African swine fever virus (ASFV) in Poland: Prevalence in a wild boar population (2017-2018)

Frant, MP; Łyjak, Magdalena; Bocian, Łukasz; Barszcz, A; Niemczuk, Krzysztof; Woźniakowski, Grzegorz

doi:10.17221/105/2019-vetmed

Cited by 28 publications

(47 citation statements)

References 23 publications

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“…Dead wild boar may therefore disappear faster from the environment in this season, which might explain the low numbers of dead wild boar detected in June. In Poland, similar patterns were found and the numbers of samples from passive surveillance were high in July, while it seems that they were significantly lower in June [ 38 ].…”

Section: Discussionmentioning

confidence: 54%

African Swine Fever and Its Epidemiological Course in Lithuanian Wild Boar

Schulz

Masiulis

Staubach

et al. 2021

Viruses

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African swine fever (ASF) has been present in Lithuania since 2014. It is mainly the wild boar population that is affected. Currently, little is known about the epidemiological course of ASF in Lithuania. In the present study, ASF surveillance data from 2016–2021 were analyzed. The numbers of samples taken from hunted wild boar and wild boar found dead per year and month were recorded and the prevalence was estimated for each study month and administrative unit. A Bayesian space–time model was used to calculate the temporal trend of the prevalence estimates. In addition, population data were analyzed on a yearly basis. Most samples were investigated in 2016 and 2017 and originated from hunted animals. Prevalence estimates of ASF virus-positive wild boar decreased from May 2019 onwards. Seroprevalence estimates showed a slight decrease at the same time, but they increased again at the end of the study period. A significant decrease in the population density was observed over time. The results of the study show that ASF is still present in the Lithuanian wild boar population. A joint interdisciplinary effort is needed to identify weaknesses in the control of ASF in Lithuania and to combat the disease more successfully.

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Section: Discussionmentioning

confidence: 54%

African Swine Fever and Its Epidemiological Course in Lithuanian Wild Boar

Schulz

Masiulis

Staubach

et al. 2021

Viruses

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“…This specific region, called Warsaw cluster, presented as one of the most affected areas by then, therefore in 2018 and 2019 over 2600 ASF cases were confirmed there. Moreover, from the beginning of the disease epidemiology, two distinct clusters might be observed there: southeastern and northwestern to Warsaw, separated by the center of the city and expressway S8 ( Figure 2 ) [ 15 ].…”

Section: Resultsmentioning

confidence: 99%

“…ASFV epidemics nearby Warsaw city began at the end of 2017, and in 2019 over 1500 infected wild boars were confirmed within this cluster. Moreover, from the beginning of the disease epidemiology, two distinct clusters might be observed there, namely the southeastern and northwestern clusters to Warsaw, separated by the center of the city and S8 expressway [ 15 ]. The previous study showed that all tested samples, which were located in the southeastern cluster, possess a unique tandem repeat within the O174L gene [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

The Spillover of African Swine Fever in Western Poland Revealed Its Estimated Origin on the Basis of O174L, K145R, MGF 505-5R and IGR I73R/I329L Genomic Sequences

Mazur-Panasiuk

Walczak

Juszkiewicz

et al. 2020

Viruses

101

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The African swine fever epidemic occurred in Poland at the beginning of 2014 and, up to date, the disease has been spreading mainly in the eastern part of the country. Unexpectedly, in November 2019 an infected wild boar case was confirmed in Lubuskie voivodship in western Poland. During the following weeks, several dozen African swine fever virus (ASFV)-positive animals were notified in the neighboring area, causing severe concern regarding further spread of the disease to the mostly pig-dense region in Poland, namely, Wielkopolskie voivodship. Moreover, almost a year after, several infected wild boar cases were confirmed for the first time in Germany, just beyond the Polish border, sending out a shock wave through the global pig market. The whole genome sequence of ASFV, isolated from the first case of ASF in western Poland, and three selected viruses from other affected areas, revealed the tandem repeat and single nucleotide polymorphism (SNP) variations in reference to the Georgia 2007/1 strain. These data, supported by the conventional sequencing of selected genomic regions from a total of 154 virus samples isolated between 2017 and 2020 in Poland, shed a new light on pathogen epidemiology. The sequence variations within the O174L gene detected in this study showed that cases identified in western Poland might be originating from the so-called southern Warsaw cluster. Moreover, the viruses originating from the northern Warsaw cluster do not possess single nucleotide polymorphism (SNP) mutations within the K145R and MGF 505-5R genes, which are specific to all of the other Polish ASFV strains. These results led to a conclusion of their distinct origin. Supporting these results, the nucleotide sequencing of I73R/I329L intergenic region revealed its new, previously undescribed variant, called IGR IV, with an additional three tandem repeats of 10 nucleotides in comparison to the reference sequence of the Georgia 2007/1 strain.

