Geographical Appraisal of COVID-19 in West Bengal, India (original) (raw)

Geospatial Distribution and Trend Analysis of Corona Pandemic (Covid-19) in West Bengal, India

Novel Corona Virus or COVID-19 a highly infectious disease was originated in Wuhan city of Hubei province of China and rapidly spread across the world. This global pandemic creates a major challenge in respect to public health infrastructures around the world. This study has prepared on West Bengal, which is located in the eastern part of India. The aim of the study is to analyze the trends of outbreak and spatial distribution of COVID-19 pandemic with the help of spatial analysis tools of GIS software. Monitoring active ties using GIS spatial analysis is very important to control such as a COVID-19 virus spreading problem. Currently 2377 confirmed cases of COVID-19 have been reported in the state. Out of which 1394 are active patients, 768 patients have cured and discharged, 143 patients died and 72 patients died due to Comorbidity. There has been increasing trends found in all the attributes, i.e. confirmed cases, Cases load, recovery, death and test per million etc. of COVID-19 in last 8 weeks. Only the delta rates have declined over the last few weeks, which indicate that the cases of COVID-19 will be declined as compared to cured or recovered cases in near future. The prediction IDW maps of COVID-19 have shown that the area under extremely affected and dangerous lies in few districts namely Kolkata, Howrah, part of Hooghly, North and South 24 Parganas in case confirmed cases, active cases and deaths. These areas are also under the highly healing zone in respect to number of cured patients.

Spatial Pattern of Covid-19 in Relation to Population Density: A Case Study in Assam (India)

Current World Environment, 2022

Since the time of occurrence of first wave of COVID-19, its study from multi dimensional directions becomes visible across academic disciplines globally. In this paper we analyze the correlation between spread of corona virus and population density. The study is undertaken at district level in the state of Assam, (North-eastern India), considering the confirmed COVID-19 cases (during the first wave) and population density of the districts. We use the Karl Pearson's correlation method for assessing the level of correlation, which is further tested with t-test application. A cartographic representation is also constructed using GIS platform to observe the COVID-19 spatial incidence in relation to population density pattern. We have observed that the number of infection and population density at district level have a positive relationship with R value 0.641, which can be considered statistically significant.

Exploring spatial distribution pattern of COVID-19 incidence in Telangana state, India

01-04-2022, 2022

The outbreak of coronavirus (COVID-19) disease is essentially considered as a severe global public health disaster and the biggest challenge that the people have met since the Second World War. The main aim of present study is to comprehend the frequency trends of total confirmed cases, currently active cases, total recovery cases, deceased rate, and their distribution pattern in the mainland of Telangana, India. As demonstrated in this study, during the first lockdown, the slopes of the confirmed cases, active cases, and mortality cases were kept increasing. In the middle of the potential second-term lockdown, the daily active incidence trend was progressively declined while the growth of the recovery rate was steadily increased. Results describe that the strict implementation of the lockdown procedure has tremendously built confidence in order to flattering the COVID-19 epidemic curve. Moreover, spatial distribution of confirmed cases of COVID-19 indicates that higher cases were recorded in Hyderabad and its surrounding areas of the investigated region. The outcome of this study will assuredly be helpful for executing certain precautionary measures and definite health policies to regulate the spread of COVID-19 in Telangana, India.

Spatial Distribution of Covid-19 Data in India by Using Geospatial Technologies

Journal of Remote Sensing, Environmental Science & Geotechnical Engineering Volume 5 Issue 2, 2020

A new Corona virus emerged in Wuhan, China, in December 2019 and spread to all the world countries. More than 200 countries with territories are affecting by the Coronavirus. As of 11 th June 2020, epidemic Coronavirus caused more than 77lakhs people infected and more than four lakhs of deaths globally. More than 3lakhs people are affected and around 9 thousand were died due to this COVID-19 in India. At present, the number of infections and death cases is drastically increasing daily in India and globally. The COVID-19 is seriously threatening health, life, production, social economy and relations with other nations. In this connection, geospatial technologies are playing a vital role in many aspects COVID-19 today. Spatial analysis of GIS is highly useful in tracking, predicting and controlling this pandemic virus. GIS is capable of data preparation, generation of models, analysis and output generation Although to survive against the virus, the objectives are to find technical methods to improve and find accurate data for sustainable planning. The focus of research is to analyze and generate a spatial distribution map of India by interpolating the positive cases of various states of the country using

Spatial analysis of prevalence of disease in greater Hyderabad: A case study of pandemic covid-19

