Predictive Factors and Risk Mapping for Rift Valley Fever Epidemics in Kenya

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.

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.

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.

Contemporary epidemiological data of Rift Valley fever virus in humans, mosquitoes and other animal species in Africa: A systematic review and meta-analysis

Rift Valley fever (RVF) is a severe zoonotic mosquito-borne disease that represents an important threat to human and animal health, with major public health and socioeconomic impacts. This disease is endemic throughout many African countries and the Arabian Peninsula. This systematic review with meta-analysis was conducted to determine the RVF prevalence in humans, mosquitoes and other animal species in Africa. The review also provides contemporary data on RVF case fatality rate (CFR) in humans. In this systematic review with meta-analysis, a comprehensive literature search was conducted on the PubMed, Embase, Web of Science and Global Index Medicus databases from January 2000 to June 2022 to identify relevant studies. Pooled CFR and prevalence estimates were calculated using the random-effects model. Subgroup analysis and sensitivity analysis were performed, and the I2 -statistic was used to investigate a potential source of heterogeneity. A total of 205 articles were included in the final analysis. The overall RVF CFR in humans was found to be 27.5% [95% CI = 8.0-52.5]. The overall pooled prevalence was 7.8% [95% CI = 6.2-9.6] in humans and 9.3% [95% CI = 8.1-10.6] in animals, respectively. The RVF prevalence in individual mosquitoes ranged from 0.0% to 25%. Subgroup analysis showed substantial heterogeneity with respect to geographical regions and human categories. The study shows that there is a correspondingly similar prevalence of RVF in human and animals; however, human CFR is much higher than the observed prevalence. The lack of a surveillance programme and the fact that this virus has subclinical circulation in animals and humans could explain these observations. The implementation of a One Health approach for RVF surveillance and control would be of great interest for human and animal health.

Geostatistical Modeling and Prediction of Rift Valley Fever Seroprevalence among Livestock in Uganda

Uganda reported cases of Rift Valley fever virus (RVFV) for the first time in almost 50 years in 2016, following an outbreak of Rift Valley fever (RVF) that caused four human infections, two of which resulted in death. Subsequent outbreak investigation serosurveys found high seroprevalence of IgG antibodies without evidence of acute infection or IgM antibodies, suggesting the possibility of undetected RVFV circulation prior to the outbreak. After the 2016 outbreak investigation, a serosurvey was conducted in 2017 among domesticated livestock herds across Uganda. Sampling data were incorporated into a geostatistical model to estimate RVF seroprevalence among cattle, sheep, and goats. Variables resulting in the best fit to RVF seroprevalence sampling data included annual variability in monthly precipitation and enhanced vegetation index, topographic wetness index, log human population density percent increase, and livestock species. Individual species RVF seroprevalence prediction maps were created for cattle, sheep, and goats, and a composite livestock prediction was created based on the estimated density of each species across the country. Seroprevalence was greater in cattle compared with sheep and goats. Predicted seroprevalence was greatest in the central and northwestern quadrant of the country, surrounding Lake Victoria, and along the Southern Cattle Corridor. We identified areas that experienced conditions conducive to potential increased RVFV circulation in 2021 in central Uganda. An improved understanding of the determinants of RVFV circulation and locations with high probability of elevated RVF seroprevalence can guide prioritization of disease surveillance and risk mitigation efforts.

Exploring potential risk pathways with high risk groups for urban Rift Valley fever virus introduction, transmission, and persistence in two urban centers of Kenya

Rift Valley fever virus (RVFV) is a zoonotic arbovirus that has profound impact on domestic ruminants and can also be transmitted to humans via infected animal secretions. Urban areas in endemic regions across Africa have susceptible animal and human hosts, dense vector distributions, and source livestock (often from high risk locations to meet the demand for animal protein). Yet, there has never been a documented urban outbreak of RVF. To understand the likely risk of RVFV introduction to urban communities from their perspective and guide future initiatives, we conducted focus group discussions with slaughterhouse workers, slaughterhouse animal product traders, and livestock owners in Kisumu City and Ukunda Town in Kenya. For added perspective and data triangulation, in-depth interviews were conducted one-on-one with meat inspector veterinarians from selected slaughterhouses. A theoretical framework relevant to introduction, transmission, and potential persistence of RVF in urban areas is presented here. Urban livestock were primarily mentioned as business opportunities, but also had personal sentiment. In addition to slaughtering risks, perceived risk factors included consumption of fresh milk. High risk groups' knowledge and experience with RVFV and other zoonotic diseases impacted their consideration of personal risk, with consensus towards lower risk in the urban setting compared to rural areas as determination of health risk was said to primarily rely on hygiene practices rather than the slaughtering process. Groups relied heavily on veterinarians to confirm animal health and meat safety, yet veterinarians reported difficulty in accessing RVFV diagnostics. We also identified vulnerable public health regulations including corruption in meat certification outside of the slaughterhouse system, and blood collected during slaughter being used for food and medicine, which could provide a means for direct RVFV community transmission. These factors, when compounded by diverse urban vector breeding habitats and dense human and animal populations, could create suitable conditions for RVFV to arrive an urban center via a viremic imported animal, transmit to locally owned animals and humans, and potentially adapt to secondary vectors and persist in the urban setting. This explorative qualitative study proposes risk pathways and provides initial insight towards determining how urban areas could adapt control measures and plan future initiatives to better understand urban RVF potential.

