Evaluation of the Relative Risk of Covid-19 Mortality Based on the Number of Hospitalizations in Iran using a Log-Linear Distributed Lag Model

Background and Objectives: The Covid-19 epidemic began in Wuhan, China in the late 2019 and became a global epidemic in March 2020. In this regard, one of the most important indicators of the healthcare systems is the in-hospital mortality rate, which occurs with a time lag of one to two weeks after hospitalization. The aim of this study was to investigate the relative risk of Covid-19 mortality considering this time lag according to the number of daily hospitalizations.   Methods: The data included the number of daily hospitalizations and deaths from Covid-19 from 15 May 2020 to 10 February 2021 in Iran, which was obtained from the Github database. A log-linear distributed lag model was used to evaluate the relationship and lag effect between daily hospitalization and relative risk of death.   Results: The mean number of daily hospitalizations and deaths were 1342.2 ± 7 731.5 and 190.6 11±118.6 in the study period, respectively. It was found that an increase in the number of daily hospitalizations had a significant relationship with an increase in the relative risk of death on the same day and in the following days. As the number of hospitalizations exceeded 2000 patients per day, the cumulative relative risk of death increased to more than one.   Conclusion: The results showed that the number of hospitalizations exceeding 2000 people per day was an alert for the country's healthcare system. Overall, prevention and observance of health protocols in the first level followed by early diagnosis of the disease, improving the hospitals facilities and preparedness of healthcare staff can reduce the relative risk of death in the possible future peaks.