Modeling the Corona Virus Outbreak in IRAN

Maryam Moghadami; Maryam Moghadami; Mohammad Hassanzadeh; ka wa; Aziz Hedayati; Mila Malekolkalami

On 31 December 2019, the World Health Organization (WHO) office located in China was informed of pneumonia of unknown etiology cases (unknown cause) detected in Wuhan City, Hubei Province of China. WHO reported that a novel coronavirus (2019-nCoV), named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and chosen by International Committee on Taxonomy of Viruses on 11 February 2020, was identified as the causative virus by Chinese authorities on 7 January. (1) During the 2019-20 coronavirus pandemic, Iran reported its first confirmed cases of SARS-CoV-2 infections on 19 February 2020 in Qom (2) . As of 17 March 2020, according to Iranian health authorities, there had been 988 COVID-19 deaths in Iran with more than 16,000 confirmed infections(3,4,5) This respiratory disease caused by a coronavirus is one of the leading causes for serious illnesses in people all over the world. According to the global statistics of fatalities caused by coronavirus, and its spread in Iran, it is vital and essential to forecast its outbreak by a model. As 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. Previously, real-time analyses have shed light on the transmissibility, severity, and natural history of an emerging pathogen in the first few weeks of an outbreak, such as with severe acute respiratory syndrome (SARS), the 2009 influenza pandemic, and Ebola. Analyses of detailed line lists of patients are particularly useful to infer key epidemiological parameters, such as the incubation and infectious periods, and delays between infection and detection, isolation, and reporting of cases. However, official individual patient data rarely become publicly available, when the information is most needed. This is an analysis of the COVID-19 out-break in Iran. In this population-level observational study, I used the Iranian Ministry of Health reports downloaded from GitHub, an online data-sharing platform. This dataset is updated on a daily basis with a 24 hour delay. The dataset includes time-stamped counts of the daily cases and deaths within each province in Iran.