Leveraging livestock movements to urban slaughterhouses for wide-spread Rift Valley fever virus surveillance in Western Kenya

Rift Valley fever virus (RVFV) is an economically devastating, zoonotic arbovirus endemic across Africa with potential to cause severe disease in livestock and humans. Viral spread is primarily driven by movement of domestic ruminants and there is a high potential for transboundary spread. Despite influx of livestock to urban areas in response to the high demand for meat and animal products, RVFV has not been detected in any urban center. The objectives of this study were to determine the feasibility of assessing risk of RVFV introduction to urban Kisumu, Kenya, by testing slaughtered livestock for RVFV exposure and mapping livestock origins. Blood was collected from cattle, sheep, and goats directly after slaughter and tested for anti-RVFV IgG antibodies. Slaughterhouse businessmen responded to a questionnaire on their individual animals' origin, marketplace, and transport means. Thereafter, we mapped livestock flow from origin to slaughterhouse using participatory methods in focus group discussions with stakeholders. Qualitative data on route choice and deviations were spatially integrated into the map. A total of 304 blood samples were collected from slaughtered livestock in October and November 2021. Most (99%) of animals were purchased from 28 different markets across eight counties in Western Kenya. The overall RVFV seroprevalence was 9% (19% cattle, 3% in sheep, and 7% in goats). Migori County bordering Tanzania had the highest county-level seroprevalence (34%) and 80% of all seropositive cattle were purchased at the Suba Kuria market in Migori County. Road quality and animal health influenced stakeholders' decisions for choice of transport means. Overall, this proof-of-concept study offers a sampling framework for RVFV that can be locally implemented and rapidly deployed in response to regional risk. This system can be used in conjunction with participatory maps to improve active livestock surveillance and monitoring of RVFV in Western Kenya, and these methods could be extrapolated to other urban centers or livestock diseases.

No evidence of Rift Valley fever antibodies in veterinarians and sheep in Northern Palestine

Background and Aim:

Rift Valley fever virus (RVFV) is a vector-borne virus that causes RVF in humans and ruminants. The clinical symptoms in humans and animals are non-specific and often misdiagnosed, but abortions in ruminants and high mortality in young animals are characteristic. Since the initial outbreak in the Rift Valley area in Kenya, the disease has spread to most African countries and the Middle East. The presence and epidemiological status of RVFV in humans and animals in Palestine are unknown. This study aimed to investigate the presence and risk factors for RVF seroprevalence in veterinarians, as occupational hazard professionals, and sheep, as highly susceptible animals, in Northern Palestine.

Materials and Methods:

A cross-sectional study was conducted. Data and blood samples of 280 Assaf sheep and 100 veterinarians in close occupational contact with sheep were collected between August and September 2020 using an indirect enzyme-linked immunosorbent assay.

Results:

No evidence of RVF antibodies was found in any human or animal sample.

Conclusion:

Our results suggest that RVFV has not circulated in livestock in Northern Palestine, yet. Surveillance and response capabilities and cooperation with the nearby endemic regions are recommended. The distribution of competent vectors in Palestine, associated with global climate change and the role of wild animals, might be a possible route for RVF spreading to Palestine from neighboring countries.

Urban risk factors for human Rift Valley fever virus exposure in Kenya

The Rift Valley fever virus (RVFV) is a zoonotic arbovirus that can also transmit directly to humans from livestock. Previous studies have shown consumption of sick animal products are risk factors for RVFV infection, but it is difficult to disentangle those risk factors from other livestock rearing activities. Urban areas have an increased demand for animal source foods, different vector distributions, and various arboviruses are understood to establish localized urban transmission cycles. Thus far, RVFV is an unevaluated public health risk in urban areas within endemic regions. We tested participants in our ongoing urban cohort study on dengue (DENV) and chikungunya (CHIKV) virus for RVFV exposure and found 1.6% (57/3,560) of individuals in two urban areas of Kenya had anti-RVFV IgG antibodies. 88% (50/57) of RVFV exposed participants also had antibodies to DENV, CHIKV, or both. Although livestock ownership was very low in urban study sites, RVFV exposure was overall significantly associated with seeing goats around the homestead (OR = 2.34 (CI 95%: 1.18-4.69, p = 0.02) and in Kisumu, RVFV exposure was associated with consumption of raw milk (OR = 6.28 (CI 95%: 0.94-25.21, p = 0.02). In addition, lack of piped water and use of small jugs (15-20 liters) for water was associated with a higher risk of RVFV exposure (OR = 5.36 (CI 95%: 1.23-16.44, p = 0.01) and this may contribute to interepidemic vector-borne maintenance of RVFV. We also investigated perception towards human vaccination for RVFV and identified high acceptance (91% (97/105) at our study sites. This study provides baseline evidence to guide future studies investigating the urban potential of RVFV and highlights the unexplored role of animal products in continued spread of RVFV.

