When Shape Matters: Using a Simple Mathematical Model to Estimate Critical Area Sizes in Conservation

In the analysis of anthropogenic impact on the environment arises the question of whether the shapes of preserved habitat fragments play an important role in the conservation of wild species. In this work we use a very simple mathematical model based on a reaction-diffusion equation to analyze the effects of geometric shape and area on the permanence of populations in habitat fragments. Our results indicate that a dimensionless quantity calculated from a combination of biological variables is the main component that determines if the species survives in the preserved fragment and whether its geometric shape is important. We provide a methodology to calculate critical area sizes for which population size is most affected by fragment shape. The calculation is based on four quantitative variables: maximum per capita reproduction rate, per capita mortality rate outside the fragment, carrying capacity in the conserved environment and mobility in the disturbed environment. The methodology is illustrated by a preliminary study, in which the model is used to estimate threshold area sizes for habitat fragments for the threatened species Sapajus xanthosternos .

Dengue virus infection modifies mosquito blood-feeding behavior to increase transmission to the host

Mosquito blood-feeding behavior is a key determinant of the epidemiology of dengue viruses (DENV), the most-prevalent mosquito-borne viruses. However, despite its importance, how DENV infection influences mosquito blood-feeding and, consequently, transmission remains unclear. Here, we developed a high-resolution, video-based assay to observe the blood-feeding behavior of Aedes aegypti mosquitoes on mice. We then applied multivariate analysis on the high-throughput, unbiased data generated from the assay to ordinate behavioral parameters into complex behaviors. We showed that DENV infection increases mosquito attraction to the host and hinders its biting efficiency, the latter resulting in the infected mosquitoes biting more to reach similar blood repletion as uninfected mosquitoes. To examine how increased biting influences DENV transmission to the host, we established an in vivo transmission model with immuno-competent mice and demonstrated that successive short probes result in multiple transmissions. Finally, to determine how DENV-induced alterations of host-seeking and biting behaviors influence dengue epidemiology, we integrated the behavioral data within a mathematical model. We calculated that the number of infected hosts per infected mosquito, as determined by the reproduction rate, tripled when mosquito behavior was influenced by DENV infection. Taken together, this multidisciplinary study details how DENV infection modulates mosquito blood-feeding behavior to increase vector capacity, proportionally aggravating DENV epidemiology. By elucidating the contribution of mosquito behavioral alterations on DENV transmission to the host, these results will inform epidemiological modeling to tailor improved interventions against dengue.

Environmental concerns about the massive use of disinfectants during COVID-19 pandemic: an overview on aquatic toxicity

Many public health measures to mitigate the spread of SARS-CoV-2 were adopted worldwide, and particularly to the environmental measure of regular cleaning and disinfection of surfaces, the increased use of disinfectant products raises environmental concerns. Quaternary ammonium compounds (QACs), povidone-iodine (PVP-I), chloroxylenol (PCMX) and chlorhexidine (CHX) are the active ingredients of most disinfectant products due to their effectiveness against various microbiological agents. Although presenting antimicrobial efficacy, these biocides have been associated with impacts on aquatic life. For instance, QACs can induce toxicity to Aliivibrio fischeri and fish (different species). Gill and liver damages are verified in Cyprinus carpio after exposure to PVP-I. CHX induces toxic effects on algae, crustaceans, and fish embryos. PCMX can induce genotoxicity to rainbow trout and malformations on zebrafish embryos, as well as it can reduce the reproduction rate of Caenorhabditis elegans. Thus, the potential to cause negative consequences on human and environmental health has resulted in activities from the U.S. and European agencies to favor the use of safer and greener disinfectant products during the COVID-19 pandemic. This review article summarizes the main findings on the impacts of disinfectants (the most used) on aquatic life. This information may help prioritize disinfectants with lower impacts on the aquatic environment for daily use, and especially for high-frequency use as verified in the COVID-19 pandemic. Furthermore, this review may help identify knowledge gaps on the aquatic hazard of disinfectants, which may drive future studies on this matter and, lastly, contribute to the development of sustainable products.

