A Statistical Analysis of Excess Mortality Mean at Covid-19 in 2020-2021
When it comes to making assessments about public health, the mortality rate is a very important factor. The COVID-19 pandemic has exacerbated well-known biases that affect the measurement of mortality, which varies with time and place. The COVID-19 pandemic took the world off surveillance, and since...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
The Scientific Association for Studies and Applied Research
2023-11-01
|
| Series: | Computational Journal of Mathematical and Statistical Sciences |
| Subjects: | |
| Online Access: | https://cjmss.journals.ekb.eg/article_318541.html |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850065036417957888 |
|---|---|
| author | Md Nurul Raihen Sultana Akter Fariha Tabassum Farjana Jahan Shakera Begum |
| author_facet | Md Nurul Raihen Sultana Akter Fariha Tabassum Farjana Jahan Shakera Begum |
| author_sort | Md Nurul Raihen |
| collection | DOAJ |
| description | When it comes to making assessments about public health, the mortality rate is a very important factor. The COVID-19 pandemic has exacerbated well-known biases that affect the measurement of mortality, which varies with time and place. The COVID-19 pandemic took the world off surveillance, and since the outbreak, it has caused damage that many would have thought unthinkable in the present era. By estimating excess mortality for 2020 and 2021, we provide a thorough and consistent evaluation of the COVID-19 pandemic's effects. Excess mortality is a term used in epidemiology and public health to describe the number of fatalities from all causes during a crisis that exceeds what would be expected under 'normal' circumstances. Excess mortality has been used for thousands of years to estimate health emergencies and pandemics like the 1918 "Spanish Flu"6. Excess mortality occurs when actual deaths exceed previous data or recognized patterns. It could demonstrate how a pandemic affected mortality rate. The estimates of excess mortality presented in this research are generated using the procedure, data, and methods described in detail in the methods section and briefly summarized in this study. We explored different regression models in order to find the most effective factor for our estimates. We predict the pandemic period all-cause deaths in locations lacking complete reported data using the Binary logistic regression, and Probit regression analysis count framework. Standardized residual plots, AIC, and Variance Inflation Factor (VIF) after checking all of those, we found some significant predictors from our choosing model , and the coefficient of all predictors gave the information that some factors have positive effect, and some has a negative effect at excess mortality at COVID-19 (2020-2021).
|
| format | Article |
| id | doaj-art-4298844fffdd4ea68165e04b94fb632c |
| institution | DOAJ |
| issn | 2974-3435 2974-3443 |
| language | English |
| publishDate | 2023-11-01 |
| publisher | The Scientific Association for Studies and Applied Research |
| record_format | Article |
| series | Computational Journal of Mathematical and Statistical Sciences |
| spelling | doaj-art-4298844fffdd4ea68165e04b94fb632c2025-08-20T02:49:06ZengThe Scientific Association for Studies and Applied ResearchComputational Journal of Mathematical and Statistical Sciences2974-34352974-34432023-11-012222323910.21608/CJMSS.2023.229207.1014A Statistical Analysis of Excess Mortality Mean at Covid-19 in 2020-2021Md Nurul Raihen0Sultana Akter 1Fariha Tabassum2Farjana Jahan3Shakera Begum4Department of Mathematics and Computer Science, Fontbonne University, Saint Louis, MO, USADepartment of Statistics, Western Michigan University, Kalamazoo, 49006, MI, USADepartment of Sociology, Western Michigan University, Kalamazoo, 49006, MI, USADepartment of Statistics, Western Michigan University, Kalamazoo, 49006, MI, USADepartment of Statistics, Western Michigan University, Kalamazoo, 49006, MI, USAWhen it comes to making assessments about public health, the mortality rate is a very important factor. The COVID-19 pandemic has exacerbated well-known biases that affect the measurement of mortality, which varies with time and place. The COVID-19 pandemic took the world off surveillance, and since the outbreak, it has caused damage that many would have thought unthinkable in the present era. By estimating excess mortality for 2020 and 2021, we provide a thorough and consistent evaluation of the COVID-19 pandemic's effects. Excess mortality is a term used in epidemiology and public health to describe the number of fatalities from all causes during a crisis that exceeds what would be expected under 'normal' circumstances. Excess mortality has been used for thousands of years to estimate health emergencies and pandemics like the 1918 "Spanish Flu"6. Excess mortality occurs when actual deaths exceed previous data or recognized patterns. It could demonstrate how a pandemic affected mortality rate. The estimates of excess mortality presented in this research are generated using the procedure, data, and methods described in detail in the methods section and briefly summarized in this study. We explored different regression models in order to find the most effective factor for our estimates. We predict the pandemic period all-cause deaths in locations lacking complete reported data using the Binary logistic regression, and Probit regression analysis count framework. Standardized residual plots, AIC, and Variance Inflation Factor (VIF) after checking all of those, we found some significant predictors from our choosing model , and the coefficient of all predictors gave the information that some factors have positive effect, and some has a negative effect at excess mortality at COVID-19 (2020-2021). https://cjmss.journals.ekb.eg/article_318541.htmlcovid-19excess mortalitypandemicprobit regressionlogistic regression |
| spellingShingle | Md Nurul Raihen Sultana Akter Fariha Tabassum Farjana Jahan Shakera Begum A Statistical Analysis of Excess Mortality Mean at Covid-19 in 2020-2021 Computational Journal of Mathematical and Statistical Sciences covid-19 excess mortality pandemic probit regression logistic regression |
| title | A Statistical Analysis of Excess Mortality Mean at Covid-19 in 2020-2021 |
| title_full | A Statistical Analysis of Excess Mortality Mean at Covid-19 in 2020-2021 |
| title_fullStr | A Statistical Analysis of Excess Mortality Mean at Covid-19 in 2020-2021 |
| title_full_unstemmed | A Statistical Analysis of Excess Mortality Mean at Covid-19 in 2020-2021 |
| title_short | A Statistical Analysis of Excess Mortality Mean at Covid-19 in 2020-2021 |
| title_sort | statistical analysis of excess mortality mean at covid 19 in 2020 2021 |
| topic | covid-19 excess mortality pandemic probit regression logistic regression |
| url | https://cjmss.journals.ekb.eg/article_318541.html |
| work_keys_str_mv | AT mdnurulraihen astatisticalanalysisofexcessmortalitymeanatcovid19in20202021 AT sultanaakter astatisticalanalysisofexcessmortalitymeanatcovid19in20202021 AT farihatabassum astatisticalanalysisofexcessmortalitymeanatcovid19in20202021 AT farjanajahan astatisticalanalysisofexcessmortalitymeanatcovid19in20202021 AT shakerabegum astatisticalanalysisofexcessmortalitymeanatcovid19in20202021 AT mdnurulraihen statisticalanalysisofexcessmortalitymeanatcovid19in20202021 AT sultanaakter statisticalanalysisofexcessmortalitymeanatcovid19in20202021 AT farihatabassum statisticalanalysisofexcessmortalitymeanatcovid19in20202021 AT farjanajahan statisticalanalysisofexcessmortalitymeanatcovid19in20202021 AT shakerabegum statisticalanalysisofexcessmortalitymeanatcovid19in20202021 |