This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research Article
Modelling the Paucity of COVID-19 Pandemic Spread Incidence across the India Nation
Pavan Kumar
Rani Lakshmi Bai Central Agriculture University
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: The highly contagious Co rona vi rus d isease (COVID-19) pandemic affected nearly all nations across the world. It was emerged as most swiftly affected disease across the world and more than 2934 lakhs population suffered in four months of the time period as on date April 26, 2020. Its first epicenter was at Wuhan city of China during the month of December 2019. Currently, the most affected people and new epicenter of Coronavirus is at the United States of America (USA). Various nation’s administration including the India government called for the regional and local lockdown. We predicted the confirmed COVID-19 cases for next May-2020 month, map the magnitude of COVID-19 disease for Indian states and model the paucity of COVID-19 disease with statistical confirmatory data analysis model for declining rate for the cases represented for the Indian proportion of population.
Method: The ARIMA model used to predict for next short-term cases, based moving average of past confirmed cases. The restriction of COVID-19 pandemic disease analyzed with predicted cases for month May 2020 data at 95 percent confidence is more than 2.5 lakh cases.
Results: The confirmatory data analysis model for the time estimation for the paucity of cases it takes in between six to eighteen months of time frame. The Confirmatory model which considers recovery rate, social, economic and government policy. To complete recovery from the COVID-19 cases it takes on an average more than next ten months.
Conclusion: The disease impacts also depend upon administrative and local people support for self-quarantine and other measures. The India nation Gross Domestic Product (GDP) based on more than 17% of its agriculture production, due to longer affect of the disease and extended lockdown period it will be severely affected. However, all the economic activities with full of its intensity takes-up after complete paucity of COVID-19 disease spread. Keywords: SARS-CoV-2; Lockdown; GDP; Nobel-Corona; Confirmatory data model
Keywords
SARS-CoV-2, Lockdown, GDP, Nobel-Corona, Confirmatory data model
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.
Amar Nath
commented on 18 May, 2020
Appreciable work of the team. It is extremely helpful in answering our queries related to covid19 pandemic. Congratulations to the team.
Abhishek Kala
commented on 19 May, 2020
1) Though the research itself is valuable but it needs some major restructuring. 2) The manuscript needs to be edited for grammatical mistakes and sentence structuring (starting from the Title itself) 3) Introduction of a research needs to focus on the problem and the novel approach that has been used to address it. This section has not been properly utilized and rather more facts and figures are mentioned here. 4) Units need to be consistent and should adhere to the one that are accepted internationally. Example: Lakhs vs Millions. 5) Not sure but where exactly has ERDAS software been used? 6) Similar to introduction - the conclusion section also needs to add more beef to it. The importance of your novel approach needs to be emphasized. 7) I feel 18 references in total is not much for a paper of such importance.
View 1 reply
Ajay Kumar Gupta
commented on 19 May, 2020
Although the present research work is the need of time, there are some grammatical errors that need to be checked. Also, it needs to be carried out at in all developing countries nearby India for better policy interventions.
Dr. Jyoti Singh
commented on 19 May, 2020
Manuscript Modelling the Paucity of COVID-19 cases in India countries using machine learning. While the topic is potentially interesting, the way the paper is presented makes it basically useful to interested researchers. MS file brings a relevant study and therefore, I congratulate the authors for conducting the research. The analysis of this study predicted continued dynamics of COVID-19 in India. The proposed models are relevant and may assist government officials and researchers in coping with the dissemination of COVID-19. COVID-19 cases piled up in India since week ago as the WHO reported a massive spike of near 3-4 thousands daily and new cases to take the cumulative tally to more than lakh. Government of India is taking all necessary steps to ensure that you are prepared well to face the challenge and threat posed by the growing pandemic of COVID-19 the Corona Virus. With active support of the people of India, you have been able to contain the spread of the Virus in India country. The most important factor in preventing the spread of the Virus locally is to empower the citizens with the right information and taking precautions as per the advisories being issued by MHFW. My advice to the authors should be a limitations section and clearly outline what could influence the accuracy of the model. For instance; we are 45 days away from your completed prediction date.
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 17 May, 2020
Community comments: 5
Metrics
Comments: 5
PDF Downloads: ...
HTML Views: ...
Subject Areas
Infectious Diseases
Learn more about our company.
This is a preprint. It has not completed peer review.
Research Article
Modelling the Paucity of COVID-19 Pandemic Spread Incidence across the India Nation
Pavan Kumar
Rani Lakshmi Bai Central Agriculture University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 17 May, 2020
Community comments: 5
Metrics
Comments: 5
PDF Downloads: ...
