Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session R17: Statistical Mechanics of Disease Propagation IIFocus Live
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Sponsoring Units: GSNP Chair: Cynthia Reichhardt, Los Alamos Natl Lab |
Thursday, March 18, 2021 8:00AM - 8:12AM Live |
R17.00001: A random-walk based epidemiological model Andrew Chu, Greg Huber, Aaron McGeever, Boris Veytsman, David Yllanes Random walkers on a two-dimensional square lattice are used to explore the spatio-temporal growth of an epidemic. We have found that a simple random-walk system generates nontrivial dynamics compared with traditional well-mixed models. Phase diagrams characterizing the long-term behaviors of the epidemics are calculated numerically. The phase boundary separating those sets of parameters leading to outbreaks dying out and those leading to indefinite growth is mapped out in detail. The functional dependence of the basic reproductive number R0 on the model's defining parameters reveals the role of spatial fluctuations and leads to a novel expression for R0. Special attention is given to simulations of inter-regional transmission of the contagion. The attack rate and the (growing) radius of gyration of the affected zones are used as measures of the severity of the outbreaks, in cases where R0 is not sufficiently prescriptive to chart the epidemic dynamics. |
Thursday, March 18, 2021 8:12AM - 8:24AM Live |
R17.00002: Superspreading of SARS-CoV-2 in the USA Calvin Pozderac, Brian Skinner A number of epidemics, including the SARS-CoV-1 epidemic of 2002-2004, have been known to exhibit superspreading, in which a small fraction of infected individuals are responsible for the majority of new infections. The existence of superspreading implies a fat-tailed distribution of infectiousness (new secondary infections caused per day) among different individuals. Here, we present a simple method to estimate the variation in infectiousness by examining the variation in early-time growth rates of new cases among different subpopulations. We use this method to estimate the mean and variance in the infectiousness, k, for SARS-CoV-2 transmission during the early stages of the pandemic within the United States. We find that σk/μk > 3.2, where μk is the mean infectiousness and σk is its standard deviation, which implies pervasive superspreading. This result allows us to estimate that in the early stages of the pandemic in the USA, nearly 81% of new cases were a result of the top 10% of most infectious individuals. |
Thursday, March 18, 2021 8:24AM - 8:36AM Live |
R17.00003: Ranking non-pharmaceutical interventions for SARS-CoV-2 pandemic using Global Sensitivity Analysis Kalpana Hanthanan Arachchilage, Mohammed Yousuff Hussaini Without an effective pharmaceutical intervention against SARS-CoV-2, policymakers worldwide encourage people to practice social distancing, use face masks and frequent hand washing to control disease transmission. However, implementing all these interventions create a significant socio-economical strain on the general public. Therefore, it is crucial to identify the individual effects of these interventions. In this study, we propose the Global Sensitivity Analysis (GSA) as a tool to rank these non-pharmaceutical interventions and provide a mathematical perspective of the impact of each of these interventions. The mathematical model consists of a compartmental model that includes social distancing and the use of face masks as non-pharmaceutical interventions. Further, the model uses a fear-based behavioral model that leads the transmission from unmasked to masked susceptible compartments. The model parameters are estimated using the reported deaths for the United States of America and Florida. Maximum hospital usage and the total number of deaths are used as the quantity of interest for the GSA. The Sobol indices are used to obtain the rankings of the input parameters. |
Thursday, March 18, 2021 8:36AM - 8:48AM Live |
R17.00004: Strategies for testing an infected population to mitigate the spread of a pandemic Mingtao Xia, Tom Chou Many mathematical models have been developed to simulate and predict |
Thursday, March 18, 2021 8:48AM - 9:00AM Live |
R17.00005: Agent-based model (ABM) reveals the potential of virus-like particles as antiviral therapy Sara Capponi Defective interfering (DI) particles are virus-like byproducts of viral infections characterized by functionally important genomic deletions making them unable to infect cells. Therefore, they require virus particles for spreading the infection. While DI particles cannot survive in absence of the ‘helper’ viruses, during an infection they act as parasite interfering and competing with viruses on cellular and viral resources. For these reasons, DI particles have been proposed as antiviral therapeutics. In addition, it has been hypothesized that DI genome triggers the immune response but the principles underlying the competition between DI and viral particles in presence of the immune response are still unclear. Given that the immune response is spatially heterogeneous, we turn to ABMs to elucidate the spatiotemporal pattern of such type of infection. We defined the rules of interactions between particles based on our previous theoretical studies and we found a complex interplay between the immune system, the DI and the viral particles modulating the spread of infection. In addition, we clarify the role of the DI particles in causing a delay of the infection onset and of the activation of the immune response. Our results will be discussed along with experimental data. |
Thursday, March 18, 2021 9:00AM - 9:12AM Live |
R17.00006: Small-number effects and cooperativity enhance epidemic containment by regional measures Philip Bittihn, Lukas Hupe, Jonas Isensee, Ramin Golestanian Epidemic containment with minimal restrictions for citizens is a central goal for policy makers. We showed earlier that population subdivision can resurrect certain stochastic effects that reduce the impact of an epidemic [Bittihn & Golestanian, Chaos, 2020]. Here, we ask whether similar effects also enhance the efficacy of regional containment measures triggered locally when infection numbers reach a critical threshold. |
Thursday, March 18, 2021 9:12AM - 9:24AM Live |
R17.00007: Exploring Network Communities with Random Walks Aditya Ballal, Willow Kion-Crosby, Alexandre V Morozov Communities within a network are sets of nodes such that the nodes within each set are connected more densely internally than with nodes outside the set. Community structures are very common in real-world networks such as social or biological networks. Detecting community structures is equivalent to clustering which is of interest in many areas of science. We propose a computationally efficient method, based on random walks, for community detection and clustering on undirected networks with weighted or unweighted edges. The method employs first-passage properties of random walks on networks, providing key statistics of network community structure such as the number of communities and the size of each community. Our method provides a complete hierarchy of clusters which is determined by the strengths of connections between them. Surprisingly, some of the key statistics can be obtained after exploring only a small fraction of nodes which is relevant to very large real-world networks. We have used this method to cluster biological networks such as gene co-expression networks as well as for finding community statistics of large real-world networks such as wikipedia. |
Thursday, March 18, 2021 9:24AM - 10:00AM Live |
R17.00008: Estimating the epidemic growth rate and the reproductive number R0 of SARS-CoV-2 Invited Speaker: Nick Hengartner
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Thursday, March 18, 2021 10:00AM - 10:12AM Live |
R17.00009: Effect of the charge distribution of virus coat proteins on the length of packaged RNAs Yinan Dong Single-stranded RNA viruses efficiently encapsulate their genome into a protein shell called the capsid. Electrostatic interactions between the positive charges in the capsid protein’s N-terminal tail and the negatively charged genome have been postulated as the main driving force for virus assembly. Recent experimental results indicate that the N-terminal tail with the same number of charges and same lengths package different amounts of RNA, which reveals that electrostatics alone cannot explain all the observed outcomes of the RNA self-assembly experiments. Using a mean-field theory, we show that the combined effect of genome configurational entropy and electrostatics can explain to some extent the amount of packaged RNA with mutant proteins where the location and number of charges on the tails are altered. Understanding the factors contributing to the virus assembly could promote the attempt to block viral infections or to build capsids for gene therapy applications. |
Thursday, March 18, 2021 10:12AM - 10:24AM Live |
R17.00010: COVID-19 Case and Fatality Data Analysis Benedikt Gutsche During the current COVID-19 epidemy various institutes collect case and |
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