scholarly journals Evaluation of SARS-CoV-2 transmission mitigation strategies on a university campus using an agent-based network model

Author(s):  
Ravi Goyal ◽  
John Hotchkiss ◽  
Robert T Schooley ◽  
Victor De Gruttola ◽  
Natasha K Martin

Abstract Universities are faced with decisions on how to resume campus activities while mitigating SARS-CoV-2 risk. To provide guidance for these decisions, we developed an agent-based network model of SARS-CoV-2 transmission to assess the potential impact of strategies to reduce outbreaks. The model incorporates important features related to risk at the University of California San Diego. We found that structural interventions for housing (singles only) and instructional changes (from in-person to hybrid with class size caps) can substantially reduce R0, but masking and social distancing are required to reduce this to at or below 1. Within a risk mitigation scenario, increased frequency of asymptomatic testing from monthly to twice weekly has minimal impact on average outbreak size (1.1-1.9), but substantially reduces the maximum outbreak size and cumulative number of cases. We conclude that an interdependent approach incorporating risk mitigation, viral detection, and public health intervention is required to mitigate risk.

2020 ◽  
Vol 14 (1) ◽  
pp. 321-335
Author(s):  
Marco Vona

Background: Seismic risk mitigation is an important issue in earthquake-prone countries, and needs to be solved in those complex communities governed by complex processes, where urban planning, socioeconomic dynamics, and, often, the need to preserve cultural assets are present simultaneously. In recent years, due to limited financial resources, mitigation activities have often been limited to post-earthquake events, and only a few in periods of inactivity, particularly in urban planning. At this point, a significant change in point of view is necessary. Methods: The seismic risk mitigation (and more generally, natural risk mitigation) must be considered as the main topic in urban planning and in the governance of communities. In fact, in several recent earthquakes, significant socioeconomic losses have been caused by the low or lack of resilience of the communities. This is mainly due to the high vulnerability of private buildings, in particular, housing units. Results: Therefore, in recent years, several studies have been conducted on the seismic resilience of communities. However, significant improvements are still needed for the resilience assessment of the housing stock, both qualitatively and quantitatively. In this study, which is applied to the housing system, a proposal regarding a change in urban planning and emergency management tools based on the concept of resilience is reported. As a first application, a case study in Italy is considered. Conclusion: The proposal is focused on defining and quantifying the improvement of the resilience of the communities and this must be obtained by modifying the current Civil Protection plan. New tools are based on a new resilience community plan by encompassing urban planning tools, resilient mitigation strategies, and consequently, emergency management planning.


Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1861
Author(s):  
Daniela Calvetti ◽  
Alexander P. Hoover ◽  
Johnie Rose ◽  
Erkki Somersalo

Understanding the dynamics of the spread of COVID-19 between connected communities is fundamental in planning appropriate mitigation measures. To that end, we propose and analyze a novel metapopulation network model, particularly suitable for modeling commuter traffic patterns, that takes into account the connectivity between a heterogeneous set of communities, each with its own infection dynamics. In the novel metapopulation model that we propose here, transport schemes developed in optimal transport theory provide an efficient and easily implementable way of describing the temporary population redistribution due to traffic, such as the daily commuter traffic between work and residence. Locally, infection dynamics in individual communities are described in terms of a susceptible-exposed-infected-recovered (SEIR) compartment model, modified to account for the specific features of COVID-19, most notably its spread by asymptomatic and presymptomatic infected individuals. The mathematical foundation of our metapopulation network model is akin to a transport scheme between two population distributions, namely the residential distribution and the workplace distribution, whose interface can be inferred from commuter mobility data made available by the US Census Bureau. We use the proposed metapopulation model to test the dynamics of the spread of COVID-19 on two networks, a smaller one comprising 7 counties in the Greater Cleveland area in Ohio, and a larger one consisting of 74 counties in the Pittsburgh–Cleveland–Detroit corridor following the Lake Erie’s American coastline. The model simulations indicate that densely populated regions effectively act as amplifiers of the infection for the surrounding, less densely populated areas, in agreement with the pattern of infections observed in the course of the COVID-19 pandemic. Computed examples show that the model can be used also to test different mitigation strategies, including one based on state-level travel restrictions, another on county level triggered social distancing, as well as a combination of the two.


