scholarly journals Explaining COVID-19 mortality rates in the first wave in Europe

2021 ◽  
Vol 16 (3) ◽  
pp. 211-221
Author(s):  
Gauss M. Cordeiro ◽  
Dalson Figueiredo ◽  
Lucas Silva ◽  
Edwin M.M. Ortega ◽  
Fábio Prataviera
Keyword(s):  
Population Density ◽  
Urban Population ◽  
Mortality Rates ◽  
Beta Regression ◽  
Dispersion Parameters ◽  
Death Rates ◽  
Running Time ◽  
Hospital Beds ◽  
Proportional Data ◽  
The Mean

The beta regression has been received considerable attention in the last decade because of its applications to proportional data in several fields. We study the variability of coronavirus death rates in the first wave of twenty European countries using the beta regression with two systematic components for the mean and dispersion parameters. We prove empirically that the population density, proportion of urban population, hospital beds per 100 thousand and running time explain the variability of the COVID-19 death rates in the first wave of these countries.

Flexible quasi-beta regression models for continuous bounded data

2018 ◽  
Vol 19 (6) ◽  
pp. 617-633 ◽  
Author(s):  
Wagner H Bonat ◽  
Ricardo R Petterle ◽  
John Hinde ◽  
Clarice GB Demétrio
Keyword(s):  
Regression Model ◽  
Regression Models ◽  
Beta Regression ◽  
Estimating Function ◽  
Dispersion Parameters ◽  
Linear Predictor ◽  
Mean And Variance ◽  
The Mean ◽  
Bounded Data ◽  
Beta Regression Model

We propose a flexible class of regression models for continuous bounded data based on second-moment assumptions. The mean structure is modelled by means of a link function and a linear predictor, while the mean and variance relationship has the form [Formula: see text], where [Formula: see text], [Formula: see text] and [Formula: see text] are the mean, dispersion and power parameters respectively. The models are fitted by using an estimating function approach where the quasi-score and Pearson estimating functions are employed for the estimation of the regression and dispersion parameters respectively. The flexible quasi-beta regression model can automatically adapt to the underlying bounded data distribution by the estimation of the power parameter. Furthermore, the model can easily handle data with exact zeroes and ones in a unified way and has the Bernoulli mean and variance relationship as a limiting case. The computational implementation of the proposed model is fast, relying on a simple Newton scoring algorithm. Simulation studies, using datasets generated from simplex and beta regression models show that the estimating function estimators are unbiased and consistent for the regression coefficients. We illustrate the flexibility of the quasi-beta regression model to deal with bounded data with two examples. We provide an R implementation and the datasets as supplementary materials.

scholarly journals Longitudinal variability in mortality predicts Covid-19 deaths

2020 ◽  
Author(s):  
Jon O. Lundberg ◽  
Hugo Zeberg
Keyword(s):  
Population Density ◽  
Excess Mortality ◽  
Viral Disease ◽  
Mortality Rates ◽  
European Countries ◽  
Death Rates ◽  
All Cause Mortality ◽  
Current Outbreak ◽  
Longitudinal Variability ◽  
Influenza Vaccinations

AbstractWithin Europe, death rates due to covid-19 vary greatly, with some countries being hardly hit while others to date are almost unaffected. It would be of interest to pinpoint the factors that determine a country’s susceptibility to a pandemic such as covid-19.Here we present data demonstrating that mortality due to covid-19 in a given country could have been largely predicted even before the pandemic hit Europe, simply by looking at longitudinal variability of all-cause mortality rates in the years preceding the current outbreak. The variability in death rates during the influenza seasons of 2015-2019 correlate to excess mortality caused by covid-19 in 2020 (R2=0.48, p<0.0001). In contrast, we found no correlation between such excess mortality and age, population density, degree of urbanization, latitude, GNP, governmental health spendings or rates of influenza vaccinations.These data may be of some relevance when discussing the effectiveness of acute measures in order to limit the spread of the disease and ultimately deaths. They suggest that in some European countries there is an intrinsic susceptibility to fatal respiratory viral disease including covid-19; a susceptibility that was evident long before the arrival of the current pandemic.

