The development of phylogenetic trees based on RNA or DNA sequences generally requires a precise ... more The development of phylogenetic trees based on RNA or DNA sequences generally requires a precise and limited choice of important RNAs, e.g., messenger RNAs of essential proteins or ribosomal RNAs (like 16S), but rarely complete genomes, making it possible to explain evolution and speciation. In this article, we propose revisiting a classic phylogeny of archaea from only the information on the succession of nucleotides of their entire genome. For this purpose, we use a new tool, the unsupervised classifier Maxwell, whose principle lies in the Burrows–Wheeler compression transform, and we show its efficiency in clustering whole archaeal genomes.
Objective: The objective of this article is to develop a robust method for forecasting the transi... more Objective: The objective of this article is to develop a robust method for forecasting the transition from endemic to epidemic phases in contagious diseases using COVID-19 as a case study. Methods: Seven indicators are proposed for detecting the endemic/epidemic transition: variation coefficient, entropy, dominant/subdominant spectral ratio, skewness, kurtosis, dispersion index and normality index. Then, principal component analysis (PCA) offers a score built from the seven proposed indicators as the first PCA component, and its forecasting performance is estimated from its ability to predict the entrance in the epidemic exponential growth phase. Results: This score is applied to the retro-prediction of endemic/epidemic transitions of COVID-19 outbreak in seven various countries for which the first PCA component has a good predicting power. Conclusion: This research offers a valuable tool for early epidemic detection, aiding in effective public health responses.
The formulation of mathematical models using differential equations has become crucial in predict... more The formulation of mathematical models using differential equations has become crucial in predicting the evolution of viral diseases in a population in order to take preventive and curative measures. In December 2019, a novel variety of Coronavirus (SARS-CoV-2) was identified in Wuhan, Hubei Province, China, which causes a severe and potentially fatal respiratory syndrome. Since then, it has been declared a pandemic by the World Health Organization and has spread around the globe. A reaction–diffusion system is a mathematical model that describes the evolution of a phenomenon subjected to two processes: a reaction process, in which different substances are transformed, and a diffusion process, which causes their distribution in space. This article provides a mathematical study of the Susceptible, Exposed, Infected, Recovered, and Vaccinated population model of the COVID-19 pandemic using the bias of reaction–diffusion equations. Both local and global asymptotic stability conditions ...
It is not entirely clear why, at some stage in its evolution, terrestrial life adopted double-str... more It is not entirely clear why, at some stage in its evolution, terrestrial life adopted double-stranded DNA as the hereditary material. To explain this, we propose that small, double-stranded, polynucleotide circlets have special catalytic properties. We then use this proposal as the basis for a ‘view from here’ that we term the Circlet hypothesis as part of a broader Ring World. To maximize the potential explanatory value of this hypothesis, we speculate boldly about the origins of several of the fundamental characteristics and briefly describe the main methods or treatments applied. The principal prediction of the paper is that the highly constrained, conformational changes will occur preferentially in dsDNA, dsRNA and hybrid RNA-DNA circlets that are below a critical size (e.g., 306 bp) and that these will favor the polymerization of precursors into RNA and DNA. We conclude that the Circlet hypothesis and the Ring World therefore have the attraction of offering the same solution t...
The statistical analysis found that the mortality rate of COVID-19 infection experienced a signif... more The statistical analysis found that the mortality rate of COVID-19 infection experienced a significant decline in the early stage of the epidemic. We suspect that the sharp deterioration of virus toxicity is related to point mutation and the deletion of the untranslated region of the virus genome. Through sequence analysis of mega-genome data, we found that the genome length of COVID-19 was deleted, which mainly occurred in the untranslated regions at both ends. Sequence similarity analysis further indicated that short UTR length strain emerged by deleting strain with long sequence length. This process is irreversible; the genome with a short sequence length could not restore to the long sequence length. By studying the relationship between genome length and mortality, we found a good correlation between them statistically, which demonstrated that the deletion of the untranslated region of the virus significantly affected the toxicity of the virus. We extracted the viral genome leng...
