Allocation strategy of medical supplies during a public health emergency: a tripartite evolutionary game perspective.

Ensuring the rational and orderly circulation of medical supplies during a public health emergency is crucial to quickly containing the further spread of the epidemic and restoring the order of rescue and treatment. However, due to the shortage of medical supplies, there are challenges to rationalizing the allocation of critical medical supplies among multiple parties with conflicting interests. In this paper, a tripartite evolutionary game model is constructed to study the allocation of medical supplies in the rescue environment of public health emergencies under conditions of incomplete information. The game's players include Government-owned Nonprofit Organizations (GNPOs), hospitals, and the government. By analyzing the equilibrium of the tripartite evolutionary game, this paper makes an in-depth study on the optimal allocation strategy of medical supplies. The findings indicate that: (1) the hospital should reasonably increase its willingness to accept the allocation plan of medical supplies, which can help medical supplies allocate more scientifically. (2) The government should design a reasonable reward and punishment mechanism to ensure the rational and orderly circulation of medical supplies, which can reduce the interference of GNPOs and hospitals in the allocation process of medical supplies. (3) Higher authorities should strengthen the supervision of the government and the accountability for loose supervision. The findings of this research can guide the government in promoting better circulation of medical supplies during public health emergencies by formulating more reasonable allocation schemes of emergency medical supplies, as well as incentives and penalties. At the same time, for GNPOs with limited emergency medical supplies, the equal allocation of emergency supplies is not the optimal solution to improve the efficiency of emergency relief, and it is simpler to achieve the goal of maximizing social benefits by allocating limited emergency resources to the demand points that match the degree of urgency. For example, in Corona Virus Disease 2019, emergency medical supplies should be prioritized for allocation to government-designated fever hospitals that are have a greater need for medical supplies and greater treatment capacity.

Do pathogens always evolve to be less virulent? The virulence-transmission trade-off in light of the COVID-19 pandemic.

The direction the evolution of virulence takes in connection with any pathogen is a long-standing question. Formerly, it was theorized that pathogens should always evolve to be less virulent. As observations were not in line with this theoretical outcome, new theories emerged, chief among them the transmission-virulence trade-off hypotheses, which predicts an intermediate level of virulence as the endpoint of evolution. At the moment, we are very much interested in the future evolution of COVID-19's virulence. Here, we show that the disease does not fulfill all the assumptions of the hypothesis. In the case of COVID-19, a higher viral load does not mean a higher risk of death; immunity is not long-lasting; other hosts can act as reservoirs for the virus; and death as a consequence of viral infection does not shorten the infectious period. Consequently, we cannot predict the short- or long-term evolution of the virulence of COVID-19.

New findings on the evolution of turtles: A symposium in honor of Marcelo S. de la Fuente.

With their particular body plan within amniotes and their amazing fossil record, turtles represent a great interest for both neontologists and paleontologists with a strong anatomical background. The Turtle Evolution Symposia are regular international meetings that gather scientists working with different aspects related to the evolutionary history of turtles, from their origin and early evolution until recent times. The latest edition of the Turtle Evolution Symposium was organized in 2021 amidst the COVID-19 outbreak and held virtually from the facilities of the Museo Paleontológico Egidio Feruglio in Trelew (Patagonia, Chubut, Argentina). More than 75 scientists from 25 countries presented their latest advances on topics related to turtle evolution, some of which are published in this Special Volume of The Anatomical Record. Both the Turtle Evolution Symposium 2021 and this Special Volume are dedicated to Marcelo S. de la Fuente who was the first researcher who specialized in the study of extinct turtles in South America, and his studies have an important regional and international impact.

Timeline of changes in spike conformational dynamics in emergent SARS-CoV-2 variants reveal progressive stabilization of trimer stalk with altered NTD dynamics.

SARS-CoV-2 emergent variants are characterized by increased viral fitness and each shows multiple mutations predominantly localized to the spike (S) protein. Here, amide hydrogen/deuterium exchange mass spectrometry has been applied to track changes in S dynamics from multiple SARS-CoV-2 variants. Our results highlight large differences across variants at two loci with impacts on S dynamics and stability. A significant enhancement in stabilization first occurred with the emergence of D614G S followed by smaller, progressive stabilization in subsequent variants. Stabilization preceded altered dynamics in the N-terminal domain, wherein Omicron BA.1 S showed the largest magnitude increases relative to other preceding variants. Changes in stabilization and dynamics resulting from S mutations detail the evolutionary trajectory of S in emerging variants. These carry major implications for SARS-CoV-2 viral fitness and offer new insights into variant-specific therapeutic development.

