Small and large scale pandemics are a natural phenomenon repeatably appearing throughout history, causing ecological and biological shifts in ecosystems and a wide range of their habitats. These pandemics usually start with a single strain but shortly become multi-strain due to a mutation process of the pathogen causing the epidemic. In this study, we propose a novel eco-epidemiological model that captures multi-species prey-predator dynamics with a multi-strain pandemic. The proposed model extends and combines the Lotka-Volterra prey-predator model and the Susceptible-Infectious-Recovered epidemiological model. We investigate the ecosystem's sensitivity and stability during such a multi-strain pandemic through extensive simulation relying on both synthetic cases as well as two real-world configurations. Our results are aligned with known ecological and epidemiological findings, thus supporting the adequacy of the proposed model in realistically capturing the complex eco-epidemiological properties of the multi-species multi-strain pandemic dynamics.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1063/5.0154968 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Real-time estimates of the emergence and dynamics of SARS-CoV-2 variants of concern: A modeling approach.
Epidemics
December 2024
Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA; School of Mathematical Sciences, Queen Mary University of London, UK; The Alan Turing Institute, London, UK.
The emergence of SARS-CoV-2 variants of concern (VOCs) punctuated the dynamics of the COVID-19 pandemic in multiple occasions. The stages subsequent to their identification have been particularly challenging due to the hurdles associated with a prompt assessment of transmissibility and immune evasion characteristics of the newly emerged VOC. Here, we retrospectively analyze the performance of a modeling strategy developed to evaluate, in real-time, the risks posed by the Alpha and Omicron VOC soon after their emergence.
View Article and Find Full Text PDFReconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course.
PLoS Biol
November 2024
MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom.
Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology in humans remains unclear. Here, we used a multilevel mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015.
View Article and Find Full Text PDFExploring the metabolic profile of A. baumannii for antimicrobial development using genome-scale modeling.
PLoS Pathog
September 2024
Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard Karl University of Tübingen, Tübingen, Germany.
With the emergence of multidrug-resistant bacteria, the World Health Organization published a catalog of microorganisms urgently needing new antibiotics, with the carbapenem-resistant Acinetobacter baumannii designated as "critical". Such isolates, frequently detected in healthcare settings, pose a global pandemic threat. One way to facilitate a systemic view of bacterial metabolism and allow the development of new therapeutics is to apply constraint-based modeling.
View Article and Find Full Text PDFA program for real-time surveillance of SARS-CoV-2 genetics.
Sci Rep
August 2024
Labcorp Center for Excellence in Data Science, AI and Bioinformatics, Burlington, NC, 27215, USA.
The COVID-19 pandemic brought forth an urgent need for widespread genomic surveillance for rapid detection and monitoring of emerging SARS-CoV-2 variants. It necessitated design, development, and deployment of a nationwide infrastructure designed for sequestration, consolidation, and characterization of patient samples that disseminates de-identified information to public authorities in tight turnaround times. Here, we describe our development of such an infrastructure, which sequenced 594,832 high coverage SARS-CoV-2 genomes from isolates we collected in the United States (U.
View Article and Find Full Text PDFReconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course.
medRxiv
April 2024
MRC Centre for Global Infectious Disease Analysis, Imperial College London.
Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology remains unclear. Here, we used a multi-level mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!