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  1. Article ; Online: Social distancing during the COVID-19 pandemic: Staying home save lives.

    Sen-Crowe, Brendon / McKenney, Mark / Elkbuli, Adel

    The American journal of emergency medicine

    2020  Volume 38, Issue 7, Page(s) 1519–1520

    MeSH term(s) Betacoronavirus ; COVID-19 ; Communicable Disease Control/methods ; Coronavirus Infections/epidemiology ; Coronavirus Infections/prevention & control ; Humans ; Mass Behavior ; Pandemics/prevention & control ; Personal Space ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/prevention & control ; SARS-CoV-2 ; Social Isolation
    Keywords covid19
    Language English
    Publishing date 2020-04-02
    Publishing country United States
    Document type Letter
    ZDB-ID 605890-5
    ISSN 1532-8171 ; 0735-6757
    ISSN (online) 1532-8171
    ISSN 0735-6757
    DOI 10.1016/j.ajem.2020.03.063
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: COVID-19 Mask Usage and Social Distancing in Social Media Images: Large-scale Deep Learning Analysis.

    Singh, Asmit Kumar / Mehan, Paras / Sharma, Divyanshu / Pandey, Rohan / Sethi, Tavpritesh / Kumaraguru, Ponnurangam

    JMIR public health and surveillance

    2022  Volume 8, Issue 1, Page(s) e26868

    Abstract: ... in the United States, from social media images, especially during the Black Lives Matter (BLM) protests, representing ... for detecting and stopping possible transmission routes of COVID-19. A study of the effects ... trends and COVID-19 cases. We looked for significant changes in mask use patterns and group posting ...

    Abstract Background: The adoption of nonpharmaceutical interventions and their surveillance are critical for detecting and stopping possible transmission routes of COVID-19. A study of the effects of these interventions can help shape public health decisions. The efficacy of nonpharmaceutical interventions can be affected by public behaviors in events, such as protests. We examined mask use and mask fit in the United States, from social media images, especially during the Black Lives Matter (BLM) protests, representing the first large-scale public gatherings in the pandemic.
    Objective: This study assessed the use and fit of face masks and social distancing in the United States and events of large physical gatherings through public social media images from 6 cities and BLM protests.
    Methods: We collected and analyzed 2.04 million public social media images from New York City, Dallas, Seattle, New Orleans, Boston, and Minneapolis between February 1, 2020, and May 31, 2020. We evaluated correlations between online mask usage trends and COVID-19 cases. We looked for significant changes in mask use patterns and group posting around important policy decisions. For BLM protests, we analyzed 195,452 posts from New York and Minneapolis from May 25, 2020, to July 15, 2020. We looked at differences in adopting the preventive measures in the BLM protests through the mask fit score.
    Results: The average percentage of group pictures dropped from 8.05% to 4.65% after the lockdown week. New York City, Dallas, Seattle, New Orleans, Boston, and Minneapolis observed increases of 5.0%, 7.4%, 7.4%, 6.5%, 5.6%, and 7.1%, respectively, in mask use between February 2020 and May 2020. Boston and Minneapolis observed significant increases of 3.0% and 7.4%, respectively, in mask use after the mask mandates. Differences of 6.2% and 8.3% were found in group pictures between BLM posts and non-BLM posts for New York City and Minneapolis, respectively. In contrast, the differences in the percentage of masked faces in group pictures between BLM and non-BLM posts were 29.0% and 20.1% for New York City and Minneapolis, respectively. Across protests, 35% of individuals wore a mask with a fit score greater than 80%.
    Conclusions: The study found a significant drop in group posting when the stay-at-home laws were applied and a significant increase in mask use for 2 of 3 cities where masks were mandated. Although a positive trend toward mask use and social distancing was observed, a high percentage of posts showed disregard for the guidelines. BLM-related posts captured the lack of seriousness to safety measures, with a high percentage of group pictures and low mask fit scores. Thus, the methodology provides a directional indication of how government policies can be indirectly monitored through social media.
    MeSH term(s) COVID-19 ; Communicable Disease Control ; Deep Learning ; Humans ; Masks ; New York City ; Physical Distancing ; SARS-CoV-2 ; Social Media ; United States
    Language English
    Publishing date 2022-01-18
    Publishing country Canada
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2369-2960
    ISSN (online) 2369-2960
    DOI 10.2196/26868
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Social distancing during the COVID-19 pandemic

    Sen-Crowe, Brendon / McKenney, Mark / Elkbuli, Adel

    The American Journal of Emergency Medicine

    Staying home save lives

    2020  Volume 38, Issue 7, Page(s) 1519–1520

    Keywords Emergency Medicine ; General Medicine ; covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ZDB-ID 605890-5
    ISSN 0735-6757
    ISSN 0735-6757
    DOI 10.1016/j.ajem.2020.03.063
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article: Social predictors of food insecurity during the stay-at-home order due to the COVID-19 pandemic in Peru. Results from a cross-sectional web-based survey.

