes, bottled water, and water pans) had 2.39 (95% CI 1.22-4.68, p-value = 0.01) and 2.24 (1.15-4.35, p-value = 0.02) times higher odds of exposure to C. burnetii than those who used unprotected wells. Streptococcus and Moraxella spp. were determined using metagenomic sequencing. Brucellosis, leptospirosis, Streptococcus and Moraxella infections are potentially important causes of non-malarial fevers in Garissa. This knowledge can guide routine diagnosis, thus helping lower the disease burden and ensure better health outcomes, especially in younger populations.

Navigating One Health in research-for-development: Reflections on the design and implementation of the CGIAR Initiative on One Health.

Adopting One Health approaches is key for addressing interconnected health challenges. Yet, how to best put One Health into practice in research-for-development initiatives aiming to 'deliver impacts' remains unclear. Drawing on the CGIAR Initiative on One Health - a global initiative to address zoonotic diseases, antimicrobial resistance, and food and water safety - we reflect on challenges during program conception and implementation, prompting us to suggest improvements in multisectoral collaboration, coordination, and communication. Our approach involves conducting a researcher-centered process evaluation, comprising individual interviews that are subsequently thematically analyzed and synthesized. The key takeaway is that limited time for planning processes and short program timelines compared to envisioned development impacts may impede research-for-development efforts. Yet, collaborative work can be successful when adequate time and resources are allocated for planning with minimal disruption throughout implementation. Additionally, due to the multifaceted nature of One Health initiatives, it is important to pay attention to co-benefits and trade-offs, where taking action in one aspect may yield advantages and disadvantages in another, aiding to identify sustainable One Health development pathways. Forming close partnerships with national governments and local stakeholders is essential not only to promote sustainability but also to ensure local relevance, enhancing the potential for meaningful impact. Finally, regularly assessing progress toward development goals is critical as development stands as an overarching objective.

Higher livestock abortion burden in arid and semi-arid lands, Kenya, 2019-2020.

Tracking livestock abortion patterns over time and across factors such as species and agroecological zones (AEZs) could inform policies to mitigate disease emergence, zoonoses risk, and reproductive losses. We conducted a year-long population-based active surveillance of livestock abortion between 2019 and 2020, in administrative areas covering 52% of Kenya's landmass and home to 50% of Kenya's livestock. Surveillance sites were randomly selected to represent all AEZs in the country. Local animal health practitioners electronically transmitted weekly abortion reports from each ward, the smallest administrative unit, to a central server, using a simple short messaging service (SMS). Data were analyzed descriptively by administrative unit, species, and AEZ to reveal spatiotemporal patterns and relationships with rainfall and temperature. Of 23,766 abortions reported in all livestock species, sheep and goats contributed 77%, with goats alone contributing 53%. Seventy-seven per cent (n = 18,280) of these abortions occurred in arid and semi-arid lands (ASALs) that primarily practice pastoralism production systems. While spatiotemporal clustering of cases was observed in May-July 2019 in the ASALs, there was a substantial seasonal fluctuation across AEZs. Kenya experiences high livestock abortion rates, most of which go unreported. We recommend further research to document the national true burden of abortions. In ASALs, studies linking pathogen, climate, and environmental surveillance are needed to assign livestock abortions to infectious or non-infectious aetiologies and conducting human acute febrile illnesses surveillance to detect any links with the abortions.

Participatory survey of risk factors and pathways for Rift Valley fever in pastoral and agropastoral communities of Uganda.

