scholarly journals Racial/Ethnic Heterogeneity and Rural-Urban Disparity of COVID-19 Case Fatality Ratio in the USA: a Negative Binomial and GIS-Based Analysis

2021 ◽  
Author(s):  
Ayodeji E. Iyanda ◽  
Kwadwo A. Boakye ◽  
Yongmei Lu ◽  
Joseph R. Oppong
Keyword(s):  
Negative Binomial ◽  
Case Fatality ◽  
Ethnic Heterogeneity ◽  
Case Fatality Ratio ◽  
The Usa ◽  
Racial Ethnic

scholarly journals Incidence and Case-Fatality Ratio of COVID-19 infection in relation to Tobacco Smoking, Population Density and Age Demographics in the USA: could Particulate Matter derived from Tobacco Smoking act as a Vector for COVID-19 transmission?

2020 ◽  
Author(s):  
Yves Muscat Baron
Keyword(s):  
Particulate Matter ◽  
Population Density ◽  
Tobacco Smoking ◽  
Case Fatality ◽  
The State ◽  
Smoking Ban ◽  
Age Group ◽  
Case Fatality Ratio ◽  
Significant Difference ◽  
The Usa

ABSTRACTBACKGROUNDTobacco smoking is known to increase the risk for bacterial and viral respiratory infections and this also applies to second-hand smoking. Smoking has been shown to increase the severity of COVID-19 infection and the consequent risk for intra-tracheal ventilation in smokers. Tobacco smoking exposes the user and nearby individuals to very high concentrations of particulate matter in a short period of time. Genes appertaining to COVID-19 have been found adherent to particulate matter. Particulate matter has been shown to travel beyond the social distance of 2 metres up to 10 metres. COVID-19 related mortality has been linked to elevated atmospheric levels of the particulate matter, PM2.5. The aim of the study was to observe the incidence of infection rate and case fatality ratios in the USA, comparing States with partial bans on tobacco smoking, to States with more restrictive smoking regulation, exploring a possible link between smoke-related particulate matter and COVID-19 transmission.METHODOLOGYTwo groups of USA States, differentiated by the degree of smoking legislative restrictions, had a number of variables compared. The incidence of COVID-19 infection, case-fatality ratio and testing frequency were obtained from the John Hopkins Coronavirus Resource Centre. The degree of smoking bans in the USA States was obtained from the websites of the Nonsmokers Rights Foundation. The percentage of the State population which smokes was collected from the Centres of Disease Control database. Population density, Body Mass Index and population percentages of individuals 65+/75+years were obtained from databases concerning USA demographics.RESULTSWith the available data there was no significant difference in COVID-19 testing prevalence between the partial smoking ban group and the more restrictive regulated group. The incidence of COVID-19 infection in the States with limited bans on tobacco smoking was 2046/100,000 (sd+/-827) while the infection incidence in States with more restrictive rulings on tobacco smoking was 1660/100,000 (sd+/-686) (p<0.038). The population percentage of smokers in States with minor limitations to smoking was 18.3% (sd+/-3.28), while States with greater smoking restrictions had a smoking population percentage of 15.2% (sd+/-2.68) (p<0.0006).The two populations of both groups did not differ numerically (p<0.24) and numbered 157,820,000 in the partial smoking ban group and 161,439,356 in the more restrictive group. Population density correlated significantly with the case-fatality ratio (R=0.66 p<0.0001), as did the 75+year age group (R=0.29 p<0.04). Reflecting the possibility of trans-border transmission, the smoking status of adjacent partial smoking ban States may influence the COVID-19 incidence of bordering States (e.g. Utah) even if the smoking regulations of the latter were stricter than the former.Other factors that could impact the COVID-19 pandemic in the USA such as the State case-fatality ratio, population density, population percentage with elevated body mass index and the percentage of the state population aged 65years or above did not show any significant difference between both groups of States.CONCLUSIONStates in the USA with high levels of tobacco smoking and limited regulation had significantly higher rates of COVID-19 infection incidences than States with greater smoking restrictions. Population density and the age group of 75+years, showed a positive significant correlation with the case-fatality ratio. Besides the adverse effects of tobacco smoking on pulmonary defences, it would be interesting to explore the possibility of infection transmission via coronavirus-laden particulate matter from exhaled fumes derived from tobacco smoking.

scholarly journals Do racial and ethnic disparities in following stay-at-home orders influence COVID-19 health outcomes? A mediation analysis approach

