Temporal evolution of COVID-19 in the states of India using SIQR Model (Preprint)

2020 ◽  
Author(s):  
Alok Tiwari
Keyword(s):  
Tamil Nadu ◽  
Temporal Evolution ◽  
Reproduction Number ◽  
Uttar Pradesh ◽  
National Average ◽  
Indian Government ◽  
Indian States ◽  
Steady Rate ◽  
Second Wave ◽  
Second Peak

BACKGROUND COVID 19 entered during the last week of April 2020 in India has caused 3,546 deaths with 1,13,321 number of reported cases. Indian government has taken many proactive steps, including strict lockdown of the entire nation for more than 50 days, identification of hotspots, app-based tracking of citizens to track infected. OBJECTIVE This paper investigated the evolution of COVID 19 in five states of India (Maharashtra, UP, Gujrat, Tamil Nadu, and Delhi) from 1st April 2020 to 20th May 2020 METHODS Variation of doubling rate and reproduction number (from SIQR) with time is used to analyse the performance of the majorly affected Indian states RESULTS . It has been determined that Uttar Pradesh is one of the best performers among five states with the doubling rate crossing 18 days as of 20th May. Tamil Nadu has witnessed the second wave of infections during the second week of May. Maharashtra is continuously improving at a steady rate with its doubling rate reaching to 12.67 days. Also these two states are performing below the national average in terms of infection doubling rate. Gujrat and Delhi have reported the doubling rate of 16.42 days and 15.49 days respectively. Comparison of these states has also been performed based on time-dependent reproduction number. Recovery rate of India has reached to 40 % as the day paper is written. CONCLUSIONS All the three major contributing states of India as improving slowly. Tamil Nadu witnessed the second peak during mid of May, Maharasthra alongwith Tamil Nadu is performing below the national average. This kind of analysis can be useful for the analysis of evolution of COVID 19 among different states of India.

scholarly journals Temporal evolution of COVID-19 in the states of India using SIQR Model

2020 ◽  
Author(s):  
Alok Tiwari
Keyword(s):  
Tamil Nadu ◽  
Temporal Evolution ◽  
Reproduction Number ◽  
Uttar Pradesh ◽  
National Average ◽  
Indian Government ◽  
Indian States ◽  
Steady Rate ◽  
Entire Nation ◽  
Second Wave

ABSTRACTCOVID 19 entered during the last week of April 2020 in India has caused 3,546 deaths with 1,13,321 number of reported cases. Indian government has taken many proactive steps, including strict lockdown of the entire nation for more than 50 days, identification of hotspots, app-based tracking of citizens to track infected. This paper investigated the evolution of COVID 19 in five states of India (Maharashtra, UP, Gujrat, Tamil Nadu, and Delhi) from 1st April 2020 to 20th May 2020. Variation of doubling rate and reproduction number (from SIQR) with time is used to analyse the performance of the majorly affected Indian states. It has been determined that Uttar Pradesh is one of the best performers among five states with the doubling rate crossing 18 days as of 20th May. Tamil Nadu has witnessed the second wave of infections during the second week of May. Maharashtra is continuously improving at a steady rate with its doubling rate reaching to 12.67 days. Also these two states are performing below the national average in terms of infection doubling rate. Gujrat and Delhi have reported the doubling rate of 16.42 days and 15.49 days respectively. Comparison of these states has also been performed based on time-dependent reproduction number. Recovery rate of India has reached to 40 % as the day paper is written.

scholarly journals Evolution of COVID-19 Pandemic in India

2020 ◽  
Author(s):  
Ali Asad ◽  
Siddharth Srivastava ◽  
Mahendra K. Verma
Keyword(s):  
Power Law ◽  
Mathematical Analysis ◽  
Predictive Models ◽  
Growth Pattern ◽  
Tamil Nadu ◽  
Linear Growth ◽  
Uttar Pradesh ◽  
Indian States ◽  
Effective Governance ◽  
Second Wave

