Predicted changes in herd immunity levels against Rift Valley fever virus in livestock following a natural exposure

Introduction Rift Valley fever virus (RVFV) transmission gets elevated following periods of excessive and persistent rainfall. The average inter-epizootic period in Kenya has been estimated to be 3.6 years (range 1–7 years). It is presumed that herd immunity plays an important role in modifying the length of these intervals given that the risk of an epidemic intensifies when herd immunity is low. The objective of this study was to evaluate the relationship between herd immunity and RVFV transmission dynamics. Materials and methods We developed a model to simulate RVFV transmission dynamics. The model comprises 2 vectors (Aedes and Culex spp.) and 2-hosts (cattle and sheep). Vector population dynamics are driven by probability functions that use precipitation obtained from Tropical Rainfall Measuring Mission (TRMM). Host related parameters are based on socio-economic data obtained from empirical studies conducted in Ijara, Kenya. Following the predicted outbreak, we prevented further transmissions and run simulations for five years to assess the evolution of herd immunity patterns. Results and discussion The model reproduces the 2006/7 RVF outbreak and predicts a high herd immunity level at the end of that outbreak (93% in cattle and 81% in sheep). Five years after the end of the outbreak, the herd immunity levels decline to an average of 5.9% [range 2.5, 7.9%] in cattle and 0.1% [range 0, 0.43%] in sheep. The period predicted by the model closely mirrors the average inter-epizootic period in Kenya. The rate of decline is higher in sheep relative to cattle probably due to the greater population turnover associated with higher fecundity rate, off take, replacement rate and shorter lifespan. Other analyses show that seasonal/inter-annual transmissions boost herd immunity. These inter-annual transmissions might be responsible for sustaining herd immunity over time especially when there are no external shocks associated with droughts, migration and tribal animosities. Conclusions This is the first study to utilize a simulation model to demonstrate the impacts of RVF immunity on RVF transmission and it has huge potentials for use in evaluation of cost-effectiveness of vaccination campaigns

Factors influencing the prevalence of trypanosomosis in Orma Boran (trypanotolerant) and Teso zebu (trypanosusceptible) cattle crosses in Teso District, western Kenya

The objective of this study was to determine factors associated with occurrence of trypanosomosis in the first generation (F1) crossbreds between trypanotolerant Orma Boran and trypanosusceptible Teso zebu cattle in a trypanosomosis endemic area in Teso District, western Kenya. The offspring were screened for trypanosomosis and other haemoparasites using parasitological methods. Packed cell volume (PCV), body weights and tsetse density (FTD) were also determined. Factors considered in the analysis included sex, age, body weight and season of the year. Generalized linear mixed models (GLMM) were used for multivariable analysis to account for clustering of observations at the animal level and estimate outcome variance parameters. The overall trypanosomosis prevalence was 2.3% (n=477) probably corresponding to low FTD in the area (<1fly/trap/day). The risk of trypanosomosis infection was higher in dry than wet season (OR = 5.4) and in older than younger offspring (OR = 1.1). The variance parameters obtained indicated that variation of trypanosomosis prevalence lay only at the animal level. Intercurrent haemoparasites detected included Anaplasma marginale, Theileria and Babesia species. Overall, the results suggested that when the tsetse density is very low, control of trypanosomosis in the Orma-Teso zebu offspring in western Kenya require targeting of individual affected animals in the dry seasons

