Unpredictable, Counter-Intuitive Geoclimatic and Demographic Correlations of COVID-19 Spread Rates

We present spread parameters for first and second waves of the COVID-19 pandemic for USA states, and for consecutive nonoverlapping periods of 20 days for the USA and 51 countries across the globe. We studied spread rates in the USA states and 51 countries, and analyzed associations between spread rates at different periods, and with temperature, elevation, population density and age. USA first/second wave spread rates increase/decrease with population density, and are uncorrelated with temperature and median population age. Spread rates are systematically inversely proportional to those estimated 80–100 days later. Ascending/descending phases of the same wave only partially explain this. Directions of correlations with factors such as temperature and median age flip. Changes in environmental trends of the COVID-19 pandemic remain unpredictable; predictions based on classical epidemiological knowledge are highly uncertain. Negative associations between population density and spread rates, observed in independent samples and at different periods, are most surprising. We suggest that systematic negative associations between spread rates 80–100 days apart could result from confinements selecting for greater contagiousness, a potential double-edged sword effect of confinements.

Modernization of Mining Scheme in Developing Peat Deposit

The article presents the results of the study of a peat deposit development scheme with improved spread parameters. The parameters are improved by forming the spread as moulded particles of a certain shape and size determined by the size of moulding machine grooves and the degree of peat relaxation. To obtain such particles a milling cutter is proposed to be replaced by a moulding mill at the stage of peat deposit milling. When excavated, the peat mass is loosened and fed into a roller moulding machine where the rollers, rotating in opposite directions, capture it and the peat is compressed. The loose structure changes into dense particle-particle packing. The circumferential speeds of roller rotations are equal. A trapezoidal groove profile is chosen for the moulded particles to leave it. The groove depth is 10 mm. The uniformity of the moulded enlarged particle distribution over a drying field is characterized by a spread variation coefficient, which allows the spread quality to be evaluated. The enlarged particle spread is normalized by some cumulative actions characterizing the spread by parameters (the thickness, the average particle size, the size uniformity, the number of layers). Therefore, the drying of enlarged particles is intensified and peat yield per unit area is increased.

Numerical assessment of the spread dynamics of the new coronavirus infection SARS-CoV-2 using multicompartmental models with distributed parameters

We propose multicompartmental models of infectious diseases dynamics for numerical study of the spread parameters of the new coronavirus infection SARS-CoV-2, which take into account the delay effects associated with the presence of the latent period of the infection, as well as the possibility of an asymptomatic course of the disease. The dynamics of the spread of COVID-19 in the Russian Federation was investigated, using these models with distributed parameters that formalize the interactions of the models’ compartments. The paper provides numerical estimates of the spread dynamics of the new coronavirus infection in various age groups of the population. We also investigate possible consequences of the mask regime and quarantine measures. We obtain an explicit estimate allowing to assess the necessary scope of these measures for the epidemy extinction.

Pandemic Management With Social Media Analytics

Social media analytics appears as one of recently developing disciplines that helps understand public perception, reaction, and emerging developments. Particularly, pandemics are one of overwhelming phenomena that push public concerns and necessitate serious management. It turned to be a useful tool to understand the thoughts, concerns, needs, expectations of public and individuals, and supports public authorities to take measures for handling pandemics. It can also be used to predict the spread of the virus, spread parameters, and to estimate the number of cases in the future. In this chapter, recent literature on use of social media analytics in pandemic management is overviewed covering all relevant studies on various aspects of pandemic management. It also introduces social media data sources, software, and tools used in the studies, methodologies, and AI techniques including how the results of the analysis are used in pandemic management. Consequently, the chapter drives conclusions out of findings and results of relevant analysis.

CBRR Model for Predicting the Dynamics of the COVID-19 Epidemic in Real Time

Because of the lack of reliable information on the spread parameters of COVID-19, there is an increasing demand for new approaches to efficiently predict the dynamics of new virus spread under uncertainty. The study presented in this paper is based on the Case-Based Reasoning method used in statistical analysis, forecasting and decision making in the field of public health and epidemiology. A new mathematical Case-Based Rate Reasoning model (CBRR) has been built for the short-term forecasting of coronavirus spread dynamics under uncertainty. The model allows for predicting future values of the increase in the percentage of new cases for a period of 2–3 weeks. Information on the dynamics of the total number of infected people in previous periods in Italy, Spain, France, and the United Kingdom was used. Simulation results confirmed the possibility of using the proposed approach for constructing short-term forecasts of coronavirus spread dynamics. The main finding of this study is that using the proposed approach for Russia showed that the deviation of the predicted total number of confirmed cases from the actual one was within 0.3%. For the USA, the deviation was 0.23%.