Genome-based survey of the SARS-CoV-2 BF.7 variant from Asia.

The SARS-CoV-2 BF.7 variant represents one of the most recent subvariant under monitoring. At the beginning of the 2023 it caused several concerns especially in Asia because of a resurge in COVID-19 cases. Here we perform a genome-based integrative approach on SARS-CoV-2 BF.7 to shed light on this emerging lineage and produce some consideration on its real dangerousness. Both genetic and structural data suggest that this new variant currently does not show evidence of an high expansion capability. It is very common in Asia, but it appears less virulent than other Omicron variants as proved by its relatively low evolutionary rate (5.62 × 10-4 subs/sites/years). The last plateau has been reached around December 14, 2022 and then the genetic variability, and thus the viral population size, no longer increased. As already seen for several previous variants, the features that may be theoretically related to advantages are due to genetic drift that allows to the virus a constant adaptability to the host, but is not strictly connected to a fitness advantage. These results have further pointed that the genome-based monitoring must continue uninterruptedly to be prepared and well documented on the real situation.

SARS-CoV-2 Molecular Evolutionary Dynamics in the Greater Accra Region, Ghana.

To assess dynamics of SARS-CoV-2 in Greater Accra Region, Ghana, we analyzed SARS-CoV-2 genomic sequences from persons in the community and returning from international travel. The Accra Metropolitan District was a major origin of virus spread to other districts and should be a primary focus for interventions against future infectious disease outbreaks.

SARSMutOnto: An Ontology for SARS-CoV-2 Lineages and Mutations.

Mutations allow viruses to continuously evolve by changing their genetic code to adapt to the hosts they infect. It is an adaptive and evolutionary mechanism that helps viruses acquire characteristics favoring their survival and propagation. The COVID-19 pandemic declared by the WHO in March 2020 is caused by the SARS-CoV-2 virus. The non-stop adaptive mutations of this virus and the emergence of several variants over time with characteristics favoring their spread constitute one of the biggest obstacles that researchers face in controlling this pandemic. Understanding the mutation mechanism allows for the adoption of anticipatory measures and the proposal of strategies to control its propagation. In this study, we focus on the mutations of this virus, and we propose the SARSMutOnto ontology to model SARS-CoV-2 mutations reported by Pango researchers. A detailed description is given for each mutation. The genes where the mutations occur and the genomic structure of this virus are also included. The sub-lineages and the recombinant sub-lineages resulting from these mutations are additionally represented while maintaining their hierarchy. We developed a Python-based tool to automatically generate this ontology from various published Pango source files. At the end of this paper, we provide some examples of SPARQL queries that can be used to exploit this ontology. SARSMutOnto might become a 'wet bench' machine learning tool for predicting likely future mutations based on previous mutations.

Detection of High Level of Co-Infection and the Emergence of Novel SARS CoV-2 Delta-Omicron and Omicron-Omicron Recombinants in the Epidemiological Surveillance of Andalusia.

Recombination is an evolutionary strategy to quickly acquire new viral properties inherited from the parental lineages. The systematic survey of the SARS-CoV-2 genome sequences of the Andalusian genomic surveillance strategy has allowed the detection of an unexpectedly high number of co-infections, which constitute the ideal scenario for the emergence of new recombinants. Whole genome sequence of SARS-CoV-2 has been carried out as part of the genomic surveillance programme. Sample sources included the main hospitals in the Andalusia region. In addition to the increase of co-infections and known recombinants, three novel SARS-CoV-2 delta-omicron and omicron-omicron recombinant variants with two break points have been detected. Our observations document an epidemiological scenario in which co-infection and recombination are detected more frequently. Finally, we describe a family case in which co-infection is followed by the detection of a recombinant made from the two co-infecting variants. This increased number of recombinants raises the risk of emergence of recombinant variants with increased transmissibility and pathogenicity.

Evolutionary plasticity of zoonotic porcine Deltacoronavirus (PDCoV): genetic characteristics and geographic distribution.

