【病毒外文文献】2018 Herd level estimation of probability of disease freedom applied on the Norwegian control program for bovine respira

Contents lists available at ScienceDirect Preventive Veterinary Medicine journal homepage Herd level estimation of probability of disease freedom applied on the Norwegian control program for bovine respiratory syncytial virus and bovine coronavirus Ingrid Toftaker a Estelle gren b Maria Stokstad a Ane N dtvedt a Jenny Fr ssling b c a Department of Production Animal Clinical Sciences Norwegian University of Life Sciences P O Box 8146 Dep Oslo Norway b Department of Disease Control and Epidemiology National Veterinary Institute Uppsala Sweden c Department of Animal Environment and Health Swedish University of Agricultural Sciences Skara Sweden ARTICLE INFO Keywords BRSV BCV BCoV Disease control BRD Cattle Bovine respiratory disease Bulk tank milk Animal movements ABSTRACT A national control program against bovine respiratory syncytial virus BRSV and bovine coronavirus BCV was launched in Norway in 2016 A key strategy in the program is to test for presence of antibodies and protect test negative herds from infection Because these viruses are endemic the rate of re introduction can be high and a disease free status will become more uncertain as time from testing elapses The aim of this study was to estimate the probability of freedom PostPFree from BRSV and BCV antibodies over time by use of bulk tank milk BTM antibody testing geographic information and animal movement data and to validate the herd level estimates against subsequent BTM testing BTM samples were collected from 1148 study herds in West Norway in 2013 and 2016 and these were analyzed for BRSV and BCV antibodies PostPFree was calculated for herds that were negative in 2013 2014 and updated periodically with new probabilities every three months Input variables were test sensitivity the probability of introduction through animal purchase and local transmission Probability of introduction through animal purchase was calculated by using real animal movement data and herd prevalence in the region of the source herd The PostPFree from the nal three months in 2015 was compared to BTM test results from March 2016 using a Wilcoxon Rank Sum Test The probability of freedom was generally high for test negative herds immediately after testing re ecting the high sensitivity of the tests It did however decrease with time since testing and was greatly a ected by pur chase of livestock When comparing the median PostPFree for the nal three months to the test results in 2016 it was signi cantly lower p 0 01 for test positive herds Furthermore there was a large di erence in the proportion of test positive herds between the rst and fourth quartile of PostPFree The results show that PostPFree provides a better estimate of herd level BTM status for both BRSV and BCV than what can be achieved by relying solely on the previous test result 1 Introduction Bovine respiratory syncytial virus BRSV and bovine coronavirus BCV are widespread infectious agents present in cattle populations around the world including the Norwegian dairy population Valarcher and Taylor 2007 Gulliksen et al 2009 Boileau and Kapil 2010 BRSV causes respiratory disease mostly in young animals but can af fect cattle of all ages Valarcher and Taylor 2007 Clinical signs vary from none to severe Valarcher and Taylor 2007 BCV is responsible for diarrhea in calves and for respiratory disease and contagious diarrhea in adult cattle winter dysentery Boileau and Kapil 2010 These infections lead to increased use of antibiotics due to common secondary bacterial infections they reduce animal welfare and the as sociated economic losses can be considerable Larsen 2000 Boileau and Kapil 2010 In 2016 a national control program against BRSV and BCV was launched in Norway as the rst country in the world The program is conducted as a joint initiative amongst producer organiza tions and participation is voluntary In early 2016 bulk tank milk BTM was collected from the majority of Norwegian dairy herds and analyzed for BRSV and BCV antibodies In a previous study dairy herds in two counties on the west coast of Norway had also been sampled and tested three years earlier Toftaker et al 2016 https doi org 10 1016 j prevetmed 2018 07 002 Received 20 May 2018 Accepted 3 July 2018 Corresponding author E mail address ingrid toftaker nmbu no I Toftaker Preventive Veterinary Medicine xxx xxxx xxx xxx 0167 5877 2018 Elsevier B V All rights reserved Please cite this article as Toftaker I Preventive Veterinary Medicine 2018 https doi org 10 1016 j prevetmed 2018 07 002 A key strategy of the control program is to protect uninfected herds by imposing restrictions on livestock trade A negative herd status based on BTM lasts for one year after testing regardless of the degree of contact with other herds In a previous Norwegian study it was shown that spread of BRSV between herds was rapid i e the elimination rates and introduction rates were