    Cañari-Casaño, Jorge L / Cochachin-Henostroza, Omaira / Elorreaga, Oliver A / Dolores-Maldonado, Gandy / Aquino-Ramírez, Anthony / Huaman-Gil, Sindy / Giribaldi-Sierralta, Juan P / Aparco, Juan Pablo / Antiporta, Daniel A / Penny, Mary E

    medRxiv : the preprint server for health sciences

    2021  

    Abstract: ... during the stay-at-home order in Peru. We used social media advertisements on Facebook to reach 18-59 ... Background: Stay-at-home orders and social distancing have been implemented as the primary tools ... the associated factors that explain this outcome during the stay-at-home order.: Methods: A cross-sectional ...

    Abstract Background: Stay-at-home orders and social distancing have been implemented as the primary tools to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, this approach has indirectly lead to the unemployment of 2·3 million Peruvians, in Lima, Perú alone. As a result, the risk of food insecurity may have increased, especially in low-income families who rely on a daily wage. This study estimates the prevalence of moderate or severe food insecurity (MSFI) and identifies the associated factors that explain this outcome during the stay-at-home order.
    Methods: A cross-sectional web-based survey, with non-probabilistic sampling, was conducted between May 18 and June 30, 2020, during the stay-at-home order in Peru. We used social media advertisements on Facebook to reach 18-59-year-olds living in Peru. MSFI was assessed using the Food Insecurity Experience Scale (FIES). Rasch model methodology requirements were considered, and factors associated with MSFI were selected using stepwise forward selection. A Poisson generalized linear model (Poisson GLM), with log link function, was employed to estimate adjusted prevalence ratios (aPR).
    Findings: This analysis is based on 1846 replies. The prevalence of MSFI was 23·2%, and FIES proved to be an acceptable instrument with reliability 0·72 and infit 0·8-1·3. People more likely to experience MSFI were those with low income (less than 255 US$/month) in the pre-pandemic period (aPR 3·77; 95%CI, 1·98-7·16), those whose income was significantly reduced during the pandemic period (aPR 2·27; 95%CI, 1·55-3·31), and those whose savings ran out in less than 21 days (aPR 1·86; 95%CI, 1·43-2·42). Likewise, heads of households (aPR 1·20; 95%CI, 1·00-1·44) and those with probable SARS-CoV2 cases as relatives (aPR 1·29; 95%CI, 1·05-1·58) were at an increased risk of MSFI. Additionally, those who perceived losing weight during the pandemic (aPR 1·21; 95%CI, 1·01-1·45), and increases in processed foods prices (aPR 1·31; 95%CI, 1·08-1·59), and eating less minimally processed food (aPR 1·82; 95%CI, 1·48-2·24) were more likely to experience MSFI.
    Interpretation: People most at risk of MSFI were those in a critical economic situation before and during the pandemic. Social protection policies should be reinforced to prevent or mitigate these adverse effects.
    Language English
    Publishing date 2021-03-31
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2021.02.06.21251221
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Detecting Topic and Sentiment Dynamics Due to COVID-19 Pandemic Using Social Media

    Yin, Hui / Yang, Shuiqiao / Li, Jianxin

    Abstract: ... social media posts. Based on a collection of 13 million tweets related to COVID-19 over two weeks, we found ... lives across the globe. Emergent measures and policies (e.g., lockdown, social distancing) have been ... comparable sentiment polarities. Some topics like ``stay safe home"are dominated with positive sentiment ...

    Abstract The outbreak of the novel Coronavirus Disease (COVID-19) has greatly influenced people's daily lives across the globe. Emergent measures and policies (e.g., lockdown, social distancing) have been taken by governments to combat this highly infectious disease. However, people's mental health is also at risk due to the long-time strict social isolation rules. Hence, monitoring people's mental health across various events and topics will be extremely necessary for policy makers to make the appropriate decisions. On the other hand, social media have been widely used as an outlet for people to publish and share their personal opinions and feelings. The large scale social media posts (e.g., tweets) provide an ideal data source to infer the mental health for people during this pandemic period. In this work, we propose a novel framework to analyze the topic and sentiment dynamics due to COVID-19 from the massive social media posts. Based on a collection of 13 million tweets related to COVID-19 over two weeks, we found that the positive sentiment shows higher ratio than the negative sentiment during the study period. When zooming into the topic-level analysis, we find that different aspects of COVID-19 have been constantly discussed and show comparable sentiment polarities. Some topics like ``stay safe home"are dominated with positive sentiment. The others such as ``people death"are consistently showing negative sentiment. Overall, the proposed framework shows insightful findings based on the analysis of the topic-level sentiment dynamics.
    Keywords covid19
    Publisher ArXiv
    Document type Article
    Database COVID19

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  6. Book ; Online: Detecting Topic and Sentiment Dynamics Due to COVID-19 Pandemic Using Social Media

    Yin, Hui / Yang, Shuiqiao / Li, Jianxin

    2020  

    Abstract: ... social media posts. Based on a collection of 13 million tweets related to COVID-19 over two weeks, we found ... lives across the globe. Emergent measures and policies (e.g., lockdown, social distancing) have been ... comparable sentiment polarities. Some topics like ``stay safe home" are dominated with positive sentiment ...

