Modeling and Analysis of Infectious Disease Transmission Considering Protection and Isolation

Based on the SEIR model, two compartments for self-protection and isolation are introduced, and a more general infectious disease transmission model is proposed.Through qualitative analysis of the model, the basic reproduction number of the model is calculated, and the local asymptotic stability of the disease-free equilibrium point and the endemic equilibrium point of the model is analyzed through eigenvalue theory and Routh-Hurwitz criterion.The numerical simulation and fitting results of COVID-19 virus show that the proposed SEIQRP model can effectively describe the dynamic transmission process of the infectious disease.In the model, the three parameters, i.e.protection rate, incubation period isolation rate, and infected person isolation rate play a very critical role in the spread of the disease.Raising people's awareness of self-protection, focusing on screening for patients in the incubation period, and isolating and treating infected people can effectively reduce the spread of infectious diseases. © 2023 Northeastern University.All rights reserved.

Impact of Pandemic Outbreak and Targeted Required Reserve Ratio Cut Policy on Stock Return Rate: Evidence from China

This study analyzed the impact of COVID-19 outbreak and targeted required reserve ratio cut policy on stock returns of Chinese listed companies. This paper uses the data of 3,449 A-share listed companies from February 3, 2020 to December 31, 2020 for research, the empirical results showed that stock prices of private enterprises with stronger debt-paying ability and looser financing constraints, and state-owned enterprises with less supply chain credit risks performed better, in the central and western regions, enterprises with stronger solvency and looser financing constraints have better stock price performance during the early stages of pandemic. After the implementation of the targeted RRR cut policy, the stock prices of enterprises with poor solvency, private enterprises, and enterprises in central and western regions with strong financing constraints, state-owned enterprises, and enterprises in eastern region with high credit risks all showed significant reversals, and the stock prices reflected the effect of the targeted RRR cut policy in the short and medium term. Over time, the pandemic has been controlled, and the resumption of work and production has freed most enterprises from financial difficulties. However, due to sporadic outbreaks, large private enterprises and eastern enterprises with strong risk resistance and loose financing constraints enjoy better stock price performance. This study is helpful for enterprises to understand the value of financial flexibility and solvency and provides a reference for enterprises to make financial decisions: how to balance the benefits and costs of solvency. © Tian Wang, Fang Fang and Linhao Zheng, 2023.

From Asymptomatics to Zombies: Visualization-Based Education of Disease Modeling for Children

Throughout the COVID-19 pandemic, visualizations became commonplace in public communications to help people make sense of the world and the reasons behind government-imposed restrictions. Though the adult population were the main target of these messages, children were affected by restrictions through not being able to see friends and virtual schooling. However, through these daily models and visualizations, the pandemic response provided a way for children to understand what data scientists really do and provided new routes for engagement with STEM subjects. In this paper, we describe the development of an interactive and accessible visualization tool to be used in workshops for children to explain computational modeling of diseases, in particular COVID-19. We detail our design decisions based on approaches evidenced to be effective and engaging such as unplugged activities and interactivity. We share reflections and learnings from delivering these workshops to 140 children and assess their effectiveness. © 2023 Owner/Author.

COVID-19 spatialization by empirical Bayesian model in São Paulo, Brazil.

The new Acute Respiratory Syndrome, COVID-19, has affected the health and the economy worldwide. Therefore, scientists have been looking for ways to understand this disease. In this context, the main objective of this study was the spatialization of COVID-19, thinking in distinguishing areas with high transmissibility yet, verifying if these areas were associated with the elderly population occurrence. The work was delineated, supposing that spatialization could support the decision-making to combat the outbreak and that the same method could be used for spatialization and prevent other diseases. The study area was a municipality near Sao Paulo Metropolis, one of Brazil's main disease epicenters. Using official data and an empirical Bayesian model, we spatialized people infected by region, including older people, obtaining reasonable adjustment. The results showed a weak correlation between regions infected and older adults. Thus, we define a robust model that can support the definition of actions aiming to control the COVID-19 spread.

187 - Cruise Ship Infectious Disease Outbreak

This chapter examines infectious disease outbreak on a cruise ship, including the outbreaks and handling of 2020 Sars-CoV-2 on cruise ships early in the COVID-19 pandemic.

THE CONTAGION NUMBER: HOW FAST CAN A DISEASE SPREAD?

