scholarly journals Periodic variations in the Covid-19 infection and fatality rates

2020 ◽  
Author(s):  
Sebastien Peirani ◽  
Jose Antonio de Freitas Pacheco ◽  
Philippe Icard
Keyword(s):  
Mortality Rate ◽  
Power Spectra ◽  
Mortality Data ◽  
Data Sets ◽  
Social Activities ◽  
Periodic Oscillations ◽  
Mortality Curve ◽  
Testing Frequency ◽  
The Moment

Power spectra of infection and mortality rate curves for nineteen countries of different continents were computed. Nine of them show the presence of oscillations with a period of about seven says either in the infection or in the mortality data sets. The computed power spectra for seven countries do no indicate any significant signal of periodicity while the three remaining countries indicate periodic oscillations only in the infection or only in the mortality curve. Data indicate that minima occur generally on weekends. The seven-day periodicity present in infection data of nine countries is robust and seems to be the consequence of different factors as, for instance, higher testing frequency during weekdays or/and an enhanced contamination during social activities during weekends. For the moment, there is no convincing explanation for the seven-day oscillations observed in the mortality curves of some countries.

scholarly journals Oscillations in U.S. COVID-19 Incidence and Mortality Data Reflect Diagnostic and Reporting Factors

mSystems ◽  
2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Aviv Bergman ◽  
Yehonatan Sella ◽  
Peter Agre ◽  
Arturo Casadevall
Keyword(s):  
Public Health ◽  
United States ◽  
Public Health System ◽  
Epidemiological Data ◽  
The United States ◽  
Mortality Data ◽  
Data Sets ◽  
Periodic Oscillations ◽  
The Public ◽  
Incidence And Mortality

ABSTRACT The coronavirus disease 2019 (COVID-19) pandemic currently in process differs from other infectious disease calamities that have previously plagued humanity in the vast amount of information that is produced each day, which includes daily estimates of the disease incidence and mortality data. Apart from providing actionable information to public health authorities on the trend of the pandemic, the daily incidence reflects the process of disease in a susceptible population and thus reflects the pathogenesis of COVID-19, the public health response, and diagnosis and reporting. Both new daily cases and daily mortality data in the United States exhibit periodic oscillatory patterns. By analyzing New York City (NYC) and Los Angeles (LA) testing data, we demonstrate that this oscillation in the number of cases can be strongly explained by the daily variation in testing. This seems to rule out alternative hypotheses, such as increased infections on certain days of the week, as driving this oscillation. Similarly, we show that the apparent oscillation in mortality in the U.S. data are mostly an artifact of reporting, which disappears in data sets that record death by episode date, such as the NYC and LA data sets. Periodic oscillations in COVID-19 incidence and mortality data reflect testing and reporting practices and contingencies. Thus, these contingencies should be considered first prior to suggesting biological mechanisms. IMPORTANCE The incidence and mortality data for the COVID-19 data in the United States show periodic oscillations, giving the curve a distinctive serrated pattern. In this study, we show that these periodic highs and lows in incidence and mortality data are due to daily differences in testing for the virus and death reporting, respectively. These findings are important because they provide an explanation based on public health practices and shortcomings rather than biological explanations, such as infection dynamics. In other words, when oscillations occur in epidemiological data, a search for causes should begin with how the public health system produces and reports the information before considering other causes, such as infection cycles and higher incidences of events on certain days. Our results suggest that when oscillations occur in epidemiological data, this may be a signal that there are shortcomings in the public health system generating that information.

Perbandingan Linieritas Dalam Pendeteksian Faktor-Faktor Yang Mempengaruhi Angka Kematian Bayi Di Provinsi Aceh

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Desfira Ahya ◽  
Inas Salsabila ◽  
Miftahuddin
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Linear Model ◽  
Health Workers ◽  
Additive Model ◽  
Infant Mortality Rate ◽  
Mortality Data ◽  
Important Indicator ◽  
Penalized Spline ◽  
Aceh Province

