scholarly journals Predicting death from COVID-19 using pre-existing conditions: implications for vaccination triage

2021 ◽  
Vol 8 (1) ◽  
pp. e001016
Author(s):  
Shujie Xiao ◽  
Neha Sahasrabudhe ◽  
Samantha Hochstadt ◽  
Whitney Cabral ◽  
Samantha Simons ◽  
...  
Keyword(s):  
Prediction Model ◽  
Case Fatality ◽  
Demographic Variables ◽  
Variable Model ◽  
Case Fatality Ratio ◽  
False Discovery ◽  
Study Population ◽  
Using Data ◽  
Selection Operator ◽  
The One

IntroductionGlobal shortages in the supply of SARS-CoV-2 vaccines have resulted in campaigns to first inoculate individuals at highest risk for death from COVID-19. Here, we develop a predictive model of COVID-19-related death using longitudinal clinical data from patients in metropolitan Detroit.MethodsAll individuals included in the analysis had a laboratory-confirmed SARS-CoV-2 infection. Thirty-six pre-existing conditions with a false discovery rate p<0.05 were combined with other demographic variables to develop a parsimonious prediction model using least absolute shrinkage and selection operator regression. The model was then prospectively validated in a separate set of individuals with confirmed COVID-19.ResultsThe study population consisted of 15 502 individuals with laboratory-confirmed SARS-CoV-2. The main prediction model was developed using data from 11 635 individuals with 709 reported deaths (case fatality ratio 6.1%). The final prediction model consisted of 14 variables with 11 comorbidities. This model was then prospectively assessed among the remaining 3867 individuals (185 deaths; case fatality ratio 4.8%). When compared with using an age threshold of 65 years, the 14-variable model detected 6% more of the individuals who would die from COVID-19. However, below age 45 years and its risk equivalent, there was no benefit to using the prediction model over age alone.DiscussionUsing a prediction model, such as the one described here, may help identify individuals who would most benefit from COVID-19 inoculation, and thereby may produce more dramatic initial drops in deaths through targeted vaccination.

scholarly journals Legionnaires’ disease in Europe, 2011 to 2015

2017 ◽  
Vol 22 (27) ◽  
Author(s):  
Julien Beauté ◽  
Keyword(s):  
Disease Surveillance ◽  
Prevention And Control ◽  
Case Fatality ◽  
Average Increase ◽  
Annual Average ◽  
Surveillance Network ◽  
Case Fatality Ratio ◽  
Study Population ◽  
Legionnaires Disease ◽  
And Control

Under the coordination of the European Centre for Disease Prevention and Control (ECDC), the European Legionnaires’ disease Surveillance Network (ELDSNet) conducts surveillance of Legionnaires’ disease (LD) in Europe. Between 2011 and 2015, 29 countries reported 30,532 LD cases to ECDC (28,188 (92.3%) confirmed and 2,344 (7.7%) probable). Four countries (France, Germany, Italy and Spain) accounted for 70.3% of all reported cases, although their combined populations represented only 49.9% of the study population. The age-standardised rate of all cases increased from 0.97 cases/100,000 population in 2011 to 1.30 cases/100,000 population in 2015, corresponding to an annual average increase of 0.09 cases/100,000 population (95%CI 0.02–0.14; p = 0.02). Demographics and infection setting remained unchanged with ca 70% of cases being community-acquired and 80% occurring in people aged 50 years and older. Clinical outcome was known for 23,164 cases, of whom 2,161 (9.3%) died. The overall case fatality ratio decreased steadily from 10.5% in 2011 to 8.1% in 2015, probably reflecting improved reporting completeness. Five countries (Austria, Czech Republic, Germany, Italy, and Norway) had increasing age-standardised LD notification rates over the 2011−15 period, but there was no increase in notification rates in countries where the 2011 rate was below 0.5/100,000 population.

scholarly journals Estimating the infection and case fatality ratio for COVID-19 using age-adjusted data from the outbreak on the Diamond Princess cruise ship

2020 ◽  
Author(s):  
Timothy W Russell ◽  
Joel Hellewell ◽  
Christopher I Jarvis ◽  
Kevin Van Zandvoort ◽  
Sam Abbott ◽  
...  
Keyword(s):  
Age Structure ◽  
Case Fatality ◽  
Cruise Ship ◽  
Case Fatality Ratio ◽  
Using Data