The overall purpose of this paper is to define a new metric on the spreadability of a disease. Herein, we define a variant of the well-known graph-theoretic burning number (BN) metric that we coin the contagion number (CN). We aver that the CN is a better metric to model disease spread than the BN as the CN concentrates on first time infections. This is important because the Centers for Disease Control and Prevention report that COVID-19 reinfections are rare. This paper delineates a novel methodology to solve for the CN of any tree, in polynomial time, which addresses how fast a disease could spread (i.e., a worst-cast analysis). We then employ Monte Carlo simulation to determine the average contagion number (ACN) (i.e., a most-likely analysis) of how fast a disease would spread. The latter is analyzed on scale-free graphs, which are specifically designed to model human social networks (sociograms). We test our method on some randomly generated scale-free graphs and our findings indicate the CN to be a robust, tractable (the BN is NP-hard even for a tree), and effective disease spread metric for decision makers. The contributions herein advance disease spread understanding and reveal the importance of the underlying network structure. Understanding disease spreadability informs public policy and the associated managerial allocation decisions. © 2023 by the authors.

Reducing the risk of indoor transmission of SARS-CoV-2 using UV-C disinfection

In this work, SARS-CoV-2 infectivity after UV-C exposure of porous and non-porous surfaces was assessed under controlled environment conditions. The irradiance of a setup of UV-C lamps, placed indoors was studied in detail as a function of the geometry and the distance to the surface. In the presence of living beings, the external UV-C lamps are turned off, and the UV-C lamps mounted inside the disinfection chamber are kept active, allowing a continuous air disinfection and a decreased risk of indoor transmission. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Susceptible exposed infectious recovered-machine learning for COVID-19 prediction in Saudi Arabia

Susceptible exposed infectious recovered (SEIR) is among the epidemiological models used in forecasting the spread of disease in large populations. SEIR is a fitting model for coronavirus disease (COVID-19) spread prediction. Somehow, in its original form, SEIR could not measure the impact of lockdowns. So, in the SEIR equations system utilized in this study, a variable was included to evaluate the impact of varying levels of social distance on the transmission of COVID-19. Additionally, we applied artificial intelligence utilizing the deep neural network machine learning (ML) technique. On the initial spread data for Saudi Arabia that were available up to June 25th, 2021, this improved SEIR model was used. The study shows possible infection to around 3.1 million persons without lockdown in Saudi Arabia at the peak of spread, which lasts for about 3 months beginning from the lockdown date (March 21st). On the other hand, the Kingdom's current partial lockdown policy was estimated to cut the estimated number of infections to 0.5 million over nine months. The data shows that stricter lockdowns may successfully flatten the COVID-19 graph curve in Saudi Arabia. We successfully predicted the COVID-19 epidemic's peaks and sizes using our modified deep neural network (DNN) and SEIR model. © 2023 Institute of Advanced Engineering and Science. All rights reserved.

Modeling and Analysis of Infectious Disease Transmission Considering Protection and Isolation.

Based on the SEIR model, two compartments for self-protection and isolation are introduced, and a more general infectious disease transmission model is proposed. Through qualitative analysis of the model, the basic reproduction number of the model is calculated, and the local asymptotic stability of the disease-free equilibrium point and the endemic equilibrium point of the model is analyzed through eigenvalue theory and Routh-Hurwitz criterion. The numerical simulation and fitting results of COVID-19 virus show that the proposed SEIQRP model can effectively describe the dynamic transmission process of the infectious disease. In the model, the three parameters, i. e. protection rate, incubation period isolation rate, and infected person isolation rate play a very critical role in the spread of the disease. Raising people' s awareness of self-protection, focusing on screening for patients in the incubation period, and isolating and treating infected people can effectively reduce the spread of infectious diseases. (English) [ FROM AUTHOR] 基于 SEIR 模型, 引入自我防护和隔离两个仓室, 提出一个更加通用的传染病传播模型. 通过对 模型进行定性分析, 计算模型的基本再生数, 通过特征值理论和 Routh - Hurwitz 判据, 分析模型的无病平衡 点和地方病平衡点的局部渐近稳定性. 数值模拟和 COVID - 19 病毒真实数据拟合结果表明, 所提出的 SEIQRP 模型能够有效地描述传染病的动态传播过程. 模型中防护率、潜伏期隔离率和感染者隔离率这三个 参数对疾病的传播起着非常关键的作用. 提高人们加强自我防护意识、重点排查潜伏期患者和对感染者进行 隔离治疗可以有效降低传染病的传播. (Chinese) [ FROM AUTHOR] Copyright of Journal of Northeastern University (Natural Science) is the property of Dongbei Daxue Xuebao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Pandemic Fatigue in Japan: Factors Affecting the Declining COVID-19 Preventive Measures

