The Moderating Effect of Demographic and Environmental Factors in the Spread and Mortality Rate of COVID-19 during Peak and Stagnant Periods

2020 ◽  
Vol 35 (2) ◽  
pp. 77-105
Author(s):  
Soonae Park ◽  
Yongho Cha
Keyword(s):  
Mortality Rate ◽  
Environmental Factors ◽  
Case Fatality Rate ◽  
Explanatory Power ◽  
Negative Relationship ◽  
Case Fatality ◽  
Statistical Correlation ◽  
Population Exposure ◽  
Fatality Rate ◽  
Hospital Beds

This study explores the demographic and environmental factors affecting the spread and mortality rate of COVID-19 in countries around the world. We performed a hierarchical regression by adding interaction terms to such factors as the proportion of people aged 65 or older, the ratio of foreign migrants, the number of hospital beds available, population density, the Gini index, smoking rate among the population, mean population exposure to PM2.5 and NOx emissions in each country. We found that countries with a higher proportion of people over 65 had a higher rate of confirmed positive cases, a higher mortality rate, and a higher case fatality rate. We also found that there was a positive and significant statistical correlation between the number of foreign migrants in a country and the rate of confirmed positive COVID19 cases and the number of deaths but an inverse relationship between this variable and the case fatality rate. We found a negative relationship between the number of hospital beds and mortality and case fatality rate while but a positive relationship between the level of nitrogen oxides in the environment and the rate of confirmed positive cases, the mortality rate, and the case fatality rate, although there was no such relationship for ultrafine dust. Overall, the variables affecting the spread and mortality of COVID-19 in June, during which it was expected there would be a lull after the virus had reached its peak in May, were similar to those affecting its spread and mortality in May, but the model’s explanatory power and significance were higher in May.

scholarly journals Risk factors for incidence and case-fatality rates of healthcare-associated infections: a 20-year follow-up of a hospital-based cohort

2015 ◽  
Vol 144 (1) ◽  
pp. 198-206 ◽  
Author(s):  
R.-F. WANG ◽  
S.-H. SHEN ◽  
A. M.-F. YEN ◽  
T.-L. WANG ◽  
T.-N. JANG ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mortality Rate ◽  
Incidence Rate ◽  
Case Fatality Rate ◽  
Tertiary Care ◽  
Case Fatality ◽  
Healthcare Associated Infections ◽  
Fatality Rate ◽  
Infection Site ◽  
Healthcare Associated

SUMMARYInformation is lacking on the integrated evaluation of mortality rates in healthcare-associated infections (HAIs). Our aim was to differentiate the risk factors responsible for the incidence from those for the case-fatality rates in association with HAIs. We therefore examined the time trends of both incidence and case-fatality rates over a 20-year period at a tertiary-care teaching medical centre in Taiwan and the mortality rate was expressed as the product of the incidence rate and the case-fatality rate. During the study period the overall mortality rate fell from 0·46 to 0·32 deaths/1000 patient-days and the incidence rate fell from 3·41 to 2·31/1000 patient-days, but the case-fatality rate increased marginally from 13·5% to 14·0%. The independent risk factors associated with incidence of HAIs were age, gender, infection site, admission type, and department of hospitalization. Significant prognostic factors for HAI case-fatality were age, infection site, intensive care, and clinical department. We conclude that the decreasing trend for the HAI mortality rate was accompanied by a significant decline in the incidence rate and this was offset by a slightly increasing trend in the case-fatality rate. This deconstruction approach could provide further insights into the underlying complex causes of mortality for HAIs.

scholarly journals SEIHCRD Model for COVID-19 spread scenarios, disease predictions and estimates the basic reproduction number, case fatality rate, hospital, and ICU beds requirement

2020 ◽  
Author(s):  
Avaneesh Singh ◽  
Manish Kumar Bajpai
Keyword(s):  
Basic Reproduction Number ◽  
Case Fatality Rate ◽  
Reproduction Number ◽  
Case Fatality ◽  
The United States ◽  
Fatality Rate ◽  
Hospital Beds ◽  
The Impact ◽  
Over Time ◽  
The Basic Reproduction Number

