Modeling COVID-19 Time Series Data

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to unprecedented global challenges for public health systems. Statistical distribution models have become a valuable tool to predict and understand the transmission dynamics of the disease. Statistical models aim to describe the distribution of COVID-19 cases over time and across different regions.

This book consists of nine chapters. In Chapter, I, a brief introduction about the origin of COVID-19, mathematical and statistical modeling of COVID-19 infected cases and trends, and the concise objectives of the book are given. The prerequisites for the book are a knowledge of Panel Data Regression Models. However, details descriptions of the tools related to panel data models are elaborately discussed in the materials and methods sections in every chapter. The statistical analysis and interpretations are thoroughly discussed. The bibliography given at the end of the book will help the reader to survey the literature in the area of statistical modeling of disease dynamics. The contents of the book are highly useful to administrators and policymakers.