Alternative control strategies against ASF in wild boar populations

Lange, Martin

doi:10.2903/sp.efsa.2015.en-843

Cited by 30 publications

(54 citation statements)

References 17 publications

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“…At the time of writing, the current report, and based on expert judgement, a time frame for carcass removal of 2-6 weeks with median at four weeks after the death of the animal is considered feasible. This observation is at odds with the assumptions underlying the simulations in 2015 (see EFSA AHAW Panel, 2015;Lange, 2015).…”

Section: Review Of the Management Options For Wild Boarmentioning

confidence: 96%

“…The intention of this simulation study was to address the validity of earlier analysis of the impact of certain control measures on the spread of ASF in spatially arranged wild boar populations (EFS AAHAW Panel, 2015). An extension of this earlier work was motivated by new insights and updated data sources since the writing of the 2015 material (EFSA AHAW Panel, 2015;Lange, 2015).…”

Section: Review Of the Management Options For Wild Boarmentioning

confidence: 99%

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Epidemiological analyses of African swine fever in the Baltic States and Poland

Depner¹,

Gortázar²,

Gubertì³

et al. 2017

EFS2

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EFSA assisted four countries in the analysis of epidemiological data on African swine fever (ASF), collected until September 2017. The temporal analysis demonstrated that the average proportions of PCR and antibody-ELISA positive samples from the hunted wild boar remained below 3.9 and 6.6, respectively. A peak in the ASF incidence was observed 6 months after the first observed case, followed by a significant reduction of the number of cases and low levels of African swine fever virus (ASFV) circulation at the end of 38 months follow-up period at different spatial resolutions. The spatial analysis concluded that human-mediated spread of ASFV continues to play a critical role in the ASF epidemiology, despite all measures currently taken. 'Wild boar density', 'total road length' (as proxy for human activity) and 'average suitable wild boar habitat availability' were identified as predictors for the occurrence of ASF in Estonia by a Bayesian hierarchical model, whereas 'wild boar density' and 'density of pig farms' were predictors according to a generalised additive model. To evaluate the preventive strategies proposed in EFSA's Scientific Opinion (2015) to stop the spread of ASFV in the wild boar population, a simulation model, building on expert knowledge and literature was used. It was concluded that reduction of wild boar population and carcass removal to stop the spread of ASFV in the wild boar population are more effective when applied preventively in the infected area. Drastic depopulation, targeted hunting of female wild boar and carcass removal solely implemented as measures to control ASF in the wild boar population need to be implemented in a highly effective manner (at or beyond the limit of reported effectivity in wild boar management) to sustainably halt the spread of ASF.

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Section: Review Of the Management Options For Wild Boarmentioning

confidence: 96%

Section: Review Of the Management Options For Wild Boarmentioning

confidence: 99%

Epidemiological analyses of African swine fever in the Baltic States and Poland

Depner¹,

Gortázar²,

Gubertì³

et al. 2017

EFS2

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“…Therefore, the parameter is defined as total distance travelled by boar rather than the straight-line distance from their starting point. Estimates for dispersal distance of boar are wide-ranging, such as less than 30km for most boar but up to 100km possible (Truvé and Lemel 2003), a maximum dispersal distance of 41.53km (Keuling et al 2010), 48km (Lange 2015) and even up to 250km (Andrzejewski and Jezierski 1978). However, these estimates are all based on straight-line distances from original location.…”

Section: Parameter Valuesmentioning

confidence: 99%

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

Taylor

Podgórski

Simons

et al. 2019

Preprint

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African swine fever (ASF) has been causing multiple outbreaks in Russia, Poland and the Baltic countries in recent years and is currently spreading westwards throughout Europe and eastwards into China, with cases occurring in wild boar and domestic pigs. Curtailing further spread of ASF requires full understanding of the transmission pathways of the disease. Wild boars have been implicated as a potential reservoir for the disease and one of the main modes of transmission within Europe. We developed a spatially explicit model to estimate the risk of infection with ASF in boar and pigs due to the natural movement of wild boar that is applicable across the whole of Europe. We demonstrate the model by using it to predict the probability that early cases of ASF in Poland were caused by wild boar dispersion. The risk of infection in 2015 is computed due to wild boar cases in Poland in 2014, compared against the reported cases in 2015 and then the procedure is repeated for 2015-2016. We find that long-and medium-distance spread of ASF (i.e. >30km) is very unlikely to have occurred due to boar dispersal, due in part to the generally short distances boar will travel (<20km on average). We also predict what the relative success of different control strategies would have been in 2015, if they were implemented in 2014. Results suggest that hunting of boar reduces the number of new cases, but a larger region is at risk of ASF compared to no control measure. Alternatively, introducing boar-proof fencing reduces the size of the region at risk in 2015, but not the total number of cases. Overall, our model suggests wild boar movement is only responsible for local transmission of disease, thus other pathways are more dominant in medium and long distance spread of the disease.where represents a cell in Area A, ( ) is the number of wild boar moving from cell to cell and is the prevalence in cell . We thus define ( ) = ∑ ( ) as the total number of infected wild boar entering

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“…The simulation results summarising the likelihood of halting ASF forward spread are expressed as the percentage of runs in which the infection did not spread beyond the zones surrounding the affected area (i.e. once 100 % success was achieved and can be scaled up to larger zones surrounding the affected area).The sizes of the zones surrounding the affected area can be found in more detail in the diagrams in Lange (2015). Table 16 provides the simulation outputs for the most plausible parameterisation (density 1.5/km²; carcass infectivity 0.9 i.e.…”

Section: Advantages and Disadvantages Of Different Wild Boar Managemementioning

confidence: 99%

“…were tested and calibrated against the spatio-temporal dynamics of the available confirmed ASFV detections in wild boar from the eastern European outbreaks (see Lange, 2015). Model quality was assessed against the observed spatio-temporal distribution of ASF detections.…”

Section: Model Justificationmentioning

confidence: 99%

African swine fever

Sihvonen¹

2015

EFS2

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Since entering the eastern EU at the start of 2014, African swine fever (ASF) has spread locally in the wild boar population, independently of outbreaks in domestic pigs. No correlation between the density of the wild boar population and the case notification in an area has been observed. The source of virus introduction appeared to be the low biosecurity level in backyard farms; yet, direct contact between pigs and wild boar has not been reported. Potential wild boar management strategies aimed at controlling ASF were evaluated. First, the published literature was searched for evidence of changes in wild boar demography after implementing different management strategies. A reduction in a wild boar population of more than 60 % as a result of conventional hunting has not been documented in Europe. Secondly, during a consultation meeting, 30 experts identified different wild boar management tools to indirectly combat ASF spread. In the third step, an epidemiological simulation model was developed, to compare the effects of implementing individual or combinations of management tools to control ASF. The model demonstrated that measures such as attempts to reduce the wild boar populations more than 70 % would, in theory, be effective in controlling ASF, but in practice would impossible to be achieved in one hunting season. On the other hand, conventional management strategies, such as implementing a feeding ban or targeted hunting of females, can effectively prevent the spread of ASF in the control area only after multiple years of application. The model predicted that a combination of different tools, such as the exclusion of contact to carcasses and the intensification of conventional hunting, reducing reproduction in the following year by 30-40%, would be effective to stop the spread of ASF in wild boar.

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Alternative control strategies against ASF in wild boar populations

Cited by 30 publications

References 17 publications

Epidemiological analyses of African swine fever in the Baltic States and Poland

Epidemiological analyses of African swine fever in the Baltic States and Poland

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

African swine fever

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