Publikationsdatenbank

Multiplex network approach for modeling the spread of African swine fever in Poland (2023)

Art

Vortrag

Autoren

Jarynowski, Andrzej (WE 16)

Semenov, Alexander

Czekaj, Łukasz

Belik, Vitaly (WE 16)

Kongress

CSoNet 2023

Hanoi, 11.12.2023

Quelle

Lecture notes in computer science

Bandzählung: 14479

Seiten: 349 – 360

Sprache

Englisch

Verweise

URL (Volltext): https://link.springer.com/chapter/10.1007/978-981-97-0669-3_32

Kontakt

Institut für Veterinär-Epidemiologie und Biometrie

Königsweg 67
14163 Berlin
+49 30 838 56034
epi@vetmed.fu-berlin.de

Abstract / Zusammenfassung

African swine fever (ASF) is a viral infection which causes acute disease in Sus scrofa - domestic pigs and wild boar. Although the virus does not cause disease in humans, the impact it has on the economy, especially via trade and farming disturbance, is substantial. We analyze 3487 ASF notifications of wild boars and pigs in Poland (infection events registered to World Animal Health Organization) from February 2014 to April 2019 comprising event time, longitude, latitude and administrative unit: county (poviat). We propose a spatial modeling approach incorporating phenomenological analysis of multiplex transmission networks due to: 1) domestic pig abundance, 2) disease vectors (wild boar) abundance, 3) human mobility related to disease propagation. We used a pseudo gravity model to simulate the future epidemic projection and calculated the most probable infection paths for all counties (poviats) as well as estimated the most likely disease arrival times with or without countermeasures such as border fencing and animals corridors blocking on the A1 motorway. According to our model, the ASF spread in Poland had been continuing and investigated jump in Autumn 2019 to wschowski poviat (Western Poland) 320 km from the closest previously affected area manifests its complex behavior. The proposed complex network approach promises to be useful for practitioners, farmers and veterinarians, helping them to choose the optimal mitigation strategies.