Angka Kematian Bayi/ Infant Mortality Rate (IMR) merupakan indikator penting dalam mengukur keberhasilan pengembangan kesehatan. Nilai IMR juga dapat digunakan untuk mengetahui tingkat kesehatan ibu, kondisi kesehatan lingkungan dan secara umum, tingkat pengembangan sosio-ekonomi masyarakat. Penelitian ini bertujuan untuk memperoleh model IMR terbaik menggunakan tiga pendekatan: Model Linear, Model Linear Tergeneralisir dan Model Aditif Tergeneralisir dengan basis P-spline. Sebagai tambahan, berdasarkan model tersebut akan terlihat variabel yang mempengaruhi tingkat kematian bayi di provinsi Aceh. Penelitian ini menggunakan data jumlah kematian bayi di tahun 2013-2015. Data dalam penelitian ini diperoleh dari Profil Kesehatan Aceh. Hasil menunjukkan bahwa model terbaik dalam menjelaskan angka kematian bayi di provinsi Aceh tahun 2013-2015 ialah Model Linear Tergeneralisir dengan basis P-spline menggunakan parameter penghalusan 100 dan titik knots 8. Faktor yang sangat mempengaruhi angka kematian ialah jumlah pekerja yang sehat.   Infant mortality rate (IMR) is an important indicator in measuring the success of health development. IMR also can be used to knowing the level of maternal health, environmental health conditions and generally the level of socio-economic development in community. This research aims to get the best model of infant mortality data using three approaches: Linear Model, Generalized Linear Model and Generalized Additive Model with Penalized Spline (P-spline) base. In addition, based on the model can be seen the variables that affect to infant mortality in Aceh Province. This research uses data number of infant mortality in Aceh Province period 2013-2015. The data in this research were obtained from Aceh’s Health Profile. The results show that the best model can be explain infant mortality rate in Aceh Province period 2013-2015 is GAM model with P-spline base using smoothing parameter 100 and knots 8. Factor that high effect to infant mortality is number of health workers.

Abstract P261: Intensive Systolic Blood Pressure Lowering Will Prevent Over 100,000 Deaths Annually

Hypertension ◽  
2016 ◽  
Vol 68 (suppl_1) ◽  
Author(s):  
Holly Kramer ◽  
Adam Bress ◽  
Srinivasan Beddhu ◽  
Paul Muntner ◽  
Richard S Cooper
Keyword(s):  
Blood Pressure ◽  
Mortality Rate ◽  
Systolic Blood Pressure ◽  
Mortality Rates ◽  
Mortality Data ◽  
Blood Pressure Lowering ◽  
Cvd Risk ◽  
Pressure Lowering ◽  
Annual Mortality ◽  
The U.S

Background: The Systolic Blood Pressure Intervention Trial (SPRINT) trial randomized 9,361 adults aged ≥50 years at high cardiovascular disease (CVD) risk without diabetes or stroke to intensive systolic blood pressure (SBP) lowering (≤120 mmHg) or standard SBP lowering (≤140 mmHg). After a median follow up of 3.26 years, all-cause mortality was 27% (95% CI 40%, 10%) lower with intensive SBP lowering. We estimated the potential number of prevented deaths with intensive SBP lowering in the U.S. population meeting SPRINT criteria. Methods: SPRINT eligibility criteria were applied to the National Health and Nutrition Examination Survey 1999-2006, a representative survey of the U.S. population, linked with the mortality data through December 2011. Eligibility included (1) age ≥50 years with (2) SBP 130-180 mmHg depending on number of antihypertensive classes being taken, and (3) presence of ≥1 CVD risk conditions (history of coronary heart disease, estimated glomerular filtration rate (eGFR) 20 to 59 ml/min/1.73 m 2 , 10-year Framingham risk score ≥15%, or age ≥75 years). Adults with diabetes, stroke history, >1 g/day proteinuria, heart failure, on dialysis, or eGFR<20 ml/min/1.73m 2 were excluded. Annual mortality rates for adults meeting SPRINT criteria were calculated using Kaplan-Meier methods and the expected reduction in mortality rates with intensive SBP lowering in SPRINT was used to determine the number of potential deaths prevented. Analyses accounted for the complex survey design. Results: An estimated 18.1 million U.S. adults met SPRINT criteria with 7.4 million taking blood pressure lowering medications. The mean age was 68.6 years and 83.2% and 7.4% were non-Hispanic white and non-Hispanic black, respectively. The annual mortality rate was 2.2% (95% CI 1.9%, 2.5%) and intensive SBP lowering was projected to prevent 107,453 deaths per year (95% CI 45,374 to 139,490). Among adults with SBP ≥145 mmHg, the annual mortality rate was 2.5% (95% CI 2.1%, 3.0%) and intensive SBP lowering was projected to prevent 60,908 deaths per year (95% CI 26, 455 to 76, 792). Conclusions: We project intensive SBP lowering could prevent over 100,000 deaths per year of intensive treatment.

