scholarly journals Reduction in mobility and COVID-19 transmission

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Pierre Nouvellet ◽  
Sangeeta Bhatia ◽  
Anne Cori ◽  
Kylie E. C. Ainslie ◽  
Marc Baguelin ◽  
...  
Keyword(s):  
Predictive Ability ◽  
Control Measures ◽  
Social Distancing ◽  
Beneficial Effects ◽  
Mobility Data ◽  
Strict Control ◽  
Before And After ◽  
Proxy Measure ◽  
Lower Transmission ◽  
The Relationship

AbstractIn response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts. Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world. Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27–77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49–91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12–48%]) post-relaxation. In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.

scholarly journals Toward a Country-Based Prediction Model of COVID-19 Infections and Deaths Between Disease Apex and End: Evidence From Countries With Contained Numbers of COVID-19

2021 ◽  
Vol 8 ◽  
Author(s):  
Tianshu Gu ◽  
Lishi Wang ◽  
Ning Xie ◽  
Xia Meng ◽  
Zhijun Li ◽  
...  
Keyword(s):  
Real Data ◽  
Control Measures ◽  
Actual Number ◽  
The Public ◽  
The Us ◽  
Multiple Regression Models ◽  
Before And After ◽  
Using Data ◽  
High Degree ◽  
The Relationship

The complexity of COVID-19 and variations in control measures and containment efforts in different countries have caused difficulties in the prediction and modeling of the COVID-19 pandemic. We attempted to predict the scale of the latter half of the pandemic based on real data using the ratio between the early and latter halves from countries where the pandemic is largely over. We collected daily pandemic data from China, South Korea, and Switzerland and subtracted the ratio of pandemic days before and after the disease apex day of COVID-19. We obtained the ratio of pandemic data and created multiple regression models for the relationship between before and after the apex day. We then tested our models using data from the first wave of the disease from 14 countries in Europe and the US. We then tested the models using data from these countries from the entire pandemic up to March 30, 2021. Results indicate that the actual number of cases from these countries during the first wave mostly fall in the predicted ranges of liniar regression, excepting Spain and Russia. Similarly, the actual deaths in these countries mostly fall into the range of predicted data. Using the accumulated data up to the day of apex and total accumulated data up to March 30, 2021, the data of case numbers in these countries are falling into the range of predicted data, except for data from Brazil. The actual number of deaths in all the countries are at or below the predicted data. In conclusion, a linear regression model built with real data from countries or regions from early pandemics can predict pandemic scales of the countries where the pandemics occur late. Such a prediction with a high degree of accuracy provides valuable information for governments and the public.

scholarly journals Socioeconomic Disparities in Social Distancing During the COVID-19 Pandemic in the United States: Observational Study (Preprint)

2020 ◽  
Author(s):  
Romain Garnier ◽  
Jan R Benetka ◽  
John Kraemer ◽  
Shweta Bansal
Keyword(s):  
United States ◽  
Black People ◽  
The United States ◽  
Control Measures ◽  
Mobility Patterns ◽  
Poverty Level ◽  
Social Distancing ◽  
Mobility Data ◽  
Black Populations ◽  
The Impact

BACKGROUND Eliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic. OBJECTIVE We aimed to assess how mobility patterns have varied across the United States during the COVID-19 pandemic and to identify associations with socioeconomic factors of populations. METHODS We used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level in the United States between February and May 2020, the period during which social distancing was widespread in this country. Using linear mixed models, we assessed the associations between social distancing and socioeconomic variables, including the proportion of people in the population below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density. RESULTS We found that the speed, depth, and duration of social distancing in the United States are heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; in contrast, we show that social distancing is intensely adopted in counties with higher population densities and larger Black populations. CONCLUSIONS Socioeconomic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of the COVID-19 pandemic in communities across the United States. These inequalities are likely to amplify existing health disparities and must be addressed to ensure the success of ongoing pandemic mitigation efforts.

scholarly journals Acute effects of coffee on neurocognitive function: an electroencephalography network analysis

2021 ◽  
Author(s):  
Hayom Kim ◽  
Sung Hoon Kang ◽  
Soon Ho Kim ◽  
Seong Hwan Kim ◽  
Jihyeon Hwang ◽  
...  
Keyword(s):  
Executive Function ◽  
Cognitive Function ◽  
Digit Span ◽  
Coffee Consumption ◽  
Beneficial Effects ◽  
Before And After ◽  
Trail Making ◽  
Network Properties ◽  
Improved Performance ◽  
The Relationship

