Non Pharmaceutical Interventions, Hospital Overload and Excess Mortality: Statistical Analysis and Mathematical Study of the NPIs Results in 'COVID19' Outbreak

2020 ◽  
Author(s):  
Gilles Pech de Laclause ◽  
Arnaud Delenda
Keyword(s):  
Statistical Analysis ◽  
Excess Mortality ◽  
Mathematical Study ◽  
Pharmaceutical Interventions

scholarly journals Assessing the lockdown effect from excess mortalities

2021 ◽  
Author(s):  
Alexej Weber
Keyword(s):  
Growth Rate ◽  
South Korea ◽  
Growth Rates ◽  
Excess Mortality ◽  
Reproduction Number ◽  
Average Growth Rate ◽  
Average Growth ◽  
Reproduction Numbers ◽  
The Difference ◽  
Pharmaceutical Interventions

AbstractBackground and AimsThe reported case numbers of COVID-19 are often used to estimate the reproduction number or the growth rate. We use the excess mortality instead, showing the difference between most restrictive non-pharmaceutical interventions (mrNPIs) and less restrictive NPIs (lrNPIs) with respect to the growth rate and death counts.MethodsWe estimate the COVID-19 growth rate for Sweden, South Korea, Italy and Germany from the excess mortality. We use the average growth rate obtained for Sweden and South Korea, two countries with lrNPIs, to estimate additional death numbers in Germany and Italy (two countries with mrNPIs) in a hypothetic lrNPIs scenario.ResultsThe growth rate estimated from excess mortality decreased faster for Germany and Italy than for Sweden and South Korea, suggesting that the mrNPIs have a non-negligible effect. This is not visible when the growth rate is calculated using the reported case numbers of COVID-19. This results in approximately 4 500 and 12 000 more death numbers for Germany and Italy, respectively.ConclusionThe reproduction numbers or growth rates obtained from reported COVID-19 cases are most likely biased. Expanding testing capacity led to an overestimation of the growth rate across all countries analyzed, masking the true decrease already visible in the excess mortality. Using our method, a more realistic estimate of the growth rate is obtained. Conclusions made for the reproduction number derived from the reported case numbers like the insignificance of most restrictive non-pharmaceutical interventions (lockdowns) might be wrong and have to be reevaluated using the growth rates obtained with our method.

scholarly journals Early Phase of the COVID-19 Outbreak in Hungary and Post-Lockdown Scenarios

Viruses ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 708 ◽  
Author(s):  
Gergely Röst ◽  
Ferenc A. Bartha ◽  
Norbert Bogya ◽  
Péter Boldog ◽  
Attila Dénes ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Spatial Heterogeneity ◽  
Early Phase ◽  
Disease Burden ◽  
Compartmental Model ◽  
Seasonal Effects ◽  
Low Levels ◽  
Age Structured ◽  
Epidemic Wave ◽  
Pharmaceutical Interventions

COVID-19 epidemic has been suppressed in Hungary due to timely non-pharmaceutical interventions, prompting a considerable reduction in the number of contacts and transmission of the virus. This strategy was effective in preventing epidemic growth and reducing the incidence of COVID-19 to low levels. In this report, we present the first epidemiological and statistical analysis of the early phase of the COVID-19 outbreak in Hungary. Then, we establish an age-structured compartmental model to explore alternative post-lockdown scenarios. We incorporate various factors, such as age-specific measures, seasonal effects, and spatial heterogeneity to project the possible peak size and disease burden of a COVID-19 epidemic wave after the current measures are relaxed.

scholarly journals Can medication mitigate the need for a strict lock down?: A mathematical study of control strategies for COVID-19 infection

2020 ◽  
Author(s):  
Mohsin Ali ◽  
Mudassar Imran ◽  
Adnan Khan
Keyword(s):  
Reproduction Number ◽  
Virus Disease ◽  
Control Strategies ◽  
Effective Control ◽  
Control Mechanisms ◽  
Mathematical Study ◽  
Epidemic Curve ◽  
The World ◽  
Asymptomatic Individuals ◽  
Pharmaceutical Interventions