We have proposed a new mathematical method, SEIHCRD-Model that is an extension of the SEIR-Model adding hospitalized and critical twocompartments. SEIHCRD model has seven compartments: susceptible (S), exposed (E), infected (I), hospitalized (H), critical (C), recovered (R), and deceased or death (D), collectively termed SEIHCRD. We have studied COVID- 19 cases of six countries, where the impact of this disease in the highest are Brazil, India, Italy, Spain, the United Kingdom, and the United States. SEIHCRD model is estimating COVID-19 spread and forecasting under uncertainties, constrained by various observed data in the present manuscript. We have first collected the data for a specific period, then fit the model for death cases, got the values of some parameters from it, and then estimate the basic reproduction number over time, which is nearly equal to real data, infection rate, and recovery rate of COVID-19. We also compute the case fatality rate over time of COVID-19 most affected countries. SEIHCRD model computes two types of Case fatality rate one is CFR daily and the second one is total CFR. We analyze the spread and endpoint of COVID-19 based on these estimates. SEIHCRD model is time-dependent hence we estimate the date and magnitude of peaks of corresponding to the number of exposed cases, infected cases, hospitalized cases, critical cases, and the number of deceased cases of COVID-19 over time. SEIHCRD model has incorporated the social distancing parameter, different age groups analysis, number of ICU beds, number of hospital beds, and estimation of how much hospital beds and ICU beds are required in near future.

scholarly journals Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States

2020 ◽  
Author(s):  
Donghai Liang ◽  
Liuhua Shi ◽  
Jingxuan Zhao ◽  
Pengfei Liu ◽  
Joel Schwartz ◽  
...  
Keyword(s):  
Air Pollution ◽  
Mortality Rate ◽  
Case Fatality Rate ◽  
Urban Air Pollution ◽  
Case Fatality ◽  
Ambient Air ◽  
County Level ◽  
Fatality Rate ◽  
P Values

AbstractBackgroundThe novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 240,000 lives worldwide, causing tremendous public health, social, and economic damages. While the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis.MethodsWe conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO2, PM2.5 and O3 and county-level COVID-19 case-fatality and mortality rates in the US. We used both single and multipollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level healthcare capacity, phase-of-epidemic, population mobility, sociodemographic, socioeconomic status, behavior risk factors, and meteorological factors.Results1,027,799 COVID-19 cases and 58,489 deaths were reported in 3,122 US counties from January 22, 2020 to April 29, 2020, with an overall observed case-fatality rate of 5.8%. Spatial variations were observed for both COVID-19 death outcomes and long-term ambient air pollutant levels. County-level average NO2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models (p-values<0.05). Per inter-quartile range (IQR) increase in NO2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 7.1% (95% CI 1.2% to 13.4%) and 11.2% (95% CI 3.4% to 19.5%), respectively. We did not observe significant associations between long-term exposures to PM2.5 or O3 and COVID-19 death outcomes (p-values>0.05), although per IQR increase in PM2.5 (3.4 ug/m3) was marginally associated with 10.8% (95% CI: −1.1% to 24.1%) increase in COVID-19 mortality rate.Discussions and ConclusionsLong-term exposure to NO2, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of longterm PM2.5 and O3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO2 levels. Moreover, continuation of current efforts to lower traffic emissions and ambient air pollution levels may be an important component of reducing population-level risk of COVID-19 deaths.

scholarly journals Coronavirus Disease 2019 (COVID-19): A Modeling Study of Factors Driving Variation in Case Fatality Rate by Country

2020 ◽  
Vol 17 (21) ◽  
pp. 8189 ◽  
Author(s):  
Jennifer Pan ◽  
Joseph Marie St. Pierre ◽  
Trevor A. Pickering ◽  
Natalie L. Demirjian ◽  
Brandon K.K. Fields ◽  
...  
Keyword(s):  
Case Fatality Rate ◽  
Smoking Prevalence ◽  
Negative Binomial ◽  
Case Fatality ◽  
Potential Interaction ◽  
Fatality Rate ◽  
Social Distancing ◽  
Interaction Terms ◽  
Hospital Beds ◽  
Ct Scanners

Background: The novel Severe Acute Respiratory Syndrome Coronavirus-2 has led to a global pandemic in which case fatality rate (CFR) has varied from country to country. This study aims to identify factors that may explain the variation in CFR across countries. Methods: We identified 24 potential risk factors affecting CFR. For all countries with over 5000 reported COVID-19 cases, we used country-specific datasets from the WHO, the OECD, and the United Nations to quantify each of these factors. We examined univariable relationships of each variable with CFR, as well as correlations among predictors and potential interaction terms. Our final multivariable negative binomial model included univariable predictors of significance and all significant interaction terms. Results: Across the 39 countries under consideration, our model shows COVID-19 case fatality rate was best predicted by time to implementation of social distancing measures, hospital beds per 1000 individuals, percent population over 70 years, CT scanners per 1 million individuals, and (in countries with high population density) smoking prevalence. Conclusion: Our model predicted an increased CFR for countries that waited over 14 days to implement social distancing interventions after the 100th reported case. Smoking prevalence and percentage population over the age of 70 years were also associated with higher CFR. Hospital beds per 1000 and CT scanners per million were identified as possible protective factors associated with decreased CFR.

