COVID-19 second wave: District level study of concentration of confirmed cases and fatality in India

While COVID-19 vaccines have been available since December 2020 and efforts have been made to vaccinate the maximum population, a large number of people are continuing to be hesitant, prolonging the pandemic in the US. While most previous studies investigated social, economic, and demographic variables that are associated with COVID-19 vaccine hesitancy, we added ecological and technological variables to better understand the spatial variations of vaccine rates in the contiguous United States using spatial regression and geographically weighted regression (GWR) models. We aim to identify spatially varying social, ecological, and technological factors that are associated with COVID-19 vaccination rates, which can aid in identifying and strengthening the public health system and vaccination programs that can eventually facilitate and overcome vaccination hesitancy. We found six statistically significant predictors; two predictors, % Republican voters (r=-0.507, p<.001) and % Black population (r=-0.360, p<.001) were negatively correlated with the vaccination rates, whereas four remaining predictors, % Population with college degree (r=0.229, p<.001), National Risk Index Score (r=0.131, p<.001), % Population with broadband access (r=0.020, p<.001), and Health facilities per 10,000 population (r=0.424, p<.001) were positively correlated with the vaccination rates at the county level. GWR results show spatially varying relationships between vaccination rate and explanatory variables, indicating the need for regional-specific public health policy. To achieve widespread vaccination, addressing social, ecological, and technological factors will be essential. We draw particular attention to the spatial variances even among positively and negatively associated factors. This research also calls for a reexamination of existing practices, including vaccination communication and other public health policies, local and national public health organizations, telecommunications agents, and mobilization of resources by the public and private sectors.

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“…SET variables to explain the COVID vaccination acceptance/hesitancy Tsai et al 2009, Ghosh et al 2021…”

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confidence: 99%

What explains spatial variations of COVID-19 vaccine hesitancy?: a social-ecological-technological systems approach

Pallathadka¹,

Chang²,

Han³

2022

Environ. Res.: Health

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“…During the 2 nd wave, maximum catastrophes were throughout the world including India. 6 Mortality rate was also very high in India. 7 From the beginning of the 3rd wave, mortality was less, but high transmissibility of the disease is noticed.…”

Section: Discussionmentioning

confidence: 99%

Spectrum of SARSCOV2 infection with the efficacy of Covaxin and Covishield vaccines during third wave of COVID-19 pandemic: an experience of a densest state of India

Saha

2022

Int J Res Med Sci

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Background: Study was conducted to assess the trend or characteristic of SARSCOV2 infection during 3rd wave of pandemic and to compare the efficacy of Covaxin and Covishield Vaccines.Methods: This descriptive cross-sectional study was conducted with a mixed-method approach (Explanatory sequential mixed method) among the SARSCOV2 infected patients of West Bengal, India on the month of January 2022. In quantitative analysis 277 SARSCOV2 infected patients who were detected as COVID positive within January, were selected randomly from the secondary data source (collected by 20 general practitioners). In qualitative analysis, 11 patients from different categories were interviewed in-depth over the telephone to explain the quantitative data. Bivariate analysis (Mann Whitney U or Kruskal Wallis test) was used as per applicability. Kaplan Meir plot compared the efficacy of Covaxin and Covishield vaccines. Results: Most commonly presented symptom were low-grade fever (78.7%), a mild cough (41.9%), mild cold (62.4%), sore throat (41.9%), body ache (47.3%), and headache (33.2%). Few patients had experienced breathing difficulty (1.4%) and hospitalization (1.1%). Mann Whitney U test significantly (p<0.001) justified that Covaxin receivers have infected in late (median 161 days) comparison to other vaccines receivers (Covishield and Sputnik V median 129 days and 115 days respectively). This finding was also demonstrated in Kaplan Meir Plot.Conclusions: During the 3rd wave of the pandemic, SARSCOV2 infected patients commonly presented with milder symptoms, minimal hospitalization and without any case fatality. Delaying of infection has been observed more among Covaxin receivers compared to others.

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“…Apart from this, Location Quotient (LQ) is a useful tool for comparing area characteristics (Moineddin et al, 2003 ;Ghosh et al, 2021 ; Pandey et al, 2021 ) and its use in healthcare has been well established (Hendayana, 2003 ; Saravanabavan et al, 2019 ; Sukmawati, 2021 ). Most of the studies in medical geography are concerned with the description of spatial and temporal variations of a particular disease and are attempted at the regional level (Bossak & Turk, 2021 ; Balaj & Saravanabavan 2019 , 2020 ; Vinothini et al, 2021 ; Bonner et al, 2019 ).…”

Section: Database and Methodologymentioning

confidence: 99%

Spatial variation of covid-19 morbidity status and identification of risk zone in Tamil Nadu (India) during first wave

Saravanabavan

Emayavaramban

et al. 2022

GeoJournal

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COVID-19 is a pandemic disease caused by severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). The study area, Tamilnadu, is a southern state in India. The present study demonstrates the significance of mapping in identifying the risk zones of COVID-19 disease by taking a study of COVID-19 cases in Tamilnadu state. The main objective of the study was to identify the risk zone of COVID-19 disease in the first wave of Tamilnadu through geospatial mapping. Data on COVID-19 cases collected during March 2020 to March 2021 month wise in all 37 districts (unit area) of Tamilnadu in two-month interval wise was analysed. The study is based on secondary sources from respective office in Tamilnadu. Z-score techniques were used for standardizing data. Correlation analysis provided a measure of correlation between COVID-19 and working population. Location Quotient analysis aided the identification of COVID-19 risk zones in Tamilnadu. Present study indicates tertiary workers are more vulnerable to COVID-19 disease.

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COVID-19 second wave: District level study of concentration of confirmed cases and fatality in India

Cited by 17 publications

References 54 publications

What explains spatial variations of COVID-19 vaccine hesitancy?: a social-ecological-technological systems approach

What explains spatial variations of COVID-19 vaccine hesitancy?: a social-ecological-technological systems approach

Spectrum of SARSCOV2 infection with the efficacy of Covaxin and Covishield vaccines during third wave of COVID-19 pandemic: an experience of a densest state of India

Spatial variation of covid-19 morbidity status and identification of risk zone in Tamil Nadu (India) during first wave

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