high Klem et al 2013 Transmission dynamics for BCV has not yet been investigated in Norway although one study describes a regional outbreak of winter dysentery Toftaker et al 2017 Studies from Sweden have shown that recent BCV infec tion is common indicating that the infection is easily transmitted Beaudeau et al 2010 Ohlson et al 2013 Due to the constant risk of virus introduction the assumption that a negative status is valid for a long time is questionable Several factors can a ect the risk of change in status Purchase of livestock is a well known route of introduction of infectious agents and herds that frequently purchase animals are likely at a higher risk of seroconversion Elvander 1996 Fr ssling et al 2012 Toftaker et al 2016 In addition to purchase of animals pre vious studies have shown that location and herd size are important risk factors for BRSV and or BCV antibody positivity Ohlson et al 2010b Toftaker et al 2016 Demonstration of freedom from di erent diseases at the national level is important for international trade purposes and the use of sce nario tree models has recently provided a more advanced and exible approach to these calculations Martin et al 2007a More et al 2013 applied this methodology at herd level within the Irish control program for Johne s disease They included information on livestock trade along with test results to calculate probability of freedom from Johne s dis ease in test negative herds In Norway information on location of herds herd size and livestock trade are available from central direc tories It was hypothesized that this information could be used along with test results to provide updated estimates of herd probability of freedom from antibodies re ecting the status more accurately than previous BTM test results alone Estimating a time varying probability of freedom could potentially form a tool for risk assessment in livestock trade or provide the basis for a risk based approach to sampling The aim of this study was to develop a method for a frequently updated estimate of probability of freedom PostPFree from BRSV and BCV antibodies at the herd level based on information from BTM testing geographic location and animal movement data 2 Materials and methods 2 1 Study area and study population The study area was two neighboring counties on the west coast of Norway The southern county Sogn og Fjordane and the northern county M re og Romsdal Herds located in the study region were included if they had either at least one ingoing animal movement or contributed with at least one BTM sample during January 2013 to March 2016 We had no information on herds without movements or BTM samples hence the total cattle population in the study region was not known A owchart was made to describe the di erent subsets of herds used for the di erent analyses Fig 1 2 2 Sampling and analysis of BTM During December 2012 to June 2013 BTM samples were collected from 1347 herds out of 1854 herds delivering milk in 2013 in the study area as part of a cross sectional risk factor study Toftaker et al 2016 For the PostPFree calculations BTM samples collected in De cember 2012 were assigned to the rst time period i e the rst three months of 2013 Some of the test negative herds were resampled the following year n 275 February 2014 August 2014 Finally 1148 herds also had a BTM sample collected in March 2016 as part of the national BRSV BCV control program All BTM samples were collected by the milk truck driver in conjunction with milk collection and cooled at a temperature of 2 4 C until received at the laboratory TINE Mas titis Laboratory Molde Norway where samples were frozen between 18 and 20 C until the time of analysis The 2013 and 2014 samples were analyzed in the Norwegian laboratory whereas the 2016 samples were shipped over night to a laboratory in Ireland Enfer Scienti c Naas Ireland BTM samples collected in 2012 2014 were tested for antibodies against BRSV and BCV using the SVANOVIR BRSV Ab and SVANOVIR BCV Ab respectively Samples were analyzed following the manu facturer s instructions as described by Toftaker et al 2016 A cut o value of 10 percent positivity PP was used for both tests according to the test manual Svanova 2018a b From 2016 all samples were analyzed with the new MVD Enferplex BCV BRSV multiplex hereafter referred to as the multiplex This test detects BRSV and BCV antibodies simultaneously using a panel of two recombinant proteins and two synthetic peptides for BRSV BRSV A D along with one recombinant protein BCV A for BCV as antigens A positive test response results in chemiluminescence captured by an imaging system and measured in relative light units RLU by the Quansys Q view software v 1 5 4 7 Antigens were combined in a parallel reading i e the test was con sidered positive when the RLU value of at least one antigen was above the cut o The applied cut o values for the four di erent BRSV an tigens were 2000 for BRSV A 4000 for BRSV B 7000 for BRSV C and 1700 for BRSV D For BCV A a cut o value of 10 