Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)—A Systemic Review and Comparison of Clinical Presentation and Symptomatology

Medicina, Год журнала: 2021, Номер 57(5), С. 418 - 418

Опубликована: Апрель 26, 2021

Background and Objectives: Long COVID defines a series of chronic symptoms that patients may experience after resolution acute COVID-19. Early reports from studies with long suggests constellation similarities to another medical illness—myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). A review study comparing contrasting ME/CFS reported yield mutualistic insight into the characterization management both conditions. Materials Methods: systemic literature search was conducted in MEDLINE PsycInfo through 31 January 2021 for related symptomatology. The accordance PRISMA methodology. Results: Twenty-one were included qualitative analysis. by compared list compiled multiple case definitions. Twenty-five out 29 known at least one selected study. Conclusions: symptomatology suggest many overlaps clinical presentation ME/CFS. need monitoring treatment post-COVID is evident. Advancements standardization research methodologies would improve quality future research, allow further investigations differences between

Язык: Английский

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A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration

Epidemiologia, Год журнала: 2021, Номер 2(3), С. 315 - 324

Опубликована: Авг. 5, 2021

As the COVID-19 pandemic continues its march around world, an unprecedented amount of open data is being generated for genetics and epidemiological research. The unparalleled rate at which many research groups world are releasing publications on ongoing allowing other scientists to learn from local experiences in front lines pandemic. However, there a need integrate additional sources that map measure role social dynamics such unique world-wide event into biomedical, biological, analyses. For this purpose, we present large-scale curated dataset over 152 million tweets, growing daily, related chatter January 1st April 4th time writing. This will allow researchers conduct number projects relating emotional mental responses distancing measures, identification misinformation, stratified measurement sentiment towards near real time.

Язык: Английский

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Review article: A systematic review and future prospects of flood vulnerability indices

Natural hazards and earth system sciences, Год журнала: 2021, Номер 21(5), С. 1513 - 1530

Опубликована: Май 17, 2021

Abstract. Despite the increasing body of research on flood vulnerability, a review methods used in construction vulnerability indices is still missing. Here, we address this gap by providing state-of-art account indices, highlighting worldwide trends and future directions. A total 95 peer-reviewed articles published between 2002–2019 were systematically analyzed. An exponential rise effort demonstrated, with 80 % being since 2015. The majority these studies (62.1 %) focused neighborhood followed city scale (14.7 %). Min–max normalization (30.5 %), equal weighting (24.2 linear aggregation (80.0 most common methods. With regard to indicators used, focus was given socioeconomic aspects (e.g., population density, illiteracy rate, gender), whilst components associated citizen's coping adaptive capacity slightly covered. Gaps current include lack sensitivity uncertainty analyses (present only 9.5 3.2 papers, respectively), inadequate or inexistent validation results 13.7 studies), transparency regarding rationale for indicator selection, use static approaches, disregarding temporal dynamics. We discuss challenges findings assessment provide agenda attending gaps. Overall, argue that should be more theoretically grounded while, at same time, considering dynamic vulnerability.

Язык: Английский

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Toward human-centric urban infrastructure: Text mining for social media data to identify the public perception of COVID-19 policy in transportation hubs

Sustainable Cities and Society, Год журнала: 2021, Номер 76, С. 103524 - 103524

Опубликована: Ноя. 4, 2021

Язык: Английский

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Qualitative analysis of visual risk communication on twitter during the Covid-19 pandemic

BMC Public Health, Год журнала: 2021, Номер 21(1)

Опубликована: Апрель 28, 2021

The Covid-19 pandemic is characterized by uncertainty and constant change, forcing governments health authorities to ramp up risk communication efforts. Consequently, visuality social media platforms like Twitter have come play a vital role in disseminating prevention messages widely. Yet date, only little known about what characterizes visual during the pandemic. To address this gap literature, study's objective was determine how used on promote World Health Organisations (WHO) recommended preventative behaviours changed over time.

Язык: Английский

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Optimism and pessimism analysis using deep learning on COVID-19 related twitter conversations

Information Processing & Management, Год журнала: 2022, Номер 59(3), С. 102918 - 102918

Опубликована: Фев. 25, 2022

This paper proposes a new deep learning approach to better understand how optimistic and pessimistic feelings are conveyed in Twitter conversations about COVID-19. A pre-trained transformer embedding is used extract the semantic features several network architectures compared. Model performance evaluated on two new, publicly available corpora of crisis-related posts. The best performing pessimism optimism detection models based bidirectional long- short-term memory networks. Experimental results four periods COVID-19 pandemic show proposed can model context health crisis. There total 150,503 tweets 51,319 unique users. Conversations characterised terms emotional signals shifts unravel empathy support mechanisms. with stronger denoted little shift (i.e. 62.21% these experienced almost no change emotion). In turn, only 10.42% laying more side maintained mood. User volatility further linked social influence.