Effects of Imunit Insecticide on Biological Characteristics and Life Table Parameters of Spodoptera cilium (Lepidoptera: Noctuidae)

Imunit is a mixture of alpha-cypermethrin + teflubenzuron, and has been launched for controlling caterpillars. In this study, the effects of Imunit at LC50 and LC30 were investigated on parental and offspring generation of S. cilium, according to age-stage, two-sex life table. The experiments were conducted by leaf dipping method at 25 °C and 60 ± 5% relative humidity, under a cycle of 16 h fluorescent light and 8 h darkness. LC30 and LC50 concentrations of Imunit increased the immature developmental time of S. cilium in the offspring generation, while the LC50 of Imunit significantly reduced the developmental time of adults. The adult pre-oviposition period and total pre-oviposition period considerably increased when offspring were treated with LC50 of Imunit. In offspring of S. cilium exposed to LC50 and LC30 concentrations of Imunit, the gross reproductive rate (GRR), net reproduction rate (R0), the intrinsic rate of population increase (r), and the finite rate of population increase (λ) significantly reduced compared to the control. This study showed that the application of Imunit at LC50 could suppress the S. cilium population and can be used in the integrated management program of this pest.

The mathematics of the reproduction number R for Covid-19: A primer for demographers

The reproduction number R is a key indicator used to monitor the dynamics of Covid-19 and to assess the effects of infection control strategies that frequently have high social and economic costs. Despite having an analog in demography’s “net reproduction rate” that has been routinely computed for a century, demographers may not be familiar with the concept and measurement of R in the context of Covid-19. This article is intended to be a primer for understanding and estimating R in demography. We show that R can be estimated as a ratio between the numbers of new cases today divided by the weighted average of cases in previous days. We present two alternative derivations for these weights based on how risks have changed over time: constant vs. exponential decay. We then provide estimates of these weights, and demonstrate their use in calculating R to trace the course of the first pandemic year in 53 countries.

Mass Media as a Mirror of the COVID-19 Pandemic

The media plays an important role in disseminating facts and knowledge to the public at critical times, and the COVID-19 pandemic is a good example of such a period. This research is devoted to performing a comparative analysis of the representation of topics connected with the pandemic in the internet media of Kazakhstan and the Russian Federation. The main goal of the research is to propose a method that would make it possible to analyze the correlation between mass media dynamic indicators and the World Health Organization COVID-19 data. In order to solve the task, three approaches related to the representation of mass media dynamics in numerical form—automatically obtained topics, average sentiment, and dynamic indicators—were proposed and applied according to a manually selected list of search queries. The results of the analysis indicate similarities and differences in the ways in which the epidemiological situation is reflected in publications in Russia and in Kazakhstan. In particular, the publication activity in both countries correlates with the absolute indicators, such as the daily number of new infections, and the daily number of deaths. However, mass media tend to ignore the positive rate of confirmed cases and the virus reproduction rate. If we consider strictness of quarantine measures, mass media in Russia show a rather high correlation, while in Kazakhstan, the correlation is much lower. Analysis of search queries revealed that in Kazakhstan the problem of fake news and disinformation is more acute during periods of deterioration of the epidemiological situation, when the level of crime and poverty increase. The novelty of this work is the proposal and implementation of a method that allows the performing of a comparative analysis of objective COVID-19 statistics and several mass media indicators. In addition, it is the first time that such a comparative analysis, between different countries, has been performed on a corpus in a language other than English.