AbstractA mathematical analysis of patterns for the evolution of COVID-19 cases is key to the development of reliable and robust predictive models potentially leading to efficient and effective governance against COVID-19. Towards this objective, we study and analyze the temporal growth pattern of COVID-19 infection and death counts in various states of India. Our analysis up to June 16, 2020 shows that several states (namely Maharashtra, Tamil Nadu, Delhi, Uttar Pradesh) have reached t2 power-law growth, while some others like Gujarat, Rajasthan, and Madhya Pradesh have reached linear growth. Karnataka and Kerala are exhibiting a second wave. In addition, we report that the death counts exhibit similar behaviour as the infection counts. These observations indicate that Indian states are far from flattening their epidemic curves.

scholarly journals Incidence of treatment for postabortion complications in India, 2015

2020 ◽  
Vol 5 (7) ◽  
pp. e002372
Author(s):  
Susheela Singh ◽  
Rubina Hussain ◽  
Chander Shekhar ◽  
Rajib Acharya ◽  
Melissa Stillman ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Large Scale ◽  
National Level ◽  
Uttar Pradesh ◽  
Primary Source ◽  
Reproductive Age ◽  
Legal Abortion ◽  
Indian States ◽  
Medication Abortion ◽  
Postabortion Care

Abortion has been legal under broad criteria in India since 1971. However, access to legal abortion services remains poor. In the past decade, medication abortion (MA) has become widely available in India and use of this method outside of health facilities accounts for over 70% of all abortions. Morbidity from unsafe abortion remains an important health issue. The informal providers who are the primary source of MA may have poor knowledge of the method and may offer inadequate or inaccurate advice on use of the method. Misuse of the method can result in women seeking treatment for true complications as well as during the normal processes of MA. An estimated 5% of all abortions are done using highly unsafe methods and performed by unskilled providers, also contributing to abortion morbidity. This paper provides new representative abortion-related morbidity measures at the national and subnational levels from a large-scale 2015 study of six Indian states—Assam, Bihar, Gujarat, Madhya Pradesh, Tamil Nadu and Uttar Pradesh. The outcomes include the number and treatment rates of women with complications resulting from induced abortion and the type of complications. The total number of women treated for abortion complications at the national level is 5.2 million, and the rate is 15.7 per 1000 women of reproductive age per year. In all six study states, a high proportion of all women receiving postabortion care were admitted with incomplete abortion from use of MA—ranging from 33% in Tamil Nadu to 65% in Assam. The paper fills an important gap by providing new evidence that can inform policy-makers and health planners at all levels and lead to improvements in the provision of postabortion care and legal abortion services—improvements that would greatly reduce abortion-related morbidity and its costs to Indian women, their families and the healthcare system.

scholarly journals COVID-19 Epidemic Forecast in Different States of India using SIR Model

2020 ◽  
Author(s):  
Mukesh Jakhar ◽  
P K Ahluwalia ◽  
Ashok Kumar
Keyword(s):  
Tamil Nadu ◽  
Reproduction Number ◽  
Epidemiological Data ◽  
Final Phase ◽  
Statistical Parameters ◽  
Indian States ◽  
Infected People ◽  
Epidemic Curve ◽  
Epidemic Size ◽  
Final Epidemic Size

The epidemiological data up to 12th May 2020 for India and its 24 states has been used to predict COVID-19 outbreak within classical SIR (Susceptible-Infected-Recovered) model. The basic reproduction number R0 of India is calculated to be 1.15, whereas for various states it ranges from 1.03 in Uttarakhand to 7.92 in Bihar. The statistical parameters for most of the states indicates the high significance of the predicted results. It is estimated that the epidemic curve flattening in India will start from the first week of July and epidemic may end in the third week of October with final epidemic size ~1,75,000. The epidemic in Kerala is in final phase and is expected to end by first week of June. Among Indian states, Maharashtra is severely affected where the ending phase of epidemic may occur in the second week of September with epidemic size of ~55,000. The model indicates that the fast growth of infection in Punjab is from 27th April 2020 to 2nd June 2020, thereafter, curve flattening will start and the epidemic is expected to finished by the first week of July with the estimated number of ~3300 infected people. The epidemic size of COVID-19 outbreak in Delhi, West Bengal, Gujrat, Tamil Nadu and Odisha can reach as large as 24,000, 18,000, 16,000, 13,000 and 11,000, respectively, however, these estimations may be invalid if large fluctuation of data occurs in coming days.