Pandemic fatigue has threatened the efforts to contain the coronavirus disease 2019 (COVID-19) worldwide;thus, government-mandated preventive measures have declined. The Japanese government has implemented several methods to address COVID-19′s spread, including hand hygiene, mask requirements, and social distancing. This study is the first to examine the socioeconomic factors affecting Japan's decline in COVID-19 prevention measures. It utilized the Preference Parameters Study of the Osaka University Institute of Social and Economic Research data of the 2021 and 2022 waves. With approximately 1580 observations, we detected a 10%, 4%, and 13% decline in hand hygiene practice, mask-wearing, and social distancing, respectively, between January 2021 and January 2022. Men were more likely to dislike the hand hygiene practice and mask-wearing and were also more reluctant to maintain social distancing. Moreover, financially satisfied individuals were positively associated with a decrease in the hand hygiene practice, while those with greater assets were more likely to dislike maintaining social distancing. People who exercised regularly were less likely to abandon the hand hygiene practices. Our results highlighted the significance of selective prevention programs targeting specific groups to promote compliance and lead to more effective pandemic management and less fatigue or discontentment. © 2023 by the authors.

Perceptions of the Vaccinated and Unvaccinated to Inform Translation to Health and Public Health Practice

OBJECTIVES/GOALS: Translating the science of vaccines to health and public health practice requires understanding how vaccine risks and benefits are understood and applying that knowledge to community translation. During the pandemic the lack of this knowledge became apparent. METHODS/STUDY POPULATION: Through the PACER community engagement special interest group of the ACTS, the University of Florida(UF)/Florida State University and 5 other CTSIs community engagement programs received Center for Disease Control and Prevention funding for the Program to Alleviate National Disparities in Ethnic and Minority Immunizations in the Community (PANDEMIC) to translate vaccinations into the community. At UF, HealthStreet's Community Health Workers, CTSI Mobile Health Vehicle nurses, and Institute of Food and Agricultural Sciences extension agents collaborated to engage adults throughout the North and Central part of the state on their vaccine status and perceptions and to offer them vaccines. RESULTS/ANTICIPATED RESULTS: Through UF, 4,587 people have been interviewed in community settings using the Survey of Perceptions;25% (1,125) had not received any COVID-19 vaccine. Among differences in perceptions, those vaccinated versus unvaccinated perceived people to be getting vaccines because they cut down on disease spread (28.9% vs. 15.2%), and perceived people NOT to be getting vaccinated because of misinformation/ignorance (27.1% vs. 11.0%) and political beliefs (16.3% vs. 6.7%). Both vaccinated and not perceived lack of trust as a reason to not get vaccinated (41.3% vs 46.4%). When asked what people were doing instead of vaccination, those vaccinated versus unvaccinated responded that people were doing nothing/very little much more often (40.6% vs. 21.8%) but were less likely to say 'trying to stay healthy' (9.1% vs. 18.9%). DISCUSSION/SIGNIFICANCE: The science of translating from bench through clinical trials and to common health and public health practice requires knowledge of reasons for successful adoption. This survey adds to knowledge of perceptions towards vaccines that inhibit translation and biases toward the vaccine-hesitant.