To assess pastoralists' and agropastoralists' knowledge on Rift Valley fever (RVF), participatory epidemiological studies were conducted with 215 livestock keepers and 27 key informants in Napak, Butebo, Isingiro and Lyantonde districts, Uganda, between January and February 2022. Livestock keepers in all four districts had knowledge of RVF and even had local names or descriptions for it. Pastoralists and agropastoralists possessed valuable knowledge of RVF clinical descriptions and epidemiological risk factors such as the presence of infected mosquitoes, living in flood-prone areas, and excessive rainfall. RVF was ranked among the top ten most important cattle diseases. Pastoralists called RVF Lonyang, symbolizing a disease associated with jaundice, high fever, abortions in pregnant cows, and sudden death in calves. Key informants identified infected domestic animals, the presence of infected mosquitoes, livestock movement and trade, and infected wild animals as risk pathways for the introduction of RVF into an area. Drinking raw blood and milk was perceived as the most likely pathway for human exposure to RVF virus; while the highest consequence was high treatment costs. The results indicate that pastoralists provided key epidemiological information that could be essential for designing an effective national RVF surveillance and early warning system.

Mapping brucellosis risk in Kenya and its implications for control strategies in sub-Saharan Africa.

In Sub-Saharan Africa (SSA), effective brucellosis control is limited, in part, by the lack of long-term commitments by governments to control the disease and the absence of reliable national human and livestock population-based data to inform policies. Therefore, we conducted a study to establish the national prevalence and develop a risk map for Brucella spp. in cattle to contribute to plans to eliminate the disease in Kenya by the year 2040. We randomly generated 268 geolocations and distributed them across Kenya, proportionate to the area of each of the five agroecological zones and the associated cattle population. Cattle herds closest to each selected geolocation were identified for sampling. Up to 25 cattle were sampled per geolocation and a semi-structured questionnaire was administered to their owners. We tested 6,593 cattle samples for Brucella immunoglobulin G (IgG) antibodies using an Enzyme-linked immunosorbent assay (ELISA). We assessed potential risk factors and performed spatial analyses and prevalence mapping using approximate Bayesian inference implemented via the integrated nested Laplace approximation (INLA) method. The national Brucella spp. prevalence was 6.8% (95% CI: 6.2-7.4%). Exposure levels varied significantly between agro-ecological zones, with a high of 8.5% in the very arid zone with the lowest agricultural potential relative to a low of 0.0% in the agro-alpine zone with the highest agricultural potential. Additionally, seroprevalence increased with herd size, and the odds of seropositivity were significantly higher for females and adult animals than for males or calves. Similarly, animals with a history of abortion, or with multiple reproductive syndromes had higher seropositivity than those without. At the herd level, the risk of Brucella spp. transmission was higher in larger herds, and herds with a history of reproductive problems such as abortion, giving birth to weak calves, or having swollen testes. Geographic localities with high Brucella seroprevalence occurred in northern, eastern, and southern regions of Kenya all primarily characterized by semi-arid or arid agro-ecological zones dominated by livestock pastoralism interspersed with vast areas with mixed livestock-wildlife systems. The large spatial extent of our survey provides compelling evidence for the widespread geographical distribution of brucellosis risk across Kenya in a manner easily understandable for policymakers. Our findings can provide a basis for risk-stratified pilot studies aiming to investigate the cost-effectiveness and efficacy of singular and combined preventive intervention strategies that seek to inform Kenya's Brucellosis Control Policy.

Seroprevalence of Brucella spp. and Rift Valley fever virus among slaughterhouse workers in Isiolo County, northern Kenya.

Brucella spp. and Rift Valley fever virus (RVFV) are classified as priority zoonotic agents in Kenya, based on their public health and socioeconomic impact on the country. Data on the pathogen-specific and co-exposure levels is scarce due to limited active surveillance. This study investigated seroprevalence and co-exposure of Brucella spp. and RVFV and associated risk factors among slaughterhouse workers in Isiolo County, northern Kenya. A cross-sectional serosurvey was done in all 19 slaughterhouses in Isiolo County, enrolling 378 participants into the study. The overall seroprevalences for Brucella spp. and RVFV were 40.2% (95% CI: 35.2-45.4) and 18.3% (95% CI: 14.5-22.5), respectively while 10.3% (95% CI 7.4%-13.8%) of individuals were positive for antibodies against both Brucella spp. and RVFV. Virus neutralisation tests (VNT) confirmed anti-RVFV antibodies in 85% of ELISA-positive samples. Our seroprevalence results were comparable to community-level seroprevalences previously reported in the area. Since most of the study participants were not from livestock-keeping households, our findings attribute most of the detected infections to occupational exposure. The high exposure levels indicate slaughterhouse workers are the most at-risk population and there is need for infection, prevention, and control programs among this high-risk group. This is the first VNT confirmation of virus-neutralising antibodies among slaughterhouse workers in Isiolo County and corroborates reports of the area being a high-risk RVFV area as occasioned by previously reported outbreaks. This necessitates sensitization campaigns to enhance awareness of the risks involved and appropriate mitigation measures.