Inclusiveness and the Progress of Indian States: Evidence from Inclusive Development Index Between 2011 and 2018

2021 ◽  
pp. 097370302110086
Author(s):  
Suresh Chand Aggarwal
Keyword(s):  
Principal Component Analysis ◽  
Tamil Nadu ◽  
Uttar Pradesh ◽  
Principal Component ◽  
Inclusive Development ◽  
Indian States ◽  
Development Index ◽  
Policy Initiatives ◽  
Low Performance ◽  
Simple Average

This article examines the progress of the Indian states in inclusiveness between 2011 and 2018, based on the “Inclusive Development Index” (IDI), which includes many important aspects of the economy and people. The study has followed the broad guidelines of the Organisation for Economic Co-operation and Development—OECD (2008) to construct IDI, and it is based on two pillars of growth—the process and the outcome. The index includes 26 sub-pillars represented by 104 indicators. The weights of the indicators are obtained separately for 2011 and 2018 by applying the principal component analysis at the indicator level, and then a simple average has been computed at the sub-pillar and pillar levels to obtain the composite IDI for the 19 major Indian states. The composite IDI shows that in 2018, while the most inclusive states are Himachal Pradesh, Tamil Nadu, Maharashtra, Karnataka, Gujarat, Chhattisgarh and Kerala, the least inclusive are the states of Rajasthan, Uttar Pradesh (UP), Madhya Pradesh (MP), Assam, Jharkhand and Bihar. The performance of the states, however, varies among pillars, sub-pillars and indicators in both 2011 and 2018. The study may help the states to identify their spheres of “low” performance and learn from their “front-runner” peers, so as to take the necessary policy initiatives.

scholarly journals Does Causation hold for Panel Data in between SDP and NTR among Indian States?

2014 ◽  
Vol 10 (1) ◽  
pp. 3-15
Author(s):  
Alok Kumar Pandey
Keyword(s):  
Growth Rate ◽  
Panel Data ◽  
Tamil Nadu ◽  
Panel Cointegration ◽  
Uttar Pradesh ◽  
Domestic Product ◽  
Tax Revenue ◽  
Federal System ◽  
Indian States ◽  
Indian Economy

Inadequate revenue sources, uncontrolled growth of current expenditures and failure of central transfers to grow as fast as the states ‘own revenues’ have been the major sources of fiscal imbalance at states level. The existence of nexus in between NTR and SDP can be examined in several ways like growth rates relating to SDP and NTR, proportion of NTR to SDP, several policies relating to accelerate SDP and NTR, etc. So far as inter-state non-tax revenue and state domestic product in India is concerned, limited studies have been done. Present study tries to explore the stationarity and cointigration between Non Tax Revenue and State Domestic Product of twenty major states of Indian federal system in panel data structure for the period 1980-81 to 2011-12.The objectives of the study are: to test the panel stationary of Domestic Production and Non Tax Revenue of the major states of the Indian federal system for the period 1980-81 to 2011-12 in terms of total and growth rate and to test the panel cointegration in between SDP and NTR for the Indian federal system of twenty major states state for the period 1980-81 to 2011-12 in terms of total and growth rate. In the present study data has been taken from Handbook of Statistics on Indian Economy and State Finance for twenty major states; Andhra Pradesh, Assam, Bihar, Gujarat, Haryana, Himachal Pradesh, Jammu & Kashmir, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Manipur, Nagaland, Orissa, Punjab, Rajasthan, Tamil Nadu, Tripura and Uttar Pradesh (Handbook of Statistics on Indian Economy 2011-12).In the present study, LLC (2002) and IPS (2003) tests of stationarity have been used. Kao (1999) test of panel cointegration shows that the SDP and NTR and NTR and SDP for the twenty states for the period under study are cointegrable. The results of the study suggest that state domestic product of the states are causing the non tax revenue of the states  and  the non tax revenue of the states  are also causing state domestic product of the states for Indian federal system.

