Application of social network analysis to describe the 2020 swine trading in the Philippines

Issue Date

1-2023

Abstract

Background: This study used social network analysis (SNA) to analyze the static characteristics of the pig trading network in the Philippines, which is a significant risk factor for the spread of diseases like African swine fever (ASF). Methods: The shipping permits issued by the Bureau of Animal Industry (BAI) in 2020 were used in this work. Networks were created for live pigs, semen, and pork products. Top trading nodes for each commodity were identified using eigenvector centrality. Additionally, betweenness, closeness, and degree centrality were calculated. Results: The top trading nodes were identified for each commodity, with Laguna being the top node overall. The other influential provinces included Rizal, Bulacan, Cavite, Cebu, Bukidnon, Tarlac, and the four districts of the National Capital Region (NCR). The average distances reached by live pigs, pork products, and swine semen were 106.80 km, 68.40 km, and 222.97 km, respectively. Conclusions: Identifying influential areas in the swine trading network can help enhance disease control strategies and prevent the spread of ASF and other diseases. Targeting these nodes for active surveillance and preventive programs could lower the risk of disease transmission and minimize its impact.

Source or Periodical Title

Philippine Journal of Veterinary Medicine

ISSN

0031-7705

Volume

60

Issue

1

Page

20-29

Document Type

Article

Frequency

semi-annually

Physical Description

illustrations; tables, graphs

Language

English

En – AGROVOC descriptors

SWINE; LIVESTOCK; SWINE INDUSTRY; AFRICAN SWINE FEVER; DISEASE CONTROL; SOCIAL NETWORK ANALYSIS; PHILIPPINES

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