Bayesian beta regression models with joint mean and dispersion modeling

2015 ◽  
Vol 21 (1) ◽  
Author(s):  
Edilberto Cepeda-Cuervo ◽  
Liliana Garrido
Keyword(s):  
Regression Models ◽  
Bayesian Method ◽  
Joint Modeling ◽  
Dispersion Modeling ◽  
Beta Regression ◽  
Dispersion Parameters ◽  
The Mean

AbstractThis paper summarizes some results of beta regression models and proposes a Bayesian method to fit these models, including joint modeling of the mean and dispersion parameters. This method is implemented through simulated and applied studies.

scholarly journals Prevalence of Metabolic Syndrom in Three Urban Communities of Dhaka City

1970 ◽  
Vol 2 (2) ◽  
pp. 44-48 ◽  
Author(s):  
Shurovi Sayeed ◽  
Akhter Banu ◽  
Parvin Akter Khanam ◽  
Sharmina Alauddin ◽  
Sabrina Makbul ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Urban Communities ◽  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Urban Population ◽  
Population Characteristics ◽  
Dhaka City ◽  
Fasting Plasma ◽  
Prevalence Of Obesity ◽  
The Mean

Bangladeshis are prone to develop type 2 diabetes mellitus (T2DM), hypertension (sHTN and dHTN) and atherosclerotic heart diseases, observed more predominantly in the urban population. Though metabolic syndrome (MetS) is a related disorder, there are few studies in this regard. The prevalence of obesity, T2DM and MetS in three urban communities of Bangladesh were addressed in this study. Nine hundred non-slum urban households in three Dhaka City Wards were randomly selected. One member (age ≥ 25y) from each household was invited for investigation with an overnight fast. Socio-demographic information as well as height, weight, waist-girth, hip-girth and blood pressure were measured. Fasting plasma glucose (FPG), total cholesterol (chol), triglycerides (TG) and high-density lipoproteins-c (HDL) were estimated. A total of 705 (m / f = 239 / 466) subjects volunteered for the study. The mean value with 95% confidence interval (CI) of age was 42.4 (40.9 - 43.1) years for men and 37.8 (36.8 - 38.7) for women. The mean (CI) body mass index (BMI) was 21.0 (20.6 - 21.5) and 22.6 (22.2 - 22.9) and waist hip ratio (WHR) was 0.84 (0.83 - 0.84) and 0.82 (0.81 - 0.83), respectively for men and women. The mean (CI) FPG (fasting plasma glucose) was 5.5 (5.2 - 5.7) for men and 5.2 (5.0 - 5.4) for women. The prevalence of obesity (BMI ≥ 25.0) was 21%, T2DM (FPG ≥ 6.1 mmol/l) was 22.2%, triglyceridemia (TG ≥ 150mg/dl) was 45.1% and low HDL-c (HDL<40mg/ dl) was 43.8%. The crude prevalence of MetS varied based on different cluster combinations, being the lowest (0.3%) recommended by WHO cluster (FPG + BMI + SBP/DBP) and the highest (8.7%) by International Diabetes Federation (IDF) cluster (waist + FPG + HDL). The MetS was found higher in male than female by NCEP criteria and higher in female than male by IDF criteria. The study revealed an increased prevalence of obesity, T2DM and MetS in the urban communities. It also revealed that T2DM and MetS are moderately common and of growing healthcare burden in the rapidly growing urban population. Additionally, the study observed the wide ranging prevalence rates of MetS in the same study population indicating the need to establish a consistent and useful MetS-cluster depending on population characteristics. Ibrahim Med. Coll. J. 2008; 2(2): 44-48 Key Words: Metabolic syndrome, urban, diabetes, hypertension, dyslipidemia   doi: 10.3329/imcj.v2i2.2936

Retrospective analysis of mortality within 30 days of systemic anticancer therapy and comparison with a previous audit at an Australian Regional Cancer Centre

2021 ◽  
pp. 107815522110160
Author(s):  
Bernadatte Zimbwa ◽  
Peter J Gilbar ◽  
Mark R Davis ◽  
Srinivas Kondalsamy-Chennakesavan
Keyword(s):  
Checkpoint Inhibitors ◽  
Anticancer Therapy ◽  
Mortality Rates ◽  
Feedback Process ◽  
Time To Death ◽  
Cancer Centre ◽  
Haematology Patients ◽  
The Mean ◽  
Regional Cancer Centre ◽  
Mean Time