Seroprevalence and related risk factors of Brucella spp. in livestock and humans in Garbatula subcounty, Isiolo county, Kenya.

BACKGROUND: Brucellosis is a neglected zoonotic disease that affects both animals and humans, causing debilitating illness in humans and socio-economic losses in livestock-keeping households globally. The disease is endemic in many developing countries, including Kenya, but measures to prevent and control the disease are often inadequate among high-risk populations. This study aimed to investigate the human and livestock seroprevalence of brucellosis and associated risk factors of Brucella spp. in a pastoralist region of northern Kenya. METHODS: A cross-sectional survey was conducted using a two-stage cluster sampling method to select households, livestock, and humans for sampling. Blood samples were collected from 683 humans and 2157 animals, and Brucella immunoglobulin G (IgG) antibodies were detected using enzyme-linked immunosorbent assays. A structured questionnaire was used to collect data on potential risk factors associated with human and animal exposures. Risk factors associated with Brucella spp. exposures in humans and livestock were identified using Multivariate logistic regression. RESULTS: The results indicated an overall livestock Brucella spp. seroprevalence of 10.4% (95% Confidence Interval (CI): 9.2-11.7). Camels had the highest exposure rates at 19.6% (95% CI: 12.4-27.3), followed by goats at 13.2% (95% CI: 9.3-17.1), cattle at 13.1% (95% CI: 11.1-15.3) and sheep at 5.4% (95% CI: 4.0-6.9). The herd-level seroprevalence was 51.7% (95% CI: 47.9-55.7). Adult animals (Adjusted Odds Ratio (aOR) = 2.3, CI: 1.3-4.0), female animals (aOR = 1.7, CI: 1.1-2.6), and large herd sizes (aOR = 2.3, CI: 1.3-4.0) were significantly associated with anti-brucella antibody detection while sheep had significantly lower odds of Brucella spp. exposure compared to cattle (aOR = 1.3, CI: 0.8-2.1) and camels (aOR = 2.4, CI: 1.2-4.8). Human individual and household seroprevalences were 54.0% (95% CI: 50.2-58.0) and 86.4% (95% CI: 84.0-89.0), respectively. Significant risk factors associated with human seropositivity included being male (aOR = 2.1, CI:1.3-3.2), residing in Sericho ward (aOR = 1.6, CI:1.1-2.5) and having no formal education (aOR = 3.0, CI:1.5-5.9). There was a strong correlation between human seropositivity and herd exposure (aOR = 1.6, CI:1.2-2.3). CONCLUSIONS: The study provides evidence of high human and livestock exposures to Brucella spp. and identifies important risk factors associated with disease spread. These findings emphasize the need for targeted prevention and control measures to curb the spread of brucellosis and implement a One Health surveillance to ensure early detection of the disease in Isiolo County, Northern Kenya.

Ecological and subject-level drivers of interepidemic Rift Valley fever virus exposure in humans and livestock in Northern Kenya.

