scholarly journals Population Mobility, Lockdowns, and COVID-19 Control: An Analysis Based on Google Location Data and Doubling Time from India

2021 ◽  
Vol 27 (4) ◽  
pp. 325-334
Author(s):  
Aravind Gandhi Periyasamy ◽  
U Venkatesh
Keyword(s):  
Urban Areas ◽  
Doubling Time ◽  
Control Measure ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Location Data ◽  
Community Mobility ◽  
Tailored Implementation

Objectives: Physical distancing is a control measure against coronavirus disease 2019 (COVID-19). Lockdowns are a strategy to enforce physical distancing in urban areas, but they are drastic measures. Therefore, we assessed the effectiveness of the lockdown measures taken in the world’s second-most populous country, India, by exploring their relationship with community mobility patterns and the doubling time of COVID-19.Methods: We conducted a retrospective analysis based on community mobility patterns, the stringency index of lockdown measures, and the doubling time of COVID-19 cases in India between February 15 and April 26, 2020. Pearson correlation coefficients were calculated between the stringency index, community mobility patterns, and the doubling time of COVID-19 cases. Multiple linear regression was applied to predict the doubling time of COVID-19.Results: Community mobility drastically fell after the lockdown was instituted. The doubling time of COVID-19 cases was negatively correlated with population mobility patterns in outdoor areas (r = –0.45 to –0.58). The stringency index and outdoor mobility patterns were also negatively correlated (r = –0.89 to –0.95). Population mobility patterns (R2 = 0.67) were found to predict the doubling time of COVID-19, and the model’s predictive power increased when the stringency index was also added (R2 = 0.73).Conclusions: Lockdown measures could effectively ensure physical distancing and reduce short-term case spikes in India. Therefore, lockdown measures may be considered for tailored implementation on an intermittent basis, whenever COVID-19 cases are predicted to exceed the health care system’s capacity to manage.

scholarly journals Mobility Patterns of the Portuguese Population During the First Year of the COVID-19 Pandemic: A Longitudinal Study

2021 ◽  
Author(s):  
Tiago Tamagusko ◽  
Adelino Ferreira
Keyword(s):  
Lower Risk ◽  
Reproduction Number ◽  
First Year ◽  
Second Phase ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Portuguese Population ◽  
Location Data ◽  
Community Mobility ◽  
The Relationship

This study analyzes the relationship between the spread of the SARS-CoV-2 virus (COVID-19) and the mobility patterns of the Portuguese population. By reducing mobility, the idea is that contacts are reduced, countering the spread of the virus in the community. As an indicator of the spread of the virus, the reproduction number (Rt) was used. Data from Google's Community Mobility Reports was used to evaluate changes in mobility patterns. This report uses location data from Android mobile phone users. The locations are divided into retail and recreation, grocery and pharmacy, parks, transit stations, workplaces and residential. In this year of the COVID-19 crisis in Portugal, population mobility patterns have changed over the various phases of the pandemic. At first, all mobility was affected uniformly, with the population avoiding much of the activity outside the home. In a second phase, there was some adaptation, and the areas considered to be of lower risk had less impact, emphasizing the changes in the relationship between daily life and the workplace.

scholarly journals Evaluating Social Distancing Measures and Their Association with the Covid-19 Pandemic in South America

2021 ◽  
Vol 10 (3) ◽  
pp. 121
Author(s):  
Gisliany Lillian Alves de Oliveira ◽  
Luciana Lima ◽  
Ivanovitch Silva ◽  
Marcel da Câmara Ribeiro-Dantas ◽  
Kayo Henrique Monteiro ◽  
...  
Keyword(s):  
South America ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Mobility Index ◽  
Social Distancing ◽  
Government Response ◽  
Community Mobility ◽  
Data Driven Approach ◽  
Local Moran ◽  
Global And Local

Social distancing is a powerful non-pharmaceutical intervention used as a way to slow the spread of the SARS-CoV-2 virus around the world since the end of 2019 in China. Taking that into account, this work aimed to identify variations on population mobility in South America during the pandemic (15 February to 27 October 2020). We used a data-driven approach to create a community mobility index from the Google Covid-19 Community Mobility and relate it to the Covid stringency index from Oxford Covid-19 Government Response Tracker (OxCGRT). Two hypotheses were established: countries which have adopted stricter social distancing measures have also a lower level of circulation (H1), and mobility is occurring randomly in space (H2). Considering a transient period, a low capacity of governments to respond to the pandemic with more stringent measures of social distancing was observed at the beginning of the crisis. In turn, considering a steady-state period, the results showed an inverse relationship between the Covid stringency index and the community mobility index for at least three countries (H1 rejected). Regarding the spatial analysis, global and local Moran indices revealed regional mobility patterns for Argentina, Brazil, and Chile (H1 rejected). In Brazil, the absence of coordinated policies between the federal government and states regarding social distancing may have played an important role for several and extensive clusters formation. On the other hand, the results for Argentina and Chile could be signals for the difficulties of governments in keeping their population under control, and for long periods, even under stricter decrees.

