Journal article
Demand-driven spreading patterns of African swine fever in China
Chaos (Woodbury, N.Y.), Vol.31(6), pp.61102-061102
06/01/2021
DOI: 10.1063/5.0053601
PMID: 34241307
Abstract
African swine fever (ASF) is a highly contagious hemorrhagic viral disease of domestic and wild pigs. ASF has led to major economic losses and adverse impacts on livelihoods of stakeholders involved in the pork food system in many European and Asian countries. While the epidemiology of ASF virus (ASFV) is fairly well understood, there is neither any effective treatment nor vaccine. In this paper, we propose a novel method to model the spread of ASFV in China by integrating the data of pork import/export, transportation networks, and pork distribution centers. We first empirically analyze the overall spatiotemporal patterns of ASFV spread and conduct extensive experiments to evaluate the efficacy of a number of geographic distance measures. These empirical analyses of ASFV spread within China indicate that the first occurrence of ASFV has not been purely dependent on the geographical distance from existing infected regions. Instead, the pork supply-demand patterns have played an important role. Predictions based on a new distance measure achieve better performance in predicting ASFV spread among Chinese provinces and thus have the potential to enable the design of more effective control interventions.
Details
- Title: Subtitle
- Demand-driven spreading patterns of African swine fever in China
- Creators
- Jiannan Yang - City University of Hong KongKaichen Tang - City University of Hong KongZhidong Cao - The State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing 100190, ChinaDirk U. Pfeiffer - City University of Hong KongKang Zhao - University of IowaQingpeng Zhang - City University of Hong KongDaniel Dajun Zeng - The State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Resource Type
- Journal article
- Publication Details
- Chaos (Woodbury, N.Y.), Vol.31(6), pp.61102-061102
- DOI
- 10.1063/5.0053601
- PMID
- 34241307
- NLM abbreviation
- Chaos
- ISSN
- 1054-1500
- eISSN
- 1089-7682
- Publisher
- Amer Inst Physics
- Number of pages
- 7
- Grant note
- 72042018; 71621002; 71972164 / National Natural Science Foundation of China; National Natural Science Foundation of China (NSFC) C1143-20GF / Collaborative Research Fund of the Research Grants Council of Hong Kong
- Language
- English
- Date published
- 06/01/2021
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380500802771
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