pwc-archive/papers-with-abstracts huggingface dataset:
Modeling COVID-19 Transmission using IDSIM, an Epidemiological-Modelling Desktop App with Multi-Level Immunization Capabilities
Authors: Eleodor Nichita, Mary-Anne Pietrusiak, Fangli Xie, Peter Schwanke, Anjali Pandya
Date: 2021-12-31 00:00:00

The COVID-19 pandemic has placed unprecedented demands on local public health units in Ontario, Canada, one of which was the need for in-house epidemiological-modelling capabilities. To address this need, Ontario Tech University and the Durham Region Health Department developed a native Windows desktop app that performs epidemiological modelling of infectious diseases. The app is an implementation of a multi-stratified compartmental epidemiological model that can accommodate multiple virus variants and levels of vaccination, as well as public health measures such as physical distancing, contact tracing followed by quarantine, and testing followed by isolation. This article presents the epidemiological model and epidemiological-simulation results obtained using the developed app. The simulations investigate the effects of different factors on COVID-19 transmission in Durham Region, including vaccination coverage, vaccine effectiveness, waning of vaccine-induced immunity, advent of the Omicron variant and effect of COVID-19 booster vaccines in reducing the number of infections and severe cases. Results indicate that, for the Delta variant, natural immunity, in addition to vaccination-induced immunity, is necessary to achieve herd immunity and that waning of vaccine-induced immunity lengthens the time necessary to reach herd immunity. In the absence of additional public health measures, a wave driven by the Omicron variant is predicted to pose significant public health challenges with infections predicted to peak in approximately two to three months, depending on the rate of administration of booster doses.
Human Niche Evolution: pathways, choices and outcomes
Authors: Miguel da Silva Pinheiro, Pablo José Francisco Pena Rodrigues
Date: 2021-12-29 00:00:00

Humankind has spread worldwide supported by cultural and technological knowledge, but the environmental sustainability on the human niche evolution depends on a new human beings relationship with the biosphere. Human lifestyles nowadays are very Antropocentric and in many ways deleterious to the other life forms. Here we try to identify future scenarios, where the less deleterious is the Natural-Technological Model that points the urgent need to change the evolutionary direction of the human niche seeking the resumption of original ecological relations. New cultural habits and novel technologies, thereby, would reverse the current anthropogenic impacts. The middle way is the Bio-Anthropogenic Model that predicts the success of the emerging ecosystems and the symbiotic relationship of humans and anthropogenic-favored species, hybrids, aliens and genetically modified organisms. For such, we must also change our way of life and adopt new conscious ways of consumption aiming at the socio-environmental good. Lastly, the Wear Out Model, which depends only on maintaining current patterns of human expansion. The lack of investments on new technologies and new cultural habits, added to the current patterns of human niche evolution that are based on the massive exploitation of world resources, will lead to a fearsome scenario with a precarious global health, biodiversity losses and food scarcity. This theoretical models indicates some pathways and can help us to choose a better future.
Branching structure of genealogies in spatially growing populations and its implications for population genetics inference
Authors: Armin Eghdami, Jayson Paulose, Diana Fusco
Date: 2021-12-27 00:00:00

Spatial models where growth is limited to the edge of the expansions have been instrumental to understand the population dynamics and the clone size distribution in growing cellular populations, such as microbial colonies and avascular tumours. A complete characterization of the coalescence process generated by spatial growth is still lacking, limiting our ability to apply classic population genetics inference to spatially growing populations. Here, we start filling this gap by investigating the statistical properties of the cell lineages generated by the two dimensional Eden model, leveraging their physical analogy with directed polymers. Our analysis provides quantitative estimates for population measurements that can easily be assessed via sequencing, such as the average number of segregating sites and the clone size distribution of a subsample of the population. Our results not only reveal remarkable features of the genealogies generated during growth, but also highlight new properties that can be misinterpreted as signs of selection if non-spatial models are inappropriately applied.
General-purpose cooperativeness and altruism in humans: elements of the mathematical framework for the Interdependence Hypothesis
Authors: Misha Perepelitsa
Date: 2021-12-21 00:00:00
Tasks: Decision Making

We propose a decision-making model for joint intentionality by interpreting it as group-mindedness at the microlevel. We apply this model to give a formal justification of the first part of the Interdependence Hypothesis due to Tomasello et al. [Current Anthropology, 2012] which asserts that the emergence of joint intentionality evolved due to the challenges of difficult collaborative foraging practices among early humans, and that its evolution led to robust collaboration and some form of altruism. In another application of the microlevel group-mindedness we consider the problem of establishing cooperation in high-risk-of-defection strategic conflicts and we show that the emergence of cooperation in such situations can be explained in the context of cultural group selection as the result of adaptive learning.
Temperature sensitivity of pest reproductive numbers in age-structured PDE models, with a focus on the invasive spotted lanternfly
Authors: Stephanie M. Lewkiewicz, Sebastiano De Bona, Matthew R. Helmus, Benjamin Seibold
Date: 2021-12-21 00:00:00
Tasks: Sensitivity

