scholarly journals Modelling transmission and control of the COVID-19 pandemic in Australia

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Sheryl L. Chang ◽  
Nathan Harding ◽  
Cameron Zachreson ◽  
Oliver M. Cliff ◽  
Mikhail Prokopenko
Keyword(s):  
Computational Simulation ◽  
International Travel ◽  
School Closures ◽  
Agent Based ◽  
Social Distancing ◽  
Fine Grained ◽  
Trade Offs ◽  
Travel Restrictions ◽  
High Level ◽  
And Control

Abstract There is a continuing debate on relative benefits of various mitigation and suppression strategies aimed to control the spread of COVID-19. Here we report the results of agent-based modelling using a fine-grained computational simulation of the ongoing COVID-19 pandemic in Australia. This model is calibrated to match key characteristics of COVID-19 transmission. An important calibration outcome is the age-dependent fraction of symptomatic cases, with this fraction for children found to be one-fifth of such fraction for adults. We apply the model to compare several intervention strategies, including restrictions on international air travel, case isolation, home quarantine, social distancing with varying levels of compliance, and school closures. School closures are not found to bring decisive benefits unless coupled with high level of social distancing compliance. We report several trade-offs, and an important transition across the levels of social distancing compliance, in the range between 70% and 80% levels, with compliance at the 90% level found to control the disease within 13–14 weeks, when coupled with effective case isolation and international travel restrictions.

Agent Support for Design of Aircraft Parts

1998 ◽  
Author(s):  
Krishna N. Jha ◽  
Andrea Morris ◽  
Ed Mytych ◽  
Judith Spering
Keyword(s):  
Preliminary Design ◽  
Formal Representation ◽  
Web Based ◽  
Agent Based ◽  
Multi Agent ◽  
High Level ◽  
Legacy Applications ◽  
The Cost ◽  
And Control ◽  
Task Structures

Abstract Designing aircraft parts requires extensive coordination among multiple distributed design groups. Achieving such a coordination is time-consuming and expensive, but the cost of ignoring or minimizing it is much higher in terms of delayed and inferior quality products. We have built a multi-agent-based system to provide the desired coordination among the design groups, the legacy applications, and other resources during the preliminary design (PD) process. A variety of agents are used to model the various design and control functionalities. The agent-representation includes a formal representation of the task-structures. A web-based user-interface provides high-level interface to the users. The agents collaborate to achieve the design goals.

scholarly journals Modeling the Spread and Control of COVID-19

Systems ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 53
Author(s):  
Ashutosh Trivedi ◽  
Nanda Kishore Sreenivas ◽  
Shrisha Rao
Keyword(s):  
Herd Immunity ◽  
Black Box ◽  
Personal Hygiene ◽  
Confined Space ◽  
Real Situation ◽  
Seir Model ◽  
Agent Based ◽  
Social Distancing ◽  
The Difference ◽  
And Control

Data-centric models of COVID-19 have been attempted, but have certain limitations. In this work, we propose an agent-based model of the epidemic in a confined space of agents representing humans. An extension to the SEIR model allows us to consider the difference between the appearance (black-box view) of the spread of disease and the real situation (glass-box view). Our model allows for simulations of lockdowns, social distancing, personal hygiene, quarantine, and hospitalization, with further considerations of different parameters, such as the extent to which hygiene and social distancing are observed in a population. Our results provide qualitative indications of the effects of various policies and parameters, for instance, that lockdowns by themselves are extremely unlikely to bring an end to an epidemic and may indeed make things worse, that social distancing is more important than personal hygiene, and that the growth of infection is significantly reduced for moderately high levels of social distancing and hygiene, even in the absence of herd immunity.

