Modeling for Corona Virus Outbreak in IRAN

BackgroundAs the outbreak of coronavirus disease 2019 (COVID-19) is a worldwide pandemic, it is rapidly expanding in Iran, real-time analyses of epidemiological data are needed to increase situational awareness and inform interventions. In this study, we built a predictive model based on the cumulative trend of new cases and deaths for the top five provinces. we will also look at modeling the trends for confirmed cases, deaths and recovered for the whole country. MethodIn this study, we have chosen to apply the exponential smoothing model to iteratively forecast future values of a regular time seires from weightedaverages of past daily values of the series. This method is exponential because the value of each level is influenced by every preceeding actual value to an exponentially decreasing degree - more recent values are given a greater weight. The available data is too small to identify seasonal patterns and make predictable variation in value, such as annual fluctuation in temperature relative to the season. Trend is a tendency in the data to increase or decrease over time. ResultsIf no control measures are put in place, it is expected that over 40,000 would be infected in Tehran around the middle of June. However, if control measures were implemented with a high degree of success, one would expect the spreadof the COV-19 virus would peak at the start of April with a downward trend dropping off by the end of May (70 days). In the scenario, that no further measures are implemented, one would expect the spread of COVID-19 to continue on a gentle incline, reaching 21,000 by mid-June. The same processhas been applied to review the confirmed, deaths and recovered dataset. The forecast has been carried out for the next 30 days, a shorter timeframe has been selected as there is a high probability that the Iranian New Years celebration, Farvardin, first month of Spring (30th March in Western calendar) will have an impact on the infection rate following the event. The best predictive model predicts the confirmed cases to be in the range of 35,000-70,000, with the number of reported COVDI-19 deaths to be between 3,000 - 5,000 and 5,000 - 30,000 of recovered cases. ConclusionsModeling outbreak of Covid-19 shows that the number of patients and deaths is still increasing. Contagious diseases follow an exponential model and the same be Haves this one. This is because, the virus can spread to others and finally each person turns into a carrier of the virus and transmit it to another person. Disease control depends on disconnection and social distancing. In addition, many factors are effective in stopping the disease. These include citizens participation in the prevention process, health education, the effectiveness of instructive traditions, environmental conditions, and so on.