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259803
Author(s):  
Songhua Hu ◽  
Weiyu Luo ◽  
Aref Darzi ◽  
Yixuan Pan ◽  
Guangchen Zhao ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Infection Rate ◽  
Ethnic Differences ◽  
Human Mobility ◽  
Ethnic Disparities ◽  
Case Fatality ◽  
Equation Modeling ◽  
Case Fatality Ratio ◽  
Racial Ethnic ◽  
At Home

Racial/ethnic disparities are among the top-selective underlying determinants associated with the disproportional impact of the COVID-19 pandemic on human mobility and health outcomes. This study jointly examined county-level racial/ethnic differences in compliance with stay-at-home orders and COVID-19 health outcomes during 2020, leveraging two-year geo-tracking data of mobile devices across ~4.4 million point-of-interests (POIs) in the contiguous United States. Through a set of structural equation modeling, this study quantified how racial/ethnic differences in following stay-at-home orders could mediate COVID-19 health outcomes, controlling for state effects, socioeconomics, demographics, occupation, and partisanship. Results showed that counties with higher Asian populations decreased most in their travel, both in terms of reducing their overall POIs’ visiting and increasing their staying home percentage. Moreover, counties with higher White populations experienced the lowest infection rate, while counties with higher African American populations presented the highest case-fatality ratio. Additionally, control variables, particularly partisanship, median household income, percentage of elders, and urbanization, significantly accounted for the county differences in human mobility and COVID-19 health outcomes. Mediation analyses further revealed that human mobility only statistically influenced infection rate but not case-fatality ratio, and such mediation effects varied substantially among racial/ethnic compositions. Last, robustness check of racial gradient at census block group level documented consistent associations but greater magnitude. Taken together, these findings suggest that US residents’ responses to COVID-19 are subject to an entrenched and consequential racial/ethnic divide.

A Note on Estimating the Case Fatality Ratio for Novel Corona Virus Disease (Covid-19)

Coronaviruses ◽  
2020 ◽  
Vol 01 ◽  
Author(s):  
Prafulla Kumar Swain
Keyword(s):  
Confidence Interval ◽  
Graphical Representation ◽  
Virus Disease ◽  
Case Fatality ◽  
Case Fatality Ratio ◽  
Healthcare Planning ◽  
Robust Estimates ◽  
University Of Oxford ◽  
Pros And Cons ◽  
Death Cases

Background: In this paper an attempt has been made to estimate the Case Fatality Ratio (CFR) for coronavirus disease of India and few selected countries. and Also, highlighted the pros and cons of obtaining crude and adjusted CFR of COVID-19 pandemic. Material and Methods: Data extracted from WHO situation report and University of Oxford website have been used for this analysis. The CFR and its 95% confidence interval were computed, trend and bar plot was used for graphical representation. Results: The worldwide crude CFR stands 6.73% (95% CI 6.69 to 6.76) based on 21, 83, 877 confirmed and 1,46,872 death cases(as on 17th April,2020). Belgium was highest CFR 13.95% as compared to others. However, India’s CFR was found to be around 3.26% (as on 17th April, 2020). Conclusion: In conclusion, the estimation and interpretation of CFR is critical in response to ongoing COVID-19. The initial CFR estimates are subject to change, still it is useful for healthcare planning over the coming months. Moreover, the precise and robust estimates of CFR will be available only at the end of the epidemic.

Covid-19 Cases in India: A Visual Exploratory Data Analysis Model (Preprint)

2020 ◽  
Author(s):  
Jayesh S
Keyword(s):  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Case Fatality ◽  
Public Health Emergency ◽  
Virus Spread ◽  
Analysis Model ◽  
Case Fatality Ratio ◽  
First Case ◽  
Exploratory Data ◽  
The Government

UNSTRUCTURED Covid-19 outbreak was first reported in Wuhan, China. The deadly virus spread not just the disease, but fear around the globe. On January 2020, WHO declared COVID-19 as a Public Health Emergency of International Concern (PHEIC). First case of Covid-19 in India was reported on January 30, 2020. By the time, India was prepared in fighting against the virus. India has taken various measures to tackle the situation. In this paper, an exploratory data analysis of Covid-19 cases in India is carried out. Data namely number of cases, testing done, Case Fatality ratio, Number of deaths, change in visits stringency index and measures taken by the government is used for modelling and visual exploratory data analysis.

scholarly journals Association between fatality rate of COVID-19 and selenium deficiency in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Viral Infections ◽  
Case Fatality ◽  
Selenium Deficiency ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Fatality Rate ◽  
Selenium Content ◽  
Individual Level ◽  
Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

scholarly journals Correlates of SARS-CoV-2 Variants on Deaths, Case Incidence and Case Fatality Ratio among the Continents for the Period of 1 December 2020 to 15 March 2021

