Well-posedness and Steady States of Kermack-McKendrick Epidemic Models with Nonlocal Aggregation
This research paper introduces and analyzes a novel approach to modeling the spatial spread of epidemics using Kermack-McKendrick type models with nonlocal aggregation terms, establishing the well-posedness of the model and exploring the existence of non-trivial steady states.
The Law of Large Numbers for the SIR Model on Stochastic Block Models: A Proof Utilizing Herd Immunity
This research paper proves a law of large numbers for the susceptible-infected-recovered (SIR) epidemic model on networks with community structures, specifically the stochastic block model (SBM), using a novel approach based on herd immunity.
네트워크에서의 풍토병 감염에 대한 간결한 모델을 사용하여 감염과 사회적 상호 작용 간의 상충 관계 조사
본 논문에서는 사회적 연결과 그에 따른 이점, 그리고 감염병 회복력 및 연결 증가로 인한 풍토병 균형 규모 증가와 관련된 비용 간의 상충 관계를 조사합니다. 저자는 네트워크 구조, 특히 이질적인 접촉 수가 이러한 상충 관계에서 발생하는 최적의 접촉 수에 상당한 영향을 미칠 수 있음을 발견했습니다.
시공간적 SQEIAR 전염병 모델을 위한 지역별 제어 전략: COVID-19 적용 및 해석적 해의 존재성 증명
본 연구는 감염병 확산, 특히 COVID-19를 효과적으로 통제하기 위해 지역별 격리 및 치료 전략을 통합하는 시공간적 SQEIAR 전염병 모델을 제시하고, 해당 모델의 해의 존재성을 증명합니다.
An SIR Epidemic Model with Overlapping Household and Workplace Structures
This paper analyzes how the degree of overlap between households and workplaces influences the spread and final size of an SIR epidemic within a population.
Derivation of Macroscopic Epidemic Models from Multi-Agent Systems with Contact Dynamics
This chapter presents a method for deriving traditional compartmental epidemic models from more detailed multi-agent systems by incorporating the dynamics of contact distribution within a population.
Parrondo's Paradox in Epidemic Modeling: How Alternating Between Two Super-Critical Networks Can Lead to Epidemic Extinction
Alternating between two network structures, each of which would individually lead to an epidemic outbreak, can surprisingly result in epidemic extinction, a phenomenon known as Parrondo's paradox.
Frequentist Inference for a Semi-Mechanistic Epidemic Model with Interventions: A Comparative Study with Bayesian Approaches
This paper presents a frequentist approach to estimate the effects of public health interventions on epidemics using a semi-mechanistic model, offering an alternative to prevalent Bayesian methods and highlighting the advantages of avoiding prior distribution specification and achieving accurate confidence intervals.
Modeling the Impact of Interventions on a Hypothetical Zombie Epidemic in Uusimaa, Finland
Timely and strict quarantine measures are crucial to effectively contain and control a rapidly spreading epidemic, as demonstrated by a stochastic agent-based simulation of a hypothetical zombie outbreak in Uusimaa, Finland.
Opinion-Driven Risk Perception and its Impact on Infection Levels in Epidemics Modeled with SIS Dynamics
Incorporating opinion dynamics, specifically risk perception related to disease spread, into traditional epidemic models like the SIS model reveals that individual and collective behaviors significantly influence infection levels, highlighting the potential for behavioral interventions in epidemic control.
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