This article was downloaded by: [Gazi University] On: 01 May 2015, At: 08:08 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
New Zealand Veterinary Journal Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tnzv20
Prevalence of endemic enteropathogens of calves in New Zealand dairy farms a
b
a
c
J Al Mawly , A Grinberg , D Prattley , J Moffat & N French
a
a
mEpiLab, Infectious Disease Research Centre, Massey University, Private Bag 11222, Palmerston North, New Zealand b
Infectious Diseases Group, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Private Bag 11222, Palmerston North, New Zealand c
MSD Animal Health, 33 Whakatiki St., Upper Hutt, New Zealand Accepted author version posted online: 19 Sep 2014.Published online: 17 Mar 2015.
Click for updates To cite this article: J Al Mawly, A Grinberg, D Prattley, J Moffat & N French (2015) Prevalence of endemic enteropathogens of calves in New Zealand dairy farms, New Zealand Veterinary Journal, 63:3, 147-152, DOI: 10.1080/00480169.2014.966168 To link to this article: http://dx.doi.org/10.1080/00480169.2014.966168
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
New Zealand Veterinary Journal 63(3), 147–152, 2015
147
Scientific Article
Prevalence of endemic enteropathogens of calves in New Zealand dairy farms
Downloaded by [Gazi University] at 08:08 01 May 2015
J Al Mawly*, A Grinberg†§, D Prattley*, J Moffat‡ and N French*
Abstract
Introduction
AIM: To conduct a country-wide prevalence study of bovine group A rotavirus, coronavirus, Cryptosporidium parvum, Salmonella spp. and enterotoxigenic K99+ Escherichia coli (K99) in calves on New Zealand dairy farms.
Good calf-rearing practice forms an integral part of dairy farming due to the continuous demand for replacement animals for the milking herd. Neonatal calf diarrhoea, defined as diarrhoea occurring during the first month of life, is arguably the most common disease of newborn calves worldwide. The condition has a negative impact on animal welfare and remains the main cause of mortality in many cattle-rearing countries (Virtala et al. 1996; Svensson et al. 2003; Lorenz et al. 2011). The economic impact of neonatal calf diarrhoea is due to the mortality and poor growth of the calves and the costs associated with its diagnosis, treatment and control.
METHODS: Faecal samples (n=1,283) were collected during the 2011 calving season from calves that were 1–5 and 9–21 days-old on 97 dairy farms, and were analysed for the presence of bovine group A rotavirus, coronavirus, Cryptosporidium and Salmonella spp., and K99. Farm-level prevalences were calculated and relationships between demographic variables and the presence of enteropathogens were examined using logistic regression models. RESULTS: Of the 97 farms, 93 (96%) had at least one sample infected with enteropathogens. The standardised farm prevalences of bovine group A rotavirus, bovine coronavirus and C. parvum were 46, 14 and 18%, respectively, in calves that were 1–5 days-old, and 57, 31 and 52%, respectively, in calves that were 9–21 days-old. The farm-level prevalence of K99 was 11% in calves that were 1–5 days-old. Salmonella spp. were found in three and four samples, from calves that were 1–5 and 9–21 days-old, respectively. No associations between explanatory variables and the presence of the enteropathogens were identified at the farm level. At the calf level, the odds of C. parvum shedding and of co-infection with any combination of pathogens were greater in calves that were 9–21 than 1–5 days-old. CONCLUSIONS AND CLINICAL RELEVANCE: This study provides epidemiological estimates of the prevalence of calves’ enteropathogens in New Zealand, which could be used for infection risk assessment or estimation of the environmental loads of pathogens shed in cattle faeces. KEY WORDS: Calf diarrhoea, Cryptosporidium, Salmonella, rotavirus, coronavirus, K99, prevalence
* mEpiLab, Infectious Disease Research Centre, Massey University, Private Bag 11222, Palmerston North, New Zealand † Infectious Diseases Group, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Private Bag 11222, Palmerston North, New Zealand ‡ MSD Animal Health, 33 Whakatiki St., Upper Hutt, New Zealand § Author for correspondence. Email: [email protected] http://dx.doi.org/10.1080/00480169.2014.966168 © 2015 New Zealand Veterinary Association