    Abstract The outbreak of the novel Coronavirus Disease (COVID-19) has greatly influenced people's daily lives across the globe. Emergent measures and policies (e.g., lockdown, social distancing) have been taken by governments to combat this highly infectious disease. However, people's mental health is also at risk due to the long-time strict social isolation rules. Hence, monitoring people's mental health across various events and topics will be extremely necessary for policy makers to make the appropriate decisions. On the other hand, social media have been widely used as an outlet for people to publish and share their personal opinions and feelings. The large scale social media posts (e.g., tweets) provide an ideal data source to infer the mental health for people during this pandemic period. In this work, we propose a novel framework to analyze the topic and sentiment dynamics due to COVID-19 from the massive social media posts. Based on a collection of 13 million tweets related to COVID-19 over two weeks, we found that the positive sentiment shows higher ratio than the negative sentiment during the study period. When zooming into the topic-level analysis, we find that different aspects of COVID-19 have been constantly discussed and show comparable sentiment polarities. Some topics like ``stay safe home" are dominated with positive sentiment. The others such as ``people death" are consistently showing negative sentiment. Overall, the proposed framework shows insightful findings based on the analysis of the topic-level sentiment dynamics.
    Keywords Computer Science - Information Retrieval ; Computer Science - Computers and Society ; Computer Science - Social and Information Networks ; covid19
    Subject code 300
    Publishing date 2020-07-05
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Social predictors of food insecurity during the stay-at-home order due to the COVID-19 pandemic in Peru. Results from a cross-sectional web-based survey

    Canari-Casano, Jorge L. / Elorreaga, Oliver A. / Cochachin-Henostroza, Omaira / Huaman-Gil, Sindy / Dolores-Maldonado, Gandy / Aquino-Ramirez, Anthony / Giribaldi-Sierralta, Juan P. / Aparco, Juan Pablo / Antiporta, Daniel A. / Penny, Mary

    medRxiv

    Abstract: ... 30, 2020, during the stay-at-home order in Peru. We used social media advertisements on Facebook ... Background Stay-at-home orders and social distancing have been implemented as the primary tool ... and identifies the associated factors that explain this outcome during the stay-at-home order. Methods ...

    Abstract Background Stay-at-home orders and social distancing have been implemented as the primary tool to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, this approach has indirectly caused, only in Lima- Peru, more than 2.3 million Peruvians to lose their jobs. As a result, the risk of food insecurity may have increased in affected low-income families, especially those that depend on daily income. This study estimates the prevalence of moderate or severe food insecurity (MSFI) and identifies the associated factors that explain this outcome during the stay-at-home order. Methods A cross-sectional web-based survey, with the non-probability sample, was conducted between May 18 and June 30, 2020, during the stay-at-home order in Peru. We used social media advertisements on Facebook to reach 18-59 year-olds living in Peru. MSFI was assessed using the Food Insecurity Experience Scale (FIES). Rasch model methodology requirements were considered, and factors associated with MSFI were selected using a stepwise forward selection. A Poisson generalized linear model (Poisson GLMs), with log link function, was employed to estimate adjusted prevalence ratios (aPR). Findings This analysis is based on 1846 replies. The prevalence of MSFI was 23.2%, and FIES proved to be an acceptable instrument with reliability 0.72 and infit 0.8-1.3. People more likely to experience MSFI were those with low income (less than 255 US$/month) in the pre-pandemic period (aPR 3.77; 95%CI, 1.98-7.16), those whose income was significantly reduced during the pandemic period (aPR 2.27; 95%CI, 1.55-3.31), and those whose savings ran out in less than 21 days (aPR 1.86; 95%CI, 1.43-2.42). Likewise, heads of households (aPR 1.20; 95%CI, 1.00-1.44) and those with relatives with probable SARS-CoV2 cases (aPR 1.29; 95%CI, 1.05-1.58) were at an increased risk of MSFI. Additionally, those who perceived losing weight during the pandemic (aPR 1.21; 95%CI, 1.01-1.45), and reported increases in processed foods prices (aPR 1.31; 95%CI, 1.08-1.59), and eating less minimally processed food (aPR 1.82; 95%CI, 1.48-2.24) were also more likely to experience MSFI. Interpretation People most at risk of MSFI were those in a critical economic situation before and during the pandemic period. It is necessary to reinforce social protection policies to prevent or mitigate these adverse effects. Funding None.
    Keywords covid19
    Language English
    Publishing date 2021-02-08
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2021.02.06.21251221
    Database COVID19

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