Purpose To retrospectively determine the rate of death occurring within 14 and 30 days of systemic anticancer therapy (SACT), compare this against a previous audit and benchmark results against other cancer centres. Secondly, to determine if the introduction of immune checkpoint inhibitors (ICI), not available at the time of the initial audit, impacted mortality rates. Method All adult solid tumour and haematology patients receiving SACT at an Australian Regional Cancer Centre (RCC) between January 2016 and July 2020 were included. Results Over a 55-month period, 1709 patients received SACT. Patients dying within 14 and 30 days of SACT were 3.3% and 7.0% respectively and is slightly higher than our previous study which was 1.89% and 5.6%. Mean time to death was 15.5 days. Males accounted for 63.9% of patients and the mean age was 66.8 years. 46.2% of the 119 patients dying in the 30 days post SACT started a new line of treatment during that time. Of 98 patients receiving ICI, 22.5% died within 30 days of commencement. Disease progression was the most common cause of death (79%). The most common place of death was the RCC (38.7%). Conclusion The rate of death observed in our re-audit compares favourably with our previous audit and is still at the lower end of that seen in published studies in Australia and internationally. Cases of patients dying within 30 days of SACT should be regularly reviewed to maintain awareness of this benchmark of quality assurance and provide a feedback process for clinicians.

scholarly journals COVID-19 Mortality Rate and Its Incidence in Latin America: Dependence on Demographic and Economic Variables

2021 ◽  
Vol 18 (13) ◽  
pp. 6900
Author(s):  
Javier Cifuentes-Faura
Keyword(s):  
Latin America ◽  
Mortality Rate ◽  
Population Density ◽  
Life Expectancy ◽  
Latin American ◽  
Positive Influence ◽  
Death Rates ◽  
Per Capita ◽  
Latin American Countries ◽  
Quality Infrastructure

The pandemic caused by COVID-19 has left millions infected and dead around the world, with Latin America being one of the most affected areas. In this work, we have sought to determine, by means of a multiple regression analysis and a study of correlations, the influence of population density, life expectancy, and proportion of the population in vulnerable employment, together with GDP per capita, on the mortality rate due to COVID-19 in Latin American countries. The results indicated that countries with higher population density had lower numbers of deaths. Population in vulnerable employment and GDP showed a positive influence, while life expectancy did not appear to significantly affect the number of COVID-19 deaths. In addition, the influence of these variables on the number of confirmed cases of COVID-19 was analyzed. It can be concluded that the lack of resources can be a major burden for the vulnerable population in combating COVID-19 and that population density can ensure better designed institutions and quality infrastructure to achieve social distancing and, together with effective measures, lower death rates.

scholarly journals Effectiveness of Government Policies in Controlling COVID-19 in India

2020 ◽  
pp. 002073142098374
Author(s):  
Ashutosh Pandey ◽  
Nitin Kishore Saxena
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Rural Population ◽  
Urban Areas ◽  
Urban Population ◽  
Demographic Factors ◽  
Poverty Rate ◽  
Government Policies ◽  
Cumulative Number ◽  
Population Number

The purpose of this study is to find the demographic factors associated with the spread of COVID-19 and to suggest a measure for identifying the effectiveness of government policies in controlling COVID-19. The study hypothesizes that the cumulative number of confirmed COVID-19 patients depends on the urban population, rural population, number of persons older than 50, population density, and poverty rate. A log-linear model is used to test the stated hypothesis, with the cumulative number of confirmed COVID-19 patients up to period [Formula: see text] as a dependent variable and demographic factors as an independent variable. The policy effectiveness indicator is calculated by taking the difference of the COVID rank of the [Formula: see text]th state based on the predicted model and the actual COVID rank of the [Formula: see text]th state[Formula: see text]Our study finds that the urban population significantly impacts the spread of COVID-19. On the other hand, demographic factors such as rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus, people residing in urban areas face a significant threat of COVID-19 as compared to people in rural areas.

scholarly journals COVID-19 in Latin America: a first glance to the mortality

2020 ◽  
pp. 1-3 ◽  
Author(s):  
Nubia Muñoz
Keyword(s):  
Latin America ◽  
Latin American ◽  
Mortality Rates ◽  
European Countries ◽  
Death Rates ◽  
Death Toll ◽  
The United Kingdom ◽  
Health Authorities ◽  
The Us ◽  
Latin American Countries