000 was used The sensitivity Se of the multiplex was set to 0 94 for BRSV and 0 995 BCV The Se was set to 0 998 for the SVANOVIR BRSV Ab and 0 999 for SVANOVIR BCV Ab Test parameters at the applied cut o values were based on a diagnostic test evaluation study evaluating the mul tiplex along with the SVANOVIR BRSV Ab and SVANOVIR BCV for BTM Toftaker et al 2018 All the tests detect antibodies not the antigen itself consequently we will in the present study use positive when referring to animals herds or regions as having BRSV and or BCV antibodies Furthermore all input variables in the probability model relates to antibodies hence the calculated probabilities relate to presences of antibodies and not necessarily infection or presence of virus 2 3 Data sources and software The Norwegian food safety authority provided data on cattle movements The Norwegian Livestock registry In the current study animal movements refer to movements where there is a change of Fig 1 Flow chart outlining the study sample and subsets of herds included in di erent calculations in a study estimating the probability of freedom from BRSV and BCV antibodies in dairy herds located in two counties in western Norway during the period January 2013 March 2016 I Toftaker et al Preventive Veterinary Medicine xxx xxxx xxx xxx 2 owner for which reporting is mandatory Information about herd size was retrieved from the Norwegian dairy herd recording system NDHRS which in 2011 included 98 of Norwegian dairy herds Espetvedt et al 2013 BTM test results were provided by the largest producer organisation TINE SA and information on location of herds coordinates EUREF89 WGS 1984 UTM 32 was provided by the Norwegian Agriculture Agency All data management calculations and analyses were performed using Stata Stata SE 14 Stata Corp College Station TX 2 4 Animal movements All recorded animal movements where the destination herd was located in the study area were included Duplicate records i e move ments where animal ID source county destination herd and movement date where identical were reduced to single records n 8237 Records of movements where the same animal was moved back and forth between the same two herds or to two di erent recipient herds on the same day were omitted n 179 Records where the source county or the source herd was missing and could not be retrieved from other variables were also omitted n 56 After editing the dataset included records of 45 208 movements to 1802 destination herds lo cated in the study region 2 5 Probability of freedom PFree was calculated for all herds starting the study period with negative BTM test results in 2013 and if tested in 2014 This was done separately for each virus The probability of freedom was updated periodically according to the chosen time period every three months The framework presented here is based on a combination of con cepts from the following studies a scenario tree modelling of freedom from disease using multiple sources of data presented by Martin et al 2007a 2007b b calculations of probability of disease freedom on herd level in the Irish control program for Johne s disease by More et al 2013 and c a novel method to identify herds with an increased probability of disease due to animal trade developed by Fr ssling et al 2014 The probability of freedom was calculated for each herd using the following Eqs 1 5 First the probability of introducing at least one positive animal PIntroTrade to the destination herd was calculated for each unique combination sd of source herd s and destination herd d for each time period PDPIntroTrade 1 1 a n sd 1 where P D a was the within herd prevalence in the source herd set to 0 5 i e a 50 50 probability of infection freedom for all herds and n was the number of animals purchased from the source herd The total probability of introduction from all animal purchases within each time period t was calculated for each destination herd PIntroTrade P DPIntroTrade 1 1 sd hall 2 where P D h is the probability that the source herd is antibody po sitive at the herd level As an estimate of P D h the herd prevalence in the county of the source herd based on the national BTM screening was used As virus can be introduced not only through purchase of livestock but also by indirect transfer we included a factor for probability of indirect transmission PIntroLocal This factor was estimated using the proportion of herds that were negative at the rst sampling 2013 and positive at the last sampling 2016 in the group that did not purchase animals hereafter designated closed herds This was done separately for the two viruses and for the two counties as we knew that the pre valence and likely the infectious pressure was higher in the northern county Toftaker et al 2016 In addition herd size was taken into account as several studies have found an association between herd size and seropositivity Norstr m et al 2000 Sol s Calder n et al 2007 Ohlson et al 2010b Toftaker et al 2016 In the study by Toftaker et al 2016 conducted