scholarly journals Risk factors affecting COVID-19 case fatality rate: A quantitative analysis of top 50 affected countries

2020 ◽  
Author(s):  
Hui Poh Goh ◽  
Wafiah Ilyani Mahari ◽  
Norhadyrah Izazie Ahad ◽  
Li Ling Chaw ◽  
Nurolaini Kifli ◽  
...  
Keyword(s):  
Risk Factors ◽  
Quantitative Analysis ◽  
Mortality Rate ◽  
Case Fatality Rate ◽  
Smoking Prevalence ◽  
Case Fatality ◽  
Data Availability ◽  
Diabetes Prevalence ◽  
Diabetic Patients ◽  
Fatality Rate

AbstractBackgroundLatest clinical data on treatment on coronavirus disease 2019 (COVID-19) indicated that older patients and those with underlying history of smoking, hypertension or diabetes mellitus might have poorer prognosis of recovery from COVID-19. We aimed to examine the relationship of various prevailing population-based risk factors in comparison with mortality rate and case fatality rate (CFR) of COVID-19.MethodsDemography and epidemiology data which have been identified as verified or postulated risk factors for mortality of adult inpatients with COVID-19 were used. The number of confirmed cases and the number of deaths until April 16, 2020 for all affected countries were extracted from Johns Hopkins University COVID-19 websites. Datasets for indicators that are fitting with the factors of COVID-19 mortality were extracted from the World Bank database. Out of about 185 affected countries, only top 50 countries were selected to be analyzed in this study. The following seven variables were included in the analysis, based on data availability and completeness: 1) proportion of people aged 65 above, 2) proportion of male in the population, 3) diabetes prevalence, 4) smoking prevalence, 5) current health expenditure, 6) number of hospital beds and 7) number of nurses and midwives. Quantitative analysis was carried out to determine the correlation between CFR and the aforementioned risk factors.ResultsUnited States shows about 0.20% of confirmed cases in its country and it has about 4.85% of CFR. Luxembourg shows the highest percentage of confirmed cases of 0.55% but a low 2.05% of CFR, showing that a high percentage of confirmed cases does not necessarily lead to high CFR. There is a significant correlation between CFR, people aged 65 and above (p = 0.35) and diabetes prevalence (p = 0.01). However, in our study, there is no significant correlation between CFR of COVID-19, male gender (p = 0.26) and smoking prevalence (p = 0.60).ConclusionOlder people above 65 years old and diabetic patients are significant risk factors for COVID-19. Nevertheless, gender differences and smoking prevalence failed to prove a significant relationship with COVID-19 mortality rate and CFR.

scholarly journals Global Pandemic Trends of COVID-19 in 2020

2021 ◽  
Author(s):  
Hai-Zhen Chen ◽  
Bo Cai ◽  
Jian-Guo Chen
Keyword(s):  
Public Health ◽  
United States ◽  
Mortality Rate ◽  
Incidence Rate ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
The United States ◽  
Cumulative Number ◽  
Fatality Rate ◽  
The World

Abstract Background: The novel coronavirus pneumonia (COVID-19) has been global threaten to public health. This paper provides perspective to the decision-making for public health control of the pandemic or the spread of epidemic.Methods: According to the WHO global reported database, we developed and used the number of cumulative cases, and the number of cumulative deaths to calculate and analyze rates of incidence, mortality, and fatality by country, with respect to the 30 highest outbreak (Top 30) countries.Results： As of December 31, 2020, of the global population of 7.585 billion, the cumulative number of reported cases was 81,475,053, and the cumulative number of deaths was 1,798,050. The incidence rate of COVID-19 was 1074.13 per 100,000 population, the mortality rate was 23.70 per 100,000, and the case fatality rate was 2.21%. Among the Top 30 countries, the five countries with the highest number of reported cumulative cases were, in rank, the United States (19,346,790 cases), India (10,266,674), Brazil (7,563,551), Russia (3,159,297) and France (2,556,708), and the five countries with the highest number of cumulative deaths were the United States (335,789 cases), Brazil (192,681), India (148,738), Mexico (123,845) and Italy (73,604). Globally, the countries with the highest incidence rate were, in rank, Andorra, Luxembourg, Montenegro, San Marino, and Czechia; the countries with the highest mortality rate were, in rank, San Marino, Belgium, Slovenia, Italy, and North Macedonia. The highest fatality rate was found in Yemen, Mexico, Montserrat, Isle of Man, and Ecuador, respectively. In China, 96,673 cases of COVID-19 and 4788 deaths were reported in 2020, ranking the 78th and the 43rd, respectively, in the world. The incidence rate and mortality rate were 6.90/105 and 0.34/105, respectively, ranking 207th and 188th in the world. The case fatality rate was 4.95%, ranking 11th in the world.Conclusions： The COVID-19 prevalence is still on the rise, and the turning points of incidence and mortality are not yet forecasted. Personal protection, anti-epidemic measures and efforts from public health personnel, medical professionals, biotechnology R&D personnel, effectiveness of the vaccination programs and the governments, are the important factors to determine the future prevalence of this coronavirus disease.

