A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic

Background: With the insurgence of the COVID-19 pandemic, many people died in the past several months, and the situation is ongoing with increasing health, social, and economic panic and vulnerability. As most of the countries relying on different preventive actions to control the outcomes of COVID-...

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Main Authors: Faruq Abdulla, Zulkar Nain, Md. Karimuzzaman, Md. Moyazzem Hossain, Azizur Rahman
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:https://www.mdpi.com/1660-4601/18/9/4491
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spelling doaj-0118d69410734ec4b8005bfcfc14de722021-04-23T23:03:54ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012021-04-01184491449110.3390/ijerph18094491A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 PandemicFaruq Abdulla0Zulkar Nain1Md. Karimuzzaman2Md. Moyazzem Hossain3Azizur Rahman4Department of Statistics, Faculty of Sciences, Islamic University, Kushtia-7003, BangladeshDepartment of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Islamic University, Kushtia-7003, BangladeshDepartment of Statistics, Faculty of Mathematical and Physical Sciences, Jahangirnagar University, Savar, Dhaka-1342, BangladeshDepartment of Statistics, Faculty of Mathematical and Physical Sciences, Jahangirnagar University, Savar, Dhaka-1342, BangladeshSchool of Computing and Mathematics, Charles Sturt University, Wagga Wagga, NSW 2650, AustraliaBackground: With the insurgence of the COVID-19 pandemic, many people died in the past several months, and the situation is ongoing with increasing health, social, and economic panic and vulnerability. As most of the countries relying on different preventive actions to control the outcomes of COVID-19, it is necessary to boost the knowledge about the effectiveness of such actions so that the policymakers take their country-based appropriate actions. This study generates evidence of taking the most impactful actions to combat COVID-19. Objective: In order to generate community-based scientific evidence, this study analyzed the outcome of COVID-19 in response to different control measures, healthcare facilities, life expectancy, and prevalent diseases. Methods: It used more than a hundred countries’ data collected from different databases. We performed a comparative graphical analysis with non-linear correlation estimation using R. Results: The reduction of COVID-19 cases is strongly correlated with the earliness of preventive initiation. The apathy of taking nationwide immediate precaution measures has been identified as one of the critical reasons to make the circumstances worse. There is significant non-linear relationship between COVID-19 case fatality and number of physicians (NCC = 0.22; <em>p</em>-value ≤ 0.001), nurses and midwives (NCC = 0.17; <em>p</em>-value ≤ 0.001), hospital beds (NCC = 0.20; <em>p</em>-value ≤ 0.001), life expectancy of both sexes (NCC = 0.22; <em>p</em>-value ≤ 0.001), life expectancy of female (NCC = 0.27; <em>p</em>-value ≤ 0.001), and life expectancy of male (NCC = 0.19; <em>p</em>-value ≤ 0.001). COVID-19 deaths were found to be reduced with increased medical personnel and hospital beds. Interestingly, no association between the comorbidities and severity of COVID-19 was found excluding asthma, cancer, Alzheimer’s, and smoking. Conclusions: Enhancing healthcare facilities and early imposing the control measures could be valuable to prevent the COVID-19 pandemic. No association between COVID-19 and other comorbidities warranted further investigation at the pathobiological level.https://www.mdpi.com/1660-4601/18/9/4491COVID-19 pandemicsocial distancelockdownquarantinecase fatality ratelife expectancy
collection DOAJ
language English
format Article
sources DOAJ
author Faruq Abdulla
Zulkar Nain
Md. Karimuzzaman
Md. Moyazzem Hossain
Azizur Rahman
spellingShingle Faruq Abdulla
Zulkar Nain
Md. Karimuzzaman
Md. Moyazzem Hossain
Azizur Rahman
A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic
International Journal of Environmental Research and Public Health
COVID-19 pandemic
social distance
lockdown
quarantine
case fatality rate
life expectancy
author_facet Faruq Abdulla
Zulkar Nain
Md. Karimuzzaman
Md. Moyazzem Hossain
Azizur Rahman
author_sort Faruq Abdulla
title A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic
title_short A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic
title_full A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic
title_fullStr A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic
title_full_unstemmed A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic
title_sort non-linear biostatistical graphical modeling of preventive actions and healthcare factors in controlling covid-19 pandemic
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1661-7827
1660-4601
publishDate 2021-04-01
description Background: With the insurgence of the COVID-19 pandemic, many people died in the past several months, and the situation is ongoing with increasing health, social, and economic panic and vulnerability. As most of the countries relying on different preventive actions to control the outcomes of COVID-19, it is necessary to boost the knowledge about the effectiveness of such actions so that the policymakers take their country-based appropriate actions. This study generates evidence of taking the most impactful actions to combat COVID-19. Objective: In order to generate community-based scientific evidence, this study analyzed the outcome of COVID-19 in response to different control measures, healthcare facilities, life expectancy, and prevalent diseases. Methods: It used more than a hundred countries’ data collected from different databases. We performed a comparative graphical analysis with non-linear correlation estimation using R. Results: The reduction of COVID-19 cases is strongly correlated with the earliness of preventive initiation. The apathy of taking nationwide immediate precaution measures has been identified as one of the critical reasons to make the circumstances worse. There is significant non-linear relationship between COVID-19 case fatality and number of physicians (NCC = 0.22; <em>p</em>-value ≤ 0.001), nurses and midwives (NCC = 0.17; <em>p</em>-value ≤ 0.001), hospital beds (NCC = 0.20; <em>p</em>-value ≤ 0.001), life expectancy of both sexes (NCC = 0.22; <em>p</em>-value ≤ 0.001), life expectancy of female (NCC = 0.27; <em>p</em>-value ≤ 0.001), and life expectancy of male (NCC = 0.19; <em>p</em>-value ≤ 0.001). COVID-19 deaths were found to be reduced with increased medical personnel and hospital beds. Interestingly, no association between the comorbidities and severity of COVID-19 was found excluding asthma, cancer, Alzheimer’s, and smoking. Conclusions: Enhancing healthcare facilities and early imposing the control measures could be valuable to prevent the COVID-19 pandemic. No association between COVID-19 and other comorbidities warranted further investigation at the pathobiological level.
topic COVID-19 pandemic
social distance
lockdown
quarantine
case fatality rate
life expectancy
url https://www.mdpi.com/1660-4601/18/9/4491
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