scholarly journals LB-10. Rapid Assessments of Non-Pharmaceutical Intervention Uptake and Population Mobility Patterns Elucidate SARS-Cov-2 Transmission Dynamics

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S848-S848
Author(s):  
Amy Wesolowski ◽  
Dustin Gibson ◽  
Smisha Agarwal ◽  
Anastasia Lambrou ◽  
Gregory Kirk ◽  
...  
Keyword(s):  
Public Transportation ◽  
Panel Member ◽  
Correlation Coefficients ◽  
Grocery Store ◽  
Mitigation Strategies ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Research Support ◽  
Pairwise Correlation ◽  
Significant Relationships

Abstract Background Current mitigation strategies for SARS-CoV-2 rely on population-wide adoption of non-pharmaceutical interventions (NPIs). Monitoring NPI adoption, mobility patterns and their association with SARS-CoV-2 infection can provide key information for public health agencies and be used to calibrate transmission models. Methods We used an online panel to accrue representative samples from Florida, Illinois, and Maryland (n=3,009, approximately 1,000 per state) from July 15–31, 2020 and capture socio-demographically and geographically resolved information about NPI adoption and mobility in the prior 2 weeks. Logistic regression was used to identify correlates of self-reported SARS-CoV-2 infection in the prior 2 weeks. Results Overall, 96% reported traveling outside their home in the prior 2 weeks, the most common reason being to visit a grocery store/pharmacy (92%), followed by visiting friends/family (61%), and visiting a place of worship (23%); 22% reporting public transportation use. In total, 44% of respondents reported always practicing social distancing and 40% reported always using a mask indoors and outdoors. Overall, 74 (2.5%) reported testing positive for SARS-CoV-2 in the prior 2 weeks, with strong dose-response relationships between several forms of movement frequency and SARS-CoV-2 positivity. Variables capturing mobility were all highly correlated with one another, suggesting there are clusters of individuals who engage in multiple activities (Figure); 41% of positive cases engaged in all forms of mobility captured compared to 1% of those who did not test positive within the prior 2 weeks. Patterns of mobility and NPI uptake did not significantly differ by state; however, there were significant relationships with age, race/ethnicity, and gender. In multivariable models including adjustment for NPIs, significant relationships remained with public transportation, visiting a place of worship, and participating in outdoor group fitness activities. Figure. Heatmap depicting pairwise Spearman correlation coefficients between survey responses. Pairwise correlation coefficients are displayed in the boxes at intersection of any two variables. Questions were asked with respect activities in the prior 2 weeks. Conclusion NPI adoption and mobility did not vary across these three states with variable policies and SARS-CoV-2 positivity rates. Rather, associations with recent positivity appear to be driven largely by mobility patterns and engagement in activities where NPI use may be challenging or inconsistent. Disclosures Shruti Mehta, PhD, MPH, Gilead Sciences (Other Financial or Material Support, Speaker) Sunil Solomon, MD, PhD, MPH, Abbott Diagnostics (Grant/Research Support)Gilead Sciences (Grant/Research Support, Advisor or Review Panel member)

A refined dichotomy on returners and explorers in urban mobility pattern

2019 ◽  
Vol 33 (22) ◽  
pp. 1950251
Author(s):  
Qing-Chao Shan ◽  
Hong-Hui Dong ◽  
Hai-Jian Li ◽  
Li-Min Jia
Keyword(s):  
Mobile Phone ◽  
Urban Areas ◽  
Human Mobility ◽  
Mobile Phone Data ◽  
Support Vector ◽  
Radius Of Gyration ◽  
Urban Mobility ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Spatial Indices