Summer COVID-19 third wave: faster high altitude spread suggests high UV adaptation

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.

Inverted Covariate Effects for First versus Mutated Second Wave Covid-19: High Temperature Spread Biased for Young

(1) Background: Here, we characterize COVID-19’s waves, following a study presenting negative associations between first wave COVID-19 spread parameters and temperature. (2) Methods: Visual examinations of daily increases in confirmed COVID-19 cases in 124 countries, determined first and second waves in 28 countries. (3) Results: The first wave spread rate increases with country mean elevation, median population age, time since wave onset, and decreases with temperature. Spread rates decrease above 1000 m, indicating high ultraviolet lights (UVs) decrease the spread rate. The second wave associations are the opposite, i.e., spread increases with temperature and young age, and decreases with time since wave onset. The earliest second waves started 5–7 April at mutagenic high elevations (Armenia, Algeria). The second waves also occurred at the warm-to-cold season transition (Argentina, Chile). Second vs. first wave spread decreases in most (77%) countries. In countries with late first wave onset, spread rates better fit second than first wave-temperature patterns. In countries with ageing populations (for example, Japan, Sweden, and Ukraine), second waves only adapted to spread at higher temperatures, not to infect the young. (4) Conclusions: First wave viruses evolved towards lower spread. Second wave mutant COVID-19 strain(s) adapted to higher temperature, infecting younger ages and replacing (also in cold conditions) first wave COVID-19 strains. Counterintuitively, low spread strains replace high spread strains, rendering prognostics and extrapolations uncertain.

Inverted covariate effects for mutated 2nd vs 1st wave Covid-19: high temperature spread biased for young

(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.

The impact of community containment implementation timing on the spread of COVID-19: A simulation study

Background: Community containment is one of the common methods used to mitigate infectious disease outbreaks. The effectiveness of such a method depends on how strictly it is applied and the timing of its implementation. An early start and being strict is very effective; however, at the same time, it impacts freedom and economic opportunity. Here we created a simulation model to understand the effect of the starting day of community containment on the final outcome, that is, the number of those infected, hospitalized and those that died, as we followed the dynamics of COVID-19 pandemic. Methods: We used a stochastic recursive simulation method to apply disease outbreak dynamics measures of COVID-19 as an example to simulate disease spread. Parameters are allowed to be randomly assigned between higher and lower values obtained from published COVID-19 literature. Results: We simulated the dynamics of COVID-19 spread, calculated the number of active infections, hospitalizations and deaths as the outcome of our simulation and compared these results with real world data. We also represented the details of the spread in a network graph structure, and shared the code for the simulation model to be used for examining other variables. Conclusions: Early implementation of community containment has a big impact on the final outcome of an outbreak.

Reproductive biology of four weedy Euphorbia species from Ile-Ife, Nigeria

Euphorbia heterophylla Linn., Euphorbia hirta Linn., Euphorbia hyssopifolia Linn. and Euphorbia prostrata Linn. are four noxious, yet economically important weeds, useful as phytomedicine in some parts of the world and also in Nigeria. Studies were carried out on their reproductive biology with a view to understanding the mode of their spread. Parameters investigated include number of days to seedling emergence, germinationpercentage, number of days to flowering, period to anthesis, pollinators, pollen viability, pollen size, floral structure, fruits type, seeds type, average number of fruit per plant, average number of seeds per plant and mode of seed dispersal. Results obtained showed that the seedlings of the four Euphorbia species studied emerged within 3 to 5 days; numbers of days to 50% flowering took 44 to 58 days; while flowering and fruiting continuedthroughout the remaining part of the year; thus exhibited r-strategy, expending more time and allocation of resources on their reproductive phases than their vegetative phases. Also differences existed in their stigma shape, perianth colour, perianth texture, pollen sizes, pollen viability as well as ripened colour of seed which were all significant characters that could be useful in delimiting the species. Furthermore, the study revealed that thefour species were essentially insect pollinated and their seeds dispersed by means of explosive mechanism usually characteristic of their schizocarpic fruits. This ability as well as their tendency to exhibit r-strategy could probably account for their ability to spread and invade cultivated fields, waste lands and roadsides. Keywords: Explosive mechanism, r-Strategy, Seed dispersal, Pollen viability, Seed set