ABSTRACT
State and local governments have imposed health policies to contain the spread of COVID-19 since it had a serious impact on human daily life. However, the public stance on these measures may be time-varying. It is likely to escalate the infection in the area where the public is negative or resistant. To take advantage of the correlation between public stance on health policies and the COVID-19 statistics, we propose a novel framework, Multitask Learning Neural Networks for Pandemic Prediction with Public Stance Enhancement (MP3), which is composed of three modules: (1) Stance awareness module to make stance detection on health policies from users' tweets in social media and convert them into a stance time series. (2) Temporal feature extraction module that applies Convolution Neural Network and Recurrent Neural Network to extract and fuse local patterns and long-term correlations from COVID-19 statistics. Moreover, a Stance Latency-aware Attention is proposed to capture dynamic social effects and fuse them with temporal features. (3) Multi-task prediction module to adopt Graph Convolution Network to model the spread of pandemic and employ multi-task learning to simultaneously predict COVID-19 statistics and the trend of public stance on health policies. The proposed framework outperforms state-of-the-art baselines on both confirmed cases and deaths prediction tasks. © 2022 IEEE.
ABSTRACT
The COVID-19 pandemic disrupted typical travel behavior worldwide. In the United States (U.S.), government entities took action to limit its spread through public health messaging to encourage reduced mobility and thus reduce the spread of the virus. Within statewide responses to COVID-19, however, there were different responses locally. Likely some of these variations were a result of individual attitudes toward the government and health messaging, but there is also likely a portion of the effects that were because of the character of the communities. In this research, we summarize county-level characteristics that are known to affect travel behavior for 404 counties in the U.S., and we investigate correlates of mobility between April and September (2020). We do this through application of three metrics that are derived via changepoint analysis—initial post-disruption mobility index, changepoint on restoration of a ‘‘new normal,'' and recovered mobility index. We find that variables for employment sectors are significantly correlated and had large effects on mobility during the pandemic. The state dummy variables are significant, suggesting that counties within the same state behaved more similarly to one another than to counties in different states. Our findings indicate that few travel characteristics that typically correlate with travel behavior are related to pandemic mobility, and that the number of COVID-19 cases may not be correlated with mobility outcomes. © National Academy of Sciences: Transportation Research Board 2021.
ABSTRACT
Covid-19 pandemic has been the cause of the most significant global revolution in recent times. The attack from an invisible enemy had caught the world unprepared since its first reported outbreak from Wuhan, China, in 2019. As a result, challenges arising from that of unimaginable proportions soon followed suit, and the world felt the impact of those challenges on so many levels. Most of the economy's industries had been greatly affected, with the construction industry being one of the hardest hit. Sarawak's construction industry is not spared either, as several construction site clusters resulting from workers' quarters popped up from the circle. The scenario creates awareness of the importance of improving the quality of workers' quarters. The Sarawak State Government, through its Ministry of Public Health, Housing and Local Government, had formulated a guideline for Local Authorities on the temporary permit application for workers' quarters' building within construction sites. The response of the permit is studied using a qualitative approach through a case study of workers' quarters within construction sites in the jurisdiction of Kuching City South as the primary research method. The study is mainly based on observation and literature review and discusses the permit implementation response among the construction industry players. The findings from this paper conclude that the implementation of the permit could be observed further to capture a greater level of compliance and accountability to improve the quality of workers' quarters for occupational safety and the general health of labourers. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since its first being reported in December 2019, COVID-19 has spread quickly around the world, and becomes a global pandemic. Previous information sources have a number of problems when providing COVID-19 information web services. First, the information from government or traditional media (i.e., TV and newspaper) is not frequently updated. Second, different layers of the government (state and federal government) may provide contradictory information. Also, there are many rumours spread on social media, which makes it difficult for people to know who and what to trust. Finally, the current information about COVID-19 is fragmented. It takes effort for people to aggregate the information they need to see from different places. © 2022 IEEE.
