Complete Blood Count (CBC) and Multivariate Analysis as Tools for Predicting Coronavirus (COVID-19) Infectious

The COVID-19 pandemic has affected millions worldwide in recent years. However, the epidemic's impact on the residents of the southern Libyan region has not been assessed. To investigate the spread of COVID-19 among the population, a study was conducted from March to June 2021. The study involved 146 people, 97 of whom were infected with COVID-19 and 49 were not infected. A complete blood count (CBC) and multivariate statistical analysis were used to determine the extent of the epidemic's spread in the study area. The CBC analysis used China's Tecom Science Corporation, model number TEK-5000. The results revealed that males (58.76%) were more affected than females (41.24%). The most affected age group was those under 46 (53.6%). The T-test analysis showed significant differences (p > 0.01) for each Red blood cell count (RBC), Mean corpuscular haemoglobin (MCH), Mean corpuscular haemoglobin concentration (MCHC), Red cell distribution width (RDW), Platelet count (PLT), White blood cell count (WBC), Platelet count (PLT), and granulocytes (GRA). However, the Hematocrit (HCT) was less than the significance level (P < 0.05), and there was no significant difference (P > 0.05) for Hemoglobin (HGB), Mean corpuscular volume (MCV), Lymphocyte (LYM), and Monocyte (MON) compared to the uninfected group. This study indicates that COVID-19 infection significantly affects the average values of blood tests, and changes in these values may cause complications for patients. Therefore, monitoring these changes in blood values is crucial to reducing the death rate among the infected.