Estimation of the transmission dynamics of African swine fever virus within a swine house
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Estimation of the transmission dynamics of African swine fever virus within a swine house. / Nielsen, J. P.; Larsen, T. S.; Halasa, T.; Christiansen, L. E.
I: Epidemiology and Infection, Bind 145, Nr. 13, 01.10.2017, s. 2787-2796.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Estimation of the transmission dynamics of African swine fever virus within a swine house
AU - Nielsen, J. P.
AU - Larsen, T. S.
AU - Halasa, T.
AU - Christiansen, L. E.
PY - 2017/10/1
Y1 - 2017/10/1
N2 - The spread of African swine fever virus (ASFV) threatens to reach further parts of Europe. In countries with a large swine production, an outbreak of ASF may result in devastating economic consequences for the swine industry. Simulation models can assist decision makers setting up contingency plans. This creates a need for estimation of parameters. This study presents a new analysis of a previously published study. A full likelihood framework is presented including the impact of model assumptions on the estimated transmission parameters. As animals were only tested every other day, an interpretation was introduced to cover the weighted infectiousness on unobserved days for the individual animals (WIU). Based on our model and the set of assumptions, the within- and between-pen transmission parameters were estimated to β w = 1·05 (95% CI 0·62-1·72), β b = 0·46 (95% CI 0·17-1·00), respectively, and the WIU = 1·00 (95% CI 0-1). Furthermore, we simulated the spread of ASFV within a pig house using a modified SEIR-model to establish the time from infection of one animal until ASFV is detected in the herd. Based on a chosen detection limit of 2·55% equivalent to 10 dead pigs out of 360, the disease would be detected 13-19 days after introduction.
AB - The spread of African swine fever virus (ASFV) threatens to reach further parts of Europe. In countries with a large swine production, an outbreak of ASF may result in devastating economic consequences for the swine industry. Simulation models can assist decision makers setting up contingency plans. This creates a need for estimation of parameters. This study presents a new analysis of a previously published study. A full likelihood framework is presented including the impact of model assumptions on the estimated transmission parameters. As animals were only tested every other day, an interpretation was introduced to cover the weighted infectiousness on unobserved days for the individual animals (WIU). Based on our model and the set of assumptions, the within- and between-pen transmission parameters were estimated to β w = 1·05 (95% CI 0·62-1·72), β b = 0·46 (95% CI 0·17-1·00), respectively, and the WIU = 1·00 (95% CI 0-1). Furthermore, we simulated the spread of ASFV within a pig house using a modified SEIR-model to establish the time from infection of one animal until ASFV is detected in the herd. Based on a chosen detection limit of 2·55% equivalent to 10 dead pigs out of 360, the disease would be detected 13-19 days after introduction.
KW - African swine fever
KW - epidemiology
KW - maximum likelihood
KW - modelling
KW - transmission
U2 - 10.1017/S0950268817001613
DO - 10.1017/S0950268817001613
M3 - Journal article
C2 - 28768556
AN - SCOPUS:85026783015
VL - 145
SP - 2787
EP - 2796
JO - Epidemiology and Infection
JF - Epidemiology and Infection
SN - 0950-2688
IS - 13
ER -
ID: 203327247