We extend the classical approach in supervised classification based on the local likelihood estim... more We extend the classical approach in supervised classification based on the local likelihood estimation to the functional covariates case. The estimation procedure of the functional parameter (slope parameter) in the linear model when the covariate is of functional kind is investigated. We show, on simulated as well on real data, that classification error rates estimated using test samples, and the estimation procedure by local likelihood seem to lead to better estimators than the classical kernel estimation. In addition, this approach is no longer assuming that the linear predictors have a specific parametric form. However, this approach also has two drawbacks. Indeed, it was more expensive and slower than the kernel regression. Thus, as mentioned earlier, kernels other than the Gaussian kernel can lead to a divergence of the Newton-Raphson algorithm. In contrast, using a Gaussian kernel, 4 to 6 iterations are then sufficient to achieve convergence.
L'aide a domicile en SESPAO (Surveillance, Education et Soins Personnalises Assistes par Ordi... more L'aide a domicile en SESPAO (Surveillance, Education et Soins Personnalises Assistes par Ordinateur) propose de nombreuses applications utiles pour le suivi des personnages âgees a domicile. Cette technologie permet entre autres la detection d'une chute, d'un malaise ou d'un episode pouvant necessiter une intervention, la surveillance d'un etat stabilise ou encore l'entree progressive dans une pathologie a l'aide de l'observation d'un certain nombres de symptomes. Apres un etat des lieux des differents capteurs existants en SESPAO et de leurs environnements virtuels, cet article interroge sur la portee ethique de ces technologies et offre une piste de reflexion sur les avancees futures.
SummaryBackgroundThe COVID-19 epidemic, which started in late December 2019 and rapidly spread th... more SummaryBackgroundThe COVID-19 epidemic, which started in late December 2019 and rapidly spread throughout the world, was accompanied by an unprecedented release of reported case data. Our objective is to propose a fresh look at this data by coupling a phenomenological description to the epidemiological dynamics.MethodsWe use a phenomenological model to describe and regularize the data. This model can be matched by a single mathematical model reproducing the epidemiological dynamics with a time-dependent transmission rate. We provide a method to compute this transmission rate and reconstruct the changes in the social interactions between people as well as changes in host-pathogen interactions. This method is applied to the cumulative case data of 8 different geographic areas.FindingsWe reconstruct the transmission rate from the data, therefore we are in position to understand the contribution of the dynamical effects of social interactions (contacts between individuals) and the contr...
Like in many countries and regions, spread of the COVID-19 pandemic has exhibited important spati... more Like in many countries and regions, spread of the COVID-19 pandemic has exhibited important spatial heterogeneity across France, one of the most affected countries so far.To better understand factors associated with incidence, mortality and lethality heterogeneity across the 96 administrative departments of metropolitan France, we thus conducted a geo-epidemiological analysis based on publicly available data, using hierarchical ascendant classification (HAC) on principal component analysis (PCA) of multidimensional variables, and multivariate analyses with generalized additive models (GAM).Our results confirm a marked spatial heterogeneity of in-hospital COVID-19 incidence and mortality, following the North East – South West diffusion of the epidemic. The delay elapsed between the first COVID-19 associated death and the onset of the national lockdown on March 17th, 2020, appeared positively associated with in-hospital incidence, mortality and lethality. Mortality was also strongly a...
The article is devoted to the parameters identification in the SI model. We consider several meth... more The article is devoted to the parameters identification in the SI model. We consider several methods, starting with an exponential fit of the early cumulative data of Sars-CoV2 in mainland China. The present methodology provides a way to compute the parameters at the early stage of the epidemic. Next, we establish an identifiability result. Then we use the Bernoulli-Verhulst model as a phenomenological model to fit the data and derive some results on the parameters identification. The last part of the paper is devoted to some numerical algorithms to fit a daily piecewise constant rate of transmission.
