The paper extends the susceptible\u2013exposed\u2013infective\u2013removed model to handle
\nheterogeneity introduced by spatially arranged populations, biologically plausible distributional
\nassumptions and incorporation of observations from additional diagnostic tests. These extensions
\nare motivated by a desire to analyse disease transmission experiments in a more detailed
\nfashion than before. Such experiments are performed by veterinarians to gain knowledge about
\nthe dynamics of an infectious disease. By fitting our spatial susceptible\u2013exposed\u2013infective\u2013
\nremoved with diagnostic testing model to data for a specific disease and production environment
\na valuable decision support tool is obtained, e.g. when evaluating on-farm control measures.
\nPartial observability of the epidemic process is an inherent problem when trying to estimate
\nmodel parameters from experimental data.We therefore extend existing work on Markov chain
\nMonte Carlo estimation in partially observable epidemics to the multitype epidemic set-up of
\nour model. Throughout the paper, data from a Belgian classical swine fever virus transmission
\nexperiment are used as a motivating example.<\/p>\n","protected":false},"excerpt":{"rendered":"
The paper extends the susceptible\u2013exposed\u2013infective\u2013removed model to handle heterogeneity introduced by spatially arranged populations, biologically plausible distributional assumptions and incorporation of observations from additional diagnostic tests. These extensions are motivated by a desire to analyse disease transmission experiments in a more detailed fashion than before. Such experiments are performed by veterinarians to gain knowledge about […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[928],"tags":[8882,13816,4822,25121,2817,19644,60,20007,26380,2771,10858,16262,17743,27282,35,20608,20911,1579,2481],"class_list":["post-5437","post","type-post","status-publish","format-standard","hentry","category-welfare","tag-al","tag-ass","tag-bayesian-inference-classical-swine-fever-virus-markov-chain-monte-carlo-methods-multitype-epidemic-on-farm-health-management","tag-chain","tag-cla","tag-dd","tag-disease","tag-gh","tag-infec","tag-iron","tag-mark","tag-pl","tag-prod","tag-production","tag-swine","tag-swine-fever","tag-t","tag-test","tag-work"],"_links":{"self":[{"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/posts\/5437","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/comments?post=5437"}],"version-history":[{"count":0,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/posts\/5437\/revisions"}],"wp:attachment":[{"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/media?parent=5437"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/categories?post=5437"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/tags?post=5437"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}