Nearly a century after the first reports of Rift Valley fever (RVF) were documented in Kenya, questions on the transmission dynamics of the disease remain. Specifically, data on viral maintenance in the quiescent years between epidemics is limited. We implemented a cross-sectional study in northern Kenya to determine the seroprevalence, risk factors, and ecological predictors of RVF in humans and livestock during an interepidemic period. Six hundred seventy-six human and 1,864 livestock samples were screened for anti-RVF Immunoglobulin G (IgG). Out of the 1,864 livestock samples tested for IgG, a subset of 1,103 samples was randomly selected for additional testing to detect the presence of anti-RVFV Immunoglobulin M (IgM). The anti-RVF virus (RVFV) IgG seropositivity in livestock and humans was 21.7% and 28.4%, respectively. RVFV IgM was detected in 0.4% of the livestock samples. Participation in the slaughter of livestock and age were positively associated with RVFV exposure in humans, while age was a significant factor in livestock. We detected significant interaction between rainfall and elevation's influence on livestock seropositivity, while in humans, elevation was negatively associated with RVF virus exposure. The linear increase of human and livestock exposure with age suggests an endemic transmission cycle, further corroborated by the detection of IgM antibodies in livestock.

A scoping review of zoonotic parasites and pathogens associated with abattoirs in Eastern Africa and recommendations for abattoirs as disease surveillance sites.

Abattoirs are facilities where livestock are slaughtered and are an important aspect in the food production chain. There are several types of abattoirs, which differ in infrastructure and facilities, sanitation and PPE practices, and adherence to regulations. In each abattoir facility, worker exposure to animals and animal products increases their risk of infection from zoonotic pathogens. Backyard abattoirs and slaughter slabs have the highest risk of pathogen transmission because of substandard hygiene practices and minimal infrastructure. These abattoir conditions can often contribute to environmental contamination and may play a significant role in disease outbreaks within communities. To assess further the risk of disease, we conducted a scoping review of parasites and pathogens among livestock and human workers in abattoirs across 13 Eastern African countries, which are hotspots for zoonoses. Our search results (n = 104 articles) showed the presence of bacteria, viruses, fungi, and macroparasites (nematodes, cestodes, etc.) in cattle, goats, sheep, pigs, camels, and poultry. Most articles reported results from cattle, and the most frequent pathogen detected was Mycobacterium bovis, which causes bovine tuberculosis. Some articles included worker survey and questionnaires that suggested how the use of PPE along with proper worker training and safe animal handling practices could reduce disease risk. Based on these findings, we discuss ways to improve abattoir biosafety and increase biosurveillance for disease control and mitigation. Abattoirs are a 'catch all' for pathogens, and by surveying animals at abattoirs, health officials can determine which diseases are prevalent in different regions and which pathogens are most likely transmitted from wildlife to livestock. We suggest a regional approach to biosurveillance, which will improve testing and data gathering for enhanced disease risk mapping and forecasting. Next generation sequencing will be key in identifying a wide range of pathogens, rather than a targeted approach.

Local and wide-scale livestock movement networks inform disease control strategies in East Africa.

Livestock mobility exacerbates infectious disease risks across sub-Saharan Africa, but enables critical access to grazing and water resources, and trade. Identifying locations of high livestock traffic offers opportunities for targeted control. We focus on Tanzanian agropastoral and pastoral communities that account respectively for over 75% and 15% of livestock husbandry in eastern Africa. We construct networks of livestock connectivity based on participatory mapping data on herd movements reported by village livestock keepers as well as data from trading points to understand how seasonal availability of resources, land-use and trade influence the movements of livestock. In communities that practise agropastoralism, inter- and intra-village connectivity through communal livestock resources (e.g. pasture and water) was 1.9 times higher in the dry compared to the wet season suggesting greater livestock traffic and increased contact probability. In contrast, livestock from pastoral communities were 1.6 times more connected at communal locations during the wet season when they also tended to move farther (by 3 km compared to the dry season). Trade-linked movements were twice more likely from rural to urban locations. Urban locations were central to all networks, particularly those with potentially high onward movements, for example to abattoirs, livestock holding grounds, or other markets, including beyond national boundaries. We demonstrate how livestock movement information can be used to devise strategic interventions that target critical livestock aggregation points (i.e. locations of high centrality values) and times (i.e. prior to and after the wet season in pastoral and agropastoral areas, respectively). Such targeted interventions are a cost-effective approach to limit infection without restricting livestock mobility critical to sustainable livelihoods.

Mapping the risk of Rift Valley fever in Uganda using national seroprevalence data from cattle, sheep and goats.