AbstractAdjusting for delay from confirmation-to-death, we estimated case and infection fatality ratios (CFR, IFR) for COVID-19 on the Diamond Princess ship as 2.3% (0.75%–5.3%) and 1.2% (0.38–2.7%). Comparing deaths onboard with expected deaths based on naive CFR estimates using China data, we estimate IFR and CFR in China to be 0.5% (95% CI: 0.2–1.2%) and 1.1% (95% CI: 0.3–2.4%) respectively.AimTo estimate the infection and case fatality ratio of COVID-19, using data from passengers of the Diamond Princess cruise ship while correcting for delays between confirmation-and-death, and age-structure of the population.

scholarly journals Development and Validation of a LASSO Prediction Model for Better Identification of Ischemic Stroke: A Case-Control Study in China

2021 ◽  
Vol 13 ◽  
Author(s):  
Zirui Meng ◽  
Minjin Wang ◽  
Shuo Guo ◽  
Yanbing Zhou ◽  
Mingxue Zheng ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Prediction Model ◽  
Area Under The Curve ◽  
Smartphone Application ◽  
Good Prognosis ◽  
Demographic Variables ◽  
Derivation Cohort ◽  
Model Based ◽  
Selection Operator ◽  
Time Critical

BackgroundTimely diagnosis of ischemic stroke (IS) in the acute phase is extremely vital to achieve proper treatment and good prognosis. In this study, we developed a novel prediction model based on the easily obtained information at initial inspection to assist in the early identification of IS.MethodsA total of 627 patients with IS and other intracranial hemorrhagic diseases from March 2017 to June 2018 were retrospectively enrolled in the derivation cohort. Based on their demographic information and initial laboratory examination results, the prediction model was constructed. The least absolute shrinkage and selection operator algorithm was used to select the important variables to form a laboratory panel. Combined with the demographic variables, multivariate logistic regression was performed for modeling, and the model was encapsulated within a visual and operable smartphone application. The performance of the model was evaluated on an independent validation cohort, formed by 304 prospectively enrolled patients from June 2018 to May 2019, by means of the area under the curve (AUC) and calibration.ResultsThe prediction model showed good discrimination (AUC = 0.916, cut-off = 0.577), calibration, and clinical availability. The performance was reconfirmed in the more complex emergency department. It was encapsulated as the Stroke Diagnosis Aid app for smartphones. The user can obtain the identification result by entering the values of the variables in the graphical user interface of the application.ConclusionThe prediction model based on laboratory and demographic variables could serve as a favorable supplementary tool to facilitate complex, time-critical acute stroke identification.

scholarly journals COVID-19, Physical Distancing and Social Inequalities: Are We all Really in this Together?

2020 ◽  
Vol 2 (2) ◽  
pp. 173-190
Author(s):  
Lakshmi Lingam ◽  
Rahul Suresh Sapkal
Keyword(s):  
Incidence Rate ◽  
Social Inequalities ◽  
National Level ◽  
Case Fatality ◽  
National Sample ◽  
Statistical Correlation ◽  
Sample Survey ◽  
Case Fatality Ratio ◽  
Using Data ◽  
Novel Coronavirus

In the absence of a vaccine for combating the novel coronavirus (COVID-19), countries globally are going in for a national lockdown and are mandating all people to stay indoors, and, if out in the public domain, to maintain 2-m distance, wear masks and wash hands with soap to mitigate the spread of the virus and its community transmission. The significance of the much neglected public health measures to deal with communicable diseases has come back to haunt several countries with a large proportion of people who are poor and who live in dense settlements with low levels of public provisioning of basic amenities. This article attempts to examine the feasibility of the recommended physical distancing using data from a national level sample from India. With the aid of data on parameters such as access to water, toilet, electricity, mobile phone and secure employment from the 75th and 76th National Sample Survey Rounds of 2017–2018, a Physical Distancing Readiness Index has been constructed. The performance of 27 states and 2 union territories of India is examined using the Index. This study examines the statistical correlation of a Physical Distancing Readiness Index to the incidence rate and case fatality ratio of COVID-19. Our results show that the poorer households are unequally endowed for observing physical distancing and ensuring the effective implementation of lockdown, which leads to disproportionate increase in the incidence rate and case fatality ratio, keeping other factors constant.

