Approach to prediction and receiver operating characteristic analysis of a regression model for assessing the severity of the course Lyme borreliosis in children.

Introduction: Lyme borreliosis (LB) is a multisystemic zoonotic disease transmitted by the bite of infected tick vectors.The aim of the study is to develop a mathematical model for predicting the risk of severity of Lyme disease by the risk factor of the disseminated form of LB in children who have had a tick attack. To test the effectiveness of the formula for predicting the development of the disseminated stage of LB, we built a receiver operating characteristic (ROC) curve and determined the specificity and sensitivity of our model.

MULTIFACTORIAL REGRESSION MODEL FOR PREDICTING THE LEVEL OF HEAT SENSITIVITY IN HEALTHY YOUNG PEOPLE IN THE CONTEXT OF GLOBAL WARMING.

Objective: The aim: To create a mathematical model for predicting the level of heat sensitivity in healthy young people based on multivariate regression analysis.

Patients And Methods: Materials and methods: 150 healthy young people aged 17-20 years answered the questionnaire "Levels of heat sensitivity", underwent a heat test and mathematical analysis of the heart rate, after which the results were used to build a regression model of heat sensitivity.

Results: Results: The model of mathematical prediction of heat sensitivity (CHSL1/CHSL2), which we proposed for the first time, takes into account the most significant factors that influence the determination of higher and lower sensitivity to heat (Q1-Q6, %LF2, %HF1, %HF2, HR1, HR2), so its use will allow timely identi¬fication of individuals who are particularly susceptible to the effects of elevated ambient temperature and prevent the development of potential negative consequences of this exposure.