Studies of COVID-19 Outbreak Control Using Agent-Based Modeling

2021 ◽  
Vol 30 (3) ◽  
pp. 297-321
Author(s):  
Shaoping Xiao ◽  
◽  
Ruicheng Liu ◽  
Keyword(s):  
Urban Communities ◽  
Control Measure ◽  
Agent Based Modeling ◽  
Control Measures ◽  
Published Data ◽  
Agent Based ◽  
Social Distancing ◽  
Outbreak Control ◽  
High Level ◽  
General Community

An agent-based model was developed to study outbreaks and outbreak control for COVID-19, mainly in urban communities. Rules for people’s interactions and virus infectiousness were derived based on previous sociology studies and recently published data-driven analyses of COVID-19 epidemics. The calculated basic reproduction number of epidemics from the developed model coincided with reported values. There were three control measures considered in this paper: social distancing, self-quarantine and community quarantine. Each control measure was assessed individually at first. Later on, an artificial neural network was used to study the effects of different combinations of control measures. To help quantify the impacts of self-quarantine and community quarantine on outbreak control, both were scaled respectively. The results showed that self-quarantine was more effective than the others, but any individual control measure was ineffective in controlling outbreaks in urban communities. The results also showed that a high level of self-quarantine and general community quarantine, assisted with social distancing, would be recommended for outbreak control.

scholarly journals Modeling the Spread and Control of COVID-19

2020 ◽  
Author(s):  
Ashutosh Trivedi ◽  
Nanda Kishore Sreenivas ◽  
Shrisha Rao
Keyword(s):  
Herd Immunity ◽  
Black Box ◽  
Personal Hygiene ◽  
Confined Space ◽  
Real Situation ◽  
Seir Model ◽  
Agent Based ◽  
Social Distancing ◽  
The Difference ◽  
And Control

ABSTRACTData-centric models of COVID-19 have been tried, but have certain limitations. In this work, we propose an agent-based model of the epidemic in a confined space of agents representing humans. An extension to the SEIR model allows us to consider the difference between the appearance (black-box view) of the spread of disease, and the real situation (glass-box view). Our model allows for simulations of lockdowns, social distancing, personal hygiene, quarantine, and hospitalization, with further considerations of different parameters such as the extent to which hygiene and social distancing are observed in a population. Our results give qualitative indications of the effects of various policies and parameters; for instance, that lockdowns by themselves are extremely unlikely to bring an end to an epidemic and may indeed make things worse, that social distancing matters more than personal hygiene, and that the growth of infection comes down significantly for moderately high levels of social distancing and hygiene, even in the absence of herd immunity.

scholarly journals Effects of worldwide interventions and vaccination on COVID-19 between waves and countries

2021 ◽  
Author(s):  
Yong Ge ◽  
Wenbin Zhang ◽  
Haiyan Liu ◽  
Corrine W Ruktanonchai ◽  
Maogui Hu ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Large Scale ◽  
International Travel ◽  
Spatiotemporal Variations ◽  
School Closures ◽  
Vaccination Strategies ◽  
Travel Restrictions ◽  
The Impact ◽  
Second Wave ◽  
Pharmaceutical Interventions

Abstract Worldwide governments have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic, together with the large-scale rollout of vaccines since late 2020. However, the effect of these individual NPI and vaccination measures across space and time has not been sufficiently explored. By the decay ratio in the suppression of COVID-19 infections, we investigated the performance of different NPIs across waves in 133 countries, and their integration with vaccine rollouts in 63 countries as of 25 March 2021. The most effective NPIs were gathering restrictions (contributing 27.83% in the infection rate reductions), facial coverings (16.79%) and school closures (10.08%) in the first wave, and changed to facial coverings (30.04%), gathering restrictions (17.51%) and international travel restrictions (9.22%) in the second wave. The impact of NPIs had obvious spatiotemporal variations across countries by waves before vaccine rollouts, with facial coverings being one of the most effective measures consistently. Vaccinations had gradually contributed to the suppression of COVID-19 transmission, from 0.71% and 0.86% within 15 days and 30 days since Day 12 after vaccination, to 1.23% as of 25 March 2021, while NPIs still dominated the pandemic mitigation. Our findings have important implications for continued tailoring of integrated NPI or NPI-vaccination strategies against future COVID-19 waves or similar infectious diseases.

