Transmission and Control of African Horse Sickness in The Netherlands: A Model Analysis
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{"title"=>"Transmission and control of African horse sickness in the Netherlands: A model analysis", "type"=>"journal", "authors"=>[{"first_name"=>"Jantien A.", "last_name"=>"Backer", "scopus_author_id"=>"34867835900"}, {"first_name"=>"Gonnie", "last_name"=>"Nodelijk", "scopus_author_id"=>"6602294431"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"79961164799", "doi"=>"10.1371/journal.pone.0023066", "issn"=>"19326203", "pui"=>"362285003", "isbn"=>"1932-6203 (Electronic)\\n1932-6203 (Linking)", "pmid"=>"21850252", "scopus"=>"2-s2.0-79961164799"}, "id"=>"e4723c9c-45ca-3a9e-9d0b-2a889b1dc99b", "abstract"=>"African horse sickness (AHS) is an equine viral disease that is spread by Culicoides spp. Since the closely related disease bluetongue established itself in The Netherlands in 2006, AHS is considered a potential threat for the Dutch horse population. A vector-host model that incorporates the current knowledge of the infection biology is used to explore the effect of different parameters on whether and how the disease will spread, and to assess the effect of control measures. The time of introduction is an important determinant whether and how the disease will spread, depending on temperature and vector season. Given an introduction in the most favourable and constant circumstances, our results identify the vector-to-host ratio as the most important factor, because of its high variability over the country. Furthermore, a higher temperature accelerates the epidemic, while a higher horse density increases the extent of the epidemic. Due to the short infectious period in horses, the obvious clinical signs and the presence of non-susceptible hosts, AHS is expected to invade and spread less easily than bluetongue. Moreover, detection is presumed to be earlier, which allows control measures to be targeted towards elimination of infection sources. We argue that recommended control measures are euthanasia of infected horses with severe clinical signs and vector control in infected herds, protecting horses from midge bites in neighbouring herds, and (prioritized) vaccination of herds farther away, provided that transport regulations are strictly applied. The largest lack of knowledge is the competence and host preference of the different Culicoides species present in temperate regions.", "link"=>"http://www.mendeley.com/research/transmission-control-african-horse-sickness-netherlands-model-analysis-5", "reader_count"=>28, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>6, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>2, "Student > Master"=>6, "Other"=>3, "Student > Bachelor"=>2, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>6, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>2, "Student > Master"=>6, "Other"=>3, "Student > Bachelor"=>2, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Environmental Science"=>2, "Mathematics"=>1, "Agricultural and Biological Sciences"=>18, "Medicine and Dentistry"=>1, "Arts and Humanities"=>1, "Veterinary Science and Veterinary Medicine"=>3, "Social Sciences"=>1, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>18}, "Mathematics"=>{"Mathematics"=>1}, "Environmental Science"=>{"Environmental Science"=>2}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>3}}, "reader_count_by_country"=>{"United Kingdom"=>2, "Spain"=>1}, "group_count"=>2}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/377777"], "description"=>"<div><p>African horse sickness (AHS) is an equine viral disease that is spread by <em>Culicoides</em> spp. Since the closely related disease bluetongue established itself in The Netherlands in 2006, AHS is considered a potential threat for the Dutch horse population. A vector-host model that incorporates the current knowledge of the infection biology is used to explore the effect of different parameters on whether and how the disease will spread, and to assess the effect of control measures. The time of introduction is an important determinant whether and how the disease will spread, depending on temperature and vector season. Given an introduction in the most favourable and constant circumstances, our results identify the vector-to-host ratio as the most important factor, because of its high variability over the country. Furthermore, a higher temperature accelerates the epidemic, while a higher horse density increases the extent of the epidemic. Due to the short infectious period in horses, the obvious clinical signs and the presence of non-susceptible hosts, AHS is expected to invade and spread less easily than bluetongue. Moreover, detection is presumed to be earlier, which allows control measures to be targeted towards elimination of infection sources. We argue that recommended control measures are euthanasia of infected horses with severe clinical signs and vector control in infected herds, protecting horses from midge bites in neighbouring herds, and (prioritized) vaccination of herds farther away, provided that transport regulations are strictly applied. The largest lack of knowledge is the competence and host preference of the different <em>Culicoides</em> species present in temperate regions.</p> </div>", "links"=>[], "tags"=>["african", "sickness"], "article_id"=>134651, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Transmission_and_Control_of_African_Horse_Sickness_in_The_Netherlands_A_Model_Analysis/134651", "title"=>"Transmission and Control of African Horse Sickness in The Netherlands: A Model Analysis", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-08-05 01:17:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/748712"], "description"=>"<p>Animals are either in a susceptible (), latently infected (), infectious () or recovered () state, with subscripts or indicating the vector or host. The stacked squares denote that this compartment is divided into multiple stages. Here is the vector mortality rate, the host mortality due to the disease, the adaptation rate of the vector population, and the transmission probabilities from host to vector and from vector to host, and the total host and vector population size, and the rate of becoming infectious for hosts and vectors, and and the leaving rate from the first and second infectious host classes.</p>", "links"=>[], "tags"=>["vector-host"], "article_id"=>419095, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_representation_of_the_vector_host_model_/419095", "title"=>"Schematic representation of the vector-host model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-08-05 02:31:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/748809"], "description"=>"<p>(a) the number of hosts (total ), (b) the number of vectors (total ), (c) the exponential function (dashed line) fitted to the number of infectious hosts and (d) the number of successful transmissions to other herds as a function of the time since introduction.</p>", "links"=>[], "tags"=>["behaviour", "default", "parameter"], "article_id"=>419184, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dynamic_behaviour_using_default_parameter_values_/419184", "title"=>"Dynamic behaviour using default parameter values.