Fear of exponential growth in Covid19 data of India and future sketching

Mondal, Supriya; Ghosh, Sabyasachi

doi:10.1101/2020.04.09.20058933

Cited by 16 publications

(23 citation statements)

References 3 publications

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“…To mark the lock down period, we have drawn two vertical red dotted lines at 25th March and 3rd May. Now, we will attempt to fit the total cases data from 25th March to onwards via different possible Sigmoid functions with standard form [7,8,9,3,4]…”

Section: States Having Noticeable Impact Of Htsmentioning

confidence: 99%

“…The new case can be grossly realized as time derivative of total cases. The time derivative of Sigmoid function follow the form [8,9,3,4]…”

Section: States Having Noticeable Impact Of Htsmentioning

confidence: 99%

“…(4), 10 more states, having ignorable impact of imported data, are discussed. In both sections (3) and (4), the Sigmoid trend of data are analyzed and based on that pattern, we classified the 15 states into 3 gross categories. At the end, we have summarized the study with extracting interpretation in Sec.…”

Section: Introductionmentioning

confidence: 99%

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Searching the Sigmoid-type trend in Lock Down period covid19 data of India and its different states

Mondal¹,

Ghosh

2020

Preprint

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We have worked on imported covid19 cases of India, detected after declaration of lock down. They are marked as hidden travelers, who are detected later during 1-2 weeks period of lock down. We have investigated the impact of those travelers on selective 15 states, having large number cases. Among them 5 states have faced a noticeable effect on their data profile, although its overall effect in country level is quite negligible. Searching the Sigmoid trends of all 15 states, we have identified 3 categories depending upon latest data of new case with respect to the peak value of Sigmoid functions. Based on our optimistic predicted curves, ongoing lock down period might be enough for getting marginal values of new cases for KL, HR, JK, TN and AP but the reamining of 15 states might need a third phase of lock down or alternative preventive measures.

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Section: States Having Noticeable Impact Of Htsmentioning

confidence: 99%

“…The new case can be grossly realized as time derivative of total cases. The time derivative of Sigmoid function follow the form [8,9,3,4]…”

Section: States Having Noticeable Impact Of Htsmentioning

confidence: 99%

See 1 more Smart Citation

Searching the Sigmoid-type trend in Lock Down period covid19 data of India and its different states

Mondal¹,

Ghosh

2020

Preprint

Self Cite

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“…The novel Coronavirus‐2019 disease 1 has posed an incredible danger to all mankind throughout the world (Mondal & Ghosh, 2020; Nadeem, 2020). It is a contagious human disease and its fast pace of infection and rate of transmission among people has introduced a new challenge for the health care system (Clara‐Rahola, 2020).…”

Section: Introductionmentioning

confidence: 99%

Understanding the spatio‐temporal pattern of COVID‐19 outbreak in India using GIS and India's response in managing the pandemic

Bag

Ghosh

Biswas

et al. 2020

Region Sci Policy Practice

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Due to the outbreak of Coronavirus, humans all over the world are facing several health problems. The present study has explored the spatio-temporal pattern of Coronavirus spread in India including spatial clustering, identification of hotspot, spatial heterogeneity, and homogeneity, spatial trend, and direction of COVID-19 cases using spatial statistical analysis during the period of 30th January to 20 June 2020. Besides, the polynomial regression model has been used for predictions of COVID-19 affected population and related deaths. The study found positive spatial heterogeneity in COVID-19 cases in India. The study has also identified seventeen epicentres across the country with high incidence rates. The directional distribution of ellipse polygon shows that the spread of COVID-19 now trending towards the east but the concentration of cases is mainly in the western part of the country. The country's trend of COVID-19 follows a fourth-order polynomial growth and is characterized by an increasing trend. The prediction results show that as on 14 th October India will reach 14,660,400 COVID-19 cases and the death toll will cross 152,945. Therefore, a 'spacespecific' policy strategy would be a more suitable strategy for reducing the spatial spread of the virus in India. Moreover, the study has broadly found out seven sectors, where Govt. of India lacks in terms of confronting the ongoing pandemic. The study has also recommended some appropriate policies which would be immensely useful for the administration to initiate strategic planning.

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“…Many people have predicted the lockdown extension date by modeling the growth as exponential nature [3,4]. Hence, it is a challenging job to model the growth and to forecast the number of total affected people.…”

Section: Introductionmentioning

confidence: 99%

Forecast and interpretation of daily affected people during 21 days lockdown due to COVID 19 pandemic in India

Bhattacharyya

Bhowmik

Mukherjee

2020

Preprint

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The problem of facing difficulty to control the spreading of newly detected novel corona virus 2019 is a matter of attention throughout the whole world. The total numbers of infected individuals have already crossed 2 million throughout the world. The government of all the affected countries have already taken many measures like lockdown to stop the spread.Therefore, it is important to study the nature of growth and interpretations are necessary for taking needful by the government. In this paper, we have tried to interpret the spreading capability of novel corona virus in India taking into consideration of 21 days lockdown data.The prediction is based on the present number of available cases and number of new cases reporting daily. We have explained the number of infected people in India comparing with Italy, China, Spain, and USA data of 21 days individually after announcing lockdown. The plot of daily new cases with the number of days spent after lockdown is fitted by linear and polynomial function. The best fitted graph is chosen for interpretation and that is based on the parameters obtained from fitting. The forecast of maximum spreading possibility is discussed with linear and 4-degree polynomial fitting parameters. Finally, some further preventive measurements are also discussed.

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Fear of exponential growth in Covid19 data of India and future sketching

Cited by 16 publications

References 3 publications

Searching the Sigmoid-type trend in Lock Down period covid19 data of India and its different states

Searching the Sigmoid-type trend in Lock Down period covid19 data of India and its different states

Understanding the spatio‐temporal pattern of COVID‐19 outbreak in India using GIS and India's response in managing the pandemic

Forecast and interpretation of daily affected people during 21 days lockdown due to COVID 19 pandemic in India

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