Biases in the estimation of size-dependent mortality models: advantages of a semiparametric approach

2009 ◽  
Vol 39 (8) ◽  
pp. 1430-1443 ◽  
Author(s):  
Ghislain Vieilledent ◽  
Benoît Courbaud ◽  
Georges Kunstler ◽  
Jean-François Dhôte ◽  
James S. Clark
Keyword(s):  
Mortality Rate ◽  
Picea Abies ◽  
Abies Alba ◽  
Mortality Data ◽  
Strongly Nonlinear ◽  
Semiparametric Approach ◽  
Mortality Models ◽  
Large Trees ◽  
Parametric Functions ◽  
Related Mortality

Mortality rate is thought to show a U-shape relationship to tree size. This shape could result from a decrease of competition-related mortality as diameter increases, followed by an increase of senescence and disturbance-related mortality for large trees. Modeling mortality rate as a function of diameter is nevertheless difficult, first because this relationship is strongly nonlinear, and second because data can be unbalanced, with few observations for large trees. Parametric functions, which are inflexible and sensitive to the distribution of observations, tend to introduce biases in mortality rate estimates. In this study we use mortality data for Abies alba Mill. and Picea abies (L.) Karst. to demonstrate that mortality rate estimates for extreme diameters were biased when using classical parametric functions. We then propose a semiparametric approach allowing a more flexible relationship between mortality and diameter. We show that the relatively shade-tolerant A. alba has a lower annual mortality rate (2.75%) than P. abies (3.78%) for small trees (DBH <15 cm). Picea abies, supposedly more sensitive to bark beetle attacks and windthrows, had a higher mortality rate (up to 0.46%) than A. alba (up to 0.30%) for large trees (DBH ≥50 cm).

scholarly journals Assessing the effect of phenotyping scoring systems and SNP calling and filtering methods on detection of QTL associated with reaction of Brassica napus to Sclerotinia sclerotiorum

2021 ◽  
Author(s):  
Fereshteh Shahoveisi ◽  
Atena Oladzad ◽  
Luis E. del Rio Mendoza ◽  
Seyedali Hosseinirad ◽  
Susan Ruud ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Missing Data ◽  
Sclerotinia Sclerotiorum ◽  
Scoring Systems ◽  
Mortality Data ◽  
Lesion Length ◽  
Data Sets ◽  
Qtl Detection ◽  
Snp Calling ◽  
The Impact

The polyploid nature of canola (Brassica napus) represents a challenge for the accurate identification of single nucleotide polymorphisms (SNPs) and the detection of quantitative trait loci (QTL). In this study, combinations of eight phenotyping scoring systems and six SNP calling and filtering parameters were evaluated for their efficiency in detection of QTL associated with response to Sclerotinia stem rot, caused by Sclerotinia sclerotiorum, in two doubled haploid (DH) canola mapping populations. Most QTL were detected in lesion length, relative areas under the disease progress curve (rAUDPC) for lesion length, and binomial-plant mortality data sets. Binomial data derived from lesion size were less efficient in QTL detection. Inclusion of additional phenotypic sets to the analysis increased the numbers of significant QTL by 2.3-fold; however, the continuous data sets were more efficient. Between two filtering parameters used to analyze genotyping by sequencing (GBS) data, imputation of missing data increased QTL detection in one population with a high level of missing data but not in the other. Inclusion of segregation-distorted SNPs increased QTL detection but did not impact their R2 values significantly. Twelve of the 16 detected QTL were on chromosomes A02 and C01, and the rest were on A07, A09, and C03. Marker A02-7594120, associated with a QTL on chromosome A02 was detected in both populations. Results of this study suggest the impact of genotypic variant calling and filtering parameters may be population dependent while deriving additional phenotyping scoring systems such as rAUDPC datasets and mortality binary may improve QTL detection efficiency.

