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1. Effects of population co-location reduction on cross-county transmission risk of COVID-19 in the United States

   https://doi.org/10.1007/s41109-021-00361-y  

   Fan, Chao ; Lee, Sanghyeon ; Yang, Yang ; Oztekin, Bora ; Li, Qingchun ; Mostafavi, Ali ( December 2021 , Applied Network Science)

   null (Ed.)

   Abstract The objective of this study is to examine the transmission risk of COVID-19 based on cross-county population co-location data from Facebook. The rapid spread of COVID-19 in the United States has imposed a major threat to public health, the real economy, and human well-being. With the absence of effective vaccines, the preventive actions of social distancing, travel reduction and stay-at-home orders are recognized as essential non-pharmacologic approaches to control the infection and spatial spread of COVID-19. Prior studies demonstrated that human movement and mobility drove the spatiotemporal distribution of COVID-19 in China. Little is known, however, about the patterns and effects of co-location reduction on cross-county transmission risk of COVID-19. This study utilizes Facebook co-location data for all counties in the United States from March to early May 2020 for conducting spatial network analysis where nodes represent counties and edge weights are associated with the co-location probability of populations of the counties. The analysis examines the synchronicity and time lag between travel reduction and pandemic growth trajectory to evaluate the efficacy of social distancing in ceasing the population co-location probabilities, and subsequently the growth in weekly new cases across counties. The results show that the mitigation effects of co-location reduction appear in the growth of weekly new confirmed cases with one week of delay. The analysis categorizes counties based on the number of confirmed COVID-19 cases and examines co-location patterns within and across groups. Significant segregation is found among different county groups. The results suggest that within-group co-location probabilities (e.g., co-location probabilities among counties with high numbers of cases) remain stable, and social distancing policies primarily resulted in reduced cross-group co-location probabilities (due to travel reduction from counties with large number of cases to counties with low numbers of cases). These findings could have important practical implications for local governments to inform their intervention measures for monitoring and reducing the spread of COVID-19, as well as for adoption in future pandemics. Public policy, economic forecasting, and epidemic modeling need to account for population co-location patterns in evaluating transmission risk of COVID-19 across counties. 

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2. Individual differences in emotional intelligence skills of people with visual impairment and loneliness amid the COVID-19 pandemic

   https://doi.org/10.1177/02646196211013860  

   Kim, Hyung Nam ; Sutharson, Sam Jotham ( January 2021 , British Journal of Visual Impairment)

   null (Ed.)

   In response to the novel coronavirus (COVID-19) pandemic, public health interventions such as social distancing and stay-at-home orders have widely been implemented, which is anticipated to contribute to reducing the spread of COVID-19. On the contrary, there is a concern that the public health interventions may increase the level of loneliness. Loneliness and social isolation are public health risks, closely associated with serious medical conditions. As COVID-19 is new to us today, little is known about emotional well-being among people with visual impairment during the COVID-19 pandemic. To address the knowledge gap, this study conducted phone interviews with a convenience sample of 31 people with visual impairment. The interview incorporated the University of California, Los Angeles (UCLA) Loneliness Scale (version 3) and the trait meta-mood scale (TMMS) to measure loneliness and emotional intelligence skills, respectively. This study found that people with visual impairment were vulnerable to the feeling of loneliness during the COVID-19 pandemic and showed individual differences in emotional intelligence skills by different degrees of loneliness. Researchers and health professionals should consider offering adequate coping strategies to those with visual impairment amid the COVID-19 pandemic. 

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3. Are stay-at-home orders more difficult to follow for low-income groups?

   https://doi.org/10.1016/j.jtrangeo.2020.102894  

   Lou, Jiehong ; Shen, Xingchi ; Niemeier, Deb ( December 2020 , Journal of transport geography)

   In response to the COVID-19 pandemic, a growing number of states, counties and cities in the United States issued mandatory stay-at-home orders as part of their efforts to slow down the spread of the virus. We argue that the consequences of this one-size-fits-all order will be differentially distributed among economic groups. In this paper, we examine social distance behavior changes for lower income populations. We conduct a comparative analysis of responses between lower-income and upper-income groups and assess their relative exposure to COVID-19 risks. Using a difference-in-difference-in-differences analysis of 3140 counties, we find social distance policy effect on the lower-income group is smaller than that of the upper-income group, by as much as 46% to 54%. Our explorations of the mechanisms behind the disparate effects suggest that for the work-related trips the stay-at-home orders do not significantly reduce low income work trips and this result is statistically significant. That is, the share of essential business defined by stay-at-home orders is significantly negatively correlated with income at county level. In the non-work-related trips, we find that both the lower-income and upper-income groups reduced visits to retail, recreation, grocery, and pharmacy visits after the stay-at-home order, with the upper-income group reducing trips more compared to lower-income group. 