scholarly journals COVID-19 and Social Distancing Measures in Queensland Australia Are Associated with Short-Term Decreases in Recorded Violent Crime

2020 ◽  
Author(s):  
Jason Leslie Payne ◽  
Anthony Morgan ◽  
Alex R. Piquero
Keyword(s):  
Domestic Violence ◽  
Sexual Assault ◽  
Violent Crime ◽  
Criminal Activity ◽  
International Travel ◽  
Social Distancing ◽  
Modeling Techniques ◽  
Travel Restrictions ◽  
Spanish Flu ◽  
Arima Modeling

Since first diagnosed in late 2019, there have been more than 4 million confirmed cases of COVID-19 and more than a quarter of a million deaths worldwide. Not since the Spanish Flu in 1918 has the world experienced such a widespread pandemic and this has motivated many countries across globe to take a series of unprecedented actions in an effort to curb the spread and impact of the virus through the adoption of unprecedented domestic and international travel restrictions as well as stay-at-home and social distancing regulations. Whether these policies have altered criminal activity is an important question. In this study, we examine officially recorded violent crime rates for the month of March and April, 2020, as reported for the state of Queensland, Australia. We use ARIMA modeling techniques to compute six-month-ahead forecasts of common assault, serious assault, sexual offense and domestic violence order breach rates and then compare these forecasts (and their 95\% confidence intervals) with the observed data for March and April 2020. We conclude that by the end of April, rates of common, serious and sexual assault had declined to their lowest level in a number of years, and for serious assault and sexual assault the decline was beyond statistical expectations. The rate at which domestic violence orders were breached in Queensland has remained unchanged throughout the first two months of the pandemic.

Computational Simulation Modeling in Population Health Research and Policy

2020 ◽  
pp. 171-184
Author(s):  
Nathaniel Osgood
Keyword(s):  
Dynamic Modeling ◽  
Multiple Scales ◽  
Computational Simulation ◽  
Discrete Event ◽  
Intervention Strategies ◽  
Agent Based ◽  
Event Simulation ◽  
Modeling Process ◽  
Trade Offs ◽  
Model Dynamics

Dynamic modeling provides a powerful tool for enabling faster learning in a complex and uncertain world. Within this contribution, we briefly survey three prominent dynamic modeling traditions—agent-based modeling, system dynamics, and discrete event simulation. Each such tradition offers unique combinations of strengths and limitations and is further distinguished by emphasis of different sets of modeling goals and norms. This chapter discusses such trade-offs between such methods, with a particular emphasis on the key distinction between aggregate and individual-based approaches, which has widespread practical ramifications. The authors further note the advent of hybrid dynamic modeling approaches, which provide unique levels of flexibility in addressing diverse intervention strategies and generative pathways at multiple scales and the capacity for the model representation to adapt with the learning and evolving understanding of key elements of model dynamics that constitute a key outcome of the modeling process.

scholarly journals Low-Impact Social Distancing Interventions to Mitigate Local Epidemics of SARS-CoV-2

2020 ◽  
Author(s):  
Michael L. Jackson
Keyword(s):  
Nursing Home ◽  
Hospital Admissions ◽  
Herd Immunity ◽  
Nursing Home Residents ◽  
King County ◽  
Rapid Testing ◽  
School Closures ◽  
Agent Based ◽  
Social Distancing ◽  
Hospital Occupancy