2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 43-43
Author(s):  
Scott C Merrill ◽  
Christopher Koliba ◽  
Gabriela Bucini ◽  
Eric Clark ◽  
Luke Trinity ◽  
...  

Abstract Disease and its consequences result in social and economic impacts to the US animal livestock industry, ranging from losses in human capital to economic costs in excess of a billion dollars annually. Impacts would dramatically escalate if a devastating disease like Foot and Mouth Disease or African Swine Fever virus were to emerge in the United States. Investing in preventative biosecurity can reduce the likelihood of disease incursions and their negative impact on our livestock industry, yet uncertainty persists with regards to developing an effective biosecurity structure and culture. Here we show the implications of human behavior and decision making for biosecurity effectiveness, from the operational level to the owner/managerial level and finally to the systems level. For example, adjustments to risk messaging strategies could double worker compliance with biosecurity practices at the operational level. The improvement of our risk communication strategy may increase willingness to invest in biosecurity. Furthermore, the adaptation of policies could nudge behavior so that we observe a short disease outbreak followed by a quick eradication instead of a pandemic. Our research shows how the emergence of now-endemic diseases, such as Porcine Epidemic Diarrhea virus, cannot be adequately modeled without the use of a human behavioral component. Focusing solely on any one sector or level of the livestock system is not sufficient to predict emergent disease patterns and their social and economic impact on livestock industries. These results provide insight toward developing more effective risk mitigation strategies and ways to nudge behavior toward more disease resilient systems.


2021 ◽  
Vol 13 (12) ◽  
pp. 6596
Author(s):  
Riccardo Ceccato ◽  
Riccardo Rossi ◽  
Massimiliano Gastaldi

The diffusion of the COVID-19 pandemic has induced fundamental changes in travel habits. Although many previous authors have analysed factors affecting observed variations in travel demand, only a few works have focused on predictions of future new normal conditions when people will be allowed to decide whether to travel or not, although risk mitigation measures will still be enforced on vehicles, and innovative mobility services will be implemented. In addition, few authors have considered future mandatory trips of students that constitute a great part of everyday travels and are fundamental for the development of society. In this paper, logistic regression models were calibrated by using data from a revealed and stated-preferences mobility survey administered to students and employees at the University of Padova (Italy), to predict variables impacting on their decisions to perform educational and working trips in the new normal phase. Results highlighted that these factors are different between students and employees; furthermore, available travel alternatives and specific risk mitigation measures on vehicles were found to be significant. Moreover, the promotion of the use of bikes, as well as bike sharing, car pooling and micro mobility among students can effectively foster sustainable mobility habits. On the other hand, countermeasures on studying/working places resulted in a slight effect on travel decisions.


Author(s):  
Agnes Ann Feemster ◽  
Melissa Augustino ◽  
Rosemary Duncan ◽  
Anand Khandoobhai ◽  
Meghan Rowcliffe

Abstract Disclaimer In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose The purpose of this study was to identify potential failure points in a new chemotherapy preparation technology and to implement changes that prevent or minimize the consequences of those failures before they occur using the failure modes and effects analysis (FMEA) approach. Methods An FMEA was conducted by a team of medication safety pharmacists, oncology pharmacists and technicians, leadership from informatics, investigational drug, and medication safety services, and representatives from the technology vendor. Failure modes were scored using both Risk Priority Number (RPN) and Risk Hazard Index (RHI) scores. Results The chemotherapy preparation workflow was defined in a 41-step process with 16 failure modes. The RPN and RHI scores were identical for each failure mode because all failure modes were considered detectable. Five failure modes, all attributable to user error, were deemed to pose the highest risk. Mitigation strategies and system changes were identified for 2 failure modes, with subsequent system modifications resulting in reduced risk. Conclusion The FMEA was a useful tool for risk mitigation and workflow optimization prior to implementation of an intravenous compounding technology. The process of conducting this study served as a collaborative and proactive approach to reducing the potential for medication errors upon adoption of new technology into the chemotherapy preparation process.