Bovine group A rotavirus and bovine coronavirus, enterotoxigenic K99+ Escherichia coli (K99) strains, the protozoan Cryptosporidium parvum and Salmonella enterica subspecies enterica serovars are commonly reported endemic infectious agents of neonatal calf diarrhoea in most cattle rearing countries (Wray et al. 1987; Bartels et al. 2010; Izzo et al. 2011). These pathogens can be found in mono- and co-infections in both diarrhoeic and non-diarrhoeic calves, and the severity of the diarrhoea is widely assumed to depend on the type of interaction between the pathogens, environmental, and host-associated factors (Bartels et al. 2010). The pathogens induce similar clinical signs, and the aetiological diagnosis can usually only be achieved by the identification of the agents in faeces (Millemann 2009). Assessment of the prevalence of infectious agents of neonatal calf diarrhoea in New Zealand is necessary for understanding the aetiology of this disease and optimising the use of vaccines, passive immunoprophylatics and chemotherapeutics. Moreover, Salmonella spp. and C. parvum have zoonotic potential, and assessment of these organisms’ prevalence is important also from a public health perspective. New Zealand is a major dairy producer, but available data on the national prevalence of enteropathogens of calves are scant and, with the exception of small-scale studies (Grinberg et al. 2005), most published studies analysed samples submitted to diagnostic laboratories (Schroeder et al. 1983; Howe et al. 2008). Extrapolating prevalence data from one country to another is problematic, due to the different environments and farming systems. In particular, most New Zealand farms manage short and concentrated winter-spring calving seasons, usually between July and October. This might influence the distribution of the agents compared to countries
K99
K99+ Escherichia coli
148
New Zealand Veterinary Journal, 2015
in which high numbers of susceptible calves are present yearround and the pathogens can build up in the farm environment. Therefore, the aim of this study was to assess the prevalence of bovine group A rotavirus, bovine coronavirus, C. parvum, Salmonella spp. and K99 in the dairy calf population.
Materials and methods
Downloaded by [Gazi University] at 08:08 01 May 2015
Selection of farms and calves
This study used faecal samples collected from newborn calves on 97 dairy farms. Sample collection was performed during the second half of the 2011 calving season in order to allow for the build-up of the pathogens on farms during the first half. The target population was the population of calves on farms milking more than 150 cows. This minimum farm size was targeted to allow the sampling of multiple calves of suitable age on each farm, to enhance aggregate testing performance at the farm level. The sampling frame was represented by all the farms milking more than 150 cows registered in the 2010 version of a commercial database (Sanson and Pearson 1997), which included data on approximately 12,000 farms. There were approximately 10,600 farms milking more than 150 cows in the database, corresponding to 90% of the dairy farms registered in the country (Anonymous 2011). Five regions of the North Island (Waikato, Wellington, Northland, Taranaki and Manawatu-Wanganui) and two of the South Island (Canterbury and Southland), collectively including approximately 9,100 farms (Anonymous 2011), were selected for sampling (Figure 1). A sample size of 120 farms was determined based on the maximum number that could be reached during the limited period of time available. Assuming a perfect aggregate farm-level testing regime (determined by testing multiple calves) and a true farm prevalence of 40% for C. parvum (Grinberg et al. 2005), a sample of 120 from a population of 12,000 provided 95% confidence that the estimated farm-level prevalence would
Al Mawly et al.
