COVID-19 is spreading within the sort of an enormous epidemic for the globe. This epidemic infects a lot of individuals in Egypt. The World Health Organization states that COVID-19 could be spread from one person to another at a very fast speed through contact and respiratory spray. On these days, Egypt and all countries worldwide should rise to an effective step to investigate this disease and eliminate the effects of this epidemic. In this paper displayed, the real database of COVID-19 for Egypt has been analysed from February 15, 2020, to June 15, 2020, and predicted with the number of patients that will be infected with COVID-19, and estimated the epidemic final size. Several regression analysis models have been applied for data analysis of COVID-19 of Egypt. In this study, we’ve been applied seven regression analysis-based models that are exponential polynomial, quadratic, third-degree, fourth-degree, fifth-degree, sixth-degree, and logit growth respectively for the COVID-19 dataset. Thus, the exponential, fourth-degree, fifth-degree, and sixth-degree polynomial regression models are excellent models specially fourth-degree model that will help the government preparing their procedures for one month. In addition, we have applied the well-known logit growth regression model and we obtained the following epidemiological insights: Firstly, the epidemic peak could possibly reach at 22-June 2020 and final time of epidemic at 8-September 2020. Secondly, the final total size for cases 1.6676E+05 cases. The action from government of interevent over a relatively long interval is necessary to minimize the final epidemic size.

Family trees, also called pedigrees, have important information about an individual's past and future life. It can be used as a diagnostic tool and help guide decisions about genetic testing for the patient and at-risk family members. There are 2% to 10% of parent-child relationships missing, and this can cause large differences in the pedigree graphs created. Hence, the evaluation of pedigrees is an essential task. In this article, we focus on the problem of isomorphism of unlabeled subpedigrees with a large number of individuals and hundreds of families, given that the two pedigrees being evaluated are generational and mating is between external parents. We address two restricted versions of the unlabeled subpedigree graph problem, Cover Unlabeled subPedigree with a Bipartite graph (CUPB), and Cover Unlabeled subPedigree with a Path (CUPP) problems. Fixed parameter algorithms are presented to solve the two problems, CUPB and CUPP.