Related papers: VacSIM: Learning Effective Strategies for COVID-19…
Understanding the dynamics of the COVID-19 pandemic is crucial for improved control and social distancing strategies. To that effect, we have employed the susceptible-exposed-infectious-recovered model, refined by contact tracing and…
Population-wide vaccination is critical for containing the SARS-CoV-2 (Covid-19) pandemic when combined with restrictive and prevention measures. In this study, we introduce SAIVR, a mathematical model able to forecast the Covid-19 epidemic…
This paper uses Covasim, an agent-based model (ABM) of COVID-19, to evaluate and scenarios of epidemic spread in New York State (USA), the UK, and the Novosibirsk region (Russia). Epidemiological parameters such as contagiousness (virus…
The Coronavirus Disease 2019 or the COVID-19 pandemic has swept almost all parts of the world since the first case was found in Wuhan, China, in December 2019. With the increasing number of COVID-19 cases in the world, SARS-CoV-2 has…
During the COVID-19 pandemic, regulatory decision-making was hampered by a lack of timely and high-quality data on rare outcomes. Studying rare outcomes following infection and vaccination requires conducting multi-center observational…
Accurate forecasts of COVID-19 is central to resource management and building strategies to deal with the epidemic. We propose a heterogeneous infection rate model with human mobility for epidemic modeling, a preliminary version of which we…
The COVID-19 pandemic has placed immense strain on hospital systems worldwide, leading to critical capacity challenges. This research proposes a two-part framework to optimize hospital capacity through patient relocation strategies. The…
Lockdowns are one of the most effective measures for containing the spread of a pandemic. Unfortunately, they involve a heavy financial and emotional toll on the population that often outlasts the lockdown itself. This article argues in…
This paper presents methods to choose individuals to test for infection during a pandemic such as COVID-19, characterized by high contagion and presence of asymptomatic carriers. The smart-testing ideas presented here are motivated by…
Warfarin, an anticoagulant medication, is formulated to prevent and address conditions associated with abnormal blood clotting, making it one of the most prescribed drugs globally. However, determining the suitable dosage remains…
Effective epidemic modeling is essential for managing public health crises, requiring robust methods to predict disease spread and optimize resource allocation. This study introduces a novel deep learning framework that advances time series…
We propose a bottom-up approach, based on Reinforcement Learning, to the design of a chain achieving efficient excitation-transfer performances. We assume distance-dependent interactions among particles arranged in a chain under…
During the COVID-19 pandemic, there were over three million infections in Los Angeles County (LAC). To facilitate distribution when vaccines first became available, LAC set up six mega-sites for dispensing a large number of vaccines to the…
The COVID-19 pandemic has so far accounted for reported 5.5M deaths worldwide, with 8.7% of these coming from India. The pandemic exacerbated the weakness of the Indian healthcare system. As of January 20, 2022, India is the second worst…
COVID-19 continues to cause a significant impact on public health. To minimize this impact, policy makers undertake containment measures that however, when carried out disproportionately to the actual threat, as a result if errorneous…
This study presents a new risk-averse multi-stage stochastic epidemics-ventilator-logistics compartmental model to address the resource allocation challenges of mitigating COVID-19. This epidemiological logistics model involves the…
Since the first wave of the COVID-19 pandemic, governments have applied restrictions in order to slow down its spreading. However, creating such policies is hard, especially because the government needs to trade-off the spreading of the…
We introduce DeepABM, a framework for agent-based modeling that leverages geometric message passing of graph neural networks for simulating action and interactions over large agent populations. Using DeepABM allows scaling simulations to…
Despite the unprecedented success in the rapid development of several effective vaccines against the Cov-SARS-2, global vaccination rollout efforts suffer from vaccine distribution inequality and vaccine acceptance, leading to insufficient…
The ongoing COVID-19 pandemic continues to affect communities around the world. To date, almost 6 million people have died as a consequence of COVID-19, and more than one-quarter of a billion people are estimated to have been infected…