Understanding Epidemic Data and Statistics: A Case Study of COVID-19

  1. Amirhoshang Hoseinpour Dehkordi
  2. Majid Alizadeh
  3. Pegah Derakhshan
  4. Peyman Babazadeh
  5. Arash Jahandideh

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Abstract

The 2019-Novel-Coronavirus (COVID-19) has affected 181 countries and out of about 1197405 confirmed cases (By April 5). Understanding the transmission dynamics of the infection in each country which affected on a daily basis and evaluating the effectiveness of control policies is critical for our further actions. To date, the statistics of COVID-19 reported cases show more than 80 percent of infected had a mild case of disease, while around 14 percent of infected experienced a severe one and about 5 percent are categorized as critical disease victims. Today’s report (2020-04-05; daily updates in the prepared website) shows the confirmed cases of COVID-19 in US, Spain, Italy, and Germany are 308850, 126168, 124632 and 96092; respectively. Calculating the total Case Fatality Rate (CFR) of Italy (2020-04-04), about 13.3% of confirmed cases passed away. Compared to South Korea’s rate of 1.8% (7 times lower than Italy) and China’s 4% (69% lower than Italy), the CFR of Italy is too high. There are some effective policies that yield significant changes in the trend of cases. The lockdown policy in China, Italy and Spain (the effect observed after some days), Shutdown of all non-essential companies in Hubei (the effect observed after 5 days), combined policy in South Korea and reducing working hours in Iran.

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    SciScore for 10.1101/2020.03.15.20036418: (What is this?)

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    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

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    Social distancing was one of the most effective policies to control past epidemic disease by limitation human to human transmission and reducing mortality and morbidity ([29], [30], [30]). However studies suggest that combination of multiple policies can boost the effectiveness. For instance, New York City Department of Health implement different policies during the influenza pandemic in 1918-19 at the same time and they have the lowest rate of mortality on the eastern seaboard of the US [31]. During COVID-19 outbreak, researchers predicted that the mass movement of people at the end of the Lunar New Year holiday, would increase the spreading of disease. Facing this concern, government of China implemented policies which was helpful in control the disease such as, extended the holiday so the holiday would long enough to shelter the incubation period of COVID-19, isolation of confirmed cases in hospitals, quarantining mild or asymptomatic persons in different hospitals, home-based quarantine of people from Hubei province (epicenter of the epidemic), and the most important one was to prevent individuals with asymptomatic infections from spreading the virus.([19], [22]) Iran is facing this concern as an important upcoming event in Iran is Nowruz which is the Iranian New Year, which recommended prompted policies from government.

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    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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  2. Version published to 10.1101/2020.03.15.20036418v2 on medRxiv
  3. Version published to 10.1002/jmv.25885
  4. Version published to 10.1101/2020.03.15.20036418v1 on medRxiv