Analysis of the Worldwide Corona Virus (COVID-19) Pandemic Trend; A Modelling Study to Predict Its Spread
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Abstract
Objective
The Coronavirus (COVID-19) has advanced into 197 countries and territories leaving behind a total of 372,757 confirmed cases and 16231 deaths.
Methods
One the basis of WHO situation reports data of COVID-19 along with daily official reports from the Japan, China and the Kore we modelled the spread of COVID19 by using the Successive Approximation Method. We defined the two state of data to find the mean ratio (η) of the present cases count to the sum of previous and present cases. This ratio further predicts the future state of COVID-19 pandemic.
Results
The mean ratio (η) of expected cases were found 0.485, while the mean ratio for deaths was found to be 0.49. We calculated worldwide expected lower bound value for confirmed cases 247007 cases with maximum limit of 1667719 cases and minimum deaths count 8660 with upper limit of 117397 deaths in next 30 days. While in the case of Iran, a large increase in the number of deaths are expected in the upcoming 30 days with lower bound value of 1140 deaths and maximum value of 598478 deaths.
Interpretation
Iran whole population is on risk.
Article activity feed
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SciScore for 10.1101/2020.03.30.20048215: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
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).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The only limitation of our model is that we did not consider the worldwide temperature differences and seasonality of coronavirus transmission. If 2019-nCoV, similar to influenza, has strong seasonality in its transmission, our epidemic forecast might be biased. Furthermore, we did not account for a vaccine to become publicly available …
SciScore for 10.1101/2020.03.30.20048215: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
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).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The only limitation of our model is that we did not consider the worldwide temperature differences and seasonality of coronavirus transmission. If 2019-nCoV, similar to influenza, has strong seasonality in its transmission, our epidemic forecast might be biased. Furthermore, we did not account for a vaccine to become publicly available to reduce the impact of the pandemic. But even in the absence of a vaccine, human behaviour and the environment itself can alter the likelihood of spread. Hospitals isolate infected people or they may self-quarantine. A further decrease also often occurs as an outbreak matures as people become immune because of previous exposure, reducing the number of susceptible hosts. It has been recently reported that COVID-19 can stay active in aerosol droplets for 3 hours and viable on solid surfaces for 72 hours so new precautionary measures according to this information can reduce viral spread.11 Further action might include a ban on paper currency notes, a suspension of all cardboard box packed delivery of items and discouragement of human-to-human contact. By using this model world health agencies need to prepare their AID program in advanced for health resources limited countries before the pandemic cause huge damages.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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