Author(s):  
Paolo Pezzini ◽  
David Tucker ◽  
Alberto Traverso

A new emergency shutdown procedure for a direct-fired fuel cell turbine hybrid power system was evaluated using a hardware-based simulation of an integrated gasifier/fuel cell/turbine hybrid cycle (IGFC), implemented through the Hybrid Performance (Hyper) project at the National Energy Technology Laboratory, U.S. Department of Energy (NETL). The Hyper facility is designed to explore dynamic operation of hybrid systems and quantitatively characterize such transient behavior. It is possible to model, test, and evaluate the effects of different parameters on the design and operation of a gasifier/fuel cell/gas turbine hybrid system and provide a means of quantifying risk mitigation strategies. An open-loop system analysis regarding the dynamic effect of bleed air, cold air bypass, and load bank is presented in order to evaluate the combination of these three main actuators during emergency shutdown. In the previous Hybrid control system architecture, catastrophic compressor failures were observed when the fuel and load bank were cut off during emergency shutdown strategy. Improvements were achieved using a nonlinear fuel valve ramp down when the load bank was not operating. Experiments in load bank operation show compressor surge and stall after emergency shutdown activation. The difficulties in finding an optimal compressor and cathode mass flow for mitigation of surge and stall using these actuators are illustrated.


Author(s):  
Leigh McCue

Abstract The purpose of this work is to develop a computationally efficient model of viral spread that can be utilized to better understand influences of stochastic factors on a large-scale system - such as the air traffic network. A particle-based model of passengers and seats aboard a single-cabin 737-800 is developed for use as a demonstration of concept on tracking the propagation of a virus through the aircraft's passenger compartment over multiple flights. The model is sufficiently computationally efficient so as to be viable for Monte Carlo simulation to capture various stochastic effects, such as number of passengers, number of initially sick passengers, seating locations of passengers, and baseline health of each passenger. The computational tool is then exercised in demonstration for assessing risk mitigation of intervention strategies, such as passenger-driven cleaning of seating environments and elimination of middle seating.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Asli Pelin Gurgun ◽  
Kerim Koc

PurposeAs a remedy to usually voluminous, complicated and not easily readable construction contracts, smart contracts can be considered as an effective and alternative solution. However, the construction industry is merely known as a frontrunner for fast adoption of recent technological advancements. Numerous administrative risks challenge construction companies to implement smart contracts. To highlight this issue, this study aims to assess the administrative risks of smart contract adoption in construction projects.Design/methodology/approachA literature survey is conducted to specify administrative risks of smart contracts followed by a pilot study to ensure that the framework is suitable to the research question. The criteria weights are calculated through the fuzzy analytical hierarchy process method, followed by a sensitivity analysis based on degree of fuzziness, which supports the robustness of the developed hierarchy and stability of the results. Then, a focus group discussion (FGD) is performed to discuss the mitigation strategies for the top-level risks in each risk category.FindingsThe final framework consists of 27 sub-criteria, which are categorized under five main criteria, namely, contractual, cultural, managerial, planning and relational. The findings show that (1) regulation change, (2) lack of a driving force, (3) works not accounted in planning, (4) shortcomings of current legal arrangements and (5) lack of dispute resolution mechanism are the top five risks challenging the adoption of smart contracts in construction projects. Risk mitigation strategies based on FGD show that improvements for the semi-automated smart contract drafting are considered more practicable compared to full automation.Originality/valueThe literature is limited in terms of the adoption of smart contracts, while the topic is receiving more attention recently. To support easy prevalence of smart contracts, this study attempts the most challenging aspects of smart contract adoption.


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