365 days with COVID-19 in Iran: data analysis and epidemic curves

Abstract

Background: The first confirmed cases of COVID-19 in Iran were reported on February 19, 2020. This study aimed to analyze the epidemic curves and to investigate the correlation between epidemic parameters and furthermore to analyze the impact of control measures on the spread of COVID-19 in Iran during 365 days of the epidemic. Methods: We used data from February 20, 2020, to February 18, 2021, on the number of COVID-19 cases reported by Iranian governments. Pearson correlation coefficient was applied to investigate the correlation between different epidemic parameters. The number of daily deaths per daily new cases was averaged to calculate daily death rate and the same method was used to investigate the rate of daily positive tests. Furthermore, we employed two different methods to calculate the effective reproduction number using reported data. Results: The results showed that there was a strong correlation between the number of daily deaths and the number of daily new cases (specially the admitted cases). The results also indicated that the mean of daily death rate of COVID-19 during 365 days was 4.9 percent, and averagely 13.9 percent of daily tests results were positive. Furthermore, epidemic curves showed that implementing strict social distancing measures effectively reduced the number of confirmed cases. The effective reproduction curve indicated that social distancing is still necessary to control the spread of COVID-19 in Iran. Conclusions: Analyzing the prevention and control measures indicated that the strict social distancing implemented by the government effectively reduces the number of new cases and deaths. The curve of reproduction number also showed that effective reproduction number is still above one; hence, it is necessary to continue strict social distancing and control travelling to prevent causing another wave of outbreak especially in Persian New Year.

Modeling COVID-19 in Iran using Particle Swarm Optimization algorithm

“…3, the effective reproduction number has increased during Newruz and it is estimated to be 1.28. The curve of effective reproduction number illustrates that it is consistent with the curves estimated by JRC [5] and RKI [6] methods in the previous work [7].…”

“…Various researchers in different fields have carried out researches on COVID-19 in Iran [8][9][10] [7]. Some studies have tried to investigate the relationship between COVID-19 and meteorological and climatological factors [11][12].…”

Modeling the Dynamics and Forecasting the fourth Peak of COVID-19 in Iran Using PSO Algorithm

“…The curve of effective reproduction number illustrates that it was consistent with the curves estimated by Joint Research Centre (JRC) 5 and Robert Koch Institute (RKI) 6 methods in the previous work. 7 The estimated values of the fitted parameters were employed to predict the short-term future trends of COVID-19 in Iran. The prediction started from 429 th day of the outbreak (April 23, 2021) when the model was successively fitted to its previous days.…”

“…By the time this study was conducted, several studies had been carried out on COVID-19 in Iran by researchers working in different disciplines. [7][8][9][10] Some studies had attempted to investigate the relationship between COVID-19 and meteorological and climatological factors. 11,12 Some other studies had employed mathematical models to analyze the epidemic curve and forecast the epidemic trend of COVID-19 in Iran.…”