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Geographical variation in COVID-19 cases, prevalence, recovery and fatality rate by phase of national Lockdown in India, March 14-May 29, 2020

Geographical variation in COVID-19 cases, prevalence, recovery and fatality rate by phase of national Lockdown in India, March 14-May 29, 2020
Geographical variation in COVID-19 cases, prevalence, recovery and fatality rate by phase of national Lockdown in India, March 14-May 29, 2020
Background: since the COVID-19 pandemic hit Indian states at varying speed, it is crucial to investigate the geographical pattern in COVID-19. We analyzed the geographical pattern of COVID-19 prevalence and mortality by the phase of national lockdown in India.

Method: using publicly available compiled data on COVID-19, we estimated the trends in new cases, period-prevalence rate (PPR), case recovery rate (CRR), and case fatality ratio (CFR) at national, state and district level.

Findings: the age and sex are missing for more than 60 percent of the COVID-19 patients. There is an exponential increase in COVID-19 cases both at national and sub-national levels. The COVID-19 infected has jumped about 235 times (from 567 cases in the pre-lockdown period to 1,33,669 in the fourth lockdown); the average daily new cases have increased from 57 in the first lockdown to 6,482 in the fourth lockdown; the average daily recovered persons from 4 to 3,819; the average daily death from 1 to 163. From first to the third lockdown, PPR (0.04 to 5.94), CRR (7.05 to 30.35) and CFR (1.76 to 1.89) have consistently escalated. At state-level, the maximum number of COVID-19 cases is found in the states of Maharashtra, Tamil Nadu, Delhi, and Gujarat contributing 66.75 percent of total cases. Whereas no cases found in some states, Kerela is the only state flattening the COVID-19 curve. The PPR is found to be highest in Delhi, followed by Maharastra. The highest recovery rate is observed in Kerala, till second lockdown; and in Andhra Pradesh in third lockdown. The highest case fatality ratio in the fourth lockdown is observed in Gujarat and Telangana. A few districts viz. like Mumbai (96.7); Chennai (63.66) and Ahmedabad (62.04) have the highest infection rate per 100 thousand population. Spatial analysis shows that clusters in Konkan coast especially in Maharashtra (Palghar, Mumbai, Thane and Pune); southern part from Tamil Nadu (Chennai, Chengalpattu and Thiruvallur), and the northern part of Jammu & Kashmir (Anantnag, Kulgam) are hot-spots for COVID-19 infection while central, northern and north-eastern regions of India are the cold-spots.

Conclusion: India has been experiencing a rapid increase of COVID-19 cases since the second lockdown phase. There is huge geographical variation in COVID-19 pandemic with a concentration in some major cities and states while disaggregated data at local levels allows understanding geographical disparity of the pandemic, the lack of age-sex information of the COVID-19 patients forbids to investigate the individual pattern of COVID-19 burden.
medRxiv
Srivastava, Ankita
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Tamrakar, Vandana
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Moradhvaj, M.
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Akhtar, Saddaf Naaz
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Kumar, Krishna
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Nagendra, Chand
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Saikia, Nandita
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Srivastava, Ankita
19d2ece0-c809-4e5b-9f4d-66700576c3e6
Tamrakar, Vandana
a5b18580-0e21-4ad2-99cc-e71775873ebd
Moradhvaj, M.
a9a2a233-eadc-402c-99fa-6f56f6703bf2
Akhtar, Saddaf Naaz
aa7e6bda-4317-4905-bbde-1582a6a7bf58
Kumar, Krishna
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Nagendra, Chand
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Saikia, Nandita
62aac0cc-9c33-4a67-a6a6-fb71089c21d1

[Unknown type: UNSPECIFIED]

Record type: UNSPECIFIED

Abstract

Background: since the COVID-19 pandemic hit Indian states at varying speed, it is crucial to investigate the geographical pattern in COVID-19. We analyzed the geographical pattern of COVID-19 prevalence and mortality by the phase of national lockdown in India.

Method: using publicly available compiled data on COVID-19, we estimated the trends in new cases, period-prevalence rate (PPR), case recovery rate (CRR), and case fatality ratio (CFR) at national, state and district level.

Findings: the age and sex are missing for more than 60 percent of the COVID-19 patients. There is an exponential increase in COVID-19 cases both at national and sub-national levels. The COVID-19 infected has jumped about 235 times (from 567 cases in the pre-lockdown period to 1,33,669 in the fourth lockdown); the average daily new cases have increased from 57 in the first lockdown to 6,482 in the fourth lockdown; the average daily recovered persons from 4 to 3,819; the average daily death from 1 to 163. From first to the third lockdown, PPR (0.04 to 5.94), CRR (7.05 to 30.35) and CFR (1.76 to 1.89) have consistently escalated. At state-level, the maximum number of COVID-19 cases is found in the states of Maharashtra, Tamil Nadu, Delhi, and Gujarat contributing 66.75 percent of total cases. Whereas no cases found in some states, Kerela is the only state flattening the COVID-19 curve. The PPR is found to be highest in Delhi, followed by Maharastra. The highest recovery rate is observed in Kerala, till second lockdown; and in Andhra Pradesh in third lockdown. The highest case fatality ratio in the fourth lockdown is observed in Gujarat and Telangana. A few districts viz. like Mumbai (96.7); Chennai (63.66) and Ahmedabad (62.04) have the highest infection rate per 100 thousand population. Spatial analysis shows that clusters in Konkan coast especially in Maharashtra (Palghar, Mumbai, Thane and Pune); southern part from Tamil Nadu (Chennai, Chengalpattu and Thiruvallur), and the northern part of Jammu & Kashmir (Anantnag, Kulgam) are hot-spots for COVID-19 infection while central, northern and north-eastern regions of India are the cold-spots.

Conclusion: India has been experiencing a rapid increase of COVID-19 cases since the second lockdown phase. There is huge geographical variation in COVID-19 pandemic with a concentration in some major cities and states while disaggregated data at local levels allows understanding geographical disparity of the pandemic, the lack of age-sex information of the COVID-19 patients forbids to investigate the individual pattern of COVID-19 burden.

Text
2020.06.04.20122028v1.full - Author's Original
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Published date: 5 June 2020

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Local EPrints ID: 491395
URI: http://eprints.soton.ac.uk/id/eprint/491395
PURE UUID: ab1b75e0-6b0f-44ad-b3e8-a304bf7b1c58
ORCID for Saddaf Naaz Akhtar: ORCID iD orcid.org/0000-0002-0346-5220

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Date deposited: 21 Jun 2024 16:40
Last modified: 22 Jun 2024 02:11

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Contributors

Author: Ankita Srivastava
Author: Vandana Tamrakar
Author: M. Moradhvaj
Author: Saddaf Naaz Akhtar ORCID iD
Author: Krishna Kumar
Author: Chand Nagendra
Author: Nandita Saikia

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