scholarly journals Awareness on Covid-19 and Covid Associated Mucormycosis During Second Wave in India

2021 ◽  
Vol 10 (39) ◽  
pp. 3480-3486
Author(s):  
Bhuvaneswari Srinivasan ◽  
Charles John Paul A. ◽  
Jayanthi Malaiyandi ◽  
Thenmozhi Mani ◽  
Kannan Kilavan Packiam ◽  
...  
Keyword(s):  
Public Awareness ◽  
Secondary Infection ◽  
Public Understanding ◽  
Indian Government ◽  
Indian States ◽  
Medical Facilities ◽  
The World ◽  
The Usa ◽  
The Uk ◽  
Second Wave

BACKGROUND COVID-19 is a viral pandemic disease reported from 222 different countries in the world. Although government agencies of various countries are responding to the suggestions of medical experts, public understanding of the nature of the disease is necessary to control the disease. Moreover, Covid associated mucormycosis (CAM) is found to emanate as a secondary infection in countries such as India. Therefore, this study was done to evaluate the awareness of COVID-19 and Covid associated mucormycosis. METHODS A questionnaire designed using google form was used to assess the public’s awareness about the airborne nature of the virus, Covid associated mucormycosis, and the government’s efforts in combating the disease. RESULTS About 690 people responded to the questions and among them 78 % were females and 21 % males. The age of the respondents ranged from 17 to 70 yrs. Nearly 69.5 % of the respondents believed that the virus was airborne. Although 89 % of respondents correctly stated that India was experiencing the second wave of COVID-19, yet majority of them could not make the same statement about other countries like the UK and the USA. Naming the mucormycosis as the black fungus had reached 88 % of the respondents. Nearly 60 % of the general public were satisfied with the government's initiatives in providing medical facilities. CONCLUSIONS The study provides the public's understanding of Covid-19 after the second wave of Covid-19 and Covid associated mucormycosis in India. The research provides inputs to the Indian government and the governments of Indian states to further raise public awareness on controlling the disease. KEY WORDS COVID -19; Airborne virus; Covid Associated Mucormycosis; Black fungus, India.

scholarly journals Impact of COVID-19 epidemic curtailment strategies in selected Indian states: an analysis by reproduction number and doubling time with incidence modelling

2020 ◽  
Author(s):  
Arun Mitra ◽  
Abhijit P Pakhare ◽  
Adrija Roy ◽  
Ankur Joshi
Keyword(s):  
Growth Rate ◽  
State Government ◽  
Doubling Time ◽  
Reproduction Number ◽  
Indian Government ◽  
Indian States ◽  
Transmission Parameters ◽  
Likelihood Approach ◽  
The Government ◽  
Novel Coronavirus

The Government of India in networks with its state government has implemented the epidemic curtailment strategies inclusive of case-isolation, quarantine and lockdown in response to ongoing novel coronavirus (COVID-19) outbreak . In this manuscript we attempt to estimate the effect of these steps across ten Indian states using crowd-sourced data. The chosen transmission parameters are -reproduction number (R0), doubling time and growth rate during the early epidemic phase (15 days into lockdown) and 30 days into lockdown (23rd April 2020) through maximum likelihood approach. The overall analysis shows the decreasing trends in reproductive numbers and growth rate (with few exceptions) and incremental doubling time. The curtailment strategies employed by the Indian government seemed to be effective in reducing the transmission parameters of the COVID-19 epidemic. The effective reproductive numbers are still higher above the threshold of 1 and the resultant absolute numbers tend to be exponentiating fundamentally. The curtailment strategy thus may take into account these findings while formulating further course of actions.

scholarly journals TERRITORIAL STRUCTURE OF INDIA IN THE CONTEXT OF ETHNIC AND CULTURAL DIVERSITY

