Three-Level Mixed-Effects Logistic Regression Analysis Reveals Complex Epidemiology of Swine Rotaviruses in Diagnostic Samples from North America.
نویسندگان
چکیده
Rotaviruses (RV) are important causes of diarrhea in animals, especially in domestic animals. Of the 9 RV species, rotavirus A, B, and C (RVA, RVB, and RVC, respectively) had been established as important causes of diarrhea in pigs. The Minnesota Veterinary Diagnostic Laboratory receives swine stool samples from North America to determine the etiologic agents of disease. Between November 2009 and October 2011, 7,508 samples from pigs with diarrhea were submitted to determine if enteric pathogens, including RV, were present in the samples. All samples were tested for RVA, RVB, and RVC by real time RT-PCR. The majority of the samples (82%) were positive for RVA, RVB, and/or RVC. To better understand the risk factors associated with RV infections in swine diagnostic samples, three-level mixed-effects logistic regression models (3L-MLMs) were used to estimate associations among RV species, age, and geographical variability within the major swine production regions in North America. The conditional odds ratios (cORs) for RVA and RVB detection were lower for 1-3 day old pigs when compared to any other age group. However, the cOR of RVC detection in 1-3 day old pigs was significantly higher (p < 0.001) than pigs in the 4-20 days old and >55 day old age groups. Furthermore, pigs in the 21-55 day old age group had statistically higher cORs of RV co-detection compared to 1-3 day old pigs (p < 0.001). The 3L-MLMs indicated that RV status was more similar within states than among states or within each region. Our results indicated that 3L-MLMs are a powerful and adaptable tool to handle and analyze large-hierarchical datasets. In addition, our results indicated that, overall, swine RV epidemiology is complex, and RV species are associated with different age groups and vary by regions in North America.
منابع مشابه
A Logistic Regression Analysis: Agro-Technical Factors Impressible from Fish Farming in Rice Fields, North of Iran
This study was carried out to identify Technical-Agronomic Factors Impressible from Fish Farming in Rice Fields. This investigation carried out by descriptive survey during July-August 2009. Studied cities including Talesh, Rezvanshahr and Masal set in Tavalesh region near to Caspian Sea, North of Iran. The questionnaire validity and reliability were determined to enhance the dependability of t...
متن کاملRotaviral Diarrhea in Pigs
Group A rotaviruses were first detected in pigs suffering from diarrhea in 1975. It is generally accepted that multiple rotavirus strains are present in most if not all conventional swine herds. Rotavirus infections are very prevalent and are commonly associated with diarrhea in suckling and weaned pigs. Early studies also demonstrated that porcine rotaviruses are physically and serologically s...
متن کاملDetermination of electrophoretype of rotaviruses causative agents of diarrhea in children under two years oid referred to Tehran and Zahedan hospitals
rotavirus infections are one of the etiological agents of infantile and children,s gastroenteritis.in this study 450 fecal samples from children under 2 years old from cities of Tehran nad Zahedan were collected.of these specimens.73 samples which were cosidered as moderately positive(++) by ELISA were selected.SDS-PAGE analysis showed fifty six different rotavirus electrophoretypes from which ...
متن کاملImpact of Season, Demographic and Environmental Factors on Salmonella Occurrence in Raccoons (Procyon lotor) from Swine Farms and Conservation Areas in Southern Ontario
Salmonella has been detected in the feces of many wildlife species, including raccoons (Procyon lotor), but little is known about the epidemiology of Salmonella in wildlife living in different habitat types. Our objective was to investigate demographic, temporal, and climatic factors associated with the carriage of Salmonella in raccoons and their environment on swine farms and conservation are...
متن کاملComparison of logistic regression and neural network models in predicting the outcome of biopsy in breast cancer from MRI findings
Background: We designed an algorithmic model based on the logistic regression analysis and a non-algorithmic model based on the Artificial Neural Network (ANN). Materials and methods: The ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patients' records. Each patient’s record consisted of 6 subjec...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- PloS one
دوره 11 5 شماره
صفحات -
تاریخ انتشار 2016