Scoping future outbreaks: a scoping review on the outbreak prediction of the WHO Blueprint list of priority diseases

BACKGROUND

The WHO's Research and Development Blueprint priority list designates emerging diseases with the potential to generate public health emergencies for which insufficient preventive solutions exist. The list aims to reduce the time to the availability of resources that can avert public health crises. The current SARS-CoV-2 pandemic illustrates that an effective method of mitigating such crises is the pre-emptive prediction of outbreaks. This scoping review thus aimed to map and identify the evidence available to predict future outbreaks of the Blueprint diseases.

METHODS

We conducted a scoping review of PubMed, Embase and Web of Science related to the evidence predicting future outbreaks of Ebola and Marburg virus, Zika virus, Lassa fever, Nipah and Henipaviral disease, Rift Valley fever, Crimean-Congo haemorrhagic fever, Severe acute respiratory syndrome, Middle East respiratory syndrome and Disease X. Prediction methods, outbreak features predicted and implementation of predictions were evaluated. We conducted a narrative and quantitative evidence synthesis to highlight prediction methods that could be further investigated for the prevention of Blueprint diseases and COVID-19 outbreaks.

RESULTS

Out of 3959 articles identified, we included 58 articles based on inclusion criteria. 5 major prediction methods emerged; the most frequent being spatio-temporal risk maps predicting outbreak risk periods and locations through vector and climate data. Stochastic models were predominant. Rift Valley fever was the most predicted disease. Diseases with complex sociocultural factors such as Ebola were often predicted through multifactorial risk-based estimations. 10% of models were implemented by health authorities. No article predicted Disease X outbreaks.

CONCLUSIONS

Spatiotemporal models for diseases with strong climatic and vectorial components, as in River Valley fever prediction, may currently best reduce the time to the availability of resources. A wide literature gap exists in the prediction of zoonoses with complex sociocultural and ecological dynamics such as Ebola, COVID-19 and especially Disease X.

Preventing the cross-border spread of zoonotic diseases: Multisectoral community engagement to characterize animal mobility-Uganda, 2020

In Uganda, the borders are highly porous to animal movement, which may contribute to zoonotic disease spread. We piloted an animal adaptation of an existing human‐focused toolkit to collect data on animal movement patterns and interactions to inform One Health programs. During January 2020, we conducted focus group discussions and key informant interviews with participatory mapping of 2 national‐level One Health stakeholders and 2 local‐level abattoir representatives from Kampala. Zoonotic disease hotspots changed in 2020 compared with reports from 2017–2019. In contrast to local‐level participants, national‐level participants highlighted districts rather than specific locations. Everyone discussed livestock species; only national‐level participants mentioned wildlife. Participants described seasonality differently. Stakeholders used the results to identify locations for zoonotic disease interventions and sites for future data collection. This implementation of an animal‐adapted population mobility mapping exercise highlights the importance of multisectoral initiatives to promote One Health border health approaches.

Invasive Alien Plants in Africa and the Potential Emergence of Mosquito-Borne Arboviral Diseases-A Review and Research Outlook

The emergence of arthropod-borne viruses (arboviruses) as linked to land-use changes, especially the growing agricultural intensification and expansion efforts in rural parts of Africa, is of growing health concern. This places an additional burden on health systems as drugs, vaccines, and effective vector-control measures against arboviruses and their vectors remain lacking. An integrated One Health approach holds potential in the control and prevention of arboviruses. Land-use changes favour invasion by invasive alien plants (IAPs) and investigating their impact on mosquito populations may offer a new dimension to our understanding of arbovirus emergence. Of prime importance to understand is how IAPs influence mosquito life-history traits and how this may affect transmission of arboviruses to mammalian hosts, questions that we are exploring in this review. Potential effects of IAPs may be significant, including supporting the proliferation of immature and adult stages of mosquito vectors, providing additional nutrition and suitable microhabitats, and a possible interaction between ingested secondary plant metabolites and arboviruses. We conclude that aspects of vector biology are differentially affected by individual IAPs and that while some plants may have the potential to indirectly increase the risk of transmission of certain arboviruses by their direct interaction with the vectors, the reverse holds for other IAPs. In addition, we highlight priority research areas to improve our understanding of the potential health impacts of IAPs.