be between ∼37% and 43% (EpiTools epidemiological calculators; Sergeant 2014). No prevalence data were found in the literature for the other analysed agents. Initially, all the eligible farms in the database were plotted on a political map, and 240 farms were selected from the seven regions using random numbers. The proportion of sampled farms from each region was determined according to their relative contribution to the total number of eligible farms. Farmers were sequentially contacted by phone, and the first 50% from each region giving their consent were requested to allow the sampling of calves that were 1–5 days-old and 9–21 days-old. The first age group was mainly targeted to assess the prevalence of K99, which is seldom pathogenic in older calves (Sherwood et al. 1983; Foster and Smith 2009). Faecal samples from these calves were also tested for bovine group A rotavirus, bovine coronavirus, Salmonella and Cryptosporidium spp. The second group was targeted as these calves were predicted to be at the peak of shedding of Cryptosporidium spp. and bovine group A rotavirus. The samples collected from these calves were tested for bovine group A rotavirus, bovine coronavirus, Cryptosporidium and Salmonella spp. but not for K99. Considering a hypothetical calving season of 60 days as well as natural mortality and the culling of bobby calves (unwanted calves 150 cows reported for that region in the database, divided by the sum of farms milking >150 cows in all the seven regions. The 95% CI for the standardised prevalences was calculated using the gamma distribution. These calculations were performed using R v2.5.0 (R Development Core Team, R Foundation for Statistical Computing, Vienna, Austria). Statistical analysis
The relationships between the presence/absence of each enteropathogen and demographic variables were assessed at farm and calf levels using multivariable logistic regression analysis, using R version 2.5.0 (R Development Core Team, R foundation for
149
Statistical Computing, Vienna, Austria). The binary variable presence/absence of an agent was used as the outcome in univariate analyses performed at the farm- and calf levels. Additional models used the binary outcome presence/absence of any coinfection with two or more agents. A farm was considered positive for an agent if there was at least one positive sample. Explanatory variables for the farm-level analysis were herd size (151–450, 451– 650 or >650 cows), location (South or North Island), breed of calf (Friesian, Jersey or other); all fixed effects. The calf-level analysis included the explanatory variables of sex, age group (1–5 or 9–21 days-old), breed and location; all fixed effects categorised as above, and the farm identifier as a random effect. The outcome of C. parvum presence/absence was determined by the result of the PCR-sequencing. Accordingly, all immunofluorescence-positive calves on the farms where C. parvum was identified by PCRsequencing were coded as C. parvum-present. If a different Cryptosporidium species was identified, all the calves were coded C. parvum-absent. Calves on farms for which the species could not be defined were eliminated from the analyses. Any difference between proportions of interest was assessed using two-tailed Fisher’s exact tests.
Results Description of calves
Due to field constraints, 97/120 farms (80.8% of target) were sampled between 11 August and 07 October 2011. A total of 1,283 calves were sampled, including 429 calves that were 1–5 days-old, 797 that were 9–21 days-old and 57 (4.4%) with no age record. There were 262/429 (61.1%) and 693/797 (86.9%) female calves aged 1–5 days-old and 9–21 days-old, respectively. Of the 1,226 calves, 643 (52.4%) were recorded as Friesian, 172 (14.0%) as Jersey, and 411 (33.5%) as other breeds (375 FriesianJersey, 23 Hereford and 13 Ayrshire). Farm-level prevalence of enteropathogens
Of the 97 farms, 93 (96%) had samples infected with one or more than one enteropathogen. Bovine group A rotavirus was identified on approximately 70% of farms, and bovine coronavirus and C. parvum on half the farms. K99 was found on 11 farms and Salmonella spp. on four farms (Table 1). There were co-infections with two or more agents on 65/97 (67%) farms. The commonest co-infections were bovine group A rotavirus and Cryptosporidium spp., and bovine group A rotavirus and coronavirus. Cryptosporidium spp. oocysts were identified by immunofluorescence on 63/97 (65%) farms. PCR-sequencing successfully identified to species level oocysts from 84 faecal samples, from 55 farms. Sequences matching C. parvum were identified in 77/84 (92%) of the samples from 49/55 (89%) farms, and matching C. bovis in 7/84 (8.%) samples from 6/55 (11%) farms. Only one species was identified in multiple samples from each PCR-positive farm. DNA from 16 samples from eight farms did not amplify at any locus. Standardised farm-level prevalences of the enteropathogens are presented in Table 2. Prevalence of enteropathogens among 1–5 days-old calves
In this age group, 133/429 (31.0%) samples were positive for at least one enteropathogen (Table 1). Bovine group A rotavirus was the most common pathogen, found in 86/429 (20.0%) samples on 48/97 (49%) farms. Cryptosporidium spp. oocysts were seen by immunofluorescence in 25/429 (6%) samples. C. parvum was identified in 14/16 (88%) genotyped samples, and C. bovis
150
New Zealand Veterinary Journal, 2015
Al Mawly et al.