Abstract The purpose of this study was to identify the mechanisms underlying effects of coffee on cognition in the context of brain networks. Here we investigated functional connectivity before and after drinking coffee using graph theoretical analysis of electroencephalography (EEG). Twenty-one healthy adults voluntarily participated in this study. The neuropsychological tests were consecutively performed at the start of the EEG recording and 30 min after coffee consumption. Graph analyses were performed and compared before and after coffee consumption. Correlation analyses were conducted to assess the relationship between changes in graph measures and those in cognitive function tests. FC was reorganized toward more efficient network properties after coffee consumption. Performance in Digit Span tests and Trail Making Test Part B improved after coffee consumption, and the improved performance in executive function was correlated with changes in graph measures, reflecting a shift toward efficient network properties. The beneficial effects of coffee on cognitive function might be attributed to the reorganization of FC toward more efficient network properties. Based on our findings, the patterns of network reorganization could be used as quantitative markers to elucidate the mechanisms underlying the beneficial effects of coffee on cognition, especially executive function.

Changes in prescribing of oral capecitabine versus intravenous (IV) 5-fluorouracil (5-FU) in gastrointestinal (GI) cancers during the COVID-19 pandemic.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18596-e18596
Author(s):  
Yasin Civelek ◽  
Daniel Cullen ◽  
David Joseph Debono ◽  
Michael Jordan Fisch ◽  
John Barron ◽  
...  
Keyword(s):  
Prescribing Patterns ◽  
Cancer Type ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Oral Capecitabine ◽  
Social Distancing ◽  
Start Date ◽  
Mobility Data ◽  
Before And After ◽  
Gi Cancers

e18596 Background: Several oncology guidelines recommend using oral drugs vs. IV to minimize COVID-19 risk for patients with cancer. We examined the association between prescribing patterns of oral capecitabine vs. IV 5FU for GI cancers and social distancing, measured by the change in population mobility patterns in response to shelter-in place policies, during the pandemic. Methods: Using claims data for commercially insured members, we included patients 18 years of age or older with colorectal, gastroesophageal, or pancreatic cancer, who had continuous health plan coverage for at least 2 months before and 1 month after initiating chemotherapy with capecitabine or 5-FU from January 2017 to August 2020. We analyzed unadjusted trends in proportion of chemotherapy that was oral during pandemic (March 1st to August 31st, 2020) compared to previous years. Then, we conducted difference-in-differences analysis using COVID-19 Community Mobility Reports, by Google, and utilizing different levels of changes in mobility trends across states over time. In our main model, we used a 20% decrease in retail and recreation visits as our threshold and compared the prescribing rates in states below and above the threshold as well as before and after the pandemic began. We also used different thresholds and categories of places to check the sensitivity of our findings. Models are adjusted for age, gender, month of year, urban status, comorbidities, and state of residence at chemotherapy start date. Results: A total of 17,414 nationally distributed patients (69% colorectal, 13% gastroesophageal, 18% pancreatic) were included (mean age, 58.8 years; 41% female). During the pandemic, 1,875 patients (65% colorectal, 15% gastroesophageal, 20% pancreatic) were identified. The proportion of oral regimens did not change significantly for colorectal and gastroesophageal patients and decreased by 7.4 percentage points (pp) (p < 0.01) for pancreatic patients. In regression modelling with mobility data, oral prescribing rates for colorectal patients increased by 3.1 pp (p < 0.01), largely driven by increases for female patients (9.2 pp, p = 0.02). We observed a decrease in oral prescribing rates among pancreatic patients (-1.20 pp, p = 0.04) and did not observe a significant change for gastroesophageal patients. Our results are not sensitive to different social distancing specifications. Conclusions: We observed differential impact of the pandemic on oral prescribing rates by GI cancer type and gender. Oral prescribing increased among colorectal cancer patients driven mostly by higher oral prescribing in females. For pancreatic and gastroesophageal patients, oral prescriptions either remained unchanged or decreased. This observation may reflect a variable impact of the pandemic on women as compared to men and might involve heightened caregiving responsibilities for women.

scholarly journals Early social distancing policies in Europe, changes in mobility & COVID-19 case trajectories: Insights from Spring 2020

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253071
Author(s):  
Liana R. Woskie ◽  
Jonathan Hennessy ◽  
Valeria Espinosa ◽  
Thomas C. Tsai ◽  
Swapnil Vispute ◽  
...  
Keyword(s):  
Comprehensive Evaluation ◽  
Population Mobility ◽  
School Closures ◽  
Social Distancing ◽  
Government Response ◽  
Mobility Data ◽  
Aggregate Population ◽  
The Impact ◽  
The Relationship ◽  
At Home

