scholarly journals Modelling fatality curves of COVID-19 and the effectiveness of intervention strategies

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9421 ◽  
Author(s):  
Giovani L. Vasconcelos ◽  
Antônio M.S. Macêdo ◽  
Raydonal Ospina ◽  
Francisco A.G. Almeida ◽  
Gerson C. Duarte-Filho ◽  
...  
Keyword(s):  
Growth Model ◽  
Intervention Strategies ◽  
Analytic Formula ◽  
The Other ◽  
Cumulative Number ◽  
Window Of Opportunity ◽  
Intervention Model ◽  
Growth Regime ◽  
Johns Hopkins University ◽  
Richards Growth Model

The main objective of the present article is twofold: first, to model the fatality curves of the COVID-19 disease, as represented by the cumulative number of deaths as a function of time; and second, to use the corresponding mathematical model to study the effectiveness of possible intervention strategies. We applied the Richards growth model (RGM) to the COVID-19 fatality curves from several countries, where we used the data from the Johns Hopkins University database up to May 8, 2020. Countries selected for analysis with the RGM were China, France, Germany, Iran, Italy, South Korea, and Spain. The RGM was shown to describe very well the fatality curves of China, which is in a late stage of the COVID-19 outbreak, as well as of the other above countries, which supposedly are in the middle or towards the end of the outbreak at the time of this writing. We also analysed the case of Brazil, which is in an initial sub-exponential growth regime, and so we used the generalised growth model which is more appropriate for such cases. An analytic formula for the efficiency of intervention strategies within the context of the RGM is derived. Our findings show that there is only a narrow window of opportunity, after the onset of the epidemic, during which effective countermeasures can be taken. We applied our intervention model to the COVID-19 fatality curve of Italy of the outbreak to illustrate the effect of several possible interventions.

scholarly journals Modelling fatality curves of COVID-19 and the effectiveness of intervention strategies

2020 ◽  
Author(s):  
Giovani L. Vasconcelos ◽  
Antônio M. S. Macêdo ◽  
Raydonal Ospina ◽  
Francisco A. G. Almeida ◽  
Gerson C. Duarte-Filho ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Growth Model ◽  
Intervention Strategies ◽  
Analytic Formula ◽  
Cumulative Number ◽  
Window Of Opportunity ◽  
Intervention Model ◽  
Growth Regime ◽  
Johns Hopkins University ◽  
Richards Growth Model

ABSTRACTThe main objective of the present paper is twofold: first, to model the fatality curves of the COVID-19 disease, as represented by the cumulative number of deaths as a function of time; and second, to use the corresponding mathematical model to study the effectiveness of possible intervention strategies. We applied the Richards growth model (RGM) to the COVID-19 fatality curves from several countries, where we used the data from the Johns Hopkins University database up to April 1, 2020. Countries selected for analysis were China, Italy, Spain, Iran, and Brazil. The RGM was shown to describe very well the fatality curves of China, which is in a late stage of the COVID-19 outbreak, as well as of Italy, Spain, and Iran, which supposedly are in the middle of the outbreak at the time of this writing. As for Brazil, which is still in the so-called exponential growth regime, we used the generalized growth model which is more appropriate for such cases. An analytic formula for the efficiency of intervention strategies within the context of the RGM is derived. Our findings show that there is only a narrow window of opportunity, after the onset of the epidemic, during which effective countermeasures can be taken. We applied our intervention model to the COVID-19 fatality curve of Italy to illustrate the effect of several possible interventions.

A modification of the Ek–Payandeh nonlinear regression model for site index curves

1988 ◽  
Vol 18 (1) ◽  
pp. 115-120 ◽  
Author(s):  
R. M. Newnham
Keyword(s):  
Regression Model ◽  
Growth Model ◽  
Nonlinear Regression ◽  
Site Index ◽  
The Other ◽  
Nonlinear Regression Model ◽  
Minimum Loss ◽  
Unconstrained Model ◽  
Pass Through ◽  
Richards Growth Model

A new nonlinear regression model for constructing site index curves is described that, unlike previous models based on the Chapman–Richards growth model, produces sets of curves that are constrained to pass through the appropriate height at the index age as well as through the origin. The model was tested on two sets of height–age data, one from published yield tables and the other from stem analyses, and was found to give a good fit in both cases. There was a minimum loss of accuracy compared with a similar, unconstrained model.

scholarly journals Using different epidemiological models to modeling the epidemic dynamics in Brazil

2020 ◽  
Author(s):  
Lucas Ravellys Pyrrho de Alcantara ◽  
Lucio Silva ◽  
Anderson Rodrigues de Almeida ◽  
Maira Galdino da Rocha Pitta ◽  
Artur Paiva Coutinho
Keyword(s):  
Growth Model ◽  
Logistic Growth ◽  
Cumulative Number ◽  
Mean Square ◽  
Epidemiological Models ◽  
Epidemic Dynamics ◽  
Absolute Relative Error ◽  
Logistic Growth Model ◽  
Richards Growth Model