Utilizing CNN-LSTM techniques for the enhancement of medical systems

COVID-19 is one of the most chronic and serious infections of recent years due to its worldwide spread. Determining who was genuinely affected when the disease spreads more widely is challenging. More than 60% of affected individuals report having a dry cough. In many recent studies, diagnostic models were developed using coughing and other breathing sounds. With the development of technology, body sounds are now collected using digital techniques for respiratory and cardiovascular tests. Early research on identifying COVID-19 utilizing speech and diagnosing signs yielded encouraging findings. The gathering of extensive, multi-group, airborne acoustical sound data is used in the developed framework to conduct an efficient assessment to test for COVID-19. An effective classification model is created to assess COVID-19 utilizing deep learning methods. The MIT-Covid-19 dataset is used as the input, and the Weiner filter is used for pre-processing. Following feature extraction done by Mel-frequency cepstral coefficients, the classification is performed using the CNN-LSTM approach. The study compared the performance of the developed framework with other techniques such as CNN, GRU, and LSTM. Study results revealed that CNN-LSTM outperformed other existing approaches by 97.7%. © 2023 Faculty of Engineering, Alexandria University

Spatial Heterogeneity in the Severity of COVID-19 Pandemic in India

The coronavirus disease (COVID-19) pandemic has affected all states and union territories in India, but the spread of infections and the fatality rate across regions have been disproportionate. In this study, inequalities in the severity of the pandemic are examined for a 15-month period, covering both the first and second waves of the virus, using alternate measures based on the official estimates of deaths from COVID-19 as a ratio of all-cause mortality. The observed differences in the severity indicators are explained using socioeconomic, meteorological, and geographical factors. A comparison of severity ratios across states and over time gives a region-specific flavor of the severity of the pandemic and increases understanding of the pressure points in the health system. Our findings are helpful for public health professionals to develop control measures and plan environmental and health policies as an alternative strategy to respond to new COVID-19 outbreaks and prevent future crises. © 2023 Asian Development Bank.

Obesity increased the risk of SARS-CoV-2 positivity in children.

AIM: To determine the effects of obesity in childhood on SARS-CoV-2 infection. METHODS: A population-based, cross-sectional study combining the Israeli Growth Survey and COVID-19 data for children with at least one SARS-CoV-2 test from 16 February 2020 to 20 December 2021. Overweight and obesity status were based on body mass index and the Center for Disease Control criteria. Multivariate logistics regression was performed to validate reliability for weight categories at the age of approximately 6 years compared with weights at approximately 12 years. RESULTS: A total of 444 868 records for children with an overall positivity rate of 22% were studied. The mean age was 9.5 years. The odds ratios of children with obesity or overweight after controlling for sex at 6 years to test positive were 1.07-1.12 and 1.06-1.08 (depending on the model), respectively, compared to those with healthy range body mass index. CONCLUSION: Excess weight appears to increase the risk of SARS-CoV-2 infection. This finding should be considered for public health planning. For example, children with overweight and obesity should be prioritised for vaccination. Excess weight in childhood can be harmful at a young age and not only for long-term health.

PURITY AND DANGER IN SPANISH AGRICULTURE: FARM WORKERS DURING THE PANDEMIC

The aim of this paper is to carry out a sociological analysis of the implications of what could be referred to as the paradox of farm labourers during the pandemic. That is, their designation as essential workers turned them simultaneously into high-risk workers and a source of public alarm. Based on the analysis of the logics of purity and danger of Mary Douglas (1991), this article analyses how some of the public health strategies developed by the institutions during the pandemic contributed to reinforcing the invisibility and vulnerability of migrant workers. The article shows how, being placed in the realm of the impure and dangerous, foreign agricultural workers were not able to receive the health care they required, and their living spaces thus became environments conducive to the spread of the virus. Through an exploration of secondary sources, a review of pertinent documents and in-depth interviews with key informants, this article firstly offers a description of the institutional process by which foreign agricultural workers in the Region of Murcia were converted into essential workers facilitated the spread of infections. Secondly, it explores the link between the precariousness of the working and living conditions of farm labourers and the absence of the ethics of self-care, which was at the heart of the chain of Covid-19 infections suffered by this population. Finally, it focuses on institutional responses to the threat posed by the threat posed by increased infections among immigrant farm workers. Copyright ©2022 CSIC.

