Understanding ASF spread and emergency control concepts in wild boar populations using individual‐based modelling and spatio‐temporal surveillance data

Abstract

African swine fever (ASF) infection is circulating in Eurasia since a decade within wild boar populations without a demonstrated vector host. Further the infection was recurrently translocated by spatio‐temporal dynamics that is incompatible with wild boar movement characteristics. Management actions are required in areas affected by ASF. Control measures address areas with recent focal introduction and areas with ASF circulating several seasons or endemic occurrence. In view of acknowledged gaps in understanding ecology and epidemiology of ASF in Eurasian wild boar, mechanistic modelling was applied. A comparative assessment of alternative control efforts in the focal situations was performed, considering pre‐emptive hunting, carcass detection and removal as well as fencing of selected zones. The individual‐based model was applied to test whether inclusion of natural barriers would affect the similarity with ADNS notification data when simulating the landscape scale spread in the Baltics and Poland. The tendency of barriers to improve the explicit space‐time predictions of the model could not be proven, more research is needed here. The comparative assessment revealed that in the focal scenario the increasing removal of carcasses will provide the greatest return on investment (given carcasses being involved in the transmission). Culling of the inner zones, usually with ASF detections, should be organised early if biosecurity standards could be guaranteed. Preventive hunting around the zones affected by ASF was an inevitable measure to cope with the risk of undetected release of the infection, although the measure alone was unable to terminate the spread. Fences assumed not wild boar proof contributed only marginally to the success but may act as demarcation of management zones in practice. The focal approach appears useful and practical to address ASF after local introductions.

Predicting spread and effective control measures for African swine fever– should we blame the boars?

“…Our estimates, which are for spread by wild boar movement only, match the lower bounds of these statistical analyses. Overall, our findings regarding boar movement and ASF spread are in line with previous work, suggesting that wild boar movements have only a small role to play in ASF transmission (Podgórski and Śmietanka 2018) although this can depend on geographical location (Iglesias et al 2018), and the fact that transmission by wild boar is driven principally by boar carcasses (Figure 3, Lange et al (2018)).…”

“…However, as already stated, many of the recent countries with new incursions have implemented a combined strategy of 3 control strategies (fencing, hunting and carcass removal) in different zones. We did not combine intervention strategies, as our focus was on the movement model rather than the control strategies, however, Lange et al (2018) considered various strategies combining zoning, hunting, carcass removal and fencing. Similar to our control strategy of fences with 10km width, they found that fencing may be ineffective if based on locations of reported cases and not on locations of actual infected boar, but in general they found fencing to be a less successful strategy and instead focussed on combining intensive hunting with carcass removal.…”

“…For example, De la Torre et al (2015) and Bosch et al (2017) assess the risk of introduction of ASF due to wild boar at a country level for those countries free of ASF disease using a semi-quantitative method. Quantitative methods include those of Simons et al (2019), which assesses risk of entry at a country level across Europe, using boar abundance and suitability at a fine scale in order to compute this risk, and the models of Thulke and Lange (2017) and Lange et al (2018). In the latter two, boar movement is modelled on a fine spatial scale using individual-based modelling but on an abstraction, i.e.…”

Epidemiological analyses of African swine fever in the European Union (November 2017 until November 2018)

“…Effort per campaign is adjusted to achieve in summary the annual efficacy of depopulation per cent. NB: The culling measures in the core + buffer zone did not alter over all simulations and were set at 90% as after 26 weeks waiting time Uncertainty discussion: Thinking of culling as a large-scale disturbance effect may create substantial uncertainty to the result (see as partial solution in Lange et al, 2018).…”

“…Both (B) and (C) cross-tabulate column-wise different permeability of the fence (left 0% wild boar proof; 5%; middle 10%; 50%; right 90% fence nearly absent) vs row-wise different carcass detection rates (top 1%; 10%; middle 20%; 40%; bottom 80%). Zoning is based on perfect knowledge about infectious carcass distribution at the moment of zoning (results for 10% chance of carcass detection, see Lange et al, 2018). Independent of the size of the buffer zone, and because the core + buffer zones are subject to a hunting ban prior to final culling, ASF will spread into the buffer zone and may subsequently break out (i.e.…”