Selected article for: "future research and high mortality"

Author: Sannigrahi, Srikanta; Pilla, Francesco; Basu, Bidroha; Basu, Arunima Sarkar; Molter, Anna
Title: Examining the association between socio-demographic composition and COVID-19 fatalities in the European region using spatial regression approach
  • Cord-id: 8u4c2xqg
  • Document date: 2020_8_1
  • ID: 8u4c2xqg
    Snippet: The socio-demographic factors have a substantial impact on the overall casualties caused by the Coronavirus (COVID-19). In this study, the global and local spatial association between the key socio-demographic variables and COVID-19 cases and deaths in the European regions were analyzed using the spatial regression models. A total of 31 European countries were selected for modelling and subsequent analysis. From the initial 28 demographic variables, a total of 2 (for COVID-19 cases) and 3 (for C
    Document: The socio-demographic factors have a substantial impact on the overall casualties caused by the Coronavirus (COVID-19). In this study, the global and local spatial association between the key socio-demographic variables and COVID-19 cases and deaths in the European regions were analyzed using the spatial regression models. A total of 31 European countries were selected for modelling and subsequent analysis. From the initial 28 demographic variables, a total of 2 (for COVID-19 cases) and 3 (for COVID-19 deaths) key variables were filtered out for the regression modelling. The spatially explicit regression modelling and mapping were done using four spatial regression models such as Geographically Weighted Regression (GWR), Spatial Error Model (SEM), Spatial Lag Model (SLM), and Ordinary Least Square (OLS). Additionally, Partial Least Square (PLS) and Principal Component Regression (PCR) was performed to estimate the overall explanatory power of the regression models. For the COVID cases, the local R(2) values, which suggesting the influences of the selected demographic variables on COVID cases and death, were found highest in Germany, Austria, Slovenia, Switzerland, Italy. The moderate local R(2) was observed for Luxembourg, Poland, Denmark, Croatia, Belgium, Slovakia. The lowest local R(2) value for COVID-19 cases was accounted for Ireland, Portugal, United Kingdom, Spain, Cyprus, Romania. Among the 2 variables, the highest local R(2) was calculated for income (R(2) = 0.71), followed by poverty (R(2) = 0.45). For the COVID deaths, the highest association was found in Italy, Croatia, Slovenia, Austria. The moderate association was documented for Hungary, Greece, Switzerland, Slovakia, and the lower association was found in the United Kingdom, Ireland, Netherlands, Cyprus. This suggests that the selected demographic and socio-economic components, including total population, poverty, income, are the key factors in regulating overall casualties of COVID-19 in the European region. This study found that the demographic composition, as well as key socio-economic determinants of the country, predominantly controls the high rate of mortality and casualties caused by COVID-19. In this study, the influence of the other controlling factors, such as environmental conditions, socio-ecological status, climatic extremity, etc. have not been considered. This could be the scope for future research.

    Search related documents:
    Co phrase search for related documents
    • accuracy robustness and acute respiratory: 1, 2, 3
    • accuracy robustness and local global: 1
    • acute respiratory and adequate medicine: 1
    • acute respiratory and living area: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
    • acute respiratory and living conditions: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • acute respiratory and local association: 1, 2, 3, 4
    • acute respiratory and local correlation: 1, 2, 3
    • acute respiratory and local global: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • acute respiratory distress syndrome and living area: 1
    • acute respiratory distress syndrome and living conditions: 1
    • acute respiratory distress syndrome and local global: 1, 2
    • adequate medicine and living conditions: 1
    • living area and local global: 1
    • living conditions and local association: 1
    • living conditions and local global: 1, 2, 3, 4, 5