Background Social distancing have been widely used to mitigate community spread of SARS-CoV-2. We sought to quantify the impact of COVID-19 social distancing policies across 27 European counties in spring 2020 on population mobility and the subsequent trajectory of disease. Methods We obtained data on national social distancing policies from the Oxford COVID-19 Government Response Tracker and aggregated and anonymized mobility data from Google. We used a pre-post comparison and two linear mixed-effects models to first assess the relationship between implementation of national policies and observed changes in mobility, and then to assess the relationship between changes in mobility and rates of COVID-19 infections in subsequent weeks. Results Compared to a pre-COVID baseline, Spain saw the largest decrease in aggregate population mobility (~70%), as measured by the time spent away from residence, while Sweden saw the smallest decrease (~20%). The largest declines in mobility were associated with mandatory stay-at-home orders, followed by mandatory workplace closures, school closures, and non-mandatory workplace closures. While mandatory shelter-in-place orders were associated with 16.7% less mobility (95% CI: -23.7% to -9.7%), non-mandatory orders were only associated with an 8.4% decrease (95% CI: -14.9% to -1.8%). Large-gathering bans were associated with the smallest change in mobility compared with other policy types. Changes in mobility were in turn associated with changes in COVID-19 case growth. For example, a 10% decrease in time spent away from places of residence was associated with 11.8% (95% CI: 3.8%, 19.1%) fewer new COVID-19 cases. Discussion This comprehensive evaluation across Europe suggests that mandatory stay-at-home orders and workplace closures had the largest impacts on population mobility and subsequent COVID-19 cases at the onset of the pandemic. With a better understanding of policies’ relative performance, countries can more effectively invest in, and target, early nonpharmacological interventions.

scholarly journals Changes in Acute Respiratory Infection Before and After COVID-19

2021 ◽  
Vol 5 (1) ◽  
pp. e11
Author(s):  
Hyemin Jung ◽  
Seol-hee Chung ◽  
Han-Sang Kim ◽  
Hyun-Joo Kim ◽  
EunKyo Kang
Keyword(s):  
Control Method ◽  
Respiratory Infections ◽  
Incidence Rates ◽  
Control Measures ◽  
Medical Utilization ◽  
National Database ◽  
Social Distancing ◽  
Infection Control Measures ◽  
Before And After ◽  
Number Of Visits

Objective: During the outbreak of COVID-19,several coping strategies were implemented including strengthened social distancing, wearing masks and hand hygiene. Thisinfection control method might have been effective for other respiratory infections; however, it had not yet been clearly revealed. Therefore,we investigatedwhetherthe incidence of infectious respiratory diseases has reduced after excluding the effect of decreased medical utilization because of COVID-19 control measures.Design or methods: We used the Korean national claims data and analyzed incidences of acute respiratory infections (ARI) and diseases except ARI. The incidence rates of winter 2019 and 2020 were compared.Results: Excluding ARI,the reduction in overall hospital visits decreased by only 2%; however,the number of visits due to ARI decreased by 13%, and the number of visits due to influenza particularly decreased by 26%.Conclusions: Using national database, this study confirmed that a significant reduction in ARI, including influenza, occurred during the COVID-19 pandemic. Infection control measures including nationally enforced social distancing may be effective in controlling the transmission of other respiratory infections. Further studies are necessary to clarify the causal relationship.

scholarly journals Socio-economic disparities in social distancing during the COVID-19 pandemic in the United States

2020 ◽  
Author(s):  
Romain Garnier ◽  
Jan R. Benetka ◽  
John Kraemer ◽  
Shweta Bansal
Keyword(s):  
United States ◽  
Black People ◽  
The United States ◽  
Control Measures ◽  
Mobility Patterns ◽  
Poverty Level ◽  
Social Distancing ◽  
Mobility Data ◽  
Black Populations ◽  
The Impact

AbstractImportanceEliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic.ObjectiveTo assess how mobility patterns have varied across the United States during the COVID-19 pandemic, and identify associations with socio-economic factors of populations.Design, Setting, and ParticipantsWe used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level between February and May 2020. Using linear mixed models, we assessed the associations between social distancing and socio-economic variables, including the proportion of people below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density.Main outcomes and ResultsWe find that the speed, depth, and duration of social distancing in the United States is heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; and in contrast, that social distancing is intense in counties with higher population densities and larger Black populations.Conclusions and relevanceSocio-economic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of COVID-19 in communities across the United States. This is likely to amplify existing health disparities, and needs to be addressed to ensure the success of ongoing pandemic mitigation efforts.

scholarly journals Influences of Social Distancing and attachment styles on the strength of the Halo Effect

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256364
Author(s):  
Giulio Gabrieli ◽  
Yun Yee Lim ◽  
Gianluca Esposito
Keyword(s):  
Impression Formation ◽  
Attachment Styles ◽  
Halo Effect ◽  
Social Scientists ◽  
Social Distancing ◽  
Aesthetic Appearance ◽  
Before And After ◽  
Experimental Works ◽  
The Stability ◽  
The Relationship