It is too early to know which will be the final death toll from the Covid-19 or SARS-CoV-2 virus epidemy in Latin America since the epidemy is still active and we will not know when it will end. The curve for new infections and deaths has not reached yet a peak (Figure 1). In addition, we know little about the epidemiology of this new virus. The daily litany of the number of people infected with the number of admissions to hospitals and intensive care units and the number of deaths guides health authorities to plan health services and politicians to gauge the degree of confinement necessary to control the transmission of the virus, but it says little about the magnitude of the problem if we do not relate it to the population at risk. At the end of the pandemic, we will be able to estimate age-standardized death rates for the different countries, but until then the crude death rates will provide a first glance or snapshot of the death toll and impact of the pandemic from March to May 2020. These rates are well below those estimated in other countries in Europe and North America: Belgium (82.6), Spain (58.0), the United Kingdom (57.5), Italy (55.0), France (42.9), Sweden (41.4), and the US (30.7). (Johns Hopkins CSSE, May 30, 2020). However, in the European countries and the US the number of deaths has reached a peak, while this is not the case in Latin American countries. (Figure 1). It should be taken into account that the above rates are crude and therefore, some of the differences could be due to the fact that European countries have a larger proportion of the population over 70 years of age in whom higher mortality rates have been reported.

scholarly journals Population density of helminths in ducks: effects of host’s age, sex, breed and season

1970 ◽  
Vol 6 (1) ◽  
pp. 45-51 ◽  
Author(s):  
T Farjana ◽  
KR Islam ◽  
MMH Mondal
Keyword(s):  
Population Density ◽  
Key Words ◽  
Parasitic Infection ◽  
Winter Season ◽  
Helminth Parasites ◽  
Domestic Ducks ◽  
The Mean

 A study was conducted to investigate the population density of helminth parasites in domestic ducks (Anas boschas domesticus) in relation to host's age, sex, breed and seasons of the year from March 2002 to May 2003. A total of 300 ducks were collected from different villages of Netrokona and Mymensingh districts of Bangladesh and autopsied to collect the parasites and counted to determine the population density of parasites. Off 300 ducks examined, 290 (96.66%) were infected with 17 species of helminth parasites in which 11 species were trematodes, 4 were cestodes and 2 nematodes. Among the parasites, density of cestodes was the highest (33.15±5.26), followed by trematodes (5.98±1.32); and nematodes (2.95±0.68). Mean density of parasites increased with the increase of age (young: 21.23±1.09, adult: 26.18±2.14 and old: 27.87±2.98) while the mean density of most of the helminth parasites was higher in female ducks (31.35±4.72) than in males (27.52±3.32). Indigenous ducks (33.72±3.61) were infected with the highest load of helminths than Khaki Campbell breed (29.61±4.32) of ducks. Mean density of most trematodes (5.42±0.80) were highest in winter season whereas mean density of all cestodes (48.43±4.85) and nematodes (4.13±1.76) were highest in summer.  The present study suggests that age, sex, breed of ducks and seasons of the year influence the parasitic infection to a greater extend. Key words: Population density, helminths, duck, Bangladesh DOI = 10.3329/bjvm.v6i1.1338 Bangl. J. Vet. Med. (2008). 6 (1): 45-51

The recent trend of mortality in Great Britain

1981 ◽  
Vol 108 (3) ◽  
pp. 413-422
Author(s):  
C. D. Daykin
Keyword(s):  
Great Britain ◽  
Recent Trend ◽  
Mortality Rates ◽  
Death Rates ◽  
England And Wales ◽  
Annual Series ◽  
Previous Note

This note continues an annual series on mortality rates in Great Britain; the previous note in the series appeared in J.I.A. 107, 529 and dealt with mortality in 1978. Tables 1 and 2 below show central death-rates for Great Britain for the years from 1966 to 1979 and Tables 3 and 4 show the ratios of these rates to the corresponding average rates for the three years 1970–72, which have been taken as a standard. Death-rates in this form for the years from 1961 to 1978 have been published in earlier notes in this series. The rates for 1979 have been calculated using the deaths recorded as occurring in Great Britain in 1979 and the ‘home’ population at 30 June 1979, i.e. the number of people actually in the country at the time, as estimated by the Registrars General of England and Wales and of Scotland.

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