Abstract BackgroundCOVID-19 is a pandemic that has swept across the world in 2020. To date the only effective control mechanisms were non-pharmaceutical interventions, however there have been encouraging reports regarding possible medication in the literature, with emergency approval given to some drugs in various countries.MethodsWe formulate a deterministic epidemic model to study the effects of medication on the transmission dynamics of Corona Virus Disease (COVID-19). We are especially interested in how the availability of medication could change the necessary quarantine measures for effective control of the disease. We model the transmission by extending the SEIR model to include asymptomatic, quarantined, isolated and medicated population compartments.ResultsWe calculate the basic reproduction number R0 and show that for R0<1 the disease dies out and for R0>1 the disease is endemic. Using sensitivity analysis we establish that R0 is most sensitive to the rates of quarantine and medication. We also study how the effectiveness and the rate of medication along with the quarantine rate affect R0. We devise optimal quarantine, medication and isolation strategies, noting that availability of medication reduces the duration and severity of the lock-down needed for effective disease control.ConclusionOur study also reinforces the idea that with the availability of medication, while the severity of the lock downs can be eased over time some social distancing protocols need to be observed, at least till a vaccine is found. We also analyze the COVID-19 outbreak data for four different countries, in two of these, India and Pakistan the curve is still rising, and in he other two, Italy and Spain, the epidemic curve is now falling due to effective quarantine measures. We provide estimates of R0 and the proportion of asymptomatic individuals in the population for these countries.

scholarly journals Early phase of the COVID-19 outbreak in Hungary and post-lockdown scenarios

2020 ◽  
Author(s):  
Gergely Röst ◽  
Ferenc A. Bartha ◽  
Norbert Bogya ◽  
Péter Boldog ◽  
Attila Dénes ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Spatial Heterogeneity ◽  
Early Phase ◽  
Disease Burden ◽  
Compartmental Model ◽  
Seasonal Effects ◽  
Low Levels ◽  
Age Structured ◽  
Epidemic Wave ◽  
Pharmaceutical Interventions

AbstractCOVID-19 epidemic has been suppressed in Hungary due to timely non-pharmaceutical interventions, prompting a huge reduction in the number of contacts and transmission of the virus. This strategy was effective in preventing epidemic growth and reducing the incidence of COVID-19 to low levels. In this report, we present the first epidemiological and statistical analysis of the early phase of the COVID-19 outbreak in Hungary. Then, we establish an age-structured compartmental model to explore alternative post-lockdown scenarios. We incorporate various factors, such as age-specific measures, seasonal effects, and spatial heterogeneity to project the possible peak size and disease burden of a COVID-19 epidemic wave after the current measures are relaxed.

scholarly journals Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Mogadishu, Somalia

2021 ◽  
Author(s):  
Abdihamid Warsame ◽  
Farah Bashiir ◽  
Terri Freemantle ◽  
Chris Williams ◽  
Yolanda Vazquez ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Excess Mortality

scholarly journals A first study on the impact of current and future control measures on the spread of COVID-19 in Germany

2020 ◽  
Author(s):  
Maria Vittoria Barbarossa ◽  
Jan Fuhrmann ◽  
Julian Heidecke ◽  
Hridya Vinod Varma ◽  
Noemi Castelletti ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Control Measures ◽  
The Novel ◽  
Mathematical Study ◽  
Preliminary Results ◽  
Novel Coronavirus ◽  
The Impact ◽  
Pharmaceutical Interventions

AbstractThe novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe, with about 571,700 confirmed cases and about 26,500 deaths as of March 28th, 2020. We present here the preliminary results of a mathematical study directed at informing on the possible application or lifting of control measures in Germany. The developed mathematical models allow to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

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