scholarly journals FREQUENCY AND CAUSES OF PERINATAL MORTALITY IN A TERTIARY CARE HOSPITAL IN PESHAWAR, PAKISTAN

2018 ◽  
Vol 16 (1) ◽  
pp. 15-19
Author(s):  
Maimoona Qadir ◽  
Sohail Amir ◽  
Samina Jadoon ◽  
Muhammad Marwat
Keyword(s):  
Mortality Rate ◽  
Perinatal Mortality ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Age Groups ◽  
Mortality Data ◽  
Care Hospital ◽  
Cross Sectional ◽  
Medical Disorders ◽  
Perinatal Mortality Rate

Background: Perinatal mortality rate indicates quality of care provided during pregnancy and delivery to the mother and to the neonate in its early neonatal period. The objective of this study was to determine the frequency and causes of perinatal mortality in a tertiary care hospital in Peshawar, Pakistan. Materials & Methods: This cross-sectional study was conducted at Department of Gynaecology & Obstetrics, Khyber Teaching Hospital, Peshawar, Pakistan from 1st January 2016 to 31st December 2016. The inclusion criteria was all singleton gestation with gestational age of at least 24 weeks presenting with perinatal mortality. Data was collected for the following variables; age groups (up to 20 years, 21-30 years, 31-40 years and > 40 years), booking status (yes/ no), period of gestation (24-31+6, 32-36+6, 37-39+6 and > 40 weeks), Foetal weight ( 3.5 kg) and cause of perinatal mortality. Results: Out of 4508 deliveries there were 288 perinatal deaths, including 228 stillbirths and 60 neonatal deaths, so perinatal mortality rate was 63.8/1000 births. 90.28% women were unbooked. Most common cause was hypertensive disorders of pregnancy (27.78%) followed by antepartum haemorrhage (25.71%) and then mechanical causes (13.88%). Congenital anomalies comprised 11.8% cases, neonatal problems 10.07% and maternal medical disorders for 4.16% cases. Cause of 4.16% cases remained unexplained. Conclusion: Appropriate strategies like control of identifiable causes, proper antenatal and postnatal care, healthy delivery practices and availability of emergency neonatal care facilities can bring down perinatal mortality rates.

scholarly journals Tornumonkpe Distribution: Statistical Properties and Goodness of Fit

2021 ◽  
pp. 12-22
Author(s):  
Barinaadaa John Nwikpe
Keyword(s):  
Goodness Of Fit ◽  
Real Life ◽  
Mathematical Expression ◽  
Information Criterion ◽  
Moment Generating Function ◽  
Data Sets ◽  
The Moment ◽  
The One ◽  
Coefficient Of Skewness ◽  
New Distribution

A new sole parameter probability distribution named the Tornumonkpe distribution has been derived in this paper. The new model is a blend of gamma (2,  and gamma(3  distributions. The shape of its density for different values of the parameter has been shown.  The mathematical expression for the moment generating function, the first three raw moments, the second and third moments about the mean, the distribution of order statistics, coefficient of variation and coefficient of skewness has been given. The parameter of the new distribution was estimated using the method of maximum likelihood. The goodness of fit of the Tornumonkpe distribution was established by fitting the distribution to three real life data sets. Using -2lnL, Bayesian Information Criterion (BIC), and Akaike Information Criterion(AIC) as criterial for selecting the best fitting model, it was revealed that the new distribution outperforms the one parameter exponential, Shanker and Amarendra distributions for the data sets used.

Trends in Deaths Fully Attributable to Alcohol in Minnesota, 2000-2018

2021 ◽  
pp. 003335492110440
Author(s):  
Nicholas J. Braun ◽  
Kari M. Gloppen ◽  
Jon Roesler
Keyword(s):  
Mortality Rate ◽  
American Indian ◽  
Alaska Native ◽  
Average Rate ◽  
Ethnic Disparities ◽  
Mortality Rates ◽  
Native People ◽  
Attributable Mortality ◽  
Mortality Data ◽  
Alcohol Outlet