Analysis of Selection Methods Used in Genetic Algorithms

This paper offers a comprehensive review of selection methods used in the generational genetic algorithms.Firstly, a brief description of the following selection methods is presented: fitness proportionate selection methods including roulette-wheel selection (RWS) and its modifications, stochastic remainder selection with replacement (SRSWR), remainder stochastic independent selection (RSIS), and stochastic universal selection (SUS); ranking selection methods including linear and nonlinear rankings; tournament selection methods including deterministic and stochastic tournaments as well as tournaments with and without replacement; elitist and truncation selection methods; fitness uniform selection scheme (FUSS).Second, basic theoretical statements on selection method properties are given. Particularly, the selection noise, selection pressure, growth rate, reproduction rate, and computational complexity are considered. To illustrate selection method properties, numerous runs of genetic algorithms using the only selection method and no other genetic operator are conducted, and numerical characteristics of analyzed properties are computed. Specifically, to estimate the selection pressure, the takeover time and selection intensity are computed; to estimate the growth rate, the ratio of best individual copies in two consecutive populations is computed; to estimate the selection noise, the algorithm convergence speed is analyzed based on experiments carried out on a specific fitness function assigning the same fitness value to all individuals.Third, the effect of selection methods on the population fitness distribution is investigated. To do this, there are conducted genetic algorithm runs starting with a binomially distributed initial population. It is shown that most selection methods keep the distribution close to the original one providing an increased mean value of the distribution, while others (such as disruptive RWS, exponential ranking, truncation, and FUSS) change the distribution significantly. The obtained results are illustrated with the help of tables and histograms.

Rumen Fermentation—Microbiota—Host Gene Expression Interactions to Reveal the Adaptability of Tibetan Sheep in Different Periods

As an important ruminant on the Qinghai-Tibet Plateau, Tibetan sheep can maintain their population reproduction rate in the harsh high-altitude environment of low temperature and low oxygen, which relies on their special plateau adaptations mechanism that they have formed for a long time. Microbiomes (known as “second genomes”) are closely related to the nutrient absorption, adaptability, and health of the host. In this study, rumen fermentation characteristics, the microbiota, and rumen epithelial gene expression of Tibetan sheep in various months were analyzed. The results show that the rumen fermentation characteristics of Tibetan sheep differed in different months. The total SCFAs (short-chain fatty acids), acetate, propionate, and butyrate concentrations were highest in October and lowest in June. The CL (cellulase) activity was highest in February, while the ACX (acid xylanase) activity was highest in April. In addition, the diversity and abundance of rumen microbes differed in different months. Bacteroidetes (53.4%) and Firmicutes (27.4%) were the dominant phyla. Prevotella_1 and Rikenellaceae_RC9_gut_group were the dominant genera. The abundance of Prevotella_1 was highest in June (27.8%) and lowest in December (17.8%). In addition, the expression of CLAUDIN4 (Claudin-4) and ZO1 (Zonula occludens 1) was significantly higher in April than in August and December, while the expression of SGLT1 (Sodium glucose linked transporter 1) was highest in August. Correlation analysis showed that there were interactions among rumen fermentation characteristics, the microbiota, and host gene expression, mainly by adjusting the amino acid metabolism pathway and energy metabolism pathway to improve energy utilization. At the same time, we adjusted the balance of the rumen “core microbiota” to promote the development of rumen and maintain the homeostasis of rumen environment, which makes Tibetan sheep better able to adapt to the harsh environment in different periods of the Qinghai-Tibet Plateau.

Branching Process Modelling of COVID-19 Pandemic Including Immunity and Vaccination

We propose modeling COVID-19 infection dynamics using a class of two-type branching processes. These models require only observations on daily statistics to estimate the average number of secondary infections caused by a host and to predict the mean number of the non-observed infected individuals. The development of the epidemic process depends on the reproduction rate as well as on additional facets as immigration, adaptive immunity, and vaccination. Usually, in the existing deterministic and stochastic models, the officially reported and publicly available data are not sufficient for estimating model parameters. An important advantage of the proposed model, in addition to its simplicity, is the possibility of direct computation of its parameters estimates from the daily available data. We illustrate the proposed model and the corresponding data analysis with data from Bulgaria, however they are not limited to Bulgaria and can be applied to other countries subject to data availability.