The emergence and rapid spread of the acute respiratory syndrome coronavirus-2 have confirmed that animal coronaviruses represent a potential zoonotic source. Porcine deltacoronavirus is a worldwide evolving enteropathogen of swine, detected first in Hong Kong, China, before its global identification. Following the recent detection of PDCoV in humans, we attempted in this report to re-examine the status of PDCoV phylogenetic classification and evolutionary characteristics. A dataset of 166 complete PDCoV genomes was analyzed using the Maximum Likelihood method in IQ-TREE with the best-fitting model GTR + F + I + G4, revealing two major genogroups (GI and GII), with further seven and two sub-genogroups, (GI a-g) and (GII a-b), respectively. PDCoV strains collected in China exhibited the broadest genetic diversity, distributed in all subgenotypes. Thirty-one potential natural recombination events were identified, 19 of which occurred between China strains, and seven involved at least one China strain as a parental sequence. Importantly, we identified a human Haiti PDCoV strain as recombinant, alarming a possible future spillover that could become a critical threat to human health. The similarity and recombination analysis showed that PDCoV spike ORF is highly variable compared to ORFs encoding other structural proteins. Prediction of linear B cell epitopes of the spike glycoprotein and the 3D structural mapping of amino acid variations of two representative strains of GI and GII showed that the receptor-binding domain (RBD) of spike glycoprotein underwent a significant antigenic drift, suggesting its contribution in the genetic diversity and the wider spread of PDCoV.

L-shaped distribution of the relative substitution rate (c/µ) observed for SARS-COV-2's genome, inconsistent with the selectionist theory, the neutral theory and the nearly neutral theory but a near-neutral balanced selection theory: Implication on "neutralist-selectionist" debate.

The genomic substitution rate (GSR) of SARS-CoV-2 exhibits a molecular clock feature and does not change under fluctuating environmental factors such as the infected human population (10°-107), vaccination etc. The molecular clock feature is believed to be inconsistent with the selectionist theory (ST). The GSR shows lack of dependence on the effective population size, suggesting Ohta's nearly neutral theory (ONNT) is not applicable to this virus. Big variation of the substitution rate within its genome is also inconsistent with Kimura's neutral theory (KNT). Thus, all three existing evolution theories fail to explain the evolutionary nature of this virus. In this paper, we proposed a Segment Substitution Rate Model (SSRM) under non-neutral selections and pointed out that a balanced mechanism between negative and positive selection of some segments that could also lead to the molecular clock feature. We named this hybrid mechanism as near-neutral balanced selection theory (NNBST) and examined if it was followed by SARS-CoV-2 using the three independent sets of SARS-CoV-2 genomes selected by the Nextstrain team. Intriguingly, the relative substitution rate of this virus exhibited an L-shaped probability distribution consisting with NNBST rather than Poisson distribution predicted by KNT or an asymmetric distribution predicted by ONNT in which nearly neutral sites are believed to be slightly deleterious only, or the distribution that is lack of nearly neutral sites predicted by ST. The time-dependence of the substitution rates for some segments and their correlation with the vaccination were observed, supporting NNBST. Our relative substitution rate method provides a tool to resolve the long standing "neutralist-selectionist" controversy. Implications of NNBST in resolving Lewontin's Paradox is also discussed.

Genetic and Structural Data on the SARS-CoV-2 Omicron BQ.1 Variant Reveal Its Low Potential for Epidemiological Expansion.

The BQ.1 SARS-CoV-2 variant, also known as Cerberus, is one of the most recent Omicron descendant lineages. Compared to its direct progenitor BA.5, BQ.1 has some additional spike mutations in some key antigenic sites, which confer further immune escape ability over other circulating lineages. In such a context, here, we perform a genome-based survey aimed at obtaining a complete-as-possible nuance of this rapidly evolving Omicron subvariant. Genetic data suggest that BQ.1 represents an evolutionary blind background, lacking the rapid diversification that is typical of a dangerous lineage. Indeed, the evolutionary rate of BQ.1 is very similar to that of BA.5 (7.6 × 10-4 and 7 × 10-4 subs/site/year, respectively), which has been circulating for several months. The Bayesian Skyline Plot reconstruction indicates a low level of genetic variability, suggesting that the peak was reached around 3 September 2022. Concerning the affinity for ACE2, structure analyses (also performed by comparing the properties of BQ.1 and BA.5 RBD) indicate that the impact of the BQ.1 mutations may be modest. Likewise, immunoinformatic analyses showed moderate differences between the BQ.1 and BA5 potential B-cell epitopes. In conclusion, genetic and structural analyses on SARS-CoV-2 BQ.1 suggest no evidence of a particularly dangerous or high expansion capability. Genome-based monitoring must continue uninterrupted for a better understanding of its descendants and all other lineages.

