Proceedings of the Conference of the International Society for Economics and Social Sciences of Animal Health - South East Asia 2019 (ISESSAH-SEA 2019)

Spatial Analysis of Swine Influenza Virus in Pig Farms Based on Active Surveillance from 2016-2017 in West Java Province, Indonesia

Authors
Nurhayati, Ali Arasyi, Farida Zenal, Caitlin Pfeifer, Mark Stevenson, Trian Mahawan, Afrizal Panus, Sodirun, Katon Kurniawan, Luuk Schoonman, James McGrane, Fajar Tjaturrasa
Corresponding Author
Ali Arasyi
Available Online December 2019.
DOI
10.2991/isessah-19.2019.28How to use a DOI?
Keywords
siv, kernel density, spatial autocorrelation, west java province
Abstract

H1N1 swine flu virus still today in the world become threat for livestock and humans.This disease is fatal to human andhas cause economic losses especially for pig farmers with 100% morbidity rate. The emergence and rapid spread of swine influenza virus (SIV) H1N1 in pig farms is closely related to increase in dense of pig populations and as a reservoir for genetically diverse influenza viruses with the potential infect to humans and backyard farming systems that allow possibility virus transmission from infected pig farm with SIV to the other pig farms. However, despite the high risk for pig farm and human health, control of SIV in Indonesia remains complex, unresolved and can cause severe economic impact on pig farming. The objectives of this study are to characterize the spatial distribution of SIV infection in pig farms in West Java Province and determine the exact pattern of spread from farm to farm and determine the effective strategy to prevent and control SIV disease using spatial analysis. The method used kernel density and spatial autocorrelation using Moran's I and Ripley’s K-Function to analyze the SIV distribution pattern randomly, disperse or cluster over a range of distance. The data used from H1N1 surveillance profiling and result from 2016-2017 from Disease Investigation Center (DIC) Subang. in West Java province, SIV lab testing result and pig population, human population data. The result indicates one clustered district in Kuningan district and 3 non clustered (non-spatial autocorrelation) district in Bogor, Bekasi and Karawang District. Based on kernel density results show pig population density as a spatial risk factor with high density per sq km. Based on k-function indicate to control program should extend to 2 km around the SIV positive farm especially in clustered disease area. This information also useful for disease policy makers for disease prevention and control program. If identified a case of SIV positive in pig farm location, surveillance efforts should extend to another pig farms a distance of 2.000 metres positive farm especially in clustered disease area

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the Conference of the International Society for Economics and Social Sciences of Animal Health - South East Asia 2019 (ISESSAH-SEA 2019)
Series
Advances in Health Sciences Research
Publication Date
December 2019
ISBN
10.2991/isessah-19.2019.28
ISSN
2468-5739
DOI
10.2991/isessah-19.2019.28How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Nurhayati
AU  - Ali Arasyi
AU  - Farida Zenal
AU  - Caitlin Pfeifer
AU  - Mark Stevenson
AU  - Trian Mahawan
AU  - Afrizal Panus
AU  - Sodirun
AU  - Katon Kurniawan
AU  - Luuk Schoonman
AU  - James McGrane
AU  - Fajar Tjaturrasa
PY  - 2019/12
DA  - 2019/12
TI  - Spatial Analysis of Swine Influenza Virus in Pig Farms Based on Active Surveillance from 2016-2017 in West Java Province, Indonesia
BT  - Proceedings of the Conference of the International Society for Economics and Social Sciences of Animal Health - South East Asia 2019 (ISESSAH-SEA 2019)
PB  - Atlantis Press
SP  - 32
EP  - 37
SN  - 2468-5739
UR  - https://doi.org/10.2991/isessah-19.2019.28
DO  - 10.2991/isessah-19.2019.28
ID  - 2019/12
ER  -