Epidemiological Investigation of a Rift Valley Fever Outbreak in Humans and Livestock in Kenya, 2018

On the last week of May of 2018, a community-based syndromic surveillance system detected mass abortions and deaths of young livestock in northeastern Kenya. Two weeks later, Rift Valley fever (RVF) was confirmed in humans presenting with febrile illness and hemorrhagic syndrome in the same region. A joint animal and human response team carried out an investigation to characterize the outbreak and identify drivers of disease transmission. Here, we describe the outbreak investigation and findings. A total of 106 human cases were identified in the months of May and June 2018: 92% (98) and 8% (8) of these cases occurring in the northern and western regions of Kenya, respectively. Seventy-six (72%) were probable cases, and 30 (28%) were laboratory confirmed by ELISA and/or PCR. Among the confirmed cases, the median age was 27.5 years (interquartile range = 20), and 60% (18) were males. Overall, the case fatality rate was 7% (n = 8). The majority of the confirmed cases, 19 (63%), reported contact with livestock during slaughter and consumption of meat from sick animals. All confirmed cases had fever, 40% (12) presented with hemorrhagic syndrome, and 23% (7) presented with jaundice. Forty-three livestock herds with at least one suspect and/or confirmed animal case were identified. Death of young animals was reported in 93% (40) and abortions in 84% (36) of livestock herds. The outbreak is indicative of the emergence potential of RVF in traditionally high- and low-risk areas and the risk posed by zoonosis to livestock keepers.

Community venue exposure risk estimator for the COVID-19 pandemic

Complexities of virus genotypes and the stochastic contacts in human society create a big challenge for estimating the potential risks of exposure to a widely spreading virus such as COVID-19. To increase public awareness of exposure risks in daily activities, we propose a birthday-paradox-based probability model to implement in a web-based system, named COSRE (community social risk estimator) and make in-time community exposure risk estimation during the ongoing COVID-19 pandemic. We define exposure risk to mean the probability of people meeting potential cases in public places such as grocery stores, gyms, libraries, restaurants, coffee shops, offices, etc. Our model has three inputs: the real-time number of active and asymptomatic cases, the population in local communities, and the customer counts in the room. With COSRE, possible impacts of the pandemic can be explored through spatiotemporal analysis, e.g., a variable number of people may be projected into public places through time to assess changes of risk as the pandemic unfolds. The system has potential to advance understanding of the true exposure risks in various communities. It introduces an objective element to plan, prepare and respond during a pandemic. Spatial analysis tools are used to draw county-level exposure risks of the United States from April 1 to July 15, 2020. The correlation experiment with the new cases in the next two weeks shows that the risk estimation model offers promise in assisting people to be more precise about their personal safety and control of daily routine and social interaction. It can inform business and municipal COVID-19 policy to accelerate recovery.

High risk for human exposure to Rift Valley fever virus in communities living along livestock movement routes: A cross-sectional survey in Kenya

Introduction

Multiple outbreaks of Rift Valley Fever (RVF) with devastating effects have occurred in East Africa. These outbreaks cause disease in both livestock and humans and affect poor households most severely. Communities living in areas practicing nomadic livestock movement may be at higher risk of infection. This study sought to i) determine the human exposure to Rift Valley fever virus (RVFV) in populations living within nomadic animal movement routes in Kenya; and ii) identify risk factors for RVFV infection in these communities.

Methods

A cross-sectional descriptive study design was used. Samples were collected from the year 2014 to 2015 in a community-based sampling exercise involving healthy individuals aged ≥18 years from Isiolo, Tana River, and Garissa counties. In total, 1210 samples were screened by ELISA for the presence of immunoglobulin IgM and IgG antibodies against RVFV. Positive results were confirmed by plaque reduction neutralization test.

Results

Overall, IgM and IgG prevalence for all sites combined was 1.4% (95% CI 0.8–2.3%) and 36.4% (95% CI 33.8–39.2%), respectively. Isiolo County recorded a non-significant higher IgG prevalence of 38.8% than Garissa 35.9% and Tana River 32.2% (Chi square = 2.5, df = 2, p = 0.287). Males were significantly at higher risk of infection by RVFV than females (OR = 1.67, 95% CI 1.17–2.39, p<0.005). Age was significantly associated with RVFV infection (Wald Chi = 94.2, df = 5, p<0.0001). Individuals who had regular contact with cattle (OR = 1.38, 95%CI 1.01–1.89) and donkeys (OR = 1.38, 95%CI 1.14–1.67), or contact with animals through birthing (OR = 1.69, 95%CI 1.14–2.51) were significantly at a greater risk of RVFV infection than those who did not.

