Abstract
Abstract In literature, various mathematical models have been developed to have a better insight into the transmission dynamics and control the spread of infectious diseases. Aiming to explore more about various aspects of infectious diseases, in this work, we propose conceptual mathematical model through a SEIQR (Susceptible-Exposed-Infected-Quarantined-Recovered) mathematical model and its control measurement. We establish the positivity and boundedness of the solutions. We also compute the basic reproduction number and investigate the stability of equilibria for its epidemiological relevance. To validate the model and estimate the parameters to predict the disease spread, we consider the special case for COVID-19 to study the real cases of infected cases from [2] for Russia and India. For better insight, in addition to mathematical model, a history based LSTM model is trained to learn temporal patterns in COVID-19 time series and predict future trends. In the end, the future predictions from mathematical model and the LSTM based model are compared to generate reliable results.
Highlights
In history, various pandemics and epidemics have emerged out several times, which have demolished humanity, sometimes resulting into end of civilizations and tremendous change in the course of history
In literature, various mathematical models have been developed to have a better insight into the transmission dynamics and control the spread of infectious diseases
To validate the model and estimate the parameters to predict the disease spread, we consider the special case for COVID-19 to study the real cases of infected cases from [2] for Russia and India
Summary
(i) the basic reproduction number (R , the average number of secondary infections produced by primary infection while coming in contact with the entire susceptible population) and (ii) the generation time (average time from the onset of symptom in primary infectious individual to symptom onset in secondary case) These two components jointly determine the likelihood and speed of the outbreaks of epidemic. Besides medical and biological research, it becomes an emergency to formulate a mathematical model which e ectively describes the development and transmission of disease This will help to make signi cant decisions and preventive measures based on the e ective assumptions provided by the model.
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