Table 1. Prevalence of bovine group A rotavirus, bovine coronavirus, Cryptosporidium parvum, Salmonella spp. and K99+ Escherichia coli (K99) on 97 dairy farms in New Zealand, and in faecal samples from calves on those farms aged 1–5 (n=429) or 9–21 (n=797) days-old. Number of calves positive (%) Enteropathogen
Number of farms positive (%)
1–5 days-old
Rotavirus (all positive)
68 (70)
86 (20.0)
158 (19.8)
Coronavirus (all positive)
46 (47)
23 (5.4)
49 (6.1)
C. parvum (all positive)a
49 (51)
25 (5.8)x
126 (16.0)y
Salmonella spp. (all positive)
9–21 days-old
4 (4)
3 (0.7)
K99 (all positive)
11 (11)
14 (3.3)
4 (0.5) Not applicable
Rotavirus + coronavirus
23 (24)
10 (2.3)
18 (2.3)
Rotavirus + C. parvum
22 (23)
9 (2.1)
33 (4.1)
C. parvum + coronavirus
6 (6)
2 (0.5)
4 (0.5)
K99 + rotavirus
8 (8)
9 (2.1)
Not applicable
Rotavirus + coronavirus + C. parvum
1 (1)
1 (0.2)
2 (0.3)
K99 + C. parvum
1 (1)
1 (0.2)
Not applicable
K99 + Coronavirus
2 (2)
2 (0.5)
Not applicable
K99 + C. parvum + rotavirus
1 (1)
1 (0.2)
Not applicable
1(1)
1 (0.2)
1 (0.1)
Rotavirus + C. parvum + Salmonella spp.
Downloaded by [Gazi University] at 08:08 01 May 2015
a
All unidentified Cryptosporidium spp. oocysts were considered C. parvum-negative and all the immunofluorescence-positive samples from C. parvum-positive farms were considered infected with C. parvum. xy Significant difference (p0.05). At the calf level, the odds of C. parvum presence were greater in 9–21 than 1–5 days-old calves (OR=2.9; 95% CI=1.8–4.6; p
New Zealand Veterinary Journal Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tnzv20
Prevalence of endemic enteropathogens of calves in New Zealand dairy farms a
b
a
c
J Al Mawly , A Grinberg , D Prattley , J Moffat & N French
a
a
mEpiLab, Infectious Disease Research Centre, Massey University, Private Bag 11222, Palmerston North, New Zealand b
Infectious Diseases Group, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Private Bag 11222, Palmerston North, New Zealand c
MSD Animal Health, 33 Whakatiki St., Upper Hutt, New Zealand Accepted author version posted online: 19 Sep 2014.Published online: 17 Mar 2015.
Click for updates To cite this article: J Al Mawly, A Grinberg, D Prattley, J Moffat & N French (2015) Prevalence of endemic enteropathogens of calves in New Zealand dairy farms, New Zealand Veterinary Journal, 63:3, 147-152, DOI: 10.1080/00480169.2014.966168 To link to this article: http://dx.doi.org/10.1080/00480169.2014.966168
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
New Zealand Veterinary Journal 63(3), 147–152, 2015
147
Scientific Article
Prevalence of endemic enteropathogens of calves in New Zealand dairy farms
Downloaded by [Gazi University] at 08:08 01 May 2015
J Al Mawly*, A Grinberg†§, D Prattley*, J Moffat‡ and N French*
Abstract
Introduction
AIM: To conduct a country-wide prevalence study of bovine group A rotavirus, coronavirus, Cryptosporidium parvum, Salmonella spp. and enterotoxigenic K99+ Escherichia coli (K99) in calves on New Zealand dairy farms.
Good calf-rearing practice forms an integral part of dairy farming due to the continuous demand for replacement animals for the milking herd. Neonatal calf diarrhoea, defined as diarrhoea occurring during the first month of life, is arguably the most common disease of newborn calves worldwide. The condition has a negative impact on animal welfare and remains the main cause of mortality in many cattle-rearing countries (Virtala et al. 1996; Svensson et al. 2003; Lorenz et al. 2011). The economic impact of neonatal calf diarrhoea is due to the mortality and poor growth of the calves and the costs associated with its diagnosis, treatment and control.