Objective Overall trends in rates of fully alcohol-attributable mortality may mask disparities among demographic groups. We investigated overall, demographic, and geographic trends in fully alcohol-attributable mortality rates in Minnesota. Methods We obtained mortality data from Minnesota death certificates and defined fully alcohol-attributable deaths as deaths that would not occur in the absence of alcohol. We calculated age-adjusted death rates during 2000-2018 using 5-year moving averages stratified by decedents’ characteristics and geographic location. Results Chronic conditions accounted for most of the alcohol-attributable deaths in Minnesota (89% during 2014-2018). Alcohol-attributable mortality rates per 100 000 population increased from an average rate of 8.0 during 2000-2004 to 12.6 during 2014-2018. During 2000-2018, alcohol-attributable mortality rates were highest among males (vs females), adults aged 55-64 (vs other ages), and American Indian/Alaska Native people (vs other racial and ethnic groups) and lowest among people aged ≤24 years and Asian or Pacific Islander people. During 2014-2018, the alcohol-attributable mortality rate among American Indian/Alaska Native people was more than 5 times higher than the overall mortality rate in Minnesota. Conclusions Results from this study may increase awareness of racial and ethnic disparities and continuing health inequities and inform public health prevention efforts, such as those recommended by the Community Preventive Services Task Force, including regulating alcohol outlet density and increasing alcohol taxes.

Syrian Civil War: a systematic review of trauma casualty epidemiology

2020 ◽  
pp. jramc-2019-001304
Author(s):  
Joshua McIntyre
Keyword(s):  
Civil War ◽  
Mortality Rate ◽  
Marked Change ◽  
Future Research ◽  
Common Mechanism ◽  
Mortality Data ◽  
Mechanism Of Injury ◽  
Eligibility Criteria ◽  
Data Set ◽  
Syrian Civil War

BackgroundThe Syrian Civil War has caused over 400 000 traumatic deaths. Understanding the nature of war casualties is crucial to deliver healthcare improvement. Historic regional conflicts and Syrian mortality data have been characterised by blast injuries. The aim of this novel review is to assess the trauma epidemiology of Syrian Civil War casualties from the perspective of healthcare facilities.MethodsThis review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method. Studies addressing Syria, trauma and war were investigated. Eligibility criteria included being conducted from a healthcare facility, published in English and peer reviewed. The outcomes were demography, mechanism of injury and anatomical injury site.Results38 papers satisfied the eligibility criteria. 13 842 casualties were reported across the entire data set. Casualties were 88.8% male (n=4035 of 4544). Children contributed to 16.1% of cases (n=398 of 2469). Mortality rate was 8.6% (n=412 of 4774). Gunshot wound was the most common mechanism of injury representing 66.3% (n=7825 of 11799). Head injury was the most common injured site at 26.6% (n=719 of 2701).ConclusionsThis conflict has a distinct trauma profile compared with regional modern wars. The prevalence of gunshot wounds represents a marked change in mechanism of injury. This may be related to higher mortality rate and proportion of head injuries identified. This review cannot correlate mechanism of injury, demographics or injuries sustained to outcomes. The quality of data from the included studies lacked standardisation; future research and consistent reporting tools are required to enable further analysis.

scholarly journals Variability in the Power Spectrum of Solar Five-Minute Oscillations

1983 ◽  
Vol 66 ◽  
pp. 411-425
Author(s):  
Frank Hill ◽  
Juri Toomre ◽  
Laurence J. November
Keyword(s):  
Large Scale ◽  
Solar Rotation ◽  
Temporal Frequency ◽  
Power Spectra ◽  
Giant Cells ◽  
Spectral Lines ◽  
Data Sets ◽  
Data Set ◽  
Temporal Sampling ◽  
Velocity Changes

AbstractTwo-dimensional power spectra of solar five-minute oscillations display prominent ridge structures in (k, ω) space, where k is the horizontal wavenumber and ω is the temporal frequency. The positions of these ridges in k and ω can be used to probe temperature and velocity structures in the subphotosphere. We have been carrying out a continuing program of observations of five-minute oscillations with the diode array instrument on the vacuum tower telescope at Sacramento Peak Observatory (SPO). We have sought to establish whether power spectra taken on separate days show shifts in ridge locations; these may arise from different velocity and temperature patterns having been brought into our sampling region by solar rotation. Power spectra have been obtained for six days of observations of Doppler velocities using the Mg I λ5173 and Fe I λ5434 spectral lines. Each data set covers 8 to 11 hr in time and samples a region 256″ × 1024″ in spatial extent, with a spatial resolution of 2″ and temporal sampling of 65 s. We have detected shifts in ridge locations between certain data sets which are statistically significant. The character of these displacements when analyzed in terms of eastward and westward propagating waves implies that changes have occurred in both temperature and horizontal velocity fields underlying our observing window. We estimate the magnitude of the velocity changes to be on the order of 100 m s -1; we may be detecting the effects of large-scale convection akin to giant cells.

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