What is life? Active particles tools towards behavioral dynamics in social-biology and economics.

This review paper is devoted to study the conceptual difficulties that mathematics meets when attempting to describe the complexity of living matter focusing on the challenging perspective of developing a mathematical theory for living systems including mutations and selection. The quest starts with the identification of a number of common complexity features of living systems. Then, mathematical structures are derived to include these features, while mathematical models are derived by inserting in the structures models of individual based interactions. Three applications are examined by active particles methods, i.e., models of SARS2-CoV-2 pandemics, models of idiosyncratic learning in open markets and of the dynamics of prices accounting for human behaviors. A critical study, which pervades the whole paper, shows that also economics can be viewed as a behavioral science thus accounting for specific aspects typical of living systems.

Disease-causing human viruses: novelty and legacy.

About 270 viruses are known to infect humans. Some of these viruses have been known for centuries, whereas others have recently emerged. During their evolutionary history, humans have moved out of Africa to populate the world. In historical times, human migrations resulted in the displacement of large numbers of people. All these events determined the movement and dispersal of human-infecting viruses. Technological advances have resulted in the characterization of the genetic variability of human viruses, both in extant and in archaeological samples. Field studies investigated the diversity of viruses hosted by other animals. In turn, these advances provided insight into the evolutionary history of human viruses back in time and defined the key events through which they originated and spread.

Women amid the COVID-19 pandemic: Self-protection through the behavioral immune system.

Studies of the activation of the behavioral immune system triggered by the coronavirus disease-2019 pandemic have demonstrated that evolutionary explanations of individual differences in self-protection should not be based only on parental investment and sexual selection theory. An evolutionary model must also incorporate individual differences that arise within each sex as a result of life history strategies and attachment patterns.

The genetic and evolutionary determinants of COVID-19 susceptibility.

Devastating pandemics, such as that due to COVID-19, can provide strong testimony to our knowledge of the genetic and evolutionary determinants of infectious disease susceptibility and severity. One of the most remarkable aspects of such outbreaks is the stunning interindividual variability observed in the course of infection. In recent decades, enormous progress has been made in the field of the human genetics of infectious diseases, and an increasing number of human genetic factors have been reported to explain, to a great extent, the observed variability for a large number of infectious agents. However, our understanding of the cellular, molecular, and immunological mechanisms underlying such disparities between individuals and ethnic groups, remains very limited. Here, we discuss recent findings relating to human genetic predisposition to infectious disease, from an immunological or population genetic perspective, and show how these and other innovative approaches have been applied to deciphering the genetic basis of human susceptibility to COVID-19 and the severity of this disease. From an evolutionary perspective, we show how past demographic and selection events characterizing the history of our species, including admixture with archaic humans, such as Neanderthals, facilitated modern human adaptation to the threats imposed by ancient pathogens. In the context of emerging infectious diseases, these past episodes of genetic adaptation may contribute to some of the observed population differences in the outcome of SARS-CoV-2 infection and the severity of COVID-19 illness.

Green Transformation of Anti-Epidemic Supplies in the Post-Pandemic Era: An Evolutionary Approach.