ABSTRACT
The COVID-19 pandemic affected the world in extraordinary ways. Various measures were taken by state and local governments, including the introduction of stay-at-home orders and closures of nonessential businesses, as well as recommendations related to social distancing and the wearing of face coverings. The rollout of testing and vaccination programs were also key actions aimed at limiting the spread of COVID-19. Collectively, these restrictions have resulted in marked changes in travel behavior and patterns throughout the world. In this study, mixed-effects linear regression models are estimated to assess the impacts of COVID-19-related travel restrictions and vaccination rates on daily travel across the United States from January 1, 2020, through August 15, 2021. The results show that daily trips per person were reduced by 15% and 31% in March and April of 2020, respectively, prior to considering the impacts of any government-imposed restrictions. This suggests that government and media coverage of the pandemic played an important role in reducing travel levels. When accounting for the introduction of interventions, ranging from travel advisories to mandatory stay-at-home orders, travel was reduced by an additional 2%-9%. Interestingly, the reductions were less pronounced in areas that strongly supported the Republican candidate in the 2020 presidential election, raising important concerns as to the role of politics and trust in government. Along these same lines, as the duration of mandatory stay-at-home orders increased, travel tended to revert toward prepandemic levels, which may be attributed to quarantine fatigue. Travel levels were also higher among areas with lower median income, as well as those counties that exhibited greater variability in income, illustrating the inequitable impacts of the pandemic on these areas, which tend to include larger proportions of workers in essential industries. The results also show that trip-making increased with vaccination rates, particularly during the early stages of large-scale vaccination programs. Collectively, these insights are important in informing future strategies to mitigate the adverse impacts associated with future outbreaks of new COVID-19 strains and variants. © 2022 American Society of Civil Engineers.
ABSTRACT
This article assesses the level of transparency of epidemiological and financial budgetary information on the COVID-19 pandemic in Brazilian state governments and the Federal District. State government web portals were assessed. A methodological instrument was developed to categorize and collect the data. We also assessed whether socioeconomic and epidemiological variables can explain state government transparency indices on pandemic information. According to our results, half of Brazilian states have advanced transparency, half have moderate transparency, and one has opaque transparency. HDI and monthly income are variables that better explain the level of transparency.
ABSTRACT
This article assesses the level of transparency of epidemiological and financial budgetary information on the COVID-19 pandemic in Brazilian state governments and the Federal District. State government web portals were assessed. A methodological instrument was developed to categorize and collect the data. We also assessed whether socioeconomic and epidemiological variables can explain state government transparency indices on pandemic information. According to our results, half of Brazilian states have advanced transparency, half have moderate transparency, and one has opaque transparency. HDI and monthly income are variables that better explain the level of transparency.
ABSTRACT
This project is to intimate start and stop time of a particular session with the help of buzzer. A faculty keep on taking his lecture continuously. If the lecture was interesting and engaging the session will be keep on going. Buzzer is used to intimate when will be the session starts and when it will be going to end. Here timing will be predefined. Next one major challenge in schools and colleges is to take attendance manually. For taking attendance with the help of using fingerprint sensor-R307.Here the fingerprints of each and every individual student were stored in the fingerprint sensor itself. If the student keeps his fingerprint, then the particular student attendance is marked. It will only mark attendance if particular person keeps his unique fingerprint. Due to COVID-19 pandemic, central and state government announced to monitor the body temperature of each and every student on daily basis. For monitoring body temperature with help of using Non-contact temperature sensor-MLX90614. We place the temperature sensor near to the fingerprint sensor. If a student comes and keep his fingerprint his attendance will be marked and then he wants to keep his hand to measure his body temperature. If the body temperature of particular student is high means it will displayed in OLED display. To intimate a particular session to the staff. Sometimes staffs have some other work while doing their work they may forget their session. To intimate the session to the staffs by triggering mail or message to the staff. © 2022 IEEE.
ABSTRACT
In response to the COVID-19 pandemic, the State Government of Victoria implemented measures, including several periods of'lockdown' that involved strict constraints on travel, and required people to work from home where possible. For most Victorians, these restrictions led to reduced noise from road traffic and from aircraft, however they appear to have resulted in increased exposure to other sources of noise. The number of pollution reports received by the Environment Protection Authority (EPA) Victoria in relation to noise more than doubled in the period from January to July 2020 (which covered several episodes of lockdown), compared with the same period in the previous year (with no lockdowns). This paper investigates the evolution of noise reports during 2020 and 2021, giving regard to the alleged noise source categories used in their triage. Copyright© (2021) by Australian Acoustical Society. All rights reserved.
