A Game-Theoretic Modeling Approach to Comprehend the Advantage of Dynamic Health Interventions in Limiting the Transmission of Multi-Strain Epidemics

In the situation of inadequate vaccines and rapid mutation of virulent strains, alternative health interventions play a crucial role in the containment of emerging epidemics. This study elucidates the critical aspects of health interventions to control epidemic resurgence. Besides, human behavioral response to epidemics plays an instrumental role in bringing the success of control efforts. The appearance of multi-strain epidemics has become a global health concern that requires special attention. Here, we introduce a novel mean-field epidemic game approach to predict the evolutionary dynamics of flu-like epidemics having multiple disease strains. Our model illustrates the importance of multiple provisions alongside their timely execution for better disease attenuation. In addition to vaccination, we introduce self-protection as a potential alternative that yields safeguard against either strain. Both these imperfect provisions render better efficacy against primary (resident) strain than secondary (mutant) to contain epidemic transmission. The simulation-backed model analysis further sheds some light on the crucial impacts of control interventions to limit the invasion of virulent strains from qualitative and quantitative viewpoints. It explicates how vaccination and self-protection complement each other as per situation demands. Our full-fledged theoretical approach further illustrates the dynamic trade-off between the cost and efficacy of a certain intervention. We confirm that the disease dies out when the basic reproduction number of individual strains is less than one and becomes endemic if it is greater than one. Finally, the model addresses the evolutionary consequences when mutation takes place from primary to secondary strain. Some impressive facts while employing dual provisions have been reinforced using a game-theoretic framework.

Study on the influencing factors of piecewise multi-strain crossover epidemic spread under data contamination

The ongoing impact of the novel coronavirus disease 2019(COVID-19)on work and daily life persists as we transition from emergency to normal circumstances.The continuous mutation of viral strains has resulted in a shift from a single strain to multiple cross-strains,contributing to the spread of the epidemic.Variations in infection rates of the same strain occur because of the implementation of diverse preventive measures at different times.This study investigated the dynamics of the pandemic in the presence of concurrent strains.Building on the classical Susceptible,Exposed,Infected,and Recovered(SEIR)model,a robust piecewise multi-strain cross-epidemic trend prediction model was proposed that employs the Hodges–Lehmann estimator to handle uncertain and contamination-prone epidemic information.A comparative analysis of epidemic spread trend curves across diverse populations using different robust methods revealed the superiority of the Hodges–Lehmann estimator-based model over the traditional method.The accurate prediction results of the model demonstrate its high reliability in tracking the changing trend of the COVID-19 outbreak,thereby supporting its implementation in subsequent epidemic prevention and control measures.

Mat hematical analysis of multi-target cells and multi-strnin age-structured model with two HIV infection routes

In this paper,we propose detailed and reasonable viral dynamics by using a multi-compartment model that incorporating the age since the infection of multiple infectedcells,multiple target cells(Langerhans-cells and CD4^(+)T-cells),multiple viral strains(CCR5 and CXR4 HIV)and multiple infection routes(cell-to-cell and cell-to-virus).Thebasic reproduction number,R_(0),of the whole model is derived from two transmissionmechanisms:one is the potential trigger from the infection routes for a single target celland other is the joint effect of multiple viral infections for multi-target cells.Accordingly,we study the global stability of the steady states for the single target model.For thewhole model,we prove that the infection-free steady state is globally asymptoticallystable if R_(0)<1,whereas viruses persist uniformly if R_(0)>1.Numerical simulations arecarried out to illustrate the theoretical results.Sensitive analyses expound the effect ofmodel parameters on the comprehensive reproduction number.It is remarkable to findthat simultaneous control of HlV infection for two target cells can effectively reducethe viral loads within-host.Finally,our work suggests that the synergetic mechanism ofmulti-target cells and multi-strain cannot be ignored during treatment.