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

Using ecological niche modelling for mapping the risk of Rift Valley fever in Kenya

Introduction Rift valley fever (RVF) is a viral zoonotic disease of economic importance caused by a virus of the Phlebovirus genus, Bunyaviridae family. The disease occurs cyclically between 5 to 15 years which is associated with El Nino weather phenomenon. Various studies have been done to map RVF distribution using a variety of approaches including the use of disease occurrence maps, statistical models which uses presence and absence data such as logistic regression method, etc. However, acquiring correct absence data is not easy and hence maps generated from standard statistical models might not be a true representation of the disease distribution. Materials and Methods In this study Ecological Niche Modeling was used to determine the distribution of RVF in Kenya using GARP algorithm which uses presence-only data. RVF occurrence data were obtained by geo-referencing all the known hotspots in the country based on historical data acquired from the Directorate of Veterinary Services (DVS). The environmental variables that were used as the input data included: landuse, soil type, elevation, vegetation index acquired from MODIS satellite spanning from October 2006 to march 2007, rainfall and temperature for the same period of time as the satellite imagery. Of the sampled data 70% was used to train the model while 30% to test the model. Results The result mapped the actual distribution of RVF in Kenya with an AUC of 0.82. A model evaluation was done using Partial ROC which had a 1.74 indicating that the model predicted well. Conclusion and Recommendations The results will be used to improve the already existing maps and for better planning of mitigation measures. It will also be used together with socio-economic variables to evaluate vulnerability indices in all the divisions across the country

Use of bio-physical indicators to map and characterize coping strategies of households to Rift Valley fever outbreaks in Ijara District

Extended and above normal rainfall across (semi-) arid Africa after a warm phase of El Niño creates conditions favorable for outbreak of Rift Valley Fever (RVF); a vector borne disease. There have been two major epizootics in the Horn of Africa in 1997/98 and 2006/07 that had the highest mortality to both humans and livestock. Our study, at Ijara District- Kenya, characterizes coping strategies used by communities in high and low risk areas to make themselves less vulnerable to effects of adverse climate variability and in consequent RVF outbreaks. RVF outbreaks resolved to division level werecollated to bio-physical factors that were significantly associated with the outbreaks. Geostatistical analyses were used to identify RVF risk areas. At selected risk areas, focus group discussions (FGDs) involving the local communities, community health workers, and veterinary officers were used to characterize coping strategies that were employed in recent RVF outbreak. Solonetz, luvisols and vertisols and areas below 1000m were significant. Low areas, fairly flat with a 0 – 15% slope rise having these soil types have higher risk compared to the other areas. The low and high RVF risk areas were approximately split halfway across district, northwards and southwards respectively. From the FGDs, actions taken by communities at high risk areas were strategic while those at low risk areas used reactive, ad hoc coping strategies. Communities at high risk areas would cope better to adverse climate variability and extended disease burden compared to those at low risk areas who lack knowledge of some of those strategies. More needs to be done to understand climate variability, disease ecology of RVF, community awareness and facilitation as there are at times the whole district is affected by the RVF

Coping capacity of households to Rift Valley fever case study: Ijara District, Kenya

East-Africa is highly vulnerable to climate variability and adverse effects of climate change. This has made it a challenge to predictors of early warning systems. Extended and above normal rainfall across arid and semi-arid Africa after a warm phase of El Niño creates conditions favourable for outbreak of Rift Valley Fever (RVF). There have been two major outbreaks in the Horn of Africa in 1997/98 and 2006/07 that had the highest mortality to both humans and livestock causing huge economic losses. RVF is a vector borne disease transmitted by a variety of mosquito species to humans and domestic animals. The disease causes abortions in domestic animals and mortality to both animals and human beings. The virus is common in sheep and cattle with secondary transmission to humans by mosquitoes and handling and consumption of infected livestock. In Kenya, the recent outbreak occurred in December 2006 to March 2007 which was confirmed by entomological and epidemiological field investigation of virus activity in areas identified at risk. The first case was reported in Garissa in early December 2006 and later antibodies were detected in blood serum from 10 humans that coincided with livestock RVF confirmations. This outbreak was the worst in history with a record death of 75 people in a span of 3 months with approximately 180 humans being affected in the whole of North Eastern. In the entire period markets remained closed for fear of further outbreak. Our study evaluates areas through an integrated geostatistical analysis where are the risk areas in Ijara, Kenya. Ijara District is one of the eleven districts that form the North Eastern Province.The site has in the past and still is the Rift Valley Fever high risk area. It lies approximately 33oE 6oN, and 43oE 5oS and is devoid of mountains. It is characterized by low undulating plains that have low-lying altitude ranging between zero and 90 metres above sea level. Utilization of remote sensing products makes it possible to capture the anomalous warming and onset of extended rainfall.This is useful to confirming episodic RVF outbreaks. Vegetation green up accompanied on precipitation has been found to be a major influence to abundance of vector populations. The vegetation green up will be determined by normalized difference vegetation index, an indicator of health of vegetation. For the ideal conditions to be created then topography and geology would be other factors to consider in space and water retention capacity respectively. All the above considered it is possible to map and utilize time series measurements to map and predict specific areas at elevated risk for RVF. The study elicits coping strategies, by way of field work, that communities have adopted to make them less exposed to Rift Valley Fever outbreaks. Coping strategies have in the past been known to influence household come community characteristics to absorb shocks that could adversely change their livelihood socially and economically. The choice of coping strategies determines the ability they have to deal with adverse climate variability and outbreaks of diseases like RVF. Then by statistical analysis evaluate which coping strategies make the communities less vulnerable to adverse climatic variability and disease outbreaks. The study also elicits which of the coping strategies adopted by the communities would require information sharing and empowerment of policy makers socio-economically

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