ABSTRACT
Nainital is a well-known hill station in Uttarakhand, India where there is footfall of thousands of tourists every year. Tourism industry at Nainital has always been the main source of income for the people of Nainital. This business has continuously aided in generating high revenue for Uttarakhand State Government. Due to the advent of Covid-19 pandemic, the Government of India enforced complete and partial lockdowns from time to time during 2020-2021 as a measure to control the existing hazardous circumstances prevailing in the country. This brought a drastic blow to the tourism industry at Nainital as well and directly affected the economy of the Uttarakhand State. The abrupt downfall in the industry due to covid -19 instigated the researchers to analyze the scenario in the duration 2020-2021. There were periods of lockdown as well as unlock/partial lockdown in this duration. The researchers analyzed the impact of the pandemic in the tourism industry at Nainital in both the stages-during lockdown and unlock/ partial lockdown. A SWOC (Strengths, Weaknesses, and Opportunities & Challenges) analysis was taken up as an effective warfare mechanism against the ubiquitous unpleasant situation. It was decoded that the surging conditions precipitated from certain psychological and behavioral impediments of all the three components- Government, Public and Covid 19 virus, which were essentially required to be mapped. The present pyramid study is imperial in nature. In the present study the researchers have focused on the study of relationship between the first two components-Government and Public and the third component-Virus of the pyramid. It attempts to trace the impact of these three components on one another through questionnaire survey, group discussion, and telephonic interview. In the present study the researchers not only consider the impact of the pandemic on the unemployment and economy of the state but also on the psychology of the local people as- a-whole. The present study is a visionary and rationalist wherein the researchers consider the scope of survival of tourism industry at Nainital in 2022. © 2021 IEEE.
ABSTRACT
Every commercial activity has exaggerated due to the ruthless covid-19 pandemic. Construction sector is one among the hardest affected industry and facing multiple challenges to proceed. The entire civil engineering related activities across the country had halted due to restrictions put in the place by the Central and State Governments of India. Cumulatively, the multiple consequences of the lock down situations would cause the socio-economic condition of the industry. In these circumstances, an insight investigation was carried out by using Likert scale based questionnaire and this study is focused on the managerial condition assessment of the stakeholder of a brick manufacturing chamber, a construction industry driven unit, situated in Warangal, Telangana State, India. The problems with respect to retention of migratory labours, consequence in economic aspects of production process including health aspects of labour and its effect on the present scenario are evaluated and presented. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
This proposal addresses the Biology and Measurement of MS symptoms focus area of FY18 MSRP Exploration Hypothesis Development Award. The overarching aim of this proposal is to assess the role of microglial activation and norepinephrine transporter binding in pathogenesis of MS-related fatigue, using novel Positron Emission Tomography (PET) radiotracers. [F-18]PBR06 and [C-11]MRB. The major developments in the progress of this project have been the following: 1. We received permission to resume recruitment of subjects on July 15, 2020. 2. We are pleased to report that we have recruited and obtained informed consent from 10 eligible subjects already (greater than 80 percent of the target sample size). 3 of these subjects have completed all the study related procedures (25 percent of the target sample size). Based on our preliminary data about the role of neuroinflammation in pathogenesis of MS-related fatigue, we had a manuscript published in the journal Neurology: Neuroimmunology and Neuroinflammation in September, 2020. The title of the manuscript is T Singhal, S Cicero, H Pan, K Carter, S Dubey, R Chu, B Glanz, S Hurwitz, S Tauhid, Mi-Ae Park, M Kijewski, E Stern, R Bakshi, D Silbersweig, and HL Weiner. Regional Microglial Activation in Substantia Nigra is linked with Fatigue in Multiple Sclerosis. (PMID 32769103)
ABSTRACT
Emerged in Wuhan city of China in December 2019, COVID-19 continues to spread rapidly across the world despite authorities having made available a number of vaccines. While the coronavirus has been around for a significant period of time, people and authorities still feel the need for awareness due to the mutating nature of the virus and therefore varying symptoms and prevention strategies. People and authorities resort to social media platforms the most to share awareness information and voice out their opinions due to their massive outreach in spreading the word in practically no time. People use a number of languages to communicate over social media platforms based on their familiarity, language outreach, and availability on social media platforms. The entire world has been hit by the coronavirus and India is the second worst-hit country in terms of the number of active coronavirus cases. India, being a multilingual country, offers a great opportunity to study the outreach of various languages that have been actively used across social media platforms. In this study, we aim to study the dataset related to COVID-19 collected in the period between February 2020 to July 2020 specifically for regional languages in India. This could be helpful for the Government of India, various state governments, NGOs, researchers, and policymakers in studying different issues related to the pandemic. We found that English has been the mode of communication in over 64% of tweets while as many as twelve regional languages in India account for approximately 4.77% of tweets. © 2021, Springer Nature Switzerland AG.