Rift Valley fever: Influence of herd immunity patterns on transmission dynamics

Introduction Rift Valley fever virus (RVFV) transmission gets elevated following periods of excessive and persistent rainfall. The average inter-epizootic period in Kenya has been estimated to be 3.6 years (range 1–7 years). It is presumed that herd immunity plays an important role in modifying the length of these intervals given that the risk of an epidemic intensifies when herd immunity is low. The objective of this study was to evaluate the relationship between herd immunity and RVFV transmission dynamics. Materials and Methods We developed a model to simulate RVFV transmission dynamics. The model comprises 2 vectors (Aedes and Culex spp.) and 2-hosts (cattle and sheep). Vector population dynamics are driven by precipitation obtained from Tropical Rainfall Measuring Mission (TRMM) while those of hosts are parameterized based on socio-economic data obtained from empirical studies conducted in Ijara, Kenya. Simulations are implemented for the period: 1st January 2005 and 23rd June 2010 in an attempt to predict the recent 2006/7 outbreak and other seasonal transmissions that occur during wet seasons. Results The model reproduces the 2006/7 RVF outbreak and predicts a high herd immunity level at the end of that outbreak, with 90% of sheep and 72% of cattle being immune. This immunity wanes overtime, declining to 18% in sheep and 42% in cattle by the end of the simulation period (~4 years). The rate of decline is higher in sheep relative to cattle probably due to the greater population turnover associated with higher fecundity rate, off take, replacement rate and shorter lifespan. These analyses also show that seasonal/inter-annual transmissions boost herd immunity. Preventing these transmissions leads to a reduction in herd immunity levels (10.9% in sheep and 30.6% in cattle) by the end of the simulation period. These inter-annual transmissions might be responsible for sustaining herd immunity over time especially when there are no external shocks associated with droughts, migration and tribal animosities. Conclusions and Recommendations This is the first study to utilize a simulation model to demonstrate the impacts of RVF immunity on RVF transmission and it has huge potentials for use in evaluation of cost-effectiveness of vaccination campaigns

Analysis of small ruminants’ pastoral management practices as risk factors of peste des petits ruminants (PPR) spread in Turkana District, Kenya

Peste des petits ruminants (PPR) is an emerging viral disease spreading throughout Kenya and East Africa causing major losses in the small stock. This study is an attempt to evaluate small stock management practices in Turkana pastoral system, Kenya as predictors of PPR outbreaks. Information on the social practices and the occurrence of PPR outbreaks was obtained by participatory techniques. The small stock management practices, evaluated as factors, in a previous study were simultaneously analyzed with seasons and administrative divisions as the independent risk factors for the presence or absence of PPR outbreaks in 142 Adakars (villages) as the dependent variable. Analyses were carried out for the years 2009 and 2010 combined as one data set and considered as longitudinal repeated data. In the analyses, the presence or absence of PPR outbreaks was the dependent variable. Data were further analyzed separately disaggregated by season where the presence or absence of PPR outbreaks in a season was considered as the dependent variable. All analyses utilized multivariable logistical regression analyses. In the longitudinal analysis, season was the only significant factor associated with PPR outbreak. Disaggregating the data by season revealed that certain seasonal-specific livestock management activities increased the risk of reporting PPR outbreaks: (1) sharing water sources leading to social aggregation of young stock in one point (Factor 3) (odds ratio (OR) = 2.0) in season 2 (wet season) of 2009; (2) sick dams left to nurse their young kids/lambs (Factor 7) (OR=1.62) in the same season in 2010. The finding of diverse risk factors in the same seasons across years suggests temporal heterogeneity in the distribution and occurrence of the determinants of PPR in the Turkana ecosystem. The study discusses the implications of these findings on disease control

Persistence of Rift Valley fever virus in East Africa

Rift Valley fever virus (RVFv) is a mosquito-borne pathogen of livestock, wildlife and humans that causes severe outbreaks in intervals of several years. One of the open questions is how the virus persists between outbreaks. We developed a spatially-explicit, individual-based simulation model of the RVFv transmission dynamics to investigate this question. The model, is based on livestock and mosquito population dynamics. Spatial aspects are explicitly represented by a set of grid cells that represent mosquito breeding sites. A grid cell measures 500×500 m and the model considers a grid of 100×100 grid cells; the model thus operates on the regional scale of 2,500 km2. Livestock herds move between grid cells, and provide connectivity between the cells. The model is used to explore the spatio-temporal dynamics of RVFv persistence in absence of a wildlife reservoir in an east African semi-arid context. Specifically, the model assesses the importance of local virus persistence in mosquito breeding sites relative to global virus persistence mitigated by movement of hosts. Local persistence is determined by the length of time the virus remains in a mosquito breeding site once introduced. In the model, this is a function of the number of mosquitoes that emerge infected and their lifespan. Global persistence is determined by the level of connectivity between isolated grid cells. Our work gives insights into the ecological and epidemiological conditions under which RVFv persists. The implication for disease surveillance and management are discussed

Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach

Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006–2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data