In this paper we provide forecasts of the cumulative number of confirmed reported cases in Brazil, specifically in Pernambuco and Ceara, by using the generalized logistic growth model, the Richards growth model and Susceptible, Un-quanrantined infected, Quarantined infected, Confirmed infected (SUQC) phenomenological model. We rely on the Nash-Sutcliffe efficiency (NSE), root-mean-square error (RMSE) and mean absolute relative error (MARE) to quantify the quality of the models fits during the calibrationAll of these analyzes have been valid until the present date, April 14, 2020. The different models provide insights of our scenario predictions.

scholarly journals Growth of the tambaqui Colossoma macropomum (Cuvier) (Characiformes: Characidae): which is the best model?

2005 ◽  
Vol 65 (1) ◽  
pp. 129-139 ◽  
Author(s):  
M. A. H Penna ◽  
M. A Villacorta-Corrêa ◽  
T. Walter ◽  
M. Petrere-JR
Keyword(s):  
Growth Model ◽  
Negative Correlation ◽  
The Other ◽  
Data Sources ◽  
Von Bertalanffy ◽  
Data Set ◽  
Colossoma Macropomum ◽  
Von Bertalanffy Model ◽  
Estimated Parameters ◽  
Schnute Model

In order to decide which is the best growth model for the tambaqui Colossoma macropomum Cuvier, 1818, we utilized 249 and 256 length-at-age ring readings in otholiths and scales respectively, for the same sample of individuals. The Schnute model was utilized and it is concluded that the Von Bertalanffy model is the most adequate for these data, because it proved highly stable for the data set, and only slightly sensitive to the initial values of the estimated parameters. The phi' values estimated from five different data sources presented a CV = 4.78%. The numerical discrepancies between these values are of not much concern due to the high negative correlation between k and L<FONT FACE=Symbol>¥</FONT> viz, so that when one of them increases, the other decreases and the final result in phi' remains nearly unchanged.

LORENZO'S OIL AND ADENOLEUKODYSTROPHY

PEDIATRICS ◽  
1994 ◽  
Vol 93 (5) ◽  
pp. 755-755
Author(s):  
J. F. L.
Keyword(s):  
Pilot Study ◽  
Medical Science ◽  
Hereditary Disease ◽  
The Other ◽  
Medical Establishment ◽  
School Of Medicine ◽  
Natural Oils ◽  
Johns Hopkins University ◽  
Important Symptom ◽  
Lorenzo’S Oil

The new movie "Lorenzo's Oil" tells how the parents of a child with a rare illness overcame indifference in the medical establishment and, by themselves, invented a cure. The message is that medical science has become detached from the needs of those it serves, but that individuals can leap bureaucratic impediments to find new cures with their own faith and efforts ... According to the movie and the account of the parents, Augusto and Michaela Odone of Fairfax, Va., they refused to accept doctors' advice that there was no hope for their son, Lorenzo, after they were told in 1984 that he was suffering from a rare hereditary disease known as adenoleukodystrophy ... ... they defied the medical establishment's pessimism, read obscure medical journals and figured that a mixture of two natural oils, known as erucic and oleic acids, would correct an important symptom of the disease ... Dr. Rizzo began the first pilot study of the oil in August 1987. Six of 8 boys in the study deteriorated rapidly. The other two seemed to stabilize for a time, but one has now had a relapse and investigators have lost contact with the other. In a study by Dr. Hugo Moser of Johns Hopkins University School of Medicine, 70 children with the rapidly progressing disease used the oil from the time of their first symptoms until they lost sight and movement. The oil, Dr. Moser concluded, "did not make any difference." Dr. Moser said that so far he had seen no evidence that Lorenzo's disease could be prevented in boys who were otherwise destined to get it ...

Impact of Theory of Accident Causation on Intervention Strategies

1979 ◽  
Vol 23 (1) ◽  
pp. 225-229 ◽  
Author(s):  
Jasper E. Shealy
Keyword(s):  
Data Base ◽  
Intervention Strategies ◽  
The Other ◽  
Effective Intervention ◽  
Accident Causation ◽  
Accident Data ◽  
The Way

Paper shows how the belief that one has about how accidents happen (Theory of Accident Causation) affects the design of the Accident Report Form, the type of information gathered, the nature of your accident data base, the analysis of the data and, finally, the way in which you intervene in the situation. Two different approaches are examined, one which is typical of most existing systems, the other represents a much improved system that points the way to more effective intervention strategies.

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