Conclusion

This study demonstrated that although the Isiolo County has been classified as being at medium risk for RVF, virus infection appeared to be as prevalent in humans as in Tana River and Garissa, which have been classified as being at high risk. Populations in these counties live within nomadic livestock movement routes and therefore at risk of being exposed to the RVFV. Interventions to control RVFV infections therefore, should target communities living along livestock movement pathways.

Rift Valley fever (RVF) is a neglected mosquito-borne zoonotic disease that causes major outbreaks and economic harm to human and ruminants health leading to increased poverty within affected communities. RVF is caused by RVF virus (RVFV) affecting humans and a wide range of ruminants. The virus is transmitted through bites from mosquitoes and exposure to blood, body fluids, or tissues of infected ruminants. It was first isolated in Kenya in 1930 and several outbreaks have been recorded in many countries in sub-Saharan Africa. We studied pastoralist communities living along livestock migratory routes. Migratory livestock do move long distances in search of water and pasture and may be at higher risk of exposure to RVFV. We also determined risk factors for RVFV infection by studying age, gender, contact with animals through birthing, and occupation. Prevention and control of RVFV infection can target significant risk factors to prevent spread and re-occurrence of outbreaks.

Integrated Early Warning Surveillance: Achilles' Heel of One Health?

Emerging and re-emerging infectious diseases and zoonoses indicate the importance of the One Health (OH) approach for early warning. At present, even when surveillance data are available, they are infrequently timeously shared between the health sectors. In the context of the MediLabSecure (MLS) Project, we investigated the collection of a set of surveillance indicators able to provide data for the implementation of integrated early warning systems in the 22 MLS countries of the Mediterranean, Black Sea and Sahel regions. We used an online questionnaire (covering vector, human, and animal sectors), focusing on seven relevant arboviruses, that was submitted to 110 officially appointed experts. Results showed that West Nile virus was perceived as the most relevant zoonotic pathogen, while Dengue virus was the most relevant non-zoonotic pathogen in the study area. Data collection of early warning indicators is in place at a different level for all the investigated pathogens and in almost all the MLS Countries. Further assessments on the reliability of the collection in place and on the feasibility of piloting an integrated early warning system for arbovirus could verify if integrated early warning really represents the Achilles' heel of OH.

Successes and challenges of the One Health approach in Kenya over the last decade

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.

Individual-based network model for Rift Valley fever in Kabale District, Uganda

Rift Valley fever (RVF) is a zoonotic disease, that causes significant morbidity and mortality among ungulate livestock and humans in endemic regions. In East Africa, the causative agent of the disease is Rift Valley fever virus (RVFV) which is primarily transmitted by multiple mosquito species in Aedes and Mansonia genera during both epizootic and enzootic periods in a complex transmission cycle largely driven by environmental and climatic factors. However, recent RVFV activity in Uganda demonstrated the capability of the virus to spread into new regions through livestock movements, and underscored the need to develop effective mitigation strategies to reduce transmission and prevent spread among cattle populations. We simulated RVFV transmission among cows in 22 different locations of the Kabale District in Uganda using real world livestock data in a network-based model. This model considered livestock as a spatially explicit factor in different locations subjected to specific vector and environmental factors, and was configured to investigate and quantitatively evaluate the relative impacts of mosquito control, livestock movement, and diversity in cattle populations on the spread of the RVF epizootic. We concluded that cattle movement should be restricted for periods of high mosquito abundance to control epizootic spreading among locations during an RVF outbreak. Importantly, simulation results also showed that cattle populations with heterogeneous genetic diversity as crossbreeds were less susceptible to infection compared to homogenous cattle populations.

Association between Rift Valley fever virus seroprevalences in livestock and humans and their respective intra-cluster correlation coefficients, Tana River County, Kenya

We implemented a cross-sectional study in Tana River County, Kenya, a Rift Valley fever (RVF)-endemic area, to quantify the strength of association between RVF virus (RVFv) seroprevalences in livestock and humans, and their respective intra-cluster correlation coefficients (ICCs). The study involved 1932 livestock from 152 households and 552 humans from 170 households. Serum samples were collected and screened for anti-RVFv immunoglobulin G (IgG) antibodies using inhibition IgG enzyme-linked immunosorbent assay (ELISA). Data collected were analysed using generalised linear mixed effects models, with herd/household and village being fitted as random variables. The overall RVFv seroprevalences in livestock and humans were 25.41% (95% confidence interval (CI) 23.49–27.42%) and 21.20% (17.86–24.85%), respectively. The presence of at least one seropositive animal in a household was associated with an increased odds of exposure in people of 2.23 (95% CI 1.03–4.84). The ICCs associated with RVF virus seroprevalence in livestock were 0.30 (95% CI 0.19–0.44) and 0.22 (95% CI 0.12–0.38) within and between herds, respectively. These findings suggest that there is a greater variability of RVF virus exposure between than within herds. We discuss ways of using these ICC estimates in observational surveys for RVF in endemic areas and postulate that the design of the sentinel herd surveillance should consider patterns of RVF clustering to enhance its effectiveness as an early warning system for RVF epidemics.