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“…Thus, methods that account for re-introduction and surveillance design are important in cases where 'single introduction' and 'perfect detection' assumptions are violated. Similar to many wildlife host-pathogen systems [31,[33][34][35], ASFv surveillance in wild boar is mostly passive [36] with only a small proportion of cases likely being detected (e.g., for ASFv in Poland: ≤ 30% of all ASFv carcasses detected by carcass surveillance, ≤ 1.7% of all active ASFv infections detected by hunter harvest, [26]), and genetic evidence suggests that at least two re-introductions from neighboring regions occurred during the time frame of our study [37].…”

Section: Introductionmentioning

confidence: 99%

Social structure defines spatial transmission of African swine fever in wild boar

Pepin

Golnar

Podgórski

2020

Preprint

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191. African swine fever virus (ASFv) is endemic in wild boar in Eastern Europe, challenging 20 elimination in domestic swine. Estimates of the distances between transmission events 21 are crucial for predicting rates of disease spread to guide allocation of surveillance and 22 23 processes in hosts, but effects of these processes on spread are poorly understood, and 24 inferences often include only one process. 25 2. To understand effects of spatial and social processes on disease dynamics we developed 26 spatially-explicit transmission models with different assumptions about social and/or 27 spatial contact processes. We fit the models to ASFv surveillance data from Eastern 28 Poland from 2014-2015 and evaluated how inclusion of social structure affected 29 inference. 30 3. The model that accounted for social along with spatial processes provided better 31 inference of spatial spread and predicted that ~80% of transmission events are within the 32 same family group. 33 4. The models predicted dramatically different effective reproductive numbers, both in 34 magnitude and variation. 35 5. Specifying contact structure with spatial but not social processes can lead to very 36 different disease dynamics and inference of epidemiological parameters. Uncertainty in 37 these processes should be accounted for in predicting spatial spread in social species. 38 39 KEYWORDS: African swine fever, Effective reproduction number, Spatial transmission kernel, 40 Surveillance, Wild boar, 41 42 45 3 disease spread per transmission event and inform how surveillance, containment, or mitigation 46 strategies should be deployed [1]. For example, information on where cases may arise can inform 47 what spatial radius should be used for ring culling, ring vaccination, spatial quarantine or 48 intensive surveillance [2]. Without detailed genetic data or contact tracing data to reconstruct 49 transmission history, STKs are predominantly estimated indirectly by fitting disease transmission 50 models to available case data [1-3] providing valuable insight for developing intervention 51 strategies [4-7]. However, models often make simplifying assumptions based on the available 52 information that could have negative impacts on policy decisions if the models are not robust to 53 violation of these assumptions. Common assumptions in models for estimating STKs include 54 assuming a single introduction event and assuming observation of all transmission events [8]. 55Methods that account for these processes are important for providing more realistic predictions 56 of spatial spread in systems where these assumptions are violated. 57 Another common issue is that the potential scope of contact heterogeneities is often 58 simplified or lacking, such that uncertainty in model specification cannot be considered despite 59 its potential importance [9]. In non-vector-borne disease systems, key drivers of contact 60 heterogeneities include social [10] and spatial processes [2], yet our understanding of the relative 61 role of these processes in ...

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African swine fever virus (ASFV) in Poland: Prevalence in a wild boar population (2017-2018)

Cited by 28 publications

References 23 publications

African Swine Fever and Its Epidemiological Course in Lithuanian Wild Boar

African Swine Fever and Its Epidemiological Course in Lithuanian Wild Boar

The Spillover of African Swine Fever in Western Poland Revealed Its Estimated Origin on the Basis of O174L, K145R, MGF 505-5R and IGR I73R/I329L Genomic Sequences

Social structure defines spatial transmission of African swine fever in wild boar

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