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العنوان
Different Statistical Applications in the Epidemiological.
المؤلف
.Mohammed,Dina Nasser Abdallah
هيئة الاعداد
باحث / دينا ناصر عبدالله محمد
مشرف / خيري محمد البيومي
مشرف / حمود صلاح الطرباني
مناقش / صلاح مهدي محمد
مناقش / ايمان السيد العربي
الموضوع
Epidemiological.
تاريخ النشر
2021.
عدد الصفحات
132 p. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
البيطري
تاريخ الإجازة
1/1/2021
مكان الإجازة
جامعة الزقازيق - كلية الطب البيطرى - تنمية الثروة الحيوانية
الفهرس
Only 14 pages are availabe for public view

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Abstract

The current study depended on two ep idemiological datasets:
A. The first LSD dataset was obtained from a cross-sectional
serop revalence study carried out during the p eriod from March 2018 to
November 2018. A total number of 665 animals (599 cattle and 66 buffa lo )
of different ages with a history of vaccination of a majority of animals
(n=651) by the sheep p ox vaccine from different five localities (El-kh a n k a,
Benha, Qalyub, El-Kanater El-Khayria, and Qaha) in El-Qalyubia
governorate were examined to study the serop revalence of LSD in El-
Qalyubia governorate and to ass ess some risk factors (animal sp ecies,
animal age, immune status, seasonality, temperature-humidity index (THI),
and locality) associated with LSD infection in cattle and buffalo. In this
regard three different statistical models were ap plied to this data:
1. Chi-square test for indep endence: was ap p lied to assess if or not
there was an association between each of the animal p rofile variables
(animal sp ecies, age, immune status, seasonality, THI, and locality) and t h e
p revalence of LSD. The results of that univariate analysis demonstrated that
animal sp ecies, age, and locality were p otential risk factors significantly
associated with LSD infection.
✓ In conclusion:
❖ Although the Chi-square test of indep endence is a tr a d itio nal o ld
model used for assessment of the disease’s associated ris k fa ct o rs
dep ending only on the differences between the o b s er v ed a n d t h e
exp ected frequencies with no resp ect to the data distribution, it
gives reasonable results with a large size dataset.