Uganda has had repeated outbreaks of Rift Valley fever (RVF) since March 2016 when human and livestock cases were reported in Kabale after a long interval. The disease has a complex and poorly described transmission patterns which involves several mosquito vectors and mammalian hosts (including humans). We conducted a national serosurvey in livestock to determine RVF virus (RVFV) seroprevalence, risk factors, and to develop a risk map that could be used to guide risk-based surveillance and control measures. A total of 3,253 animals from 175 herds were sampled. Serum samples collected were screened at the National Animal Disease Diagnostics and Epidemiology Centre (NADDEC) using a competition multispecies anti-RVF IgG ELISA kit. Data obtained were analyzed using a Bayesian model that utilizes integrated nested Laplace approximation (INLA) and stochastic partial differential equation (SPDE) approaches to estimate posterior distributions of model parameters, and account for spatial autocorrelation. Variables considered included animal level factors (age, sex, species) and multiple environmental data including meteorological factors, soil types, and altitude. A risk map was generated by projecting fitted (mean) values, from a final model that had environmental factors onto a spatial grid that covered the entire domain. The overall RVFV seroprevalence was 11.3% (95% confidence interval: 10.2-12.3%). Higher RVFV seroprevalences were observed in older animals compared to the young, and cattle compared to sheep and goats. RVFV seroprevalence was also higher in areas that had (i) lower precipitation seasonality, (ii) haplic planosols, and (iii) lower cattle density. The risk map generated demonstrated that RVF virus was endemic in several regions including those that have not reported clinical outbreaks in the northeastern part of the country. This work has improved our understanding on spatial distribution of RVFV risk in the country as well as the expected burden of the disease in livestock.

Using Multiplex Amplicon PCR Technology to Efficiently and Timely Generate Rift Valley Fever Virus Sequence Data for Genomic Surveillance.

Rift Valley fever (RVF) is a febrile vector-borne disease endemic in Africa and continues to spread in new territories. It is a climate-sensitive disease mostly triggered by abnormal rainfall patterns. The disease is associated with high mortality and morbidity in both humans and livestock. RVF is caused by the Rift Valley fever virus (RVFV) of the genus Phlebovirus in the family Phenuiviridae. It is a tripartite RNA virus with three genomic segments: small (S), medium (M) and large (L). Pathogen genomic sequencing is becoming a routine procedure and a powerful tool for understanding the evolutionary dynamics of infectious organisms, including viruses. Inspired by the utility of amplicon-based sequencing demonstrated in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and Ebola, Zika and West Nile viruses, we report an RVFV sample preparation based on amplicon multiplex polymerase chain reaction (amPCR) for template enrichment and reduction of background host contamination. The technology can be implemented rapidly to characterize and genotype RVFV during outbreaks in a near-real-time manner. To achieve this, we designed 74 multiplex primer sets covering the entire RVFV genome to specifically amplify the nucleic acid of RVFV in clinical samples from an animal tissue. Using this approach, we demonstrate achieving complete RVFV genome coverage even from samples containing a relatively low viral load. We report the first primer scheme approach of generating multiplex primer sets for a tripartite virus which can be replicated for other segmented viruses.

A global analysis of One Health Networks and the proliferation of One Health collaborations.

There has been a renewed focus on threats to the human-animal-environment interface as a result of the COVID-19 pandemic, and investments in One Health collaborations are expected to increase. Efforts to monitor the development of One Health Networks (OHNs) are essential to avoid duplication or misalignment of investments. This Series paper shows the global distribution of existing OHNs and assesses their collective characteristics to identify potential deficits in the ways OHNs have formed and to help increase the effectiveness of investments. We searched PubMed, Google, Google Scholar, and relevant conference websites for potential OHNs and identified 184 worldwide for further analysis. We developed four case studies to show important findings from our research and exemplify best practices in One Health operationalisation. Our findings show that, although more OHNs were formed in the past 10 years than in the preceding decade, investment in OHNs has not been equitably distributed; more OHNs are formed and headquartered in Europe than in any other region, and emerging infections and novel pathogens were the priority focus area for most OHNs, with fewer OHNs focusing on other important hazards and pressing threats to health security. We found substantial deficits in the OHNs collaboration model regarding the diversity of stakeholder and sector representation, which we argue impedes effective and equitable OHN formation and contributes to other imbalances in OHN distribution and priorities. These findings are supported by previous evidence that shows the skewed investment in One Health thus far. The increased attention to One Health after the COVID-19 pandemic is an opportunity to focus efforts and resources to areas that need them most. Analyses, such as this Series paper, should be used to establish databases and repositories of OHNs worldwide. Increased attention should then be given to understanding existing resource allocation and distribution patterns, establish more egalitarian networks that encompass the breadth of One Health issues, and serve communities most affected by emerging, re-emerging, or endemic threats at the human-animal-environment interface.

