Risk of African swine fever virus transmission among wild boar and domestic pigs in Poland

Introduction

African swine fever (ASF) is a notifiable disease of swine that impacts global pork trade and food security. In several countries across the globe, the disease persists in wild boar (WB) populations sympatric to domestic pig (DP) operations, with continued detections in both sectors. While there is evidence of spillover and spillback between the sectors, the frequency of occurrence and relative importance of different risk factors for transmission at the wildlife-livestock interface remain unclear.

Methods

To address this gap, we leveraged ASF surveillance data from WB and DP across Eastern Poland from 2014-2019 in an analysis that quantified the relative importance of different risk factors for explaining variation in each of the ASF surveillance data from WB and DP.

Results

ASF prevalence exhibited different seasonal trends across the sectors: apparent prevalence was much higher in summer (84% of detections) in DP, but more consistent throughout the year in WB (highest in winter with 45%, lowest in summer at 15%). Only 21.8% of DP-positive surveillance data included surveillance in WB nearby (within 5 km of the grid cell within the last 4 weeks), while 41.9% of WB-positive surveillance samples included any DP surveillance samples nearby. Thus, the surveillance design afforded twice as much opportunity to find DP-positive samples in the recent vicinity of WB-positive samples compared to the opposite, yet the rate of positive WB samples in the recent vicinity of a positive DP sample was 48 times as likely than the rate of positive DP samples in the recent vicinity of a positive WB sample. Our machine learning analyses found that positive samples in WB were predicted by WB-related risk factors, but not to DP-related risk factors. In contrast, WB risk factors were important for predicting detections in DP on a few spatial and temporal scales of data aggregation.

Discussion

Our results highlight that spillover from WB to DP might be more frequent than the reverse, but that the structure of current surveillance systems challenge quantification of spillover frequency and risk factors. Our results emphasize the importance of, and provide guidance for, improving cross-sector surveillance designs.

Predictive Analytics of Cattle Host and Environmental and Micro-Climate Factors for Tick Distribution and Abundance at the Livestock-Wildlife Interface in the Lower Okavango Delta of Botswana

Tick distribution and abundance is influenced by several factors that include micro-climate and environmental and host factors. Contextual understanding of the role played by these factors is critical to guide control measures. The aim of this study was to determine the predictive value of these factors for changes in tick distribution and abundance at the livestock-wildlife interface of the lower Okavango Delta. A two-stage quota sampling design was adopted to select 30 clusters of seven cattle each for tick investigation. Tick investigation was done by lifting the tail to count the total number of ticks at the anno-vulva region during the four meteorological seasons of the year. Additional data were collected on ear tag number, location of origin, sex, age, body condition score (BCS), season of the year, stocking density, and Normalized Difference Vegetation Index values of source terrain. A random effects model was used to evaluate predictive value of the above for tick abundance. Additional mapping of tick distribution pattern in the abattoir catchment area was conducted using spatial autocorrelation and hot-spot analysis. Tick intensity of infection increased linearly from males to females (Z = 3.84, p < 0.001), decreased linearly from lower to higher BCS (Z = -4.11, p < 0.001), and increased linearly from cold-dry through dry to wet seasons (Z = 10.19, p < 0.001). Significant clustering of neighboring crushes on account of tick count was noted in the late-hot-dry season, with high tick count in crushes located along the seasonal flood plains and low tick counts in those located in the dry grasslands. It was concluded from this study that cattle tick abundance is influenced largely by season of the year and that the micro-climatic conditions brought about by the seasonal flooding of the delta have a decided effect on tick distribution during the driest of the seasons. Our study has, for the first time, profiled drivers of tick distribution and population growth in this unique ecosystem. This has the potential to benefit human and veterinary public health in the area through implementation of sustainable tick control strategies that are not heavily reliant on acaricides.

Modeling Thermal Suitability for Reindeer (Rangifer tarandus ssp.) Brainworm (Elaphostrongylus rangiferi) Transmission in Fennoscandia

The brainworm, Elaphostrongylus rangiferi, is a nematode which causes neurological disorders (elaphostrongylosis) in reindeer (Rangifer tarandus ssp.). Favorable climatic conditions have been inferred as the cause of sporadic outbreaks of elaphostrongylosis in Norway, supported by positive associations between observed outbreaks/intensity of infection and summer temperatures in the previous years. Climate warming which results in increased transmission of E. rangiferi therefore presents a risk to the health of semi-domesticated and wild reindeer in Fennoscandia (Norway, Sweden, and Finland), the health of co-grazing small ruminants, and the livelihoods of indigenous Sámi herders. As a first step toward developing climate change impact assessments for E. rangiferi, a degree-day model was developed for larval development in a range of gastropod hosts and applied to historic weather data. Predictions were validated by statistical and qualitative comparison against historic parasitological and outbreak records. The model predicted an overall increase in thermal suitability for E. rangiferi, which was statistically significant in the north and along the Scandinavian mountain ranges, where reindeer density is highest. In these regions annual cumulative temperature conditions are suitable for larval development within a single year, potentially changing E. rangiferi epidemiology from a 2-year transmission cycle to a 1-year transmission cycle. This is the first mechanistic model developed for E. rangiferi and could be used to inform veterinary risk assessments on a broad spatial scale. Limitations and further developments are discussed.