AbstractBackgroundAfter many jurisdictions have implemented intensive social distancing to suppress SARS-CoV-2 transmission, the challenge now is to mitigate the ongoing COVID-19 epidemic without overburdening economic and social activities. This report explores “low-impact” interventions to mitigate SARS-CoV-2 with a minimum of social and economic disruption.MethodsAn agent-based model simulated the population of King County, Washington, with agents that interact in homes, schools, workplaces, and other community sites. SARS-CoV-2 transmission probabilities were estimated by fitting simulated to observed hospital admissions from February – May 2020. Interventions considered were (a) encouraging telecommuting; (b) reducing contacts to seniors and nursing home residents; (c) modest reductions to contacts outside of the home; (d) encouraging self-isolation of persons with COVID-19 symptoms; (e) rapid testing and household quarantining.ResultsIndividual interventions are not expected to have a large impact on COVID-19 hospitalizations. No intervention reduced COVID-19 hospitalizations by more than 12.7% (95% confidence interval [CI], 12.0% to 13.3%). Removing all interventions would result in nearly 42,000 COVID- 19 hospitalizations between June 2020 and January 2021, with peak hospital occupancy exceeding available beds 6-fold. Combining the interventions is predicted to reduce total hospitalizations by 48% (95% CI, 47-49%), with peak COVID-19 hospital occupancy of 70% of total beds. Targeted school closures can further reduce the peak occupancy.ConclusionsCombining low-impact interventions may mitigate the course of the COVID-19 epidemic, keeping hospital burden within the capacity of the healthcare system. Under this approach SARS-CoV-2 can spread through the community, moving toward herd immunity, while minimizing social and economic disruption.

Agent Support for Collaborative Design

1998 ◽  
Author(s):  
Krishna N. Jha ◽  
Andrea Morris ◽  
Ed Mytych ◽  
Judith Spering
Keyword(s):  
Collaborative Design ◽  
Formal Representation ◽  
Web Based ◽  
Agent Based ◽  
Interface Agents ◽  
Multi Agent ◽  
High Level ◽  
The Cost ◽  
And Control ◽  
Task Structures

Abstract Extensive collaboration among multiple distributed design groups is required to design aircraft parts. Achieving such a collaboration manually is time-consuming, expensive, and inefficient; but the cost of ignoring or minimizing it is much higher in terms of delayed and/or inferior quality products. We describe a multi-agent-based approach to support the desired collaboration among the design groups during the preliminary design (PD) process. A variety of agents including interface agents and control agents are used to model the various collaboration functionalities. The agent-representation includes a formal representation of the task-structures. A web-based user-interface provides high-level interface to the users. The agents collaborate to produce optimized and feasible designs.

scholarly journals Covid-19 Social Distancing Interventions by State Mandate and Their Correlation to Mortality

2020 ◽  
Author(s):  
sean mccafferty ◽  
sean ashley
Keyword(s):  
Mortality Rate ◽  
Negative Correlation ◽  
Statistical Correlation ◽  
The State ◽  
Daily Mortality ◽  
School Closures ◽  
Social Distancing ◽  
Social Interventions ◽  
Effective Reduction ◽  
Travel Restrictions

Abstract Purpose Evaluate the correlation between state mandated social interventions and Covid-19 mortality Design Prospective design and retrospective analysis of Institute for Health Metrics and Evaluation (IHME) state data. Methods Twelve European Union countries were selected on April 12, 2020 from IHME data which had clearly defined and dated establishment of statewide mandates for social distancing measures to include: School closures, stay at home orders, severe travel restrictions, and closure of non-essential businesses. The state Covid-19 mortality prevalence was defined as total normalized deaths to the peak daily mortality rate. The state mortality prevalence was correlated to the total number of mandates-days from their date of establishment to the peak daily mortality date. The slope of the maximum daily mortality rate was also correlated to mandate-days. Results The slope of standardized mortality per country did have a slight negative correlation to the total mandate days (R2 = 0.083, p= 0.36), though the negative correlation was not statistically significant. The standardized mortality prevalence to the peak mortality rate per country exhibited no discernable statistical correlation to the total mandate days (R2 = 0.004,p=0.85). Discussion The analysis appears to suggest a mandate effective reduction in the slope of the mortality rate, but no effective reduction in Covid-19 mortality to its defined initial peak when interpreting the mean-effect of the mandates as present in the data. The study is presented as a potential methodology to evaluate the effectiveness of state mandated social distancing policy.

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