The spatial analysis of prevalence of disease focus on the disease prone areas. The Hyderabad city is the one of Metros in the India, which is evident of highest number of Pandemic Corona Virus Disease 2019 (COVID-19) cases. Spatial analysis of COVID-19 gives the understanding of pattern of disease spread in Hyderabad. Most of the cases in Telangana State are reported from Grater Hyderabad only. In this paper an attempt is made to study the spatial distribution pattern of Pandemic COVID-19 in Greater Hyderabad, in the months of April 2020 and July 2020. The spatial distribution is presented using GIS (Geographical Information System).The study revealed that, in the southeastern part of the city, Hayath Nagar circle in L.B Nagar zone is not being recorded any COVID-19 cases.

A spatial exploratory study on COVID-19 disaster - current outbreak in Tamil Nadu, India

Turkish Journal of Physiotherapy and Rehabilitation, 2021

Background: The COVID -19 which is also called as Novel Coronavirus Pneumonia (NCP) is a serious disease which got emerged on December 2019 in China. In the context of India, the first case was diagnosed and reported in the state of Kerala during the month of January 2020.The distribution of virus inflated gradually to the different parts of the country. The overall cases recorded in India surged more than 600nos till March 2019. The concept of medical geography is an emerging tool to identify the spatial distribution, pattern, concentration of the virus spread and also it determines health status of the local community. The main aim of the current research work is to figure out the prevailing situation and further to delineate the COVID Vulnerability Zone (CVZ) for the districts of Tamil Nadu. Methods: The researchers in the current study categorized the non-spatial data as COVID cases (Till March 28th, 2020). COVID -19 quarantine follow-up cases, Population data, COVID-19 testing ...

Geospatial Distribution of District Data in Delhi and Telangana: A Comparative Study of Covid-19

In India, Covid-19 spread has set panic in the mindset of humans. In this study, the focus is on the districts of Delhi and Telangana. Delhi is third leading state with almost 1,07,051 confirmed cases (as on July 10, 2020) of Covid-19. Geoinformatics is the tool used to map hotspot areas in Delhi with Central Delhi (184) cases and Telangana where Hyderabad stands with 24,710 cases. In this study, coronavirus affected areas are mapped using GIS to monitor the viral infected areas within each city. Thus, helps to take the preventive measures for the virus spread. Thereby determines containment zone areas and integrates with socio-demographic data for assessment and making necessary action plan during lockdown situation. Spatial data is an excellent way for measuring the impact of Covid-19 pandemic disease over all the affected regions. In fact, it gives the glance of total visualization at a time over the whole world. On comparison of both curves of day-wise increase of Delhi and Telangana, Telangana state does not flattened as Delhi curve.

Patterns of Spatial Variations of the Determinants of COVID-19 Cases in India

Indian Journal of Spatial Sience, Spring Issue, 12(1), 2021

The paper tries to analyse the spatial distribution of Covid-19 cases in India and the fundamental determinants behind this pattern. Some pre-identified factors that are responsible for rising infection rate are analysed thoroughly through geographically weighted regression to identify the level of the association behind the spatial variation of Covid-19 cases in Indian states. Migration and international mobility are having a strong positive relationship with the rising of Covid-19 cases in north Indian states. In contrast, Chronic morbidity is the most influential factor in shaping the trajectories of infection in southern states of India. The major proportion of cases was confined within the Urban and metropolitan cities in India indicating the correlation between the level of urbanization and population density with raising the cases; which is highly significant for Delhi-NCR region and Mumbai metropolitan region. On the contrary, irrespective of an increased level of immunization it is not positively associated in arresting the rate of infection of Covid-19.

Distribution and Trend Analysis of COVID-19 in India: Geospatial Approach

Journal of Geographical Studies

COVID-19 Coronavirus is now one of the most contagious diseases of the recently discovered and spread across the China in 2019 and has received global attention. In most COVID-19-infected individuals, respiratory symptoms should be mild to moderate and improve without the need for medical care. The risk of serious disease is higher for senior citizens and people with serious health problems, such as heart disease, diabetes, severe respiratory disease, and cancer. The World Health Organization (WHO) has formally declared the outbreak of COVID-19 to be a global pandemic. As on 11th April 2020 in India the largest number of persons testing positive for COVID-19 since the outbreak earlier month with samples of people, mostly contacts of already confirmed patients, rendering positive. In India total confirmed cases 7364, 633 are cured/discharged, with 240 deaths had been reported by the Ministry of Health and Family Welfare Government of India. The aim of the research is to analyze the s...