scholarly journals Mortality Rate and Case Fatality Rate of COVID-19 Around The World: An Adjusted Estimation

2021 ◽  
Author(s):  
Moslem Taheri Soodejani ◽  
Ali Akbar Haghdoost ◽  
Mohammad Hassan Lotfi ◽  
Marzieh Mahmudimanesh ◽  
Seyyed Mohammad Tabatabaei
Keyword(s):  
Diabetes Mellitus ◽  
Health Status ◽  
Mortality Rate ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Total Expenditure ◽  
Fatality Rate ◽  
The World ◽  
Per Capita ◽  
Prevalence Of Diabetes Mellitus

Abstract Background: The present study is designed to predict the global adjusted values for mortality rate and case fatality rate of COVID-19 around the world. Methods: This research was conducted at the ecological level using data from 100 countries which were chosen randomly. The adjusted values were predicted using beta regression considering predictive factors such as total expenditure on health per capita, expenditure on health as a percentage of GDP, life expectancy and the percentage of the population aged over 65 years, hospital beds (per 1000 population), physicians (per 1000 population), nurses (per 1000 population), prevalence of smoking, prevalence of diabetes mellitus, and number of confirmed tests in each country. In the end, applying Monte Carlo simulation, the adjusted values of mortality rate and case fatality rate for the whole world were estimated.Results: The results of this study showed that two factors including percentage of population ages 65 and above (P=0.03) and Total expenditure on health as % of GDP (P = 0.04) had a statistically significant relationship with the case fatality rate. Moreover, there was a statistically significant relationship between the mortality rate and life expectancy (P = 0.02), total expenditure on health per capita (P < 0.001), nurses (Per 1000 Population) (P=0.04), and the prevalence of Diabetes Mellitus (P=0.04). The mortality rate and case fatality rate for the whole world were estimated to be 0.000001 and 0.026, respectively.Conclusion: It seems that what can cause global concern is not the case fatality rate of the disease, but its mortality rate, which is directly related to the health status of a community. The worse the health status of a community, the greater the number of infected people likely to be there, that ultimately increases the mortality rate of the disease in the community.

scholarly journals Covid-19 High Attack Rate Can Lead to High Case Fatality Rate

2021 ◽  
Author(s):  
Tareef Fadhil Raham
Keyword(s):  
Mortality Rate ◽  
Attack Rate ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Positive Influence ◽  
P Value ◽  
Fatality Rate ◽  
Mean Values ◽  
Paired Samples ◽  
Significant Difference

Background: During the current Covid-19 pandemic case fatality rate (CFR) estimates were subjected to a lot of debates regarding the accuracy of its estimations, predictions, and the reason of across countries variances. In this context, we conduct this study to see the relationship between attack rate (AR) and CFR. The study hypothesis is based on two: 1- evidence suggests that the mortality rate (MR) has a positive influence on case fatality ratio (CFR), 2- and increase number of Covid-19 cases leads to increased mortality rate (MR). Material and methods: Thirty countries and territories were chosen. Inclusion criterion was > 500 Covid-19 reported cases per 10,000 population inhabitants. Data on covid-19 cases and deaths was selected as it was on March 10, 2021. Statistical methods used are descriptive and one-sample Kolmogorov-Smirnov (K-S), the one-way ANOVA, Levene, least significant different (LSD), and matched paired-samples T-tests. Results: ANOVA test showed a significant difference at P<0.01 among all studied groups concerning AR and CFR mean values. Group of countries with MR ≥ 15 death / 104 inhabitants recorded the highest level of crude mean CFR and AR values, and recorded the highest gap with leftover groups, especially with countries reported MR of <10 death/ 104 inhabitants. There were independence 95% confidence intervals of mean CFR and AR values between countries with ≥ 15 death / 104 MR and countries with MR of <10 death /104. There was a significant difference between countries with MR ≥ 15 death / 104 inhabitants and countries with MR of <10 death / 10 4 inhabitants groups through least significant difference (LSD) test for CFR%( 0.042 p-values) and Games Howell (GH) test for AR/104 (p-value 0.000). Conclusions: CFR has a positive significant association with AR.

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