scholarly journals Epidemiology of Measles in Bale Zone South East Ethiopia 2019

2021 ◽  
Author(s):  
Geremew tsegaye ◽  
Yenealem gezahagn ◽  
Naod Berhanu ◽  
Gemechu Gudina
Keyword(s):  
Vaccine Coverage ◽  
Case Fatality ◽  
Immunization Coverage ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Study Population ◽  
Unknown Status ◽  
Using Data ◽  
Case Based ◽  
Bale Zone

Abstract Background: - Measles remains causes of vaccine preventable death in children worldwide. Cases comes to health facilities after complication developed, and miss diagnosed as the complication than measles, which is a reason for under reporting of measles cases and number of reported cases represents small proportion of expected cases. While aim of this study is to analyze seven years (2013-2019) measles surveillance data of Bale zone and to indicate measles surveillance related gaps. Method: - Cross sectional study conducted from May 25-June 25/2019. Study population and sample was all measles cases reported to bale zone from 2013-2019. Data abstracted by reviewing seven years measles line list and case-based report by investigator using data abstraction check list. Data entered and analyzed by Microsoft excel. Tables, graph and percent presented the data. Result: - Overall, 4241 measles cases were reported with a case fatality of 3.07/1000 population. About 248(5.8%) were measles IgM confirmed. Mean age of the case patients were 7.15 and 2147 (50.6%) were males. The most affected age group were <4 years, 1685 (39.7%) of cases. The highest prevalence rate 141 / 100,000 populations reported in 2019.Unvaccinated and unknown status were 890(21%) and 731(17.2%). The highest numbers of cases reported from Ginir and Gololcha. Measles cases increase in autumn season of the year and reaches peak in May. Conclusion: - Measles is the major causes of morbidity and Mortality in Bale zone due to poor immunization coverage, 890(21%) of case patients were un vaccinated. Though community death is not included case fatality is high. Ginir reported the highest number of cases. Increasing vaccine coverage of the zone, early preparedness before annual cycle and strengthening measles case-based surveillance is mandatory.

Stock Market Prediction using Data Mining Techniques

2020 ◽  
pp. 310-313
Author(s):  
Karunesh Makker ◽  
Prince Patel ◽  
Hrishikesh Roy ◽  
Sonali Borse
Keyword(s):  
Neural Network ◽  
Stock Market ◽  
Prediction Model ◽  
Efficient Market Hypothesis ◽  
Deterministic System ◽  
Vast Number ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Using Data ◽  
Robust Prediction

Stock market is a very volatile in-deterministic system with vast number of factors influencing the direction of trend on varying scales and multiple layers. Efficient Market Hypothesis (EMH) states that the market is unbeatable. This makes predicting the uptrend or downtrend a very challenging task. This research aims to combine multiple existing techniques into a much more robust prediction model which can handle various scenarios in which investment can be beneficial. Existing techniques like sentiment analysis or neural network techniques can be too narrow in their approach and can lead to erroneous outcomes for varying scenarios. By combing both techniques, this prediction model can provide more accurate and flexible recommendations. Embedding Technical indicators will guide the investor to minimize the risk and reap better returns.

Siblings and Illness

2011 ◽  
Vol 7 ◽  
Author(s):  
Leah Sawyer Vanderwerp
Keyword(s):  
Depressive Symptoms ◽  
Birth Order ◽  
Family Size ◽  
Multivariate Analyses ◽  
Social Role ◽  
Chronically Ill ◽  
Demographic Variables ◽  
Future Research ◽  
Mother And Child ◽  
Using Data

Using data from the National Longitudinal Survey of Youth-Mother and Child samples, I investigated the relationships among child and adolescent depressive symptoms, having a chronically ill sibling, and other child and familial demographic variables. From research on social support and social role transitions, with the Stress Process as a theoretical model, I hypothesized that children with chronically ill siblings experience more depressive symptoms. Specifically, I looked at age, gender, birth order and family size as potentially reducing the effect size of having a chronically ill sibling. Findings showed that having a chronically ill sibling is associated with demonstrating more depressive symptoms both in the bivariate and multivariate analyses. Although age, gender, birth order and family size do not interact significantly with having a chronically ill sibling in predicting depressive symptoms, they do present interesting findings about childhood depressive symptoms in general. Thus, the results of this study suggest specific and meaningful paths for future research.

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.

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