Anthrax hotspot mapping in Kenya support establishing a sustainable two-phase elimination program targeting less than 6% of the country landmass.

Using data collected from previous (n = 86) and prospective (n = 132) anthrax outbreaks, we enhanced prior ecological niche models (ENM) and added kernel density estimation (KDE) approaches to identify anthrax hotspots in Kenya. Local indicators of spatial autocorrelation (LISA) identified clusters of administrative wards with a relatively high or low anthrax reporting rate to determine areas of greatest outbreak intensity. Subsequently, we modeled the impact of vaccinating livestock in the identified hotspots as a national control measure. Anthrax suitable areas included high agriculture zones concentrated in the western, southwestern and central highland regions, consisting of 1043 of 1450 administrative wards, covering 18.5% country landmass, and hosting 30% of the approximately 13 million cattle population in the country. Of these, 79 wards covering 5.5% landmass and hosting 9% of the cattle population fell in identified anthrax hotspots. The rest of the 407 administrative wards covering 81.5% of the country landmass, were classified as low anthrax risk areas and consisted of the expansive low agricultural arid and semi-arid regions of the country that hosted 70% of the cattle population, reared under the nomadic pastoralism. Modelling targeted annual vaccination of 90% cattle population in hotspot administrative wards reduced > 23,000 human exposures. These findings support an economically viable first phase of anthrax control program in low-income countries where the disease is endemic, that is focused on enhanced animal and human surveillance in burden hotspots, followed by rapid response to outbreaks anchored on public education, detection and treatment of infected humans, and ring vaccination of livestock. Subsequently, the global anthrax elimination program focused on sustained vaccination and surveillance in livestock in the remaining few hotspots for a prolonged period (> 10 years) may be implemented.

Co-creation and priority setting for applied and implementation research in One Health: Improving capacities in public and animal health systems in Kenya.

Background: The Kenyan government has successfully been implementing sector specific and multisectoral projects aligned to the Global Health Security Agenda (GHSA). For operational readiness and to enhance the effective planning and implementation of Global Health Security Programs (GHSP) at national and subnational level, there is an urgent need for stakeholders' engagement process to seek input in identifying challenges, prioritise activities for field implementation, and identify applied research and development questions, that should be addressed in the next five years. Methods: The modified Child Health and Nutrition Research Initiative (CHNRI) method was used to identify global health security related priorities for multisectoral implementation in Kenya. Subject matter experts from human, animal and environmental health sectors at national and subnational level contributed to predefined research questions from a number of sources and activities for consideration for implementation using a One Health approach. Sixty-two experts scored the 193 questions based on five pre-defined criteria: 1) feasibility and answerability; 2) potential for burden reduction; 3) potential for a paradigm shift; 4) potential for translation and implementation; and 5) impact on equity. Data resulting from this process was then analysed in a Microsoft Excel spreadsheet to determine the research priorities and experts' agreements. Results: Among the priority activities identified for implementation research were; strengthening One Health governance and legal frameworks; integration of ecosystem health into One Health programming; strengthening disease reporting, integrated data collection, information sharing and joint outbreak response; socio-anthropological and gender-based approaches in improving risk and behavioural change communication and community engagement; and one health workforce development. In addition, the potentials to invest in collaborative predictive risk modelling to enhance epidemic intelligence systems, while strengthening the One Health approach in the food safety incident and emergency response plans are feasible. Interpretation: Successful multisectoral implementation of global health security program in Kenya calls for a whole of society approach that will harness community and private sector knowledge to build preparedness and response capacities while targeting neglected and marginalised populations. This research provides a framework that is worth emulating for cost-effective planning and implementation of overarching One Health programs.

