Subgroup Contributed Talks

eSMB2020 eSMB2020 Follow Thursday at 1:30pm EDT
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Folashade Agusto

University of Kansas
"To isolate or not to isolate: The impact of changing behavior on COVID-19 transmission"
In this talk I will present a model developed for COVID-19 using a system of ordinary differential equation following the natural history of the infection. Using appropriate payoff functions relating to the perception of risk measured using disease incidence and severity of infection the model is coupled to a series of human behaviors including ignoring social distancing, and breaking out of isolation and quarantine. Analysis and simulations of the model show the possibility of multiple waves of infection. Discouraging the population from disease magnifying behavior such as escaping from isolation and quarantine eliminates the multiple waves of infection and greatly flattens the curves.

Alexander Beams

University of Utah
"Mask, or JASC? What are the conditions under which SARS-CoV-2 becomes Just Another Seasonal Coronavirus?"
Background: Will SARS-CoV-2 become Just Another Seasonal Coronavirus? It bears some important resemblances with its more benign cold-causing relatives, after all. For example, Coronavirus NL63 uses the same ACE2 receptor to gain entry into cells, and circumstantial evidence suggests Coronavirus OC43 may have caused a pandemic in the late 1800's. Both are now just 'common colds'. Is it possible that SARS-CoV-2 will take the same path? Hypotheses: We are writing models to address how three factors might push SARS-CoV-2 towards JASC. First, evidence suggests asymptomatic cases tend to shed less virus. If viral dose affects disease severity, and vice versa, selection might act to alleviate virulence. Second, we know that kids are far less likely to experience more severe forms of COVID-19, and different disease outcomes in kids vs adults will influence the epidemiology in important ways. Third, the JASC hypothesis might be sensitive to the duration of immunity to SARS-CoV-2. Eventually we hope to consider cross-immunity or interaction with other viruses, including seasonal coronaviruses, with a view to understand the COVID-19 pandemic in the context of the pre-existing respiratory virome. Results: Our models show that JASC is possible if viral dose correlates with disease severity and if immunity is sufficiently strong and long-lasting. We will present analyses of how our three factors influence the long-term outcomes of the pandemic. Conclusions: Although it is too early to say for certain, it is possible that SARS-CoV-2 could persist in humans as another cold-causing virus.

Juan Gutierrez

University of Texas at San Antonio
"Modeling COVID-19 Under Lockdown Conditions"
Coronavirus disease 2019 (COVID-19) is a novel human respiratory disease caused by the SARS-CoV-2 virus. Asymptomatic carriers of the virus display no clinical symptoms but are known to be contagious. Recent evidence reveals that this sub-population, as well as persons with mild symptoms, are major contributors in the propagation of COVID-19, a first for a respiratory virus. In another first, COVID-19 caused generalized restrictions to human movement and interactions. In this talk, we will discuss a traditional compartmentalized mathematical model taking into account asymptomatic carriers and lock-down conditions. The theoretical model is used to calibrate a model for the City of San Antonio, Texas.

Diego Volpatto

Laboratorio Nacional de Computacao Cientifica
"A Bayesian approach to assess the spread of COVID-19 using an extended SEIRD model with implicit quarantine mechanism: applications in Brazilian locations"
In this work, we develop a generalized SEIRD model that implicitly takes into account the quarantine mechanism to describe the spread of COVID-19 with applications in Brazil. We assume uncertain scenarios with limited testing capacity, lack of reliable data, under-reporting of cases, and restricted testing policy. To deal with data and model uncertainties, we developed a Bayesian framework for the identification of model parameters. A global sensitivity analysis is performed beforehand to identify the most significant parameters on either the cumulative numbers of confirmed and death cases, or the effective reproduction number. Less important parameter values are set according to the current knowledge on the disease in order to overcome the bottleneck of parameter identifiability. We show that the model parameter related to social distancing measures is one of the most influential along all stages of the disease spread and the most influential after the infection peak. Different relaxation strategies of social distancing measures are then investigated in order to determine which strategies are viable and less hazardous to the population. The results highlight the need of keeping social distancing policies to control the disease spread. Specifically, the considered scenario of abrupt social distancing relaxation implemented after the occurrence of the peak of positively diagnosed cases can prolong the epidemic, with a significant increase of the projected numbers of confirmed and death cases. An even worse scenario could occur if the quarantine relaxation policy is implemented before evidence of the epidemiological control, indicating the importance of the proper choice of when to start relaxing social distancing measures. The employed approach and subsequent analysis applied over the Brazilian scenarios may be used to other locations.

Julie Spencer

Los Alamos National Lab
"Prioritizing Mitigation Strategies for COVID-19 in New Mexico"
As of July 12, 2020, the novel zoonotic virus SARS-CoV-2 caused 15,028 confirmed infections and 545 deaths in the State of New Mexico. New Mexico ranks as the third highest state in the United States for per capita testing, and the time from identification of a traced contact to quarantine is two days; however, during the past seven days, cases have been increasing by 1.8% per day, leaving open the question of how best to intervene in the epidemic, given limited resources. Recent modeling studies have addressed mitigation strategies for COVID-19; however, there is a need for an age-structured mitigation model that provides pre-symptomatic, asymptomatic, symptomatic, testing, and quarantine compartments. We developed a deterministic, Susceptible-Exposed-Infected-Recovered (SEIR) model to assess the merits of a range of non-pharmaceutical intervention measures. We simulated all combinations of three social distancing levels, six testing levels, three testing turnaround speeds, and four testing accuracy levels, in order to evaluate 216 mitigation scenarios. We found that social distancing and testing are both necessary for decreasing total infections and for delaying the peak of the epidemic. We additionally found that increasing the turnaround speed of test results and decreasing the proportion of false negative tests has the potential to result in 27% fewer infections and 33% fewer deaths over the course of a two-year simulated epidemic. The epidemic outcomes are mitigated more effectively when school-aged individuals have less contact, as when schools are closed or operating virtually, than when working-aged individuals have less contact, as when businesses are closed or operating virtually. These are difficult but important prioritizations. UNCLASSIFIED LA-UR-20-25199
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