METHODS: Faecal samples (n=1,283) were collected during the 2011 calving season from calves that were 1–5 and 9–21 days-old on 97 dairy farms, and were analysed for the presence of bovine group A rotavirus, coronavirus, Cryptosporidium and Salmonella spp., and K99. Farm-level prevalences were calculated and relationships between demographic variables and the presence of enteropathogens were examined using logistic regression models. RESULTS: Of the 97 farms, 93 (96%) had at least one sample infected with enteropathogens. The standardised farm prevalences of bovine group A rotavirus, bovine coronavirus and C. parvum were 46, 14 and 18%, respectively, in calves that were 1–5 days-old, and 57, 31 and 52%, respectively, in calves that were 9–21 days-old. The farm-level prevalence of K99 was 11% in calves that were 1–5 days-old. Salmonella spp. were found in three and four samples, from calves that were 1–5 and 9–21 days-old, respectively. No associations between explanatory variables and the presence of the enteropathogens were identified at the farm level. At the calf level, the odds of C. parvum shedding and of co-infection with any combination of pathogens were greater in calves that were 9–21 than 1–5 days-old. CONCLUSIONS AND CLINICAL RELEVANCE: This study provides epidemiological estimates of the prevalence of calves’ enteropathogens in New Zealand, which could be used for infection risk assessment or estimation of the environmental loads of pathogens shed in cattle faeces. KEY WORDS: Calf diarrhoea, Cryptosporidium, Salmonella, rotavirus, coronavirus, K99, prevalence
* mEpiLab, Infectious Disease Research Centre, Massey University, Private Bag 11222, Palmerston North, New Zealand † Infectious Diseases Group, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Private Bag 11222, Palmerston North, New Zealand ‡ MSD Animal Health, 33 Whakatiki St., Upper Hutt, New Zealand § Author for correspondence. Email: [email protected] http://dx.doi.org/10.1080/00480169.2014.966168 © 2015 New Zealand Veterinary Association
Bovine group A rotavirus and bovine coronavirus, enterotoxigenic K99+ Escherichia coli (K99) strains, the protozoan Cryptosporidium parvum and Salmonella enterica subspecies enterica serovars are commonly reported endemic infectious agents of neonatal calf diarrhoea in most cattle rearing countries (Wray et al. 1987; Bartels et al. 2010; Izzo et al. 2011). These pathogens can be found in mono- and co-infections in both diarrhoeic and non-diarrhoeic calves, and the severity of the diarrhoea is widely assumed to depend on the type of interaction between the pathogens, environmental, and host-associated factors (Bartels et al. 2010). The pathogens induce similar clinical signs, and the aetiological diagnosis can usually only be achieved by the identification of the agents in faeces (Millemann 2009). Assessment of the prevalence of infectious agents of neonatal calf diarrhoea in New Zealand is necessary for understanding the aetiology of this disease and optimising the use of vaccines, passive immunoprophylatics and chemotherapeutics. Moreover, Salmonella spp. and C. parvum have zoonotic potential, and assessment of these organisms’ prevalence is important also from a public health perspective. New Zealand is a major dairy producer, but available data on the national prevalence of enteropathogens of calves are scant and, with the exception of small-scale studies (Grinberg et al. 2005), most published studies analysed samples submitted to diagnostic laboratories (Schroeder et al. 1983; Howe et al. 2008). Extrapolating prevalence data from one country to another is problematic, due to the different environments and farming systems. In particular, most New Zealand farms manage short and concentrated winter-spring calving seasons, usually between July and October. This might influence the distribution of the agents compared to countries
K99
K99+ Escherichia coli
148
New Zealand Veterinary Journal, 2015
in which high numbers of susceptible calves are present yearround and the pathogens can build up in the farm environment. Therefore, the aim of this study was to assess the prevalence of bovine group A rotavirus, bovine coronavirus, C. parvum, Salmonella spp. and K99 in the dairy calf population.