The development of phylogenetic trees based on RNA or DNA sequences generally requires a precise ... more The development of phylogenetic trees based on RNA or DNA sequences generally requires a precise and limited choice of important RNAs, e.g., messenger RNAs of essential proteins or ribosomal RNAs (like 16S), but rarely complete genomes, making it possible to explain evolution and speciation. In this article, we propose revisiting a classic phylogeny of archaea from only the information on the succession of nucleotides of their entire genome. For this purpose, we use a new tool, the unsupervised classifier Maxwell, whose principle lies in the Burrows–Wheeler compression transform, and we show its efficiency in clustering whole archaeal genomes.
Objective: The objective of this article is to develop a robust method for forecasting the transi... more Objective: The objective of this article is to develop a robust method for forecasting the transition from endemic to epidemic phases in contagious diseases using COVID-19 as a case study. Methods: Seven indicators are proposed for detecting the endemic/epidemic transition: variation coefficient, entropy, dominant/subdominant spectral ratio, skewness, kurtosis, dispersion index and normality index. Then, principal component analysis (PCA) offers a score built from the seven proposed indicators as the first PCA component, and its forecasting performance is estimated from its ability to predict the entrance in the epidemic exponential growth phase. Results: This score is applied to the retro-prediction of endemic/epidemic transitions of COVID-19 outbreak in seven various countries for which the first PCA component has a good predicting power. Conclusion: This research offers a valuable tool for early epidemic detection, aiding in effective public health responses.
The formulation of mathematical models using differential equations has become crucial in predict... more The formulation of mathematical models using differential equations has become crucial in predicting the evolution of viral diseases in a population in order to take preventive and curative measures. In December 2019, a novel variety of Coronavirus (SARS-CoV-2) was identified in Wuhan, Hubei Province, China, which causes a severe and potentially fatal respiratory syndrome. Since then, it has been declared a pandemic by the World Health Organization and has spread around the globe. A reaction–diffusion system is a mathematical model that describes the evolution of a phenomenon subjected to two processes: a reaction process, in which different substances are transformed, and a diffusion process, which causes their distribution in space. This article provides a mathematical study of the Susceptible, Exposed, Infected, Recovered, and Vaccinated population model of the COVID-19 pandemic using the bias of reaction–diffusion equations. Both local and global asymptotic stability conditions ...
It is not entirely clear why, at some stage in its evolution, terrestrial life adopted double-str... more It is not entirely clear why, at some stage in its evolution, terrestrial life adopted double-stranded DNA as the hereditary material. To explain this, we propose that small, double-stranded, polynucleotide circlets have special catalytic properties. We then use this proposal as the basis for a ‘view from here’ that we term the Circlet hypothesis as part of a broader Ring World. To maximize the potential explanatory value of this hypothesis, we speculate boldly about the origins of several of the fundamental characteristics and briefly describe the main methods or treatments applied. The principal prediction of the paper is that the highly constrained, conformational changes will occur preferentially in dsDNA, dsRNA and hybrid RNA-DNA circlets that are below a critical size (e.g., 306 bp) and that these will favor the polymerization of precursors into RNA and DNA. We conclude that the Circlet hypothesis and the Ring World therefore have the attraction of offering the same solution t...
The statistical analysis found that the mortality rate of COVID-19 infection experienced a signif... more The statistical analysis found that the mortality rate of COVID-19 infection experienced a significant decline in the early stage of the epidemic. We suspect that the sharp deterioration of virus toxicity is related to point mutation and the deletion of the untranslated region of the virus genome. Through sequence analysis of mega-genome data, we found that the genome length of COVID-19 was deleted, which mainly occurred in the untranslated regions at both ends. Sequence similarity analysis further indicated that short UTR length strain emerged by deleting strain with long sequence length. This process is irreversible; the genome with a short sequence length could not restore to the long sequence length. By studying the relationship between genome length and mortality, we found a good correlation between them statistically, which demonstrated that the deletion of the untranslated region of the virus significantly affected the toxicity of the virus. We extracted the viral genome leng...