HTML Views: ...
Subject Areas
Infectious Diseases
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: The highly contagious Co rona vi rus d isease (COVID-19) pandemic affected nearly all nations across the world. It was emerged as most swiftly affected disease across the world and more than 2934 lakhs population suffered in four months of the time period as on date April 26, 2020. Its first epicenter was at Wuhan city of China during the month of December 2019. Currently, the most affected people and new epicenter of Coronavirus is at the United States of America (USA). Various nation’s administration including the India government called for the regional and local lockdown. We predicted the confirmed COVID-19 cases for next May-2020 month, map the magnitude of COVID-19 disease for Indian states and model the paucity of COVID-19 disease with statistical confirmatory data analysis model for declining rate for the cases represented for the Indian proportion of population.
Method: The ARIMA model used to predict for next short-term cases, based moving average of past confirmed cases. The restriction of COVID-19 pandemic disease analyzed with predicted cases for month May 2020 data at 95 percent confidence is more than 2.5 lakh cases.
Results: The confirmatory data analysis model for the time estimation for the paucity of cases it takes in between six to eighteen months of time frame. The Confirmatory model which considers recovery rate, social, economic and government policy. To complete recovery from the COVID-19 cases it takes on an average more than next ten months.
Conclusion: The disease impacts also depend upon administrative and local people support for self-quarantine and other measures. The India nation Gross Domestic Product (GDP) based on more than 17% of its agriculture production, due to longer affect of the disease and extended lockdown period it will be severely affected. However, all the economic activities with full of its intensity takes-up after complete paucity of COVID-19 disease spread. Keywords: SARS-CoV-2; Lockdown; GDP; Nobel-Corona; Confirmatory data model
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.
Amar Nath
commented on 18 May, 2020
Appreciable work of the team. It is extremely helpful in answering our queries related to covid19 pandemic. Congratulations to the team.
Abhishek Kala
commented on 19 May, 2020
1) Though the research itself is valuable but it needs some major restructuring. 2) The manuscript needs to be edited for grammatical mistakes and sentence structuring (starting from the Title itself) 3) Introduction of a research needs to focus on the problem and the novel approach that has been used to address it. This section has not been properly utilized and rather more facts and figures are mentioned here. 4) Units need to be consistent and should adhere to the one that are accepted internationally. Example: Lakhs vs Millions. 5) Not sure but where exactly has ERDAS software been used? 6) Similar to introduction - the conclusion section also needs to add more beef to it. The importance of your novel approach needs to be emphasized. 7) I feel 18 references in total is not much for a paper of such importance.
View 1 reply
Manoj Kumar
ORCiDreplied on 21 May, 2020
Thanks a lot Dr. Kala for your valuable inputs and suggestions for improving the MS. We will definitely restructure various sentences, paragraphs, title as suggested by you. We will look to resolve all the issues raised by you in the revised MS. I appreciate that you spared your precious time for providing valuable suggestions. Thanks a lot.
Ajay Kumar Gupta
commented on 19 May, 2020
Although the present research work is the need of time, there are some grammatical errors that need to be checked. Also, it needs to be carried out at in all developing countries nearby India for better policy interventions.
Dr. Jyoti Singh
commented on 19 May, 2020
Manuscript Modelling the Paucity of COVID-19 cases in India countries using machine learning. While the topic is potentially interesting, the way the paper is presented makes it basically useful to interested researchers. MS file brings a relevant study and therefore, I congratulate the authors for conducting the research. The analysis of this study predicted continued dynamics of COVID-19 in India. The proposed models are relevant and may assist government officials and researchers in coping with the dissemination of COVID-19. COVID-19 cases piled up in India since week ago as the WHO reported a massive spike of near 3-4 thousands daily and new cases to take the cumulative tally to more than lakh. Government of India is taking all necessary steps to ensure that you are prepared well to face the challenge and threat posed by the growing pandemic of COVID-19 the Corona Virus. With active support of the people of India, you have been able to contain the spread of the Virus in India country. The most important factor in preventing the spread of the Virus locally is to empower the citizens with the right information and taking precautions as per the advisories being issued by MHFW. My advice to the authors should be a limitations section and clearly outline what could influence the accuracy of the model. For instance; we are 45 days away from your completed prediction date.
Manoj Kumar
ORCiDreplied on 21 May, 2020
Thanks a lot Dr. Kala for your valuable inputs and suggestions for improving the MS. We will definitely restructure various sentences, paragraphs, title as suggested by you. We will look to resolve all the issues raised by you in the revised MS. I appreciate that you spared your precious time for providing valuable suggestions. Thanks a lot.