Jacques Demongeot
Profile Url: jacques-demongeot
Researcher at Laboratory AGEIS EA 7407, Team Tools for e-Gnosis Medical and Labcom CNRS/UGA/OrangeLabs Telecom4Health, Faculty of Medicine, Université Grenoble Alpes (UGA)
(1) Background: Here, we characterize COVID-19 2nd waves, following a study presenting negative associations between 1st wave COVID-19 spread parameters and temperature; (2) Methods: Visual examinations of daily increase in confirmed COVID-19 cases in 124 countries, determined 1st and 2nd waves in 28 countries; (3) Results: 1st wave spread rate increases with country mean elevation, temperature, time since wave onset, and median age. Spread rates decrease above 1000m, indicating high UV decrease spread rate. For 2nd waves, associations are opposite: viruses adapted to high temperature and to infect young populations. Earliest 2nd waves started April 5-7 at mutagenic high elevations (Armenia, Algeria). 2nd waves occurred also at warm-to-cold season transition (Argentina, Chile). Spread decreases in most (77%) countries. Death-to-total case ratios decrease during the 2nd wave, also when comparing with the same period for countries where the 1st wave is ongoing. In countries with late 1st wave onset, spread rates fit better 2nd than 1st wave-temperature patterns; In countries with ageing populations (examples: Japan, Sweden, Ukraine), 2nd waves only adapted to spread at higher temperatures, not to infect children. (4) Conclusions: 1st wave viruses evolved towards lower spread and mortality. 2nd wave mutant COVID-19 strain(s) adapted to higher temperature, infecting children and replace (also in cold conditions) 1st wave COVID-19 strains. Counterintuitively, low spread strains replace high spread strains, rendering prognostics and extrapolations uncertain.
(1) BackgroundThe estimation of daily reproduction rates throughout the infectivity period is rarely considered and only their sum Ro is calculated to quantify the level of virulence of an infectious agent; (2) MethodsWe give the equation of the discrete dynamics of epidemic growth and we obtain an estimation of the daily reproduction rates, by using a technique of deconvolution of the series of observed new cases of Covid-19; (3) ResultsWe give both simulation results as well as estimations for several countries for the Covid-19 outbreak; (4) ConclusionsWe discuss the role of the noise on the precision of the estimation and we open on perspectives of forecasting methods to predict the distribution of daily reproduction rates along the infectivity period.
We describe in this paper, based on already published articles, a contribution to the theory postulating the existence of a proto-ribosome, which could have appeared early at the origin of life and we discuss the interest of this notion in an evolutionary perspective, taking into account the existence of possible RNA relics of this proto-ribosome.
We present spread parameters for first and second waves of the COVID-19 pandemy for USA states, and third wave for 32 regions (19 countries and 13 states of the USA) detected beginning of August 2020. USA first/second wave spreads increase/decrease with population density, are uncorrelated with temperature and median population age. Pooling all 32 regions, third wave spread is slower than for first wave, similar to second wave, and increases with mean altitude (second wave slopes decrease above 900m). Apparently, viruses adapted in spring (second wave) to high temperatures and infecting the young, and in summer (third) waves for spread at altitudes above 1000m. Third wave slopes are not correlated to temperature, so patterns with elevation presumably indicate resistance to relatively high UV regimes. Environmental trends of the COVID-19 pandemy change at incredible rates, making predictions based on classical epidemiological knowledge particularly uncertain.
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 geoepidemiological 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 associated with incidence. Mortality and lethality rates were significantly higher in departments with older population, but they were not significantly associated with the number of intensive-care beds available in 2018. We did not find any significant association between incidence, mortality or lethality rates and incidence of new chloroquine and hydroxychloroquine dispensations in pharmacies either, nor between COVID 19 incidence and climate, nor between economic indicators and in-hospital COVID 19 incidence or mortality. This ecological study highlights the impact of population age structure, epidemic spread and transmission mitigation policies in COVID-19 morbidity or mortality heterogeneity.