One Health gains momentum in Africa but room exists for improvement.

Objectives: The degree of One-Healthiness of a system relates to the effectiveness of an institution to operate within the six main dimensions which identify to what extent it complies with One Health concept. This paper evaluates institutional compliance with One Health concept in 14 institutions from eight African countries. Methods: We utilised the adapted Network for the Evaluation of One Health (NEOH) tool. The institutions included six national One Health platforms and eight other institutions utilizing One Health approaches. Semi-quantitative evaluation of One Health platforms' competencies in six aspects/dimensions concerning One Health operations and infrastructure: Systems Thinking, Planning, Transdisciplinary working, Sharing, Learning and Systemic Organization, was conducted. Results: The evaluation revealed that although all aspects of One Health scored above average, systemic organization and working in One Health were the strongest areas where tremendous gains had been made across the evaluated countries. The aspects of planning, sharing, learning, and thinking should be optimized to achieve gains emanating from One Health approaches in Africa. Cultural and social balance, and integrated health approach were the strongest areas under working and thinking respectively. Thinking was particularly challenged in areas of dimensions coverage and balance, while planning was challenged in the areas of capacity for detection, identification, monitoring of infectious diseases; biosafety and quality management; skills through taught and distance-learning programmes; information and communication technologies to support learning and skills through research apprenticeships. Conclusion: We conclude that although One Health has gained momentum in Africa, there still exists room for improvement. The revealed strengths, weaknesses, opportunities, and gaps in One Health implementation provide an opportunity for prioritization and refocusing of efforts and resources to strengthen the identified weak areas.

Longitudinal Study of Selected Bacterial Zoonoses in Small Ruminants in Tana River County, Kenya.

Brucellosis, Q fever, and leptospirosis are priority zoonoses worldwide, yet their epidemiology is understudied, and studies investigating multiple pathogens are scarce. Therefore, we selected 316 small ruminants in irrigated, pastoral, and riverine settings in Tana River County and conducted repeated sampling for animals that were initially seronegative between September 2014 and June 2015. We carried out serological and polymerase chain reaction tests and determined risk factors for exposure. The survey-weighted serological incidence rates were 1.8 (95% confidence intervals [CI]: 1.3-2.5) and 1.3 (95% CI: 0.7-2.3) cases per 100 animal-months at risk for Leptospira spp. and C. burnetii, respectively. We observed no seroconversions for Brucella spp. Animals from the irrigated setting had 6.83 (95% CI: 2.58-18.06, p-value = 0.01) higher odds of seropositivity to C. burnetii than those from riverine settings. Considerable co-exposure of animals to more than one zoonosis was also observed, with animals exposed to one zoonosis generally having 2.5 times higher odds of exposure to a second zoonosis. The higher incidence of C. burnetii and Leptospira spp. infections, which are understudied zoonoses in Kenya compared to Brucella spp., demonstrate the need for systematic prioritization of animal diseases to enable the appropriate allocation of resources.

Evidence of co-exposure with Brucella spp, Coxiella burnetii, and Rift Valley fever virus among various species of wildlife in Kenya.

