A multi-scale agent-based model of infectious disease transmission to assess the impact of vaccination and non-pharmaceutical interventions: The COVID-19 case
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Mathematical and computational models are useful tools for virtual policy experiments on infectious disease control. Most models fail to provide flexible and rapid simulation of various epidemic scenarios for policy assessment. This paper establishes a multi-scale agent-based model to investigate the infectious disease propagation between cities and within a city using the knowledge from person-to-person transmission. In the model, the contact and infection of individuals at the micro scale where an agent represents a person provide insights for the interactions of agents at the meso scale where an agent refers to hundreds of individuals. Four cities with frequent population movements in China are taken as an example and actual data on traffic patterns and demographic parameters are adopted. The scenarios for dynamic propagation of infectious disease with no external measures are compared versus the scenarios with vaccination and non-pharmaceutical interventions. The model predicts that the peak of infections will decline by 67.37% with 80% vaccination rate, compared to a drop of 89.56% when isolation and quarantine measures are also in place. The results highlight the importance of controlling the source of infection by isolation and quarantine throughout the epidemic. We also study the effect when cities implement inconsistent public health interventions, which is common in practical situations. Based on our results, the model can be applied to COVID-19 and other infectious diseases according to the various needs of government agencies.Keywords:
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Agent-Based Model
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Isolation
2019-20 coronavirus outbreak
Disease Control
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Agent-based models are a tool that can be used to better understand the dynamics of an infectious disease outbreak. An infectious disease outbreak is influenced by many factors including vaccination or immunity levels, population density, and the age structure of the population. We hypothesize that these factors along with interactions of factors and the actions of individuals would lead to outbreaks of different size and severity even in two towns that appear similar on paper. Thus, it is necessary to implement a model that is able to capture these interactions and the actions of individuals. Using openly available data we create a data-driven agent-based model to simulate the spread of an airborne infectious disease in an Irish town. Agent-based models have been known to produce results that include the emergence of patterns and behaviours that are not directly programmed into the model. Our model is tested by simulating an outbreak of measles that occurred in Schull, Ireland in 2012. We simulate the same outbreak in 33 different towns and look at the correlations between the model results and the town characteristics (population, area, vaccination rates, age structure) to determine if the results of the model are affected by interactions of those town characteristics and the decisions on the agents in the model. As expected our results show that the outbreaks are not strongly correlated with any of the main characteristics of the towns and thus the model is most likely capturing such interactions and the agent-based model is successful in capturing the differences in the outbreaks.
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Abstract During the COVID-19 pandemic, international travelling has been altered. Thailand requires a 14-day travel quarantine for travelers entering the country. However, extra self-quarantine might be ordered by the local authorities, so the healthy travelers could be kept isolated and excluded from work or other responsibilities. We reported a male traveler who was unnecessarily quarantined for 30 days since he arrived Thailand. Based on a symptom and an antibody result, we also proposed the promising quarantine decision for international travelers in Thailand. Reducing the length of quarantine may make it easier for people to quarantine by reducing the time they cannot work. A shorter quarantine period also can lessen stress on the public health system, especially when new infections are rapidly rising. Keywords: COVID-19, International travelers, Quarantine decision, Thailand
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2019-20 coronavirus outbreak
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Analysis of 17 quarantine species of fruit flies intercepted by the Yunnan Entry-Exit Inspection and Quarantine Bureau in recent years showed that the dominant species are Bactrocera dorsalis (Hendel), B. cucurbitae (Coquillett) and B. tau (Walker), according to their number and frequency. This paper analyzes their revival regions and non-survival regions, respectively, and recommends different quarantine measures based on the species of the pests, the circumstances along Yunnan border, affected fruit and vegetable species and the biology of the fruit flies.
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This manuscript assesses the public's understanding of and trust in the CDC following its recent statement shortening the recommended time for isolation. Overall, reviewers feel that while timely, the preprint has a number of limitations, specifically in regards to sampling.
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2019-20 coronavirus outbreak
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This study reports on a timely topic as recent studies have demonstrated that low trust in the CDC has implications for health beliefs and behaviors related to COVID-19.Many of the CDC's recent changes have been criticized by prominent scientists, policy experts, and health care professionals.Less is known, however, about how Americans perceived changing guidance on how long individuals must isolate and quarantine following COVID-19 infection or exposure.To answer this research question,
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This report provides an overview of federal and state public health laws as they relate to the quarantine and isolation of individuals and a discussion of constitutional issues that may be raised should individual liberties be restricted in a quarantine or isolation situation.
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To separate and isolate the ill have been important goals in medicine, in cultural practices, and in the resulting architectural forms when faced with the urgent problem of infection in society. In history, the isolation settings that have been designed and built were almost universally well distanced from the daily life of the community. The lazaretto, the pesthouse, the monastery infirmary, and the fever hospital are early examples of architects answering the call of science (of the time) and society to provide that all-important separation and isolation. Buildings that were specifically designed to isolate and treat difficult diseases include the Paimio Hospital by Alvaar Alto in 1932 and the Saranac Cure Cottages, such as the 1915 Trudeau Sanatorium that addressed tuberculosis, the massive general hospitals of Europe in the late 19th and early 20th century, and the so-called plague hospitals in North America that resulted from an imperfect understanding of the worldwide influenza pandemic of 1918. As knowledge grew, and especially as the germ theory of disease displaced the miasma theory of disease, designers collaborated with the medical world to create life-sustaining health care environments that call on different approaches to prevent the spread of infectious disease.
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To limit SARS-CoV-2 spread, quarantine and isolation are obligatory in several situations in Norway. We found low self-reported adherence to requested measures among 1,704 individuals (42%; 95% confidence interval: 37–48). Adherence was lower in May–June–July (33–38%) compared with April (66%), and higher among those experiencing COVID-19-compatible symptoms (71%) compared with those without (28%). These findings suggest that consideration is required of strategies to improve people’s adherence to quarantine and isolation.
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2019-20 coronavirus outbreak
Social Isolation
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Objective In this paper,we develop a method of differential equations based on the simulation of infectious diseases in studying the effects of vaccination on the inhibition of spreading infectious diseases.Methods In this experiment,the vaccination factors were divided into vaccination delay time and vaccination rate,the two sub-factors.Infectious disease research drew on the thought ofchamberapproach,combined with computer simulation technology for simulation.The study of vaccination on the spread of infectious diseases was adjusted according to the length of the delay time of vaccination and the rate of vaccination.Results In this simulation,the results showed that vaccination played an important role in inhibiting the spread of infectious diseases.And during the spread of infectious diseases,as for the healthy people,the shorter the delay,the greater the vaccination rate is,and we are able to control the spread of infectious diseases to greater extent.Conclusion The study of this method shows that the mathematical model combined with computer simulation technology is a very effective way to analyze infectious diseases and provide a theoretical basis for the prevention and treatment of infectious disease.
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