نوع مقاله : مقاله کامل پژوهشی
نویسندگان
دانشگاه علم و صنعت ایران
کلیدواژهها
موضوعات
عنوان مقاله English
نویسندگان English
Growth is a phenomenon observed in many different kinds of processes. The growth curve is an empirical model used to describe the evolution of a quantity over time. These curves are widely applied in fields such as biology, physics, engineering, economics, and social sciences. Accurate description and prediction of growth systems using well-known deterministic models, such as logistic, Richards and Gompertz are one of the current topics in this research field.
In this study, we propose a new deterministic differential equation model for the growth speed profile in single-wave and two-waves epidemics. We show that our model offers high flexibility in growth inflection points, i.e., these points can be adjusted so that to simulate real epidemic data. The results demonstrate that, in the two-wave case, our model can describe the growth speed profile effectively using fewer parameters compared to common models such as the bi logistic and bi Richards models.
we analyze the features and capabilities of our model, and validate it against COVID-19 pandemic real data in several countries as well as the 2003 SARS epidemic in Singapore.
کلیدواژهها English