Peri-urban schools of Kinshasa before and during COVID-19: an evaluation of water, handwashing facilities, and girl students' hand hygiene practices

The COVID-19 pandemic has led communities, including Kinshasa peri-urban schools, to reinforce WASH-related practices as a key com-ponent in preventing the spread of COVID-19. This study aimed to determine the institutional and behavioural changes in adolescent girl students' handwashing practices before and during the COVID-19 pandemic. A cross-sectional study was performed, observing the hand hygiene of adolescent girl students, and assessing WASH facilities at schools, chosen from a sample previously selected in the study area. The results indicate significant increases in the prevalence of water points in schools from 10.9 to 22.5%, of handwashing facilities from 43 to 60.1% of schools with an average number of handwashing facilities from one to two, and the prevalence of school WASH brigades from 4.8 to 11.8% of schools. There was also a significant increase in schools receiving funds, and other support for WASH, respectively, from 24.9 to 70.3%, and from 17 to 45.9%, while the proportion of adolescent girl students washing their hands after using the toilet and before eating significantly increased from 6 to 28.4%. However, to improve the current WASH picture, and succeed in curtailing the spread of COVID-19 and related impacts, additional efforts to enhance handwashing practice and WASH items' coverage are expected. © 2023 The Authors.

A methodological approach for modeling the spread of disease using geographical discrete-event spatial models

The study of infectious disease models has become increasingly important during the COVID-19 pandemic. The forecasting of disease spread using mathematical models has become a common practice by public health authorities, assisting in creating policies to combat the spread of the virus. Common approaches to the modeling of infectious diseases include compartmental differential equations and cellular automata, both of which do not describe the spatial dynamics of disease spread over unique geographical regions. We introduce a new methodology for modeling disease spread within a pandemic using geographical models. We demonstrate how geography-based Cell-Discrete-Event Systems Specification (DEVS) and the Cadmium JavaScript Object Notation (JSON) library can be used to develop geographical cellular models. We exemplify the use of these methodologies by developing different versions of a compartmental model that considers geographical-level transmission dynamics (e.g. movement restriction or population disobedience to public health guidelines), the effect of asymptomatic population, and vaccination stages with a varying immunity rate. Our approach provides an easily adaptable framework that allows rapid prototyping and modifications. In addition, it offers deterministic predictions for any number of regions simulated simultaneously and can be easily adapted to unique geographical areas. While the baseline model has been calibrated using real data from Ontario, we can update and/or add different infection profiles as soon as new information about the spread of the disease become available. © The Author(s) 2023.

The employment of Italians and foreigners in the first year of the pandemic

The research using data from Istat's Continuous Labor Force Survey aims to describe the trend of the main labor market indicators before and during the pandemic and to measure, through the use of a logis-tic regression, the variations in probability of being employed, inactive and hired with a fixed-term contract by Italians and foreigners. © 2023, Fondazione Centro Studi Emigrazione. All rights reserved.

Bicycle tourism, from pandemic to sustainability: "Terre di Casole Bike Hub” project

The outbreak of COVID-19 and the subsequent lockdowns have impelled us to question and reconsider our standards, schedules and lifestyle. One of the market sectors that was most affected by the mobility reduction was tourism. Its demand in 2020 showed indeed a significant change: tourists opted for unusual destinations, presumably less crowded, favouring smaller villages and mountain areas. Moreover, tourists have chosen destinations that feature the possibility to do sports, especially trekking and cycling. Considering these trends, this paper focuses on the bicycle tourism in Italy and analyses its development potential. More specifically, it analyses the "Terre di Casole Bike Hub” project as an example of best practices to promote the territory through cycling, aiming to support the territory recovery in the post-pandemic tourism. © 2022 Societe Belge de Geographie. All rights reserved.

Relationship among leadership styles, employee's well-being and employee's safety behavior: an empirical evidence of COVID-19 from the frontline healthcare workers

The study investigates the association among leadership styles, employee well-being and employee's safety behavior of healthcare workers. The study used social learning theory (SLT) for examining the relationship between leadership styles and employee safety behavior. Moreover, social exchange theory (SET) has been incorporated to narrate the moderating effect of employee well-being on the relationship between leadership styles and employee safety behavior. Data have been collected with the help of questionnaires from 515 healthcare workers working in the public hospitals of Punjab, Pakistan. Structural equation modeling has been utilized to test the study hypothesis. Findings indicate that both transactional and transformational leaderships have significant and positive relationship with employee safety behavior. Interestingly, employee well-being negatively moderates the relationship between transformational leadership and employee safety behavior. Furthermore, no moderation was found on the relationship between transactional leadership and employee safety behavior. The findings propose that healthcare management should invest to aware employees regarding their well-being. The findings also suggest that leaders should influence their followers to adopt safety measures at workplace. Furthermore, leaders must be role models in order to attain a competitive advantage and make a balance between management and workers. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.