We extend the classical approach in supervised classification based on the local likelihood estim... more We extend the classical approach in supervised classification based on the local likelihood estimation to the functional covariates case. The estimation procedure of the functional parameter (slope parameter) in the linear model when the covariate is of functional kind is investigated. We show, on simulated as well on real data, that classification error rates estimated using test samples, and the estimation procedure by local likelihood seem to lead to better estimators than the classical kernel estimation. In addition, this approach is no longer assuming that the linear predictors have a specific parametric form. However, this approach also has two drawbacks. Indeed, it was more expensive and slower than the kernel regression. Thus, as mentioned earlier, kernels other than the Gaussian kernel can lead to a divergence of the Newton-Raphson algorithm. In contrast, using a Gaussian kernel, 4 to 6 iterations are then sufficient to achieve convergence.
L'aide a domicile en SESPAO (Surveillance, Education et Soins Personnalises Assistes par Ordi... more L'aide a domicile en SESPAO (Surveillance, Education et Soins Personnalises Assistes par Ordinateur) propose de nombreuses applications utiles pour le suivi des personnages âgees a domicile. Cette technologie permet entre autres la detection d'une chute, d'un malaise ou d'un episode pouvant necessiter une intervention, la surveillance d'un etat stabilise ou encore l'entree progressive dans une pathologie a l'aide de l'observation d'un certain nombres de symptomes. Apres un etat des lieux des differents capteurs existants en SESPAO et de leurs environnements virtuels, cet article interroge sur la portee ethique de ces technologies et offre une piste de reflexion sur les avancees futures.
SummaryBackgroundThe COVID-19 epidemic, which started in late December 2019 and rapidly spread th... more SummaryBackgroundThe COVID-19 epidemic, which started in late December 2019 and rapidly spread throughout the world, was accompanied by an unprecedented release of reported case data. Our objective is to propose a fresh look at this data by coupling a phenomenological description to the epidemiological dynamics.MethodsWe use a phenomenological model to describe and regularize the data. This model can be matched by a single mathematical model reproducing the epidemiological dynamics with a time-dependent transmission rate. We provide a method to compute this transmission rate and reconstruct the changes in the social interactions between people as well as changes in host-pathogen interactions. This method is applied to the cumulative case data of 8 different geographic areas.FindingsWe reconstruct the transmission rate from the data, therefore we are in position to understand the contribution of the dynamical effects of social interactions (contacts between individuals) and the contr...
Like in many countries and regions, spread of the COVID-19 pandemic has exhibited important spati... more Like in many countries and regions, spread of the COVID-19 pandemic has exhibited important spatial heterogeneity across France, one of the most affected countries so far.To better understand factors associated with incidence, mortality and lethality heterogeneity across the 96 administrative departments of metropolitan France, we thus conducted a geo-epidemiological analysis based on publicly available data, using hierarchical ascendant classification (HAC) on principal component analysis (PCA) of multidimensional variables, and multivariate analyses with generalized additive models (GAM).Our results confirm a marked spatial heterogeneity of in-hospital COVID-19 incidence and mortality, following the North East – South West diffusion of the epidemic. The delay elapsed between the first COVID-19 associated death and the onset of the national lockdown on March 17th, 2020, appeared positively associated with in-hospital incidence, mortality and lethality. Mortality was also strongly a...
The article is devoted to the parameters identification in the SI model. We consider several meth... more The article is devoted to the parameters identification in the SI model. We consider several methods, starting with an exponential fit of the early cumulative data of Sars-CoV2 in mainland China. The present methodology provides a way to compute the parameters at the early stage of the epidemic. Next, we establish an identifiability result. Then we use the Bernoulli-Verhulst model as a phenomenological model to fit the data and derive some results on the parameters identification. The last part of the paper is devoted to some numerical algorithms to fit a daily piecewise constant rate of transmission.
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Papers by Jacques Demongeot