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-08-05 02:33:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/748972"], "description"=>"<p>Effects of all input parameters (: latent period of hosts (days), : infectious period of recovering host (days), : host mortality, : temperature (C), : transmission probability from host to vector, : transmission probability from vector to host, : vector-to-host ratio, : herd size, : herd-to-herd distance, : vector diffusion coefficient) on all model outcomes (: epidemic fraction, : reproduction number, : exponential growth rate, : time of first successful transmission to other herds, : total number of successful transmissions to other herds). Dots indicate the average epidemic fraction (first row) or the median values of the continuous model outcomes (other rows), with the running average (solid line) and the 25%–75% interval for the continuous model outcomes (shaded area).</p>", "links"=>[], "tags"=>["public health and epidemiology", "Computational biology"], "article_id"=>419353, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_of_uncertainty_and_sensitivity_analysis_/419353", "title"=>"Results of uncertainty and sensitivity analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-08-05 02:35:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/749045"], "description"=>"<p>The bars show the fraction of introductions that lead to an epidemic (left axis) and the shaded area denotes the median and 25%–75% interval of the reproduction number at the time of introduction (right axis).</p>", "links"=>[], "tags"=>["public health and epidemiology", "Computational biology"], "article_id"=>419424, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_the_time_of_introduction_on_the_epidemic_/419424", "title"=>"Effect of the time of introduction on the epidemic.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-08-05 02:37:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/749136"], "description"=>"<p>Box and whisker plots of Kendall rank correlation coefficient (KRCC) between ten input parameters and (a) the reproductive number , (b) the exponential growth rate , (c) the time of successful transmission to other herds and (d) the number of successful transmissions to other herds. The input parameters are the latent period of hosts , the infectious period of (recovering) hosts , the host mortality , the temperature , the transmission probability from host to vector , the transmission probability from vector to host , the vector to host ratio , the herd size , the herd-to-herd distance and the vector diffusion coefficient . Boxes enclose the lower quartile, median and upper quartile, the whiskers indicate 1.5 times the interquartile range and crosses indicate outlying values. Mean coefficients that do not significantly differ from zero (p-value) are shown in gray.</p>", "links"=>[], "tags"=>["coefficients"], "article_id"=>419511, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Kendall_rank_correlation_coefficients_of_uncertainty_and_sensitivity_analysis_/419511", "title"=>"Kendall rank correlation coefficients of uncertainty and sensitivity analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-08-05 02:38:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/749260"], "description"=>"<p>Effect of reduction of controlled parameters (: infectious period of recovering host (days), : biting rate vectors, : life span vectors, : transmission probability from host to vector, : transmission probability from vector to host) on all model outcomes (: epidemic fraction, : reproduction number, : exponential growth rate, : time of first successful transmission to other herds, : total number of successful transmissions to other herds). The controlled parameters are reduced with a factor between 0 (no effect) and 1 (full effect). Dots indicate the average epidemic fraction (first row) or the median values of the continuous model outcomes (other rows), with the running average (solid line) and the 25%–75% interval for the continuous model outcomes (shaded area).</p>", "links"=>[], "tags"=>["public health and epidemiology", "Computational biology"], "article_id"=>419643, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_of_control_analysis_/419643", "title"=>"Results of control analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-08-05 02:40:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/749349"], "description"=>"<p>Box and whisker plots of Kendall rank correlation coefficient (KRCC) between the reduction of five controlled parameters and (a) the reproductive number , (b) the exponential growth rate , (c) the time of successful transmission to other herds and (d) the number of successful transmissions to other herds. The controlled parameters are the infectious period of (recovering) hosts , the biting rate of vectors, the life span of vectors, the transmission probability from host to vector and the transmission probability from vector to host . Boxes enclose the lower quartile, median and upper quartile, the whiskers indicate 1.5 times the interquartile range and crosses indicate outlying values. Mean coefficients that do not significantly differ from zero (p-value) are shown in gray.</p>", "links"=>[], "tags"=>["coefficients"], "article_id"=>419732, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Kendall_rank_correlation_coefficients_of_control_analysis_/419732", "title"=>"Kendall rank correlation coefficients of control analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-08-05 02:42:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/749461"], "description"=>"<p>Ten key parameters are varied in the uncertainty and sensitivity analysis, according to their distribution functions.</p>*<p>Five parameters are varied in the control analysis, their reduction ranging from 0 (no effect) to 1 (full effect).</p>a<p>The length of the average infectious periods of dying and recovering hosts have a fixed ratio: .</p>", "links"=>[], "tags"=>["ahs", "default"], "article_id"=>419840, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Parameters_used_in_the_AHS_transmission_model_and_their_default_values_/419840", "title"=>"Parameters used in the AHS transmission model and their default values.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-08-05 02:44:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/749483"], "description"=>"<p>Results of the reduced logistic regression model on absence and presence of epidemics, with SE the standard error.</p>a<p>residual deviance on 9992 degrees of freedom.</p>", "links"=>[], "tags"=>["reduced", "logistic", "regression"], "article_id"=>419862, "categories"=>["Biological Sciences", "Biotechnology"], "users"=>["Jantien A. Backer", "Gonnie Nodelijk"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0023066.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_of_the_reduced_logistic_regression_model_on_absence_and_presence_of_epidemics_/419862", "title"=>"Results of the reduced logistic regression model on absence and presence of epidemics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-08-05 02:44:22"}

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Relative Metric

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