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 1061
Author(s):  
Wajdy J. Al-Awaida ◽  
Baker Jawabrah Al Hourani ◽  
Samer Swedan ◽  
Refat Nimer ◽  
Foad Alzoughool ◽  
...  
Keyword(s):  
Negative Correlation ◽  
Significant Positive Correlation ◽  
Vaccine Development ◽  
Case Fatality ◽  
Significant Negative Correlation ◽  
Reference Sequence ◽  
Genome Sequences ◽  
Positive Correlation ◽  
Case Fatality Ratio ◽  
Epidemiological Surveys

The outbreak of coronavirus disease 2019 (COVID-19), by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has quickly developed into a worldwide pandemic. Mutations in the SARS-CoV-2 genome may affect various aspects of the disease including fatality ratio. In this study, 553,518 SARS-CoV-2 genome sequences isolated from patients from continents for the period 1 December 2020 to 15 March 2021 were comprehensively analyzed and a total of 82 mutations were identified concerning the reference sequence. In addition, associations between the mutations and the case fatality ratio (CFR), cases per million and deaths per million, were examined. The mutations having the highest frequencies among different continents were Spike_D614G and NSP12_P323L. Among the identified mutations, NSP2_T153M, NSP14_I42V and Spike_L18F mutations showed a positive correlation to CFR. While the NSP13_Y541C, NSP3_T73I and NSP3_Q180H mutations demonstrated a negative correlation to CFR. The Spike_D614G and NSP12_P323L mutations showed a positive correlation to deaths per million. The NSP3_T1198K, NS8_L84S and NSP12_A97V mutations showed a significant negative correlation to deaths per million. The NSP12_P323L and Spike_D614G mutations showed a positive correlation to the number of cases per million. In contrast, NS8_L84S and NSP12_A97V mutations showed a negative correlation to the number of cases per million. In addition, among the identified clades, none showed a significant correlation to CFR. The G, GR, GV, S clades showed a significant positive correlation to deaths per million. The GR and S clades showed a positive correlation to number of cases per million. The clades having the highest frequencies among continents were G, followed by GH and GR. These findings should be taken into consideration during epidemiological surveys of the virus and vaccine development.

scholarly journals COVID-19-related state-wise racial and ethnic disparities across the USA: an observational study based on publicly available data from The COVID Tracking Project

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e048006
Author(s):  
Zhaoying Xian ◽  
Anshul Saxena ◽  
Zulqarnain Javed ◽  
John E Jordan ◽  
Safa Alkarawi ◽  
...  
Keyword(s):  
Asian American ◽  
Alaska Native ◽  
Ethnic Disparities ◽  
Relative Difference ◽  
Ethnic Composition ◽  
Regional Patterns ◽  
Population Proportion ◽  
Asian Populations ◽  
The Usa ◽  
Racial Ethnic

ObjectiveTo evaluate COVID-19 infection and mortality disparities in ethnic and racial subgroups in a state-wise manner across the USA.MethodsPublicly available data from The COVID Tracking Project at The Atlantic were accessed between 9 September 2020 and 14 September 2020. For each state and the District of Columbia, % infection, % death, and % population proportion for subgroups of race (African American/black (AA/black), Asian, American Indian or Alaska Native (AI/AN), and white) and ethnicity (Hispanic/Latino, non-Hispanic) were recorded. Crude and normalised disparity estimates were generated for COVID-19 infection (CDI and NDI) and mortality (CDM and NDM), computed as absolute and relative difference between % infection or % mortality and % population proportion per state. Choropleth map display was created as thematic representation proportionate to CDI, NDI, CDM and NDM.ResultsThe Hispanic population had a median of 158% higher COVID-19 infection relative to their % population proportion (median 158%, IQR 100%–200%). This was followed by AA, with 50% higher COVID-19 infection relative to their % population proportion (median 50%, IQR 25%–100%). The AA population had the most disproportionate mortality, with a median of 46% higher mortality than the % population proportion (median 46%, IQR 18%–66%). Disproportionate impact of COVID-19 was also seen in AI/AN and Asian populations, with 100% excess infections than the % population proportion seen in nine states for AI/AN and seven states for Asian populations. There was no disproportionate impact in the white population in any state.ConclusionsThere are racial/ethnic disparities in COVID-19 infection/mortality, with distinct state-wise patterns across the USA based on racial/ethnic composition. There were missing and inconsistently reported racial/ethnic data in many states. This underscores the need for standardised reporting, attention to specific regional patterns, adequate resource allocation and addressing the underlying social determinants of health adversely affecting chronically marginalised groups.

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