Assessment of impact of relaxation in lockdown and forecast of preparation for combating COVID-19 pandemic in India using Group Method of Data Handling

Vaishnav, Vaibhav; Vajpai, Jayashri

doi:10.1016/j.chaos.2020.110191

Cited by 17 publications

(11 citation statements)

References 49 publications

(45 reference statements)

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“…[18] From 18 May 2020, LD4 continued and more power were given to states to demarcate zones. The average daily number of tests have increased from 1,717 (19)(20)(21)(22)(23)(24)(25) to 131,772 (25-31 May) with an estimated testing shortfall of 4.58 million tests nationally by 31 May 2020. [19] In view of economical impacts of lockdown, relaxations in ULD1 allowed shopping malls, religious places, hotels and restaurants to reopen.…”

Section: Discussionmentioning

confidence: 99%

“…They reported that apart from relaxations in LD3 and LD4, the increased testing capacity and migration of laborers were important reasons of increased positive cases. [20] During LD5, major relaxations include opening of cinema halls with 50% sitting capacity and reopening of hill stations, beaches and national parks. The results showed that the evolution of death cases due to COVID-19 closely parallels the evolution of new cases of infection .…”

Section: Discussionmentioning

confidence: 99%

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COVID-19 and lockdown in India: Evaluation using analysis of covariance

Tak

Das

Gahlot³

2020

Preprint

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Background: The lockdown in India has entered into its ninth month to curb the Coronavirus disease-19 (COVID-19) pandemic. The objective of the present study is to evaluate impact of different phases of lockdown on evolution of new cases of infection and deaths due to COVID-19.Methods: In this retrospective longitudinal study, the Indian data on new cases of infection and deaths due to COVID-19 were retrieved from John Hopkins University dashboard. The cases from 25 March to 31 October 2020 were analyzed using analysis of covariance for four phases of lockdown and five phases of unlockdown.Results: The coefficients of regression for new cases did not differ significantly for initial four phases of lockdown and unlock-1, while from unlock-2 the coefficients showed significant decrease till unlock-5. While death cases showed no significant differences between coefficients of regression for initial four phases of lockdown and unlock, but coefficient of unlock-5 was significantly lower than unlock-4. Conclusion: The trends of coefficients of regression of new cases and deaths reveals positive effects of lockdown in flattening the epidemic curve. Though the pandemic is on downslope, till the availability of vaccine, non-pharmaceutical measures such as social distancing, wearing of mask need to be implemented.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

COVID-19 and lockdown in India: Evaluation using analysis of covariance

Tak

Das

Gahlot³

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…[18] From 18 May 2020, LD4 continued and more power was given to states to demarcate zones. The average daily number of tests have increased from 1,717 (19)(20)(21)(22)(23)(24)(25) to 131,772 (25-31 May) with an estimated testing shortfall of 4.58 million tests nationally by 31 May 2020. [19] In view of economical impacts of lockdown, relaxations in ULD1 allowed shopping malls, religious places, hotels and restaurants to reopen.…”

Section: [13]mentioning

confidence: 99%

COVID-19 and Lockdown in India: Evaluation using Analysis of Covariance

Tak

Das

Gahlot³

2021

Preprint

View full text Add to dashboard Cite

Background: The lockdown in India has entered into its ninth month to curb the Coronavirus disease-19 (COVID-19) pandemic. The objective of the present study is to evaluate impact of different phases of lockdown on evolution of new cases of infection and deaths due to COVID-19.Methods: In this retrospective longitudinal study, the Indian data on new cases of infection and deaths due to COVID-19 were retrieved from John Hopkins University dashboard. The cases from 25 March to 31 October 2020 were analyzed using analysis of covariance for four phases of lockdown and five phases of unlockdown.Results: The coefficients of regression for new cases did not differ significantly for initial four phases of lockdown and unlock-1, while from unlock-2 the coefficients showed significant decrease till unlock-5. While death cases showed no significant differences between coefficients of regression for initial four phases of lockdown and unlock, but coefficient of unlock-5 was significantly lower than unlock-4. Conclusion: The trends of coefficients of regression of new cases and deaths reveals positive effects of lockdown in flattening the epidemic curve. Though the pandemic is on downslope, till the availability of vaccines, non-pharmaceutical measures such as social distancing, wearing of masks need to be implemented.

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“…Also noteworthy is the Ukrainian work by Nastenko et al [47], which used Group Method of Data Handling (GMDH) [48] models and Simplex Method [49] optimization algorithm to select the treatment strategy.…”

Section: Information Systems Of State Assessment and Forecastingmentioning

confidence: 99%

Personalized Clinical Treatment Selection Using Genetic Algorithm and Analytic Hierarchy Process

Nosovets¹,

Babenko²,

Davydovych³

et al. 2021

Adv. sci. technol. eng. syst. j.

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The development of Machine Learning methods and approaches offers enormous growth opportunities in the Healthcare field. One of the most exciting challenges in this field is the automation of clinical treatment selection for patient state optimization. Using necessary medical data and the application of Machine Learning methods (like the Genetic Algorithm and the Analytic Hierarchy Process) provides a solution to such a challenge. Research presented in this paper gives the general approach to solve the clinical treatment selection task, which can be used for any type of disease. The distinguishing feature of this approach is that clinical treatment is tailored to the patient's initial state, thus making treatment personalized. The article also presents a comparison of the different classification methods used to model patient indicators after treatment. Additionally, special attention was paid to the possibilities and potential of using the developed approach in real Healthcare challenges and tasks.

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Assessment of impact of relaxation in lockdown and forecast of preparation for combating COVID-19 pandemic in India using Group Method of Data Handling

Cited by 17 publications

References 49 publications

COVID-19 and lockdown in India: Evaluation using analysis of covariance

COVID-19 and lockdown in India: Evaluation using analysis of covariance

COVID-19 and Lockdown in India: Evaluation using Analysis of Covariance

Personalized Clinical Treatment Selection Using Genetic Algorithm and Analytic Hierarchy Process

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