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4. “I don’t feel safe sitting in my own yard”: Chicago resident experiences with urban rats during a COVID-19 stay-at-home order

   https://doi.org/10.1186/s12889-021-11095-y  

   Murray, Maureen H. ; Byers, Kaylee A. ; Buckley, Jacqueline ; Magle, Seth B. ; Maffei, Dorothy ; Waite, Preeya ; German, Danielle ( December 2021 , BMC Public Health)

   null (Ed.)

   Abstract Background Encounters with rats in urban areas increase risk of human exposure to rat-associated zoonotic pathogens and act as a stressor associated with psychological distress. The frequency and nature of human-rat encounters may be altered by social distancing policies to mitigate the COVID-19 pandemic. For example, restaurant closures may reduce food availability for rats and promote rat activity in nearby residential areas, thus increasing public health risks during a period of public health crisis. In this study, we aimed to identify factors associated with increased perceived exposure to rats during a stay-at-home order, describe residents’ encounters with rats relevant to their health and well-being, and identify factors associated with increased use of rodent control. Methods Urban residents in Chicago, a large city with growing concerns about rats and health disparities, completed an online questionnaire including fixed response and open-ended questions during the spring 2020 stay-at-home order. Analyses included ordinal multivariate regression, spatial analysis, and thematic analysis for open-ended responses. Results Overall, 21% of respondents ( n  = 835) reported an increase in rat sightings around their homes during the stay-at-home order and increased rat sightings was positively associated with proximity to restaurants, low-rise apartment buildings, and rat feces in the home ( p  ≤ 0.01). Many respondents described feeling unsafe using their patio or yard, and afraid of rats entering their home or spreading disease. Greater engagement with rodent control was associated with property ownership, information about rat control, and areas with lower incomes ( p  ≤ 0.01). Conclusions More frequent rat encounters may be an unanticipated public health concern during periods of social distancing, especially in restaurant-dense areas or in low-rise apartment buildings. Rat presence may also limit residents’ ability to enjoy nearby outdoor spaces, which otherwise might buffer stress experienced during a stay-at-home order. Proactive rat control may be needed to mitigate rat-associated health risks during future stay-at-home orders. 

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5. Topics and Sentiments of Public Concerns Regarding COVID-19 Vaccines: Social Media Trend Analysis

   https://doi.org/10.2196/30765  

   Monselise, Michal ; Chang, Chia-Hsuan ; Ferreira, Gustavo ; Yang, Rita ; Yang, Christopher C ( January 2021 , Journal of Medical Internet Research)

   Background As a number of vaccines for COVID-19 are given emergency use authorization by local health agencies and are being administered in multiple countries, it is crucial to gain public trust in these vaccines to ensure herd immunity through vaccination. One way to gauge public sentiment regarding vaccines for the goal of increasing vaccination rates is by analyzing social media such as Twitter. Objective The goal of this research was to understand public sentiment toward COVID-19 vaccines by analyzing discussions about the vaccines on social media for a period of 60 days when the vaccines were started in the United States. Using the combination of topic detection and sentiment analysis, we identified different types of concerns regarding vaccines that were expressed by different groups of the public on social media. Methods To better understand public sentiment, we collected tweets for exactly 60 days starting from December 16, 2020 that contained hashtags or keywords related to COVID-19 vaccines. We detected and analyzed different topics of discussion of these tweets as well as their emotional content. Vaccine topics were identified by nonnegative matrix factorization, and emotional content was identified using the Valence Aware Dictionary and sEntiment Reasoner sentiment analysis library as well as by using sentence bidirectional encoder representations from transformer embeddings and comparing the embedding to different emotions using cosine similarity. Results After removing all duplicates and retweets, 7,948,886 tweets were collected during the 60-day time period. Topic modeling resulted in 50 topics; of those, we selected 12 topics with the highest volume of tweets for analysis. Administration and access to vaccines were some of the major concerns of the public. Additionally, we classified the tweets in each topic into 1 of the 5 emotions and found fear to be the leading emotion in the tweets, followed by joy. Conclusions This research focused not only on negative emotions that may have led to vaccine hesitancy but also on positive emotions toward the vaccine. By identifying both positive and negative emotions, we were able to identify the public's response to the vaccines overall and to news events related to the vaccines. These results are useful for developing plans for disseminating authoritative health information and for better communication to build understanding and trust. 

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