Epidemiológiai és ökológiai mutatók statisztikai és valószínűségelméleti modellezése, térbeli szerkezetének vizsgálata

Abstract

Prevalence of a disease or a risk factor plays a central role in epidemiology. Perfect diagnosis of a disease is frequently not possible; diagnoses may end up with false positive or false negative results. In this study my first goal is to construct a new confidence interval for true prevalence taking into account that sensitivity and specificity of the diagnostic test have been estimated from outcomes of previous trials. My second theme involves application of exact statistical methods for estimating true prevalence based on data of the national BHV-1 eradication program in Hungary, supposing known sensitivity and specificity.