2017 ◽  
pp. 62-68
Author(s):  
Артур Мочалов ◽  
Artur Mochalov
Keyword(s):  
Tamil Nadu ◽  
Indian Society ◽  
Indian Government ◽  
Indian States ◽  
North East ◽  
The North ◽  
Territorial Structure ◽  
Territorial Organization ◽  
Structure Of Population ◽  
Constitutional Regime

In the article the constitutional arrangements of territorial structure of India are discussed in the context of ethnic, linguistic and religious fragmentation of Indian society. The author highlights the three main approaches to territorial structurization of a plural multiethnic state: federalism, territorial autonomy, and creation of territories with special constitutional regime and reveals the mechanism of each of them on the example of India. Pluralism in approaches to territorial organization of India is stipulated by complex and extremely mosaic ethnic and cultural structure of population of the state. Federalism is applied in India mainly for accommodation of concentrated linguistic groups. Now federalism is also applied for reducing militant separatism in the Indian North-East. At the same time, federalism aims at integration of different ethnic groups into a common political and legal space. Accommodation of a range of tribes in the North-East is achieved through territorial autonomy as well. But tribal peoples living in the central part of India don’t enjoy autonomy. The lands occupied by them have a special constitutional regime (so-called “scheduled territories”) instead. It is emphasized that the choice of a certain solution for an ethnic group is often “situational” and depends on a degree of separatism. From the author’s opinion sometimes territorial solutions are implemented as compromises between the Indian government and political leaders of ethnic separatist movements. Also the article briefly describes ethnic, linguistic, and religious diversity of Indian society and its territorial fragmentation. It contains examples connected with creation of Indian States such as Tamil Nadu, Punjab and Nagaland. The information and conclusions in the article rely on materials gathered by the author during the research trip to India in summer 2016.

scholarly journals Preliminary Analysis of Excess Mortality in India During the Covid-19 Pandemic (Update August 4, 2021).

2021 ◽  
Author(s):  
Christopher T Leffler ◽  
Joseph D. Lykins ◽  
Edward Yang
Keyword(s):  
Tamil Nadu ◽  
Andhra Pradesh ◽  
Excess Mortality ◽  
West Bengal ◽  
Uttar Pradesh ◽  
Madhya Pradesh ◽  
Systems Science ◽  
Mortality Data ◽  
Indian States ◽  
All Cause Mortality

Background. As both testing for SARS Cov-2 and death registrations are incomplete or not yet available in many countries, the full impact of the Covid-19 pandemic is currently unknown in many world regions. Methods. We studied the Covid-19 and all-cause mortality in 18 Indian states (combined population of 1.26 billion) with available all-cause mortality data during the pandemic for the entire state or for large cities: Gujarat, Karnataka, Kerala, Maharashtra, Tamil Nadu, West Bengal, Delhi, Madhya Pradesh, Andhra Pradesh, Telangana, Assam, Bihar, Odisha, Haryana, Rajasthan, Himachal Pradesh, Punjab, and Uttar Pradesh. Excess mortality was calculated by comparison with available data from years 2015-2019. The known Covid-19 deaths reported by the Johns Hopkins University Center for Systems Science and Engineering for a state were assumed to be accurate, unless excess mortality data suggested a higher toll during the pandemic. Data from Uttar Pradesh were not included in the final model due to anomalies. Results. In several regions, fewer deaths were registered in 2020 than expected. The excess mortality in Mumbai (in Maharashtra) in 2020 was 137.0 / 100K. Areas in Tamil Nadu, Kolkata (in West Bengal), Delhi, Madhya Pradesh, Karnataka, Haryana, and Andhra Pradesh saw spikes in mortality in the spring of 2021. Conclusions. The pandemic-related mortality through June 30, 2021 in 17 Indian states was estimated to be 132.9 to 194.4 per 100,000 population. If these rates apply to India as a whole, then between 1.80 to 2.63 million people may have perished in India as a result of the Covid-19 pandemic by June 30, 2021. This per-capita mortality rate is similar to that in the United States and many other regions.

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