Mathematical Modelling of SIR for COVID-19 Forecasting

ABSTRACT

This paper uses a mathematical model for COVID-19 pandemic forecasting estimation. The continuum of mathematical and statistical models on communicable and non-communicable diseases has shown a great concern for risk to human lives. The three terms of the SIR model, S (susceptible), I (infectious) and R (recovered), are the main factors of any disease model. This SIR model was introduced in 1927 for forecasting communicable diseases. The SIR model is a simple disease technique by which we can explain mathematically the spread of a virus through a population using mathematical models. The SIR model answers the main three question of this study under specific assumptions. The key parameter in the derivative equations is the value of Q, which is the ratio of contact and the proportion of the total population that comes into contact with a contaminated individual. In the COVID-19 outbreak, this value is very high and the virus is spreading fast. What we see is that, if the value of Q is high, then the disease will spread widely and will result in an epidemic (in our case, it is already at pandemic level). Hence what can we do to reduce the value of Q? This is why currently we are told to wash our hands, because, if we wash our hands, even if we have been in a contact with somebody with the disease, we are much less likely to then become infected. Similarly, social distancing tells us to to keep away from people, because if we stay away from other people we are reducing our probability of coming into contact with someone who has the disease and we are therefore contributing to reducing the value Q and controlling the spread.