Environmental limits of Rift Valley fever revealed using ecoepidemiological mechanistic models

Vector-borne diseases (VBDs) of humans and domestic animals are a significant component of the global burden of disease and a key driver of poverty. The transmission cycles of VBDs are often strongly mediated by the ecological requirements of the vectors, resulting in complex transmission dynamics, including intermittent epidemics and an unclear link between environmental conditions and disease persistence. An important broader concern is the extent to which theoretical models are reliable at forecasting VBDs; infection dynamics can be complex, and the resulting systems are highly unstable. Here, we examine these problems in detail using a case study of Rift Valley fever (RVF), a high-burden disease endemic to Africa. We develop an ecoepidemiological, compartmental, mathematical model coupled to the dynamics of ambient temperature and water availability and apply it to a realistic setting using empirical environmental data from Kenya. Importantly, we identify the range of seasonally varying ambient temperatures and water-body availability that leads to either the extinction of mosquito populations and/or RVF (nonpersistent regimens) or the establishment of long-term mosquito populations and consequently, the endemicity of the RVF infection (persistent regimens). Instabilities arise when the range of the environmental variables overlaps with the threshold of persistence. The model captures the intermittent nature of RVF occurrence, which is explained as low-level circulation under the threshold of detection, with intermittent emergence sometimes after long periods. Using the approach developed here opens up the ability to improve predictions of the emergence and behaviors of epidemics of many other important VBDs.

Enhanced surveillance for Rift Valley Fever in livestock during El Niño rains and threat of RVF outbreak, Kenya, 2015-2016

Background

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.

Methodology/Principal findings

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.

Conclusion/Significance

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.

Occurrence of Rift Valley Fever (RVF) outbreak is associated with heavy El-Niño rainfall. In July 2015, an alert on the likelihood of El-Niño rainfall and RVF outbreak in Eastern Africa region was issued by the United States, Food and Agriculture Organization, and Kenya Meteorological Department. 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 in the 22 counties that had previously been identified as RVF high-risk counties. The surveillance system collected data on RVF-associated syndromes and risk factors in cattle, sheep, goats and camels from more than 1100 farmers. Of the 10,958 field reports submitted, 45 were consistent with suspect RVF disease and 24 of these identified as probable RVF, triggering an immediate response. Whereas investigations of the suspect cases and laboratory testing did not confirm RVF cases, the surveillance system served as an excellent early warning system that could detect disease in animal before spillover to humans.

Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal

Background

Chikungunya virus (CHIKV) originated in a sylvatic cycle of transmission between non-human animal hosts and vector mosquitoes in the forests of Africa. Subsequently the virus jumped out of this ancestral cycle into a human-endemic transmission cycle vectored by anthropophilic mosquitoes. Sylvatic CHIKV cycles persist in Africa and continue to spill over into humans, creating the potential for new CHIKV strains to enter human-endemic transmission. To mitigate such spillover, it is first necessary to delineate the distributions of the sylvatic mosquito vectors of CHIKV, to identify the environmental factors that shape these distributions, and to determine the association of mosquito presence with key drivers of virus spillover, including mosquito and CHIKV abundance. We therefore modeled the distribution of seven CHIKV mosquito vectors over two sequential rainy seasons in Kédougou, Senegal using Maxent.

Methods

Mosquito data were collected in fifty sites distributed in five land cover classes across the study area. Environmental data representing land cover, topographic, and climatic factors were included in the models. Models were compared and evaluated using area under the receiver operating characteristic curve (AUROC) statistics. The correlation of model outputs with abundance of individual mosquito species as well as CHIKV-positive mosquito pools was tested.

Results

Fourteen models were produced and evaluated; the environmental variables most strongly associated with mosquito distributions were distance to large patches of forest, landscape patch size, rainfall, and the normalized difference vegetation index (NDVI). Seven models were positively correlated with mosquito abundance and one (Aedes taylori) was consistently, positively correlated with CHIKV-positive mosquito pools. Eight models predicted high relative occurrence rates of mosquitoes near the villages of Tenkoto and Ngary, the areas with the highest frequency of CHIKV-positive mosquito pools.