in the same region the odds of testing positive increased with 12 across the inter quartile range of herd size The e ect of herd size was the same for both viruses Based on this we divided the study herds into two groups with median herd size as cut point and assigned a value of PIntroLocal 12 higher in the large compared to the small herds In summary this resulted in four cate gories of PIntroLocal for each virus based on herd size below or above median and which county the herd was located in north south The total probability of introduction through animal purchase and by in direct transmission for each time period t was then calculated PIntroTrade PIntroLocalPIntroTotal 1 1 1 tt 3 The prior probability of infection at time t PriorPInf t was estimated as follows f PIntroTotal PostPInf PIntroTotal PostPInfPriorPIn t t t t t1 1 4 For the rst time period the prior probability of infection PriorPInf was set to 0 5 resembling testing a herd with unknown status i e no prior information on herd prevalence in the region available and an equal probability of being positive and negative PriorPInf was then calculated for each time period by taking the posterior probability of infection from the previous time period PostPInf t 1 and adding the probability of introduction during time period t calculated from Eq 3 and adjusting for the possibility that the herd might already have been antibody positive but undetected at the end of the previous time period t 1 After each three month period an updated probability of freedom PostPFree was calculated using Bayes theorem as described by Martin et al 2007b PriorPInf PriorPInf TotalSe PostPFree 1 1 5 The probability of infection PostPInf was the complement to PostPFree The change in PostPFree over time was visualized for two example herds in a line plot 2 6 Sensitivity analysis Due to the uncertainty of the local factor a sensitivity analysis was performed using 50 lower and 50 higher values of PIntroLocal and assessing the e ect on the outcome PostPFree 2 7 Model evaluation To assess the usefulness of the developed method the PostPFree calculations for the nal three month period was compared to the re sults from BTM testing in 2016 using a Wilcoxon Rank Sum Test Bar charts were made showing the proportion of test positive herds in each quartile of PostPFree The accuracy of the PostPInf was explored by treating it as a diagnostic test comparing the PostPInf results to the 2016 BTM test results used as gold standard A smoothed line plot of Se and Sp versus probability cut o of PostPInf was made and the Se and Sp at di erent cut o sofPostPInf were tabulated results not shown 3 Results 3 1 Study population The dataset consisted of 2432 beef and dairy herds located in Sogn og Fjordane and M re og Romsdal counties A BTM result from 2013 was available for 1347 herds of which 275 had a follow up sample in 2014 Of the 1347 herds 676 and 333 did not have antibodies against I Toftaker et al Preventive Veterinary Medicine xxx xxxx xxx xxx 3 BRSV and BCV in 2013 or 2014 respectively and were used for probability of freedom calculations Of the 1347 herds sampled in 2013 1148 also had a BTM sample in 2016 of which 569 and 270 were in itially negative for BRSV and BCV respectively and were used for validation of PostPFree PostPInf For an overview of study sample and subset of herds used in di erent calculations see Fig 1 3 2 BTM results At the rst sampling in 2013 622 out of 1347 sampled herds were BRSV antibody positive and 973 were BCV antibody positive i e a proportion of test positive of 46 2 for BRSV and 72 2 for BCV as previously reported Toftaker et al 2016 The national control pro gram started in March 2016 resulting in BTM samples from 1565 herds in the study area On this nal screening 688 herds 44 0 were an tibody positive for BRSV and 1210 herds 77 3 were antibody posi tive for BCV Of the initially negative herds that were also sampled in 2016 178 29 had changed status for BRSV and 89 29 for BCV An overview of counts and proportions of test outcomes are presented in Table 1 3 3 Local transmission factor 3 3 1 BRSV Of the closed herds n 384 104 herds were initially test negative for BRSV in each county When retested in 2016 21 20 of the in itially negative herds had changed status in the southern county and 36 35 in the northern county 3 3 2 BCV For BCV 60 herds were initially test negative in the northern county and 66 in the southern county in the group that did not pur chase animals When retested in 2016 16 27 and seven 11 herds went from negative to positive in the northern and southern county respectively The resulting local transmission rate PIntroLocal per three month time period for each virus is presented in Table 2 3 4 Probability of freedom PostPFree was high after the initial negative tests for both viruses The median PostPFree in the 12th i e the last time period was 0 62 range 0 0 91 for BRSV and 0 80 range 0 0 95 for BCV The dis tribution of PostPFree in time period twelve is shown by county in Fig