BACKGROUND: Co-infection, especially with pathogens of dissimilar genetic makeup, may result in a more devastating impact on the host. Investigations on co-infection with neglected zoonotic pathogens in wildlife are necessary to inform appropriate prevention and control strategies to reduce disease burden in wildlife and the potential transmission of these pathogens between wildlife, livestock and humans. This study assessed co-exposure of various Kenyan wildflife species with Brucella spp, Coxiella burnetii and Rift Valley fever virus (RVFV). METHODOLOGY: A total of 363 sera from 16 different wildlife species, most of them (92.6%) herbivores, were analysed by Enzyme-linked immunosorbent assay (ELISA) for IgG antibodies against Brucella spp, C. burnetii and RVFV. Further, 280 of these were tested by PCR to identify Brucella species. RESULTS: Of the 16 wildlife species tested, 15 (93.8%) were seropositive for at least one of the pathogens. Mean seropositivities were 18.9% (95% CI: 15.0-23.3) for RVFV, 13.7% (95% CI: 10.3-17.7) for Brucella spp and 9.1% (95% CI: 6.3-12.5) for C. burnetii. Buffaloes (n = 269) had higher seropositivity for Brucella spp. (17.1%, 95% CI: 13.0-21.7%) and RVFV (23.4%, 95% CI: 18.6-28.6%), while giraffes (n = 36) had the highest seropositivity for C. burnetii (44.4%, 95% CI: 27.9-61.9%). Importantly, 23 of the 93 (24.7%) animals positive for at least one pathogen were co-exposed, with 25.4% (18/71) of the positive buffaloes positive for brucellosis and RVFV. On molecular analysis, Brucella DNA was detected in 46 (19.5%, CI: 14.9-24.7) samples, with 4 (8.6%, 95% CI: 2.2-15.8) being identified as B. melitensis. The Fisher's Exact test indicated that seropositivity varied significantly within the different animal families, with Brucella (p = 0.013), C. burnetii (p = <0.001) and RVFV (p = 0.007). Location was also significantly associated (p = <0.001) with Brucella spp. and C. burnetii seropositivities. CONCLUSION: Of ~20% of Kenyan wildlife that are seropositive for Brucella spp, C. burnetii and RVFV, almost 25% indicate co-infections with the three pathogens, particularly with Brucella spp and RVFV.

Genomic surveillance of Rift Valley fever virus: from sequencing to lineage assignment.

Genetic evolution of Rift Valley fever virus (RVFV) in Africa has been shaped mainly by environmental changes such as abnormal rainfall patterns and climate change that has occurred over the last few decades. These gradual environmental changes are believed to have effected gene migration from macro (geographical) to micro (reassortment) levels. Presently, 15 lineages of RVFV have been identified to be circulating within the Sub-Saharan Africa. International trade in livestock and movement of mosquitoes are thought to be responsible for the outbreaks occurring outside endemic or enzootic regions. Virus spillover events contribute to outbreaks as was demonstrated by the largest epidemic of 1977 in Egypt. Genomic surveillance of the virus evolution is crucial in developing intervention strategies. Therefore, we have developed a computational tool for rapidly classifying and assigning lineages of the RVFV isolates. The computational method is presented both as a command line tool and a web application hosted at https://www.genomedetective.com/app/typingtool/rvfv/ . Validation of the tool has been performed on a large dataset using glycoprotein gene (Gn) and whole genome sequences of the Large (L), Medium (M) and Small (S) segments of the RVFV retrieved from the National Center for Biotechnology Information (NCBI) GenBank database. Using the Gn nucleotide sequences, the RVFV typing tool was able to correctly classify all 234 RVFV sequences at species level with 100% specificity, sensitivity and accuracy. All the sequences in lineages A (n = 10), B (n = 1), C (n = 88), D (n = 1), E (n = 3), F (n = 2), G (n = 2), H (n = 105), I (n = 2), J (n = 1), K (n = 4), L (n = 8), M (n = 1), N (n = 5) and O (n = 1) were also correctly classified at phylogenetic level. Lineage assignment using whole RVFV genome sequences (L, M and S-segments) did not achieve 100% specificity, sensitivity and accuracy for all the sequences analyzed. We further tested our tool using genomic data that we generated by sequencing 5 samples collected following a recent RVF outbreak in Kenya. All the 5 samples were assigned lineage C by both the partial (Gn) and whole genome sequence classifiers. The tool is useful in tracing the origin of outbreaks and supporting surveillance efforts.Availability: https://github.com/ajodeh-juma/rvfvtyping.