Conclusions

Of the environmental factors considered here, landscape fragmentation and configuration had the strongest influence on mosquito distributions. Of the mosquito species modeled, the distribution of Ae. taylori correlated most strongly with abundance of CHIKV, suggesting that presence of this species will be a useful predictor of sylvatic CHIKV presence.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2832-6) contains supplementary material, which is available to authorized users.

Catalysts for implementation of One Health in Kenya

The recent Zika outbreak in the Americas, Ebola epidemic in West Africa and the increased frequency and impact of emerging and re-emerging infections of animal origin have increased the calls for greater preparedness in early detection and responses to public health events. One-Health approaches that emphasize collaborations between human health, animal health and environmental health sectors for the prevention, early detection and response to disease outbreaks have been hailed as a key strategy. Here we highlight three main efforts that have progressed the implementation of One Health in Kenya.

Innate Immune Basis for Rift Valley Fever Susceptibility in Mouse Models

Rift Valley fever virus (RVFV) leads to varied clinical manifestations in animals and in humans that range from moderate fever to fatal illness, suggesting that host immune responses are important determinants of the disease severity. We investigated the immune basis for the extreme susceptibility of MBT/Pas mice that die with mild to acute hepatitis by day 3 post-infection compared to more resistant BALB/cByJ mice that survive up to a week longer. Lower levels of neutrophils observed in the bone marrow and blood of infected MBT/Pas mice are unlikely to be causative of increased RVFV susceptibility as constitutive neutropenia in specific mutant mice did not change survival outcome. However, whereas MBT/Pas mice mounted an earlier inflammatory response accompanied by higher amounts of interferon (IFN)-α in the serum compared to BALB/cByJ mice, they failed to prevent high viral antigen load. Several immunological alterations were uncovered in infected MBT/Pas mice compared to BALB/cByJ mice, including low levels of leukocytes that expressed type I IFN receptor subunit 1 (IFNAR1) in the blood, spleen and liver, delayed leukocyte activation and decreased percentage of IFN-γ-producing leukocytes in the blood. These observations are consistent with the complex mode of inheritance of RVFV susceptibility in genetic studies.

Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'.

Ethnic groups' knowledge, attitude and practices and Rift Valley fever exposure in Isiolo County of Kenya

Rift Valley fever (RVF) is an emerging mosquito-borne viral hemorrhagic fever in Africa and the Arabian Peninsula, affecting humans and livestock. For spread of infectious diseases, including RVF, knowledge, attitude and practices play an important role, and the understanding of the influence of behavior is crucial to improve prevention and control efforts. The objective of the study was to assess RVF exposure, in a multiethnic region in Kenya known to experience RVF outbreaks, from the behavior perspective. We investigated how communities in Isiolo County, Kenya were affected, in relation to their knowledge, attitude and practices, by the RVF outbreak of 2006/2007. A cross-sectional study was conducted involving 698 households selected randomly from three different ethnic communities. Data were collected using a structured questionnaire regarding knowledge, attitudes and practices that could affect the spread of RVF. In addition, information was collected from the communities regarding the number of humans and livestock affected during the RVF outbreak. This study found that better knowledge about a specific disease does not always translate to better practices to avoid exposure to the disease. However, the high knowledge, attitude and practice score measured as a single index of the Maasai community may explain why they were less affected, compared to other investigated communities (Borana and Turkana), by RVF during the 2006/2007 outbreak. We conclude that RVF exposure in Isiolo County, Kenya during the outbreak was likely determined by the behavioral differences of different resident community groups. We then recommend that strategies to combat RVF should take into consideration behavioral differences among communities.

Distribution and abundance of key vectors of Rift Valley fever and other arboviruses in two ecologically distinct counties in Kenya

Background

Rift Valley fever (RVF) is a mosquito-borne viral zoonosis of ruminants and humans that causes outbreaks in Africa and the Arabian Peninsula with significant public health and economic consequences. Humans become infected through mosquito bites and contact with infected livestock. The virus is maintained between outbreaks through vertically infected eggs of the primary vectors of Aedes species which emerge following rains with extensive flooding. Infected female mosquitoes initiate transmission among nearby animals, which amplifies virus, thereby infecting more mosquitoes and moving the virus beyond the initial point of emergence. With each successive outbreak, RVF has been found to expand its geographic distribution to new areas, possibly driven by available vectors. The aim of the present study was to determine if RVF virus (RVFV) transmission risk in two different ecological zones in Kenya could be assessed by looking at the species composition, abundance and distribution of key primary and secondary vector species and the level of virus activity.

Methodology

Mosquitoes were trapped during short and long rainy seasons in 2014 and 2015 using CO₂ baited CDC light traps in two counties which differ in RVF epidemic risk levels(high risk Tana-River and low risk Isiolo),cryo-preserved in liquid nitrogen, transported to the laboratory, and identified to species. Mosquito pools were analyzed for virus infection using cell culture screening and molecular analysis.