Invasive pest establishment is a pervasive threat to global ecosystems, agriculture, and public health. The recent establishment of the invasive spotted lanternfly in the northeastern United States has proven devastating to farms and vineyards, necessitating urgent development of population dynamical models and effective control practices. In this paper, we propose a stage- and age-structured system of PDEs to model insect pest populations, in which underlying dynamics are dictated by ambient temperature through rates of development, fecundity, and mortality. The model incorporates diapause and non-diapause pathways, and is calibrated to experimental and field data on the spotted lanternfly. We develop a novel moving mesh method for capturing age-advection accurately, even for coarse discretization parameters. We define a one-year reproductive number ($R_0$) from the spectrum of a one-year solution operator, and study its sensitivity to variations in the mean and amplitude of the annual temperature profile. We quantify assumptions sufficient to give rise to the low-rank structure of the solution operator characteristic of part of the parameter domain. We discuss establishment potential as it results from the pairing of a favorable $R_0$ value and transient population survival, and address implications for pest control strategies.
Interpreting how nonlinear diffusion affects the fate of bistable populations using a discrete modelling framework
Authors: Yifei Li, Pascal R. Buenzli, Matthew J. Simpson
Date: 2021-12-21 00:00:00

Understanding whether a population will survive and flourish or become extinct is a central question in population biology. One way of exploring this question is to study population dynamics using reaction-diffusion equations, where migration is usually represented as a linear diffusion term, and birth-death is represented with a bistable source term. While linear diffusion is most commonly employed to study migration, there are several limitations of this approach, such as the inability of linear diffusion-based models to predict a well-defined population front. One way to overcome this is to generalise the constant diffusivity, $D$, to a nonlinear diffusivity function $D(C)$, where $C>0$ is the density. While it has been formally established that the choice of $D(C)$ affects long-term survival or extinction of a bistable population, working solely in a classical continuum framework makes it difficult to understand precisely how the choice of $D(C)$ affects survival or extinction. Here, we address this question by working with a simple discrete simulation model that is easy to interpret. The continuum limit of the discrete model is a nonlinear reaction-diffusion equation, where the flux involves a nonlinear diffusion term and the source term is given by the strong Allee effect bistable model. We study population extinction/survival using this very intuitive discrete framework together with numerical solutions of the reaction-diffusion continuum limit equation. This approach provides clear insight into how the choice of $D(C)$ either encourages or suppresses population extinction relative to the classical linear diffusion model.
Are Travel Bans the Answer to Stopping the Spread of COVID-19 Variants? Lessons from a Multi-Country SIR Model
Authors: Frederic Docquier, Nicolas Golenvaux, Pierre Schaus
Date: 2021-12-18 00:00:00

Detections of mutations of the SARS-CoV-2 virus gave rise to new packages of interventions. Among them, international travel restrictions have been one of the fastest and most visible responses to limit the spread of the variants. While inducing large economic losses, the epidemiological consequences of such travel restrictions are highly uncertain. They may be poorly effective when the new highly transmissible strain of the virus already circulates in many regions. Assessing the effectiveness of travel bans is difficult given the paucity of data on daily cross-border mobility and on existing variant circulation. The question is topical and timely as the new omicron variant -- classified as a variant of concern by WHO -- has been detected in Southern Africa, and perceived as (potentially) more contagious than previous strains. In this study, we develop a multi-country compartmental model of the SIR type. We use it to simulate the spread of a new variant across European countries, and to assess the effectiveness of unilateral and multilateral travel bans.
Mechanistic Models of COVID-19: Insights into Disease Progression, Vaccines, and Therapeutics
Authors: Rajat Desikan, Pranesh Padmanabhan, Andrzej M. Kierzek, Piet H. van der Graaf
Date: 2021-12-17 00:00:00

The COVID-19 pandemic has severely impacted health systems and economies worldwide. Significant global efforts are therefore ongoing to improve vaccine efficacies, optimize vaccine deployment, and develop new antiviral therapies to combat the pandemic. Mechanistic viral dynamics and quantitative systems pharmacology models of SARS-CoV-2 infection, vaccines, immunomodulatory agents, and antiviral therapeutics have played a key role in advancing our understanding of SARS-CoV-2 pathogenesis and transmission, the interplay between innate and adaptive immunity to influence the outcomes of infection, effectiveness of treatments, mechanisms and performance of COVID-19 vaccines, and the impact of emerging SARS-CoV-2 variants. Here, we review some of the critical insights provided by these models and discuss the challenges ahead.
Forward-backward algorithms with a biallelic mutation-drift model: Orthogonal polynomials, and a coalescent/urn-model based approach
Authors: Claus Vogl, Sandra Peer, Lynette Caitlin Mikula
Date: 2021-12-17 00:00:00
Tasks: model