ABSTRACT
In response to the pandemic caused by the rapidly spreading COVID-19 virus, several highly effective vaccines have been developed by Pfizer, Moderna, and Janssen. Despite the promising efficacy of those vaccines, there remains the challenge of properly distributing vaccines to those who need it most in the US. of particular concern are individuals who are at higher risk due to underlying medical conditions which have been shown to exacerbate COVID-19 symptoms and at times lead to fatal illnesses. In addition to this, a variety of socioeconomic factors have been linked to increased COVID-19 rates and increased mortality, such as race, age, income, mobility, and education level.This project aims to develop an information system to help advise vaccine distributors and state governments on how to effectively distribute vaccines to prioritize high risk individuals. The information system incorporates state-level data of the population with underlying medical conditions, demographics, overall state income, education level, and state mobility to formulate a mortality index. State-level data on the number of vaccines available and doses already administered are also incorporated into the information system to generate a vaccine index. The mortality and vaccine indices for each state are coupled to generate a vaccine priority ranking which can be used to advise vaccine distribution.The prototype can successfully link the data described above to a map of the US and then color code states according to the vaccine priority ranking. Implementation of this prototype will enable optimal vaccine distribution and reduce instances of severe or fatal COVID-19 illnesses as well as reduce costs associated with oversupply of vaccines in a single region. Future work will focus on improving the granularity of data down to the county-level, as well as increasing the scope of the system to the global scale. Additionally, the team plans to expand the application space of this information system to other diseases. © 2021 IEEE.
ABSTRACT
In this research work, we have presented a brief study of the impact of the Novel Coronavirus in my hometown Dehradun, in the State of Uttarakhand, India. Here we discussed the impact of Coronovirus on various sectors and districts of the State. Here we have also discussed the State government’s steps and precautions to fight this global epidemic. We have also presented a change detection methodology to identify coronavirus’s impact on the patient’s chest using image processing techniques. Pre and post-DICOM images of Covid infected person are analyzed based on the statistical image parameters. Texture classification of the pre and post DICOM images is performed based on the visual statistical features, i.e., contrast, correlation, energy, and homogeneity. Finally, for both the images histogram signature plotting is performed, and based on this, changes developed in the DICOM images are monitored. © 2021 IEEE
ABSTRACT
Resumo O presente artigo tem como objetivo analisar as estratégias de intervenção adotadas pela gestão pública frente à crise desencadeada pela COVID-19 para redução da insegurança alimentar, baseado em um estudo de caso no Rio Grande do Norte. Com abordagem qualitativa, foram utilizadas a Teoria do Programa e a abordagem dos múltiplos fluxos para análise das ações emergenciais. No estado, a pandemia confluiu para uma janela de oportunidade, evidenciando o papel importante das Políticas Públicas na agenda governamental, como o Programa Restaurante Popular, e favorecendo a elaboração de respostas rápidas e de medidas de adequação na implementação da política. Conclui-se, neste estudo, que esta pode ser considerada uma boa prática e que ela pode servir de referência a outras ações semelhantes pelo país.
Resumen Este artículo tiene como objetivo analizar las estrategias de intervención adoptadas por la administración pública frente a la crisis desencadenada por la COVID-19 para reducir la inseguridad alimentaria, con base en un estudio de caso en Río Grande do Norte. Con un enfoque cualitativo, se utilizaron la teoría del programa y el enfoque de múltiples flujos para el análisis de acciones de emergencia. En el estado, la pandemia se convirtió en una ventana de oportunidad, destacando el importante papel de las políticas públicas en la agenda gubernamental, como el Programa Restaurante Popular, y favoreciendo la elaboración de respuestas rápidas y de medidas de adecuación en la implementación de las políticas. Se concluye que esta puede ser una buena práctica y que puede ser una referencia para otras acciones similares en todo el país.
Abstract This article aims to analyze the intervention strategies adopted by public management during the COVID-19 pandemic to reduce food insecurity, based on a case study in the Brazilian state of Rio Grande do Norte. The study used a qualitative approach based on Program Theory and the multiple streams model to analyze the actions. In the state, the pandemic brought a window of opportunity, showing the importance of public policy in the government agenda, such as the program "Restaurante Popular," which offers low-cost meals, and favors quick response and adequacy of means of implementation. The study highlights best practices, inspiring actions all over the country.