Findings

Over 69,000 mosquitoes were sampled and identified as 40 different species belonging to 6 genera (Aedes, Anopheles, Mansonia, Culex, Aedeomyia, Coquillettidia). The presence and abundance of Aedes mcintoshi and Aedes ochraceus, the primary mosquito vectors associated with RVFV transmission in outbreaks, varied significantly between Tana-River and Isiolo. Ae. mcintoshi was abundant in Tana-River and Isiolo but notably, Aedes ochraceus found in relatively high numbers in Tana-River (n = 1,290), was totally absent in all Isiolo sites. Fourteen virus isolates including Sindbis, Bunyamwera, and West Nile fever viruses were isolated mostly from Ae. mcintoshi sampled in Tana-River. RVFV was not detected in any of the mosquitoes.

Conclusion

This study presents the geographic distribution and abundance of arbovirus vectors in two Kenyan counties, which may assist with risk assessment for mosquito borne diseases.

Rift Valley fever (RVF) is a mosquito-borne disease caused by the Rift Valley fever virus (RVFV) transmitted by diverse species of mosquitoes broadly classified into primary vectors and secondary vectors. Primary vectors consist of floodwater Aedes (e.g Ae. mcintoshi, Ae. ochraceus, Ae. sudanensis, Ae. dentatus etc), known to maintain the virus in their drought resistant eggs which are deposited on wet soils on low lying depressions on land, remaining viable in dry soil for variable number of years during dry periods. Following heavy persistent rains with flooding, such eggs hatch with a proportion already infected. Emerging infected adult female mosquitoes initiate transmission to nearby animals which serve as amplifiers, infecting more mosquitoes resulting in outbreaks. Another group of mosquito species, the secondary vectors, mainly from the Culex (Culex pipiens and Culex poicilipes), and other potential vectors including, Culex univittatus, Anopheles and Mansonia species may take over such breeding sites, breed in abundance and incidentally propagate RVFV transmission. Outbreaks of RFV occur at varying intensities among livestock in different counties in Kenya, and counties are classified into high, medium and low risk zones. We assessed the species composition, distribution and abundance of primary and secondary vectors in two counties; Isiolo (medium risk) and Tana-River (high risk). Striking difference in composition of primary vector species between Isiolo and Tana-River was observed suggesting that vector species composition in different regions could further be applied to assess risk of RVF outbreaks and intensity. We propose further evaluation of vector species surveillance as an additional risk assessment tool for RVFV and other mosquito borne viruses.

Effects of climate change on the occurrence and distribution of livestock diseases

The planet's mean air and ocean temperatures have been rising over the last century because of increasing greenhouse gas (GHG) emissions. These changes have substantial effects on the epidemiology of infectious diseases. We describe direct and indirect processes linking climate change and infectious diseases in livestock with reference to specific case studies. Some of the studies are used to show a positive association between temperature and expansion of the geographical ranges of arthropod vectors (e.g. Culicoides imicola, which transmits bluetongue virus) while others are used to illustrate an opposite trend (e.g. tsetse flies that transmit a range of trypanosome parasites in sub-Saharan Africa). We further describe a positive association between extreme events: droughts and El Niño/southern oscillation (ENSO) weather patterns and Rift Valley fever outbreaks in East Africa and some adaptation practices used to mitigate the impacts of climate change that may increase risk of exposure to infectious pathogens. We conclude by outlining mitigation and adaptation measures that can be used specifically in the livestock sector to minimize the impacts of climate change-associated livestock diseases.

Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa

Rift Valley fever (RVF), a mosquito-borne disease affecting ruminants and humans, is one of the most important viral zoonoses in Africa. The objective of the present study was to develop a geographic knowledge-based method to map the areas suitable for RVF amplification and RVF spread in four East African countries, namely, Kenya, Tanzania, Uganda and Ethiopia, and to assess the predictive accuracy of the model using livestock outbreak data from Kenya and Tanzania. Risk factors and their relative importance regarding RVF amplification and spread were identified from a literature review. A numerical weight was calculated for each risk factor using an analytical hierarchy process. The corresponding geographic data were collected, standardized and combined based on a weighted linear combination to produce maps of the suitability for RVF transmission. The accuracy of the resulting maps was assessed using RVF outbreak locations in livestock reported in Kenya and Tanzania between 1998 and 2012 and the ROC curve analysis. Our results confirmed the capacity of the geographic information system-based multi-criteria evaluation method to synthesize available scientific knowledge and to accurately map (AUC = 0.786; 95% CI [0.730-0.842]) the spatial heterogeneity of RVF suitability in East Africa. This approach provides users with a straightforward and easy update of the maps according to data availability or the further development of scientific knowledge.