Materials and methods
Downloaded by [Gazi University] at 08:08 01 May 2015
Selection of farms and calves
This study used faecal samples collected from newborn calves on 97 dairy farms. Sample collection was performed during the second half of the 2011 calving season in order to allow for the build-up of the pathogens on farms during the first half. The target population was the population of calves on farms milking more than 150 cows. This minimum farm size was targeted to allow the sampling of multiple calves of suitable age on each farm, to enhance aggregate testing performance at the farm level. The sampling frame was represented by all the farms milking more than 150 cows registered in the 2010 version of a commercial database (Sanson and Pearson 1997), which included data on approximately 12,000 farms. There were approximately 10,600 farms milking more than 150 cows in the database, corresponding to 90% of the dairy farms registered in the country (Anonymous 2011). Five regions of the North Island (Waikato, Wellington, Northland, Taranaki and Manawatu-Wanganui) and two of the South Island (Canterbury and Southland), collectively including approximately 9,100 farms (Anonymous 2011), were selected for sampling (Figure 1). A sample size of 120 farms was determined based on the maximum number that could be reached during the limited period of time available. Assuming a perfect aggregate farm-level testing regime (determined by testing multiple calves) and a true farm prevalence of 40% for C. parvum (Grinberg et al. 2005), a sample of 120 from a population of 12,000 provided 95% confidence that the estimated farm-level prevalence would
Al Mawly et al.
be between ∼37% and 43% (EpiTools epidemiological calculators; Sergeant 2014). No prevalence data were found in the literature for the other analysed agents. Initially, all the eligible farms in the database were plotted on a political map, and 240 farms were selected from the seven regions using random numbers. The proportion of sampled farms from each region was determined according to their relative contribution to the total number of eligible farms. Farmers were sequentially contacted by phone, and the first 50% from each region giving their consent were requested to allow the sampling of calves that were 1–5 days-old and 9–21 days-old. The first age group was mainly targeted to assess the prevalence of K99, which is seldom pathogenic in older calves (Sherwood et al. 1983; Foster and Smith 2009). Faecal samples from these calves were also tested for bovine group A rotavirus, bovine coronavirus, Salmonella and Cryptosporidium spp. The second group was targeted as these calves were predicted to be at the peak of shedding of Cryptosporidium spp. and bovine group A rotavirus. The samples collected from these calves were tested for bovine group A rotavirus, bovine coronavirus, Cryptosporidium and Salmonella spp. but not for K99. Considering a hypothetical calving season of 60 days as well as natural mortality and the culling of bobby calves (unwanted calves 150 cows reported for that region in the database, divided by the sum of farms milking >150 cows in all the seven regions. The 95% CI for the standardised prevalences was calculated using the gamma distribution. These calculations were performed using R v2.5.0 (R Development Core Team, R Foundation for Statistical Computing, Vienna, Austria). Statistical analysis
The relationships between the presence/absence of each enteropathogen and demographic variables were assessed at farm and calf levels using multivariable logistic regression analysis, using R version 2.5.0 (R Development Core Team, R foundation for
149
Statistical Computing, Vienna, Austria). The binary variable presence/absence of an agent was used as the outcome in univariate analyses performed at the farm- and calf levels. Additional models used the binary outcome presence/absence of any coinfection with two or more agents. A farm was considered positive for an agent if there was at least one positive sample. Explanatory variables for the farm-level analysis were herd size (151–450, 451– 650 or >650 cows), location (South or North Island), breed of calf (Friesian, Jersey or other); all fixed effects. The calf-level analysis included the explanatory variables of sex, age group (1–5 or 9–21 days-old), breed and location; all fixed effects categorised as above, and the farm identifier as a random effect. The outcome of C. parvum presence/absence was determined by the result of the PCR-sequencing. Accordingly, all immunofluorescence-positive calves on the farms where C. parvum was identified by PCRsequencing were coded as C. parvum-present. If a different Cryptosporidium species was identified, all the calves were coded C. parvum-absent. Calves on farms for which the species could not be defined were eliminated from the analyses. Any difference between proportions of interest was assessed using two-tailed Fisher’s exact tests.