Post-pandemic, the use of medical supplies, such as masks, for epidemic prevention remains high. The explosive growth of medical waste during the COVID-19 pandemic has caused significant environmental problems. To alleviate this, environment-friendly epidemic prevention measures should be developed, used, and promoted. However, contradictions exist between governments, production enterprises, and medical institutions regarding the green transformation of anti-epidemic supplies. Consequently, this study aimed to investigate how to effectively guide the green transformation. Concerning masks, a tripartite evolutionary game model, consisting of governments, mask enterprises, and medical institutions, was established for the supervision of mask production and use, boundary conditions of evolutionary stabilization strategies and government regulations were analyzed, and a dynamic system model was used for the simulation analysis. This analysis revealed that the only tripartite evolutionary stability strategy is for governments to deregulate mask production, enterprises to increase eco-friendly mask production, and medical institutions to use these masks. From the comprehensive analysis, a few important findings are obtained. First, government regulation can promote the green transformation process of anti-epidemic supplies. Government should realize the green transformation of anti-epidemic supplies immediately in order to avoid severe reputation damage. Second, external parameter changes can significantly impact the strategy selection process of all players. Interestingly, it is further found that the cost benefit for using environmentally friendly masks has a great influence on whether green transformation can be achieved. Consequently, the government should establish a favorable marketplace for, and promote the development of, inexpensive, high-quality, and effective environmentally friendly masks in order to achieve the ultimate goal of green transformation of anti-epidemic supplies in the post-pandemic era.

Meaningful Use of Pathogen Genomic Data.

Population genomic analysis is a powerful tool to understand the evolutionary history of pathogens and the factors contributing to the success or failure of lineages. These studies have significant implications for human health, as evident from our ongoing tracking of SARS-CoV-2. In their article, Gill et al. (J. L. Gill, J. Hedge, D. J. Wilson, and R. C. MacLean, mBio 12:e02168-21, 2021, https://doi.org/10.1128/mBio.02168-21) demonstrate the utility of pathogen genomic data by comprehensively elucidating the origin of methicillin-resistant Staphylococcus aureus ST239. To accomplish this, they leveraged newly developed tools for querying large genomic data sets. Overall, these analyses rely on the availability of representative genomic data along with their associated metadata-information about where and when samples were collected, clinical and epidemiological characteristics, and phenotypic properties. However, in many instances, these data are missing. Here, I borrow the term "meaningful use" from the Health IT field to describe the need to maximize the utility of genomic data and make suggestions for how to address the current limitations.

Defining the risk of SARS-CoV-2 variants on immune protection.

The global emergence of many severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants jeopardizes the protective antiviral immunity induced after infection or vaccination. To address the public health threat caused by the increasing SARS-CoV-2 genomic diversity, the National Institute of Allergy and Infectious Diseases within the National Institutes of Health established the SARS-CoV-2 Assessment of Viral Evolution (SAVE) programme. This effort was designed to provide a real-time risk assessment of SARS-CoV-2 variants that could potentially affect the transmission, virulence, and resistance to infection- and vaccine-induced immunity. The SAVE programme is a critical data-generating component of the US Government SARS-CoV-2 Interagency Group to assess implications of SARS-CoV-2 variants on diagnostics, vaccines and therapeutics, and for communicating public health risk. Here we describe the coordinated approach used to identify and curate data about emerging variants, their impact on immunity and effects on vaccine protection using animal models. We report the development of reagents, methodologies, models and notable findings facilitated by this collaborative approach and identify future challenges. This programme is a template for the response to rapidly evolving pathogens with pandemic potential by monitoring viral evolution in the human population to identify variants that could reduce the effectiveness of countermeasures.

Codon Usage and Phenotypic Divergences of SARS-CoV-2 Genes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first occurred in Wuhan (China) in December of 2019, causes a severe acute respiratory illness with a high mortality rate, and has spread around the world. To gain an understanding of the evolution of the newly emerging SARS-CoV-2, we herein analyzed the codon usage pattern of SARS-CoV-2. For this purpose, we compared the codon usage of SARS-CoV-2 with that of other viruses belonging to the subfamily of Orthocoronavirinae. We found that SARS-CoV-2 has a high AU content that strongly influences its codon usage, which appears to be better adapted to the human host. We also studied the evolutionary pressures that influence the codon usage of five conserved coronavirus genes encoding the viral replicase, spike, envelope, membrane and nucleocapsid proteins. We found different patterns of both mutational bias and natural selection that affect the codon usage of these genes. Moreover, we show here that the two integral membrane proteins (matrix and envelope) tend to evolve slowly by accumulating nucleotide mutations on their corresponding genes. Conversely, genes encoding nucleocapsid (N), viral replicase and spike proteins (S), although they are regarded as are important targets for the development of vaccines and antiviral drugs, tend to evolve faster in comparison to the two genes mentioned above. Overall, our results suggest that the higher divergence observed for the latter three genes could represent a significant barrier in the development of antiviral therapeutics against SARS-CoV-2.