Introduction: One of the unusual aspects in coronavirus disease 2019 (COVID-19) pandemic is changing case fatality rate (CFR) in different time series. Many researchers are trying to find the reasons of this variability.
Objectives: This study aimed to present a model for a 30-day trend of CFR in any infectious disease epidemic using the example of COVID-19 in Iran. Patients and Methods: As a case study, we tried to use statistical mining of scientific databases. A descriptive approach with quantitative tools was conducted. The World Health Organization (WHO) database was used to access daily reports of CFR. Funnel plot and Z score were used to study and graph the trend.
Results: During this period of time, a total of 20610 cases were confirmed based on real-time polymerase chain reaction (PCR). Among them, 1556 individuals died. Therefore, CFR was calculated as 7.549% (95% confidence intervals 7.189%-7.910%). This frequency was considered as the pooled frequency. Daily CFR with 95% CI was compared with the pooled frequency.
Conclusion: In our case, the epidemic was started from high CFR due to low number of cases and testing only highly suspicious individuals. Then, the CFR was reduced due to increased number of patients and improvement in screening. Finally, CFR went back to its moderate rate due to the addition of the death numbers related to the cases of previous days.