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Following the spread of the COVID-19 pandemic and pending the establishment of vaccination campaigns, several non pharmaceutical interventions such as partial and full lockdown, quarantine and measures of physical distancing have been…

The COVID-19 pandemic has placed unprecedented demands on local public health units in Ontario, Canada, one of which was the need for in-house epidemiological-modelling capabilities. To address this need, Ontario Tech University and the…

The unprecedented coronavirus disease 2019 (COVID-19) pandemic is still a worldwide threat to human life since its invasion into the daily lives of the public in the first several months of 2020. Predicting the size of confirmed cases is…

This study evaluates and extends the findings made by Piatti et al., who introduced GovSim, a simulation framework designed to assess the cooperative decision-making capabilities of large language models (LLMs) in resource-sharing…

The SARS-CoV-2 infectious outbreak has rapidly spread across the globe and precipitated varying policies to effectuate physical distancing to ameliorate its impact. In this study, we propose a new hybrid machine learning model, SIRNet, for…

As of Aug. 2020, coronavirus disease 2019 (COVID-19) is still spreading in the world. In Japan, the Ministry of Health, Labor, and Welfare developed "COVID-19 Contact-Confirming Application (COCOA)," which was released on Jun. 19, 2020. By…

The recent history of respiratory pathogen epidemics, including those caused by influenza and SARS-CoV-2, has highlighted the urgent need for advanced modeling approaches that can accurately capture heterogeneous disease dynamics and…

Game theory has been an effective tool in the control of disease spread and in suggesting optimal policies at both individual and area levels. In this paper, we propose a multi-region SEIR model based on stochastic differential game theory,…

Major interventions have been introduced worldwide to slow down the spread of the SARS-CoV-2 virus. Large-scale lockdowns of human movements are effective in reducing the spread, but they come at a cost of significantly limited societal…

We present a new mathematical model to explicitly capture the effects that the three restriction measures: the lockdown date and duration, social distancing and masks, and, schools and border closing, have in controlling the spread of…

During the COVID-19 pandemic, a large variance of incidence rates on local level, e.g. cities and districts, within one country has been observed, while the same non-pharmaceutical measures have been taken to control the spread of the…

To curb the initial spread of SARS-CoV-2, many countries relied on nation-wide implementation of non-pharmaceutical intervention measures, resulting in substantial socio-economic impacts. Potentially, subnational implementations might have…

Deciphering travel behavior and mode choices is a critical aspect of effective urban transportation system management, particularly in developing countries where unique socio-economic and cultural conditions complicate decision-making.…

Background: Early detection and isolation of COVID-19 patients are essential for successful implementation of mitigation strategies and eventually curbing the disease spread. With a limited number of daily COVID-19 tests performed in every…

This paper proposes a framewrok for analyzing how the welfare effects of policy interventions are distributed across individuals when those effects are unobserved. Rather than focusing solely on average outcomes, the approach uses readily…

This paper studies the unconditional effects of a general policy intervention, which includes location-scale shifts and simultaneous shifts as special cases. The location-scale shift is intended to study a counterfactual policy aimed at…

The rapid spread of the novel coronavirus (COVID-19) has severely impacted almost all countries around the world. It not only has caused a tremendous burden on health-care providers to bear, but it has also brought severe impacts on the…

In order to slow the spread of the CoViD-19 pandemic, governments around the world have enacted a wide set of policies limiting the transmission of the disease. Initially, these focused on non-pharmaceutical interventions; more recently,…

The global spread of pandemics is facilitated by the mobility of populations, transforming localized infections into widespread phenomena. To contain it, timely identification of influential regions that accelerate this process is…

Accurate forecasts of the number of newly infected people during an epidemic are critical for making effective timely decisions. This paper addresses this challenge using the SIMLR model, which incorporates machine learning (ML) into the…