Inference of the marginal likelihood of sample allele configurations using backward algorithms yields identical results with the Kingman coalescent, the Moran model, and the diffusion model (up to a scaling of time). For inference of probabilities of ancestral population allele frequencies at any given point in the past - either of discrete ancestral allele configurations as in the coalescent, or of ancestral allele proportions as in the backward diffusion - backward approaches need to be combined with corresponding forward ones. This is done in so-called forward-backward algorithms. In this article, we utilize orthogonal polynomials in forward-backward algorithms. They enable efficient calculation of past allele configurations of an extant sample and probabilities of ancestral population allele frequencies in equilibrium and in non-equilibrium. We show that the genealogy of a sample is fully described by the backward polynomial expansion of the marginal likelihood of its allele configuration.
Analysis of hybridization in French wild boar populations using genome-wide genotyping data
Authors: Nicolas Mary, Nathalie Iannuccelli, Geoffrey Petit, Nathalie Bonnet, Alain Pinton, Vladimir Grosbois, Bertrand Servin, Juliette Riquet, Alain Ducos
Date: 2021-12-16 00:00:00

The "genetic purity" of French wild boar populations has been monitored since the 1980s based on a cytogenetic difference between wild boars and domestic pigs (36 and 38 chromosomes, respectively). This difference makes it possible to identify any boar with 37 or 38 chromosomes as "hybrid", without however being able to determine the origin (recent or ancient) of the hybridization, nor guarantee the "purity" of an animal with 36 chromosomes. Analysis of results of more than 4,600 tests performed over the last 12 years reveals an average "hybrid" rate of 15.8%, with high variability between populations. To analyse hybridization in greater detail and overcome inherent limitations of the cytogenetic approach, 362 wild boars recently collected in different regions of France were genotyped on a 70K SNP (GeneSeek GGP Porcine HD) chip. This study showed that for 96.4% of the wild boars analysed, includingmost of those with 37 or 38 chromosomes, the percentage of the genome of "domestic pig" origin varied from 0 to 18%. This suggests that hybridization is a fairly common phenomenon but of moderate intensity, and often ancient. Nevertheless, higher rates of hybridization have been observed in some regions such as Ard{\`e}che, and several cases of recent hybridization with domestic pigs were found in 3.6% of the wild boars analysed, most of them with pigs of Asian origin.
Complementary Theory of Evolutionary Genetics
Authors: Xiaoqiu Huang
Date: 2021-12-15 00:00:00

This theory seeks to define species and to explore evolutionary forces and genetic elements in speciation and species maintenance. The theory explains how speciation and species maintenance are caused by natural selection acting on non-Mendelian and Mendelian variation, respectively. The emergence and maintenance of species as groups of populations are balanced by evolutionary forces including complementary mechanisms of gene flow within and between populations at population-specific rates: sexual and asexual reproduction, recombining and nonrecombining genome regions, vertical and horizontal DNA transfer, and transposon proliferation and control. While recombining genome regions carry conserved genes and are subjected to meiotic recombination, nonrecombining genome regions carry accessory genes and are not subjected to such structural restrain. Sexual reproduction, vertical DNA transfer, recombining genome regions and transposon control keep species in existence by maintaining recombining chromosome number and structure, while asexual reproduction, horizontal DNA transfer, nonrecombining genome regions and transposon proliferation help species emerge by promoting reproductive isolation and changes in chromosome number and structure. The theory is based on the analysis of the genome sequences of isolates in the Fusarium oxysporum complex. The rate of horizontal supernumerary chromosome transfer in this complex was estimated to be 0.1 per genome per year.
Counting and optimising maximum phylogenetic diversity sets
Authors: Kerry Manson, Charles Semple, Mike Steel
Date: 2021-12-15 00:00:00
Tasks: Diversity

