Spatial mapping of COVID-19 for Indian states using Principal Component Analysis

Joshua, Vasna; Grace, Jamie; Emmanuel, J. Godwin; Satish, S; Arumugam, Elangovan

doi:10.1016/j.cegh.2020.100690

Cited by 5 publications

(4 citation statements)

References 2 publications

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“…PCA is frequently used to study natural disaster behavior, 46 and it has the potential to identify common COVID-19 factors globally. [47][48][49] We considered the COVID-19 pandemic as a hazard in this study. Therefore, we have used the IPCC's 2007 hazard framework to assess Asian countries' vulnerability to COVID-19, incorporating 16 variables that quantify each country's vulnerability.…”

Section: Discussionmentioning

confidence: 99%

COVID-19 Vulnerability Mapping of Asian Countries

Sarkar

Morshed

Chakraborty

2022

Disaster med. public health prep.

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Objective: The objective of this study is to map vulnerability of Asian countries to the COVID-19 pandemic. Method: According to the Intergovernmental Panel on Climate Change (IPCC) 2007 framework for natural hazards, vulnerability is a function of exposure, sensitivity, and adaptive capacity. From an extensive literature review, we identified 16 socioeconomic, meteorological, environmental, and health factors that influence coronavirus disease 2019 (COVID-19) cases and deaths. The underlying factors of vulnerability were identified using principal component analysis. Results: Our findings indicate that the percentage of the urban population, obesity rate, air connectivity, and the population aged 65 and over, diabetes prevalence, and PM2.5 levels all contributed significantly to COVID-19 sensitivity. Subsequently, governance effectiveness, human development index (HDI), vaccination rate, and life expectancy at birth, and gross domestic product (GDP) all had a positive effect on adaptive capacity. The estimated vulnerability was corroborated by a Pearson correlation of 0.615 between death per million population and vulnerability. Conclusion: This study demonstrates the application of universal indicators for assessing pandemic vulnerability for informed policy interventions such as the COVAX vaccine roll-out priority. Despite data limitations and a lack of spatiotemporal analysis, this study’s methodological framework allows for ample data incorporation and replication.

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Section: Discussionmentioning

confidence: 99%

COVID-19 Vulnerability Mapping of Asian Countries

Sarkar

Morshed

Chakraborty

2022

Disaster med. public health prep.

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“…The second group is associated with studies that analyze exposure factors to COVID-19 in different geographic areas (Martines et al, 2021 ; Weinstein et al, 2021 ). Finally, the third group covers studies that map the areas of exposure to COVID-19 from demographic and socioeconomic composite indicators (Acharya et al, 2020 ; Dlamini et al, 2020 ; Nicodemo et al, 2020 ; Joshua et al, 2021 ; Karácsonyi et al, 2021 ; Sarkar & Chouhan, 2021 ; Yigitcanlar et al, 2021 ).…”

Section: Multidimensional Analysis Of Covid-19mentioning

confidence: 99%

Factors that most expose countries to COVID-19: a composite indicators-based approach

et al. 2021

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Studies carried out in different countries correlate social, economic, environmental, and health factors with the number of cases and deaths from COVID-19. However, such studies do not reveal which factors make one country more exposed to COVID-19 than other. Based on the composite indicators approach, this research identifies the factors that most impact the number of cases and deaths of COVID-19 worldwide and measures countries’ exposure to COVID-19. Three composite indicators of exposure to COVID-19 were constructed through Principal Component Analysis, Simple Additive Weighting, and k-means clustering. The number of cases and deaths from COVID-19 is strongly correlated ( R > 0.60) with composite indicator scores and moderately concordant ( K > 0.4) with country clusters. Factors directly or indirectly associated with the age of the population are the ones that most expose countries to COVID-19. The population of countries most exposed to COVID-19 is 12 years older on average. The proportion of the elderly population in these countries is at least twice that of countries less exposed to COVID-19. Factors that can increase the population’s life expectancy, such as Gross Domestic Product per capita and the Human Development Index, are four times and 1.3 times higher in more exposed countries to COVID-19. Providing better living conditions increases both the population’s life expectancy and the country’s exposure to COVID-19.

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“…In late 2019 the world witnessed the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has out broken from Wuhan, China, to the rest of the world in a short period, and as of February 03, 2022, 448 million confirmed cases and 6 million deaths have been reported worldwide [5] , [6] . During the spread of the virus to 210 countries, in March 2020, the World Health Organization (WHO) declared the infection a pandemic [7] .…”

Section: Introductionmentioning

confidence: 99%