Язык: Английский

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A region-wide survey on emotional and psychological impacts of COVID-19 on public transport choices in Sicily, Italy

Transactions on Transport Sciences, Год журнала: 2021, Номер 12(3), С. 34 - 43

Опубликована: Июнь 14, 2021

Public transport generally addresses the evident mobility needs and offers an often-irreplaceable service, especially for captive users other disadvantaged population groups. design services are closely related to physical size of modern cities, number people living or working in them, distribution organization work social activities. However, public has been restricted with spread COVID-19 pandemic Italy, since March 2020. demand collapsed, during lockdown period (March-May 2020), adverse effects were reported even subsequent periods. In fact, distancing restrictions have highlighted numerous problems systems worldwide, primarily due two factors. The first is virus via respiratory route, which more likely infect areas, second associated a system that by definition high occupancy rates low spacing throughout journey (e.g., positioning seats standing places train bus). Thus, substantially impacted travel choices users. also negatively affected psychological state, generating specific anxiety, fear, stress among all groups, when choosing means with. Given emerging challenges, present study examines characteristics various phases Sicily, one most regions Italy. investigates mental state sample frequently used local urban regional before Sicilian territory. Through administration online survey, it was possible collect sociodemographic data understand propensity use transport. A series inferential statistical tests applied assess correlation aspects (i.e., stress) socio-demographic variables modal choice habits (trip frequency). Results highlight evaluate each issue groups their relative role shaping transport-related preferences. highlights some proposals implementation strategies prevent negative emotions encourage Sicily generally.

Язык: Английский

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Tracking the Impact of COVID-19 and Lockdown Policies on Public Mental Health Using Social Media: Infoveillance Study

Journal of Medical Internet Research, Год журнала: 2022, Номер 24(10), С. e39676 - e39676

Опубликована: Окт. 3, 2022

The COVID-19 pandemic and its corresponding preventive control measures have increased the mental burden on public. Understanding tracking changes in public status can facilitate optimizing health intervention strategies.This study aimed to build a social media-based pipeline that tracks use it understand regarding pandemic.This used COVID-19-related tweets posted from February 2020 April 2022. were downloaded using unique identifiers through Twitter application programming interface. We created lexicon of 4 problems (depression, anxiety, insomnia, addiction) identify health-related developed dictionary for identifying care workers. analyzed temporal geographic distributions during further compared among workers versus general public, supplemented by topic modeling their underlying foci. Finally, we interrupted time series analysis examine statewide impact lockdown policy 12 states.We extracted 4,213,005 related 2,316,817 users. Of these tweets, 2,161,357 (51.3%) "depression," whereas 1,923,635 (45.66%), 225,205 (5.35%), 150,006 (3.56%) "anxiety," "insomnia," "addiction," respectively. Compared had higher risks all types (all P<.001), they more concerned about clinical topics than everyday issues (eg, "students' pressure," "panic buying," "fuel problems") significant associations with out states studied, which Pennsylvania showed positive association, Michigan, North Carolina, Ohio opposite P<.05).The public's is dynamic shows variability different cohorts disease types, occupations, regional groups. Health agencies makers should primarily focus depression (reported 51.3% tweets) insomnia (which has an ever-increasing trend since beginning pandemic), especially Our timely analyzes changes, when primary studies large-scale surveys are difficult conduct.

Язык: Английский

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Non-linear impacts of COVID-19 pandemic on human mobility: Lessons from its variations across three pandemic waves

Sustainable Cities and Society, Год журнала: 2023, Номер 97, С. 104769 - 104769

Опубликована: Июль 1, 2023

Язык: Английский

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Sentiment Analysis of Rumor Spread Amid COVID-19: Based on Weibo Text

Healthcare, Год журнала: 2021, Номер 9(10), С. 1275 - 1275

Опубликована: Сен. 27, 2021

(1) Background: in early 2020, COVID-19 broke out. Driven by people's psychology of conformity, panic, group polarization, etc., various rumors appeared and spread wildly, the Internet became a hotbed rumors. (2) Methods: study selected Weibo as research media, using topic models, time series analysis, sentiment Granger causality testing methods to analyze social media texts related (3) Results: 1, we obtained 21 topics "COVID-19 rumors" "outbreak after conducting model analysis on texts; 2, explored emotional changes netizens before rumor dispelling information was released found positive emotions first declined then rose; 3, also "Wuhan lockdown" event people non-Wuhan areas increased, while negative Wuhan increased; 4, studied relationship between polarity causally interrelated. (4) Conclusion: These findings could help us intuitively understand impact during pandemic government take measures reduce panic.

Язык: Английский

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