In conservation biology, phylogenetic diversity (PD) provides a way to quantify the impact of the current rapid extinction of species on the evolutionary `Tree of Life'. This approach recognises that extinction not only removes species but also the branches of the tree on which unique features shared by the extinct species arose. In this paper, we investigate three questions that are relevant to PD. The first asks how many sets of species of given size $k$ preserve the maximum possible amount of PD in a given tree. The number of such maximum PD sets can be very large, even for moderate-sized phylogenies. We provide a combinatorial characterisation of maximum PD sets, focusing on the setting where the branch lengths are ultrametric (e.g. proportional to time). This leads to a polynomial-time algorithm for calculating the number of maximum PD sets of size $k$ by applying a generating function; we also investigate the types of tree shapes that harbour the most (or fewest) maximum PD sets of size $k$. Our second question concerns optimising a linear function on the species (regarded as leaves of the phylogenetic tree) across all the maximum PD sets of a given size. Using the characterisation result from the first question, we show how this optimisation problem can be solved in polynomial time, even though the number of maximum PD sets can grow exponentially. Our third question considers a dual problem: If $k$ species were to become extinct, then what is the largest possible {\em loss} of PD in the resulting tree? For this question, we describe a polynomial-time solution based on dynamical programming.
Probabilistic Models of k-mer Frequencies (Extended Abstract)
Authors: Askar Gafurov, Tomáš Vinař, Broňa Brejová
Date: 2021-12-30 00:00:00

In this article, we review existing probabilistic models for modeling abundance of fixed-length strings (k-mers) in DNA sequencing data. These models capture dependence of the abundance on various phenomena, such as the size and repeat content of the genome, heterozygosity levels, and sequencing error rate. This in turn allows to estimate these properties from k-mer abundance histograms observed in real data. We also briefly discuss the issue of comparing k-mer abundance between related sequencing samples and meaningfully summarizing the results.
Un nouvel algorithme pour la detection des transferts horizontaux de genes partiels entre les especes et pour la classification des transferts inferes
Authors: Boc Alix, Diallo Alpha Boubacar, Makarenkov Vladimir
Date: 2021-12-25 00:00:00
Tasks: Multiple Sequence Alignment

In this article we are describing a new algorithm for detecting and validating partial horizontal gene transfers (HGT). The presented algorithm is based on a sliding window procedure which analyzes fragments of the given multiple sequence alignment. A bootstrap procedure incorporated in our method can be used to estimate the support of each inferred partial HGT. The new algorithm can be also applied to confirm or discard complete (i.e., traditional) horizontal gene transfers detected by any HGT inferring algorithm. While working on a full-genome scale, the introduced algorithm can be used to assess the level of mosaicism of the whole species genomes as well as the rates of complete and partial HGT underlying the evolution of the considered set of species.
Mathematical Properties of Incremental Effect Additivity and Other Synergy Theories
Authors: Leonid Hanin, Liyang Xie, Rainer Sachs
Date: 2021-12-24 00:00:00

Synergy theories for multi-component agent mixtures use 1-agent dose-effect relations, assumed known from analyzing previous 1-agent experiments, to calculate baseline Neither-Synergy-Nor-Antagonism mixture dose-effect relations. The most commonly used synergy theory, Simple Effect Additivity, is not self-consistent mathematically. Many nonlinear alternatives have been suggested, almost all of which require an assumption that effects increase monotonically as dose increases. We here emphasize the recently introduced Incremental Effect Additivity synergy theory and briefly discuss Loewe Additivity. By utilizing the fact that, when dose increments approach zero, dose-effect relations approach linearity, Incremental Effect Additivity theory to some extent circumvents the non-linearity of dose-effect relations that plague Simple Effect Additivity calculations. We study mathematical properties of Incremental Effect Additivity that are relevant to practical implementation of this synergy theory and hold whatever particular area of biology, medicine, toxicology or pharmacology is involved. However, as yet Incremental Effect Additivity synergy theory has only been applied to mixture experiments simulating the toxic galactic cosmic ray mixture encountered during voyages in interplanetary space. Our main results are theorems, propositions, examples and counterexamples revealing various properties of Incremental Effect Additivity synergy theory including whether or not Neither-Synergy-Nor-Antagonism dose-effect relations lie between 1-agent dose-effect relations. These results are amply illustrated with figures.
Ensemble Method for Cluster Number Determination and Algorithm Selection in Unsupervised Learning
Authors: Antoine Zambelli
Date: 2021-12-23 00:00:00
Tasks: Clustering

Unsupervised learning, and more specifically clustering, suffers from the need for expertise in the field to be of use. Researchers must make careful and informed decisions on which algorithm to use with which set of hyperparameters for a given dataset. Additionally, researchers may need to determine the number of clusters in the dataset, which is unfortunately itself an input to most clustering algorithms. All of this before embarking on their actual subject matter work. After quantifying the impact of algorithm and hyperparameter selection, we propose an ensemble clustering framework which can be leveraged with minimal input. It can be used to determine both the number of clusters in the dataset and a suitable choice of algorithm to use for a given dataset. A code library is included in the Conclusion for ease of integration.