The Halo Effect is a widely studied phenomenon that interests multiple disciplines. The relationship between Aesthetics Appearance and perceived Trustworthiness has especially gathered the attention of social scientists. While experimental works compared the strength of the Halo Effect in different situations (e.g. different genders’ faces), little is known about the stability of the Halo. During the COVID-19 pandemic, we have been urged to distance ourselves from others. Similar suggestions may alter the relationship between Aesthetic Appearance and Perceived Trustworthiness. Moreover, previous works reported that individuals’ attachment styles affected their emotional responses to the pandemic. Individuals’ attachment styles may influence the magnitude of change of the Halo. Here we investigate how priming (Social Distancing or Contact with others) affects the strength of the Halo Effect, with respect to individuals’ attachment styles. Participants (N = 298) rated the Aesthetics and Perceived Trustworthiness of strangers’ faces (N = 96) presented twice, before and after the presentation of a prime. Results revealed that individuals’ attachment styles affect the strength of the Halo. However, we found no evidence supporting the fact that different attachment styles lead to differences in the magnitude of changes after priming. Results help shed light on how attachment styles influence individuals’ impression formation.

scholarly journals Mobility indicators and COVID-19 growth ratio in Iraq: a correlation study

2021 ◽  
Author(s):  
Faris Lami ◽  
Hanan Abdulghafoor Khaleel ◽  
Yousef S Khader
Keyword(s):  
General Linear Model ◽  
Correlation Study ◽  
Control Measures ◽  
P Value ◽  
Growth Ratio ◽  
Mobility Index ◽  
Mobility Data ◽  
Community Mobility ◽  
The Relationship ◽  
Moderate Positive Correlation

Abstract Background There is no prior study of the effect of mobility-limiting measures on the occurrence of COVID-19 in Iraq. Objectives To determine the relationship between publicly available mobility index data and the growth ratio (GR) of COVID-19. Method We used Google COVID-19 Community Mobility Reports to extract Iraq’s mobility data and the official Ministry of Health COVID-19 statements. We used the data to calculate the Pearson’s correlation coefficient and fit a linear regression model to determine the relationship between percentage change from the baseline in the mobility indices and the GR of COVID-19 in Iraq. Results There was a moderate positive correlation between each of the mobility indices except the residential index and COVID-19 GR in Iraq. The general linear model indicated that as each of the mobility indices increases by one unit, the GR of COVID19 increases by 0.002–0.003 except for the residential index. As the residential mobility index increases by one unit, the GR decreases by 0.009. All the findings were statistically significant (P-value &lt; 0.0001). Conclusion Mobility-limiting measures may be able to reduce the growth rate of COVID-19 moderately. Accordingly, mobility-limiting measures should be combined with other public control measures particularly mass mask use.

scholarly journals Inequality in Risk-Taking: Evidence From Location Tracking in Mexican Cities During COVID 19

2021 ◽  
Vol 3 ◽  
Author(s):  
Melissa Ziegler Rogers ◽  
Yuzhu Zeng ◽  
Andrew Marx ◽  
Mia Poynor ◽  
Morgan Lu
Keyword(s):  
Low Income ◽  
Risk Taking ◽  
Individual Risk ◽  
Location Tracking ◽  
Policy Responses ◽  
Mobility Data ◽  
Before And After ◽  
The Government ◽  
The Many ◽  
The Relationship

Among the many striking features of the COVID 19 pandemic is the geographic heterogeneity of its incidence and its disproportionate effects on low income people. We examine links between individual risk and COVID 19 outcomes in the federal context in Mexico characterized by high socioeconomic and political heterogeneity. Using highly detailed individual mobility data for five Mexican cities, we document the relationship between local income and education factors and the behaviors associated with COVID 19 risk after the national lockdown: staying home, going to work, and going other places. While low income people are disproportionately likely to contract COVID 19 and die from illnesses associated with COVID 19 in Mexico, we find very mixed evidence that people living in low income urban census blocs are engaging in observably riskier behaviors. Both before and after the national lockdown, people in low income locations spend more time at home and less time going other places, suggesting a lower overall risk of contracting the virus based on voluntary movement. However, people in low income and less educated places appear to shift their movement less in response to Mexico’s national lockdown. Less educated people, in particular, show much less change in their movement patterns in response to the lockdown. At the same time, we find enormous variance between cities and in some cities such as Mexico City and Ecatepec people in low income places changed their behavior more after the lockdown. Understanding the reasons for these income and education differences in outcomes is crucial for policy responses–whether the government should focus on educating individuals about their behavior, or whether the response requires a much more difficult overhaul of societal protections.

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