Abstract : Mathematical epidemiology, the modeling of the spread of epidemics, has a distinguished history and continues to be a very active field, with fruitful interaction of mathematical theory, computation, and data analysis. In the wake of the COVID-19 pandemic, modeling has played an important role in providing a framework for understanding empirical data and guiding policy. This mini-symposium will include presentations of recent results related to the mathematical modeling of epidemics, and provide a forum for discussion among researchers. Issues to be addressed include control measures for epidemics, population immunity and vaccination, heterogeneity of populations, and parameter inference for epidemic models.
Organizer(s) : Nir Gavish, Guy Katriel, Yukihiko Nakata
[03453] Optimal vaccination at high reproductive numbers: sharp transitions and counter-intuitive allocations
Format : Talk at Waseda University
Author(s) :
Nir Gavish (Technion - Israeli Institute of Technology)
Guy Katriel (Braude College of Engineering)
Abstract : Optimizing vaccine allocation is crucial for effective vaccination campaigns against epidemics. Contrary to intuition and classic vaccination theory, we show that for leaky vaccines and high basic reproduction numbers, the optimal allocation strategy for minimizing infections prioritizes those least likely to be infected. These findings have important implications for managing vaccination campaigns against highly transmissible infections.
[04794] An epidemic model for reinfection dynamics with heterogeneous susceptibility
Format : Talk at Waseda University
Author(s) :
Yukihiko Nakata (Aoyama Gakuin University)
Abstract : Individuals in a population vary in susceptibility. To explore the impact of the distributed susceptibility, we consider an epidemic model, where individuals acquire a degree of susceptibility with a probability after infection. It is shown that heterogeneous susceptibility adds complexity to the reinfection dynamics, and changes in the distribution of susceptibility may cause unexpected epidemics. We revisit the epidemic model studied by Katriel in 2010. The study is partly a joint work with Ryosuke Omori.
[03972] Effective screening with rapid antigen tests for COVID-19 patients: simulation with viral dynamics model
Format : Talk at Waseda University
Author(s) :
Yong Dam Jeong (Nagoya University)
Keisuke Ejima (Nanyang Technological University)
Ajelli Marco (Indiana University School of Public Health-Bloomington)
Shingo Iwami (Nagoya University)
Abstract : In this study, we assessed the effectiveness of various screening strategies with rapid antigen tests in schools and workplaces. For this, we developed two models with different scales: a transmission model in the community where those facilities under screening tests belong, and a viral dynamics model of each infected case in those facilities. Those screening strategies were compared through quantitative simulations. Our computational framework will be useful to evaluate screening strategies for infectious disease transmission.
[03510] Evaluation of Effectiveness of Global COVID-19 Vaccination Campaign in 2021
Format : Talk at Waseda University
Author(s) :
Daihai He (Hong Kong Polytechnic University)
Abstract : To model estimated deaths averted by COVID-19 vaccines, we used state-of-the-art mathematical modeling, likelihood-based inference, and reported COVID-19 death and vaccination data. We estimated that >1.5 million deaths were averted in 12 countries. Our model can help assess effectiveness of the vaccination program, which is crucial for curbing the COVID-19 pandemic.
[03458] Exploring the dynamics of contagion models with stages
Format : Talk at Waseda University
Author(s) :
Guy Katriel (Braude College of Engineering)
Abstract : We study models which are similar to classical epidemiological models, but in which becoming `contagion' involves a process with several stages. Such mechanisms are natural when considering phenomena of `social contagion' - the transmission of beliefs, behaviors. It is shown that these models display a variety of nonlinear behaviors that are absent in the corresponding `classical' epidemiological models, including: bistability, critical transitions, endogenous oscillations, and excitability. These phenomena, and the bifurcations involved, are studied by a combination of analytical and numerical means. We thus suggest that two-stage (or multi-stage) contagion can serve as a possible explanatory mechanism for some of the complex dynamical phenomena observed in social life.
[04574] Mathematical modeling of COVID-19 transmission with pandemic response in South Korea
Format : Talk at Waseda University
Author(s) :
Yongin Choi (National Institute for Mathematical Sciences)
Kyeongah Nah (National Institute for Mathematical Sciences)
Abstract : In this study, we investigated the effects of control policies on the COVID-19 outbreak in South Korea using a transmission dynamics model, where its transmission rate is estimated by a machine-learning algorithm. Our findings showed that the effectiveness of these policies varied across different waves of the epidemic and was influenced by various factors, such as vaccination coverage and mobility levels. Our findings emphasize the importance of a data-driven approach to evaluate COVID-19 policies.
[03885] Front propagation in an epidemiological model with mutations
Format : Talk at Waseda University
Author(s) :
Hiroshi Matano (Meiji University)
Quentin Griette (Université Le Havre Normandie)
Abstract : We consider a reaction-diffusion system describing the propagation of disease that involves mutation of the pathogen. More precisely this is an S-I-S epidemic model with diffusion in which two types of pathogens appear (wild and mutant). We assume that mutation occurs reciprocally between the two types at a certain rate. The resulting reaction-diffusion system has a peculiar feature: it is of the cooperative nature for small density of infected population while it is of the competitive nature for large density. This model was introduced by Q.Griette and G.Raoul in 2016 for a spatially homogeneous environment. Similar systems were also studied slightly later by L.Girardin and by E.Crooks et al, also for the spatially homogeneous case.
In this talk, I will consider this system in spatially periodic environments and present the following results: (1) existence of traveling waves; (2) spreading speed of infection when starting from localized initial data; (3) stability and asymptotic profile of propagating fronts. I will also discuss the homogenization limit of the problem when the spatial period of the environment tends t
[05100] Resolving the enigma of COVID-19 outbreaks in Iquitos and Manaus
Format : Talk at Waseda University
Author(s) :
lewi stone (RMIT University)
Daihai He (Hong Kong Polytechnic University)
Abstract : The nearby cities of Iquitos (Peru) and Manaus (Brazil) experienced the world’s highest infection and mortality rates
during the first 2020 COVID-19 wave. Key studies suggested >70% of the Manaus population was infected, and thus
close to herd immunity and protected. It remains an enigma as to why a deadly second wave followed in Manaus. We
present a data-driven model of epidemic dynamics in Iquitos to help explain and model events in Manaus