Results Description of calves
Due to field constraints, 97/120 farms (80.8% of target) were sampled between 11 August and 07 October 2011. A total of 1,283 calves were sampled, including 429 calves that were 1–5 days-old, 797 that were 9–21 days-old and 57 (4.4%) with no age record. There were 262/429 (61.1%) and 693/797 (86.9%) female calves aged 1–5 days-old and 9–21 days-old, respectively. Of the 1,226 calves, 643 (52.4%) were recorded as Friesian, 172 (14.0%) as Jersey, and 411 (33.5%) as other breeds (375 FriesianJersey, 23 Hereford and 13 Ayrshire). Farm-level prevalence of enteropathogens
Of the 97 farms, 93 (96%) had samples infected with one or more than one enteropathogen. Bovine group A rotavirus was identified on approximately 70% of farms, and bovine coronavirus and C. parvum on half the farms. K99 was found on 11 farms and Salmonella spp. on four farms (Table 1). There were co-infections with two or more agents on 65/97 (67%) farms. The commonest co-infections were bovine group A rotavirus and Cryptosporidium spp., and bovine group A rotavirus and coronavirus. Cryptosporidium spp. oocysts were identified by immunofluorescence on 63/97 (65%) farms. PCR-sequencing successfully identified to species level oocysts from 84 faecal samples, from 55 farms. Sequences matching C. parvum were identified in 77/84 (92%) of the samples from 49/55 (89%) farms, and matching C. bovis in 7/84 (8.%) samples from 6/55 (11%) farms. Only one species was identified in multiple samples from each PCR-positive farm. DNA from 16 samples from eight farms did not amplify at any locus. Standardised farm-level prevalences of the enteropathogens are presented in Table 2. Prevalence of enteropathogens among 1–5 days-old calves
In this age group, 133/429 (31.0%) samples were positive for at least one enteropathogen (Table 1). Bovine group A rotavirus was the most common pathogen, found in 86/429 (20.0%) samples on 48/97 (49%) farms. Cryptosporidium spp. oocysts were seen by immunofluorescence in 25/429 (6%) samples. C. parvum was identified in 14/16 (88%) genotyped samples, and C. bovis
150
New Zealand Veterinary Journal, 2015
Al Mawly et al.
Table 1. Prevalence of bovine group A rotavirus, bovine coronavirus, Cryptosporidium parvum, Salmonella spp. and K99+ Escherichia coli (K99) on 97 dairy farms in New Zealand, and in faecal samples from calves on those farms aged 1–5 (n=429) or 9–21 (n=797) days-old. Number of calves positive (%) Enteropathogen
Number of farms positive (%)
1–5 days-old
Rotavirus (all positive)
68 (70)
86 (20.0)
158 (19.8)
Coronavirus (all positive)
46 (47)
23 (5.4)
49 (6.1)
C. parvum (all positive)a
49 (51)
25 (5.8)x
126 (16.0)y
Salmonella spp. (all positive)
9–21 days-old
4 (4)
3 (0.7)
K99 (all positive)
11 (11)
14 (3.3)
4 (0.5) Not applicable
Rotavirus + coronavirus
23 (24)
10 (2.3)
18 (2.3)
Rotavirus + C. parvum
22 (23)
9 (2.1)
33 (4.1)
C. parvum + coronavirus
6 (6)
2 (0.5)
4 (0.5)
K99 + rotavirus
8 (8)
9 (2.1)
Not applicable
Rotavirus + coronavirus + C. parvum
1 (1)
1 (0.2)
2 (0.3)
K99 + C. parvum
1 (1)
1 (0.2)
Not applicable
K99 + Coronavirus
2 (2)
2 (0.5)
Not applicable
K99 + C. parvum + rotavirus
1 (1)
1 (0.2)
Not applicable
1(1)
1 (0.2)
1 (0.1)
Rotavirus + C. parvum + Salmonella spp.
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a
All unidentified Cryptosporidium spp. oocysts were considered C. parvum-negative and all the immunofluorescence-positive samples from C. parvum-positive farms were considered infected with C. parvum. xy Significant difference (p0.05). At the calf level, the odds of C. parvum presence were greater in 9–21 than 1–5 days-old calves (OR=2.9; 95% CI=1.8–4.6; p