With the change in people’s lifestyle and travel mode, understanding the individual and population mobility patterns in urban areas remains to an outstanding problem. Pervasive mobile communication technologies generate voluminous data related to human mobility, such as mobile phone data. To further study the characteristics of returning and exploration patterns of human movement in urban space, a multi-index model is proposed based on the original radius of the gyration index. In this paper, the classification mechanism of a single ratio of the radius of gyration for k-explorers and k-returners is illustrated. Some disadvantages of this mechanism are noted. A few indices of the model are proposed for deep mining of data on human mobility exploration and returning characteristics. Taking a mobile phone data during an entire month as a sample, and after data processing on the Spark platform, the characteristics of various indicators and their correlations are analyzed. The classification effects of different spatial indices for human exploration and returning are compared by using a support vector machine and the binary classification algorithm and are further compared with existing research results. The differences in the classification effects of these indicators are analyzed, which is helpful for in-depth studies of urban mobility patterns.

scholarly journals Data-Driven Approach to Understand the Mobility Patterns of the Portuguese Population during the COVID-19 Pandemic

2020 ◽  
Vol 12 (22) ◽  
pp. 9775
Author(s):  
Tiago Tamagusko ◽  
Adelino Ferreira
Keyword(s):  
Distance Measures ◽  
Data Driven ◽  
Definitive Treatment ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Portuguese Population ◽  
Community Mobility ◽  
Pattern Change ◽  
Data Driven Approach ◽  
The Impact

SARS-CoV-2 emerged in late 2019. Since then, it has spread to several countries, becoming classified as a pandemic. So far, there is no definitive treatment or vaccine, so the best solution is to prevent transmission between individuals through social distancing. However, it is not easy to measure the effectiveness of these distance measures. Therefore, this study uses data from Google COVID-19 Community Mobility Reports to understand the Portuguese population’s mobility patterns during the COVID-19 pandemic. In this study, the Rt value was modeled for Portugal. In addition, the changepoint was calculated for the population mobility patterns. Thus, the mobility pattern change was used to understand the impact of social distance measures on the dissemination of COVID-19. As a result, it can be stated that the initial Rt value in Portugal was very close to 3, falling to values close to 1 after 25 days. Social isolation measures were adopted quickly. Furthermore, it was observed that public transport was avoided during the pandemic. Finally, until the emergence of a vaccine or an effective treatment, this is the new normal, and it must be understood that new patterns of mobility, social interaction, and hygiene must be adapted to this reality.

Reliability of the Minimum Masking Level as Outcome Variable in Tinnitus Clinical Research

2020 ◽  
Vol 29 (3) ◽  
pp. 429-435
Author(s):  
Patricia C. Mancini ◽  
Richard S. Tyler ◽  
Hyung Jin Jun ◽  
Tang-Chuan Wang ◽  
Helena Ji ◽  
...  
Keyword(s):  
Standard Deviation ◽  
High Frequency ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Outcome Variable ◽  
Reliable Estimate ◽  
Moderate Correlation ◽  
Trained Subjects ◽  
The Relationship ◽  
Minimum Intensity

Purpose The minimum masking level (MML) is the minimum intensity of a stimulus required to just totally mask the tinnitus. Treatments aimed at reducing the tinnitus itself should attempt to measure the magnitude of the tinnitus. The objective of this study was to evaluate the reliability of the MML. Method Sample consisted of 59 tinnitus patients who reported stable tinnitus. We obtained MML measures on two visits, separated by about 2–3 weeks. We used two noise types: speech-shaped noise and high-frequency emphasis noise. We also investigated the relationship between the MML and tinnitus loudness estimates and the Tinnitus Handicap Questionnaire (THQ). Results There were differences across the different noise types. The within-session standard deviation averaged across subjects varied between 1.3 and 1.8 dB. Across the two sessions, the Pearson correlation coefficients, range was r = .84. There was a weak relationship between the dB SL MML and loudness, and between the MML and the THQ. A moderate correlation ( r = .44) was found between the THQ and loudness estimates. Conclusions We conclude that the dB SL MML can be a reliable estimate of tinnitus magnitude, with expected standard deviations in trained subjects of about 1.5 dB. It appears that the dB SL MML and loudness estimates are not closely related.

Comparative Responses to Squats Completed with Free Weights and an Exoskeleton

2020 ◽  
Vol 4 (1) ◽  
pp. 51-63
Author(s):  
Peter Neuhaus ◽  
Chris Jumonville ◽  
Rachel A. Perry ◽  
Roman Edwards ◽  
Jake L. Martin ◽  
...  
Keyword(s):  
Data Collection ◽  
Female Athletes ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Actual Data ◽  
Limited Data ◽  
Comparative Similarity ◽  
Insufficient Amount ◽  
Force Data ◽  
Familiarization Session

AbstractTo assess the comparative similarity of squat data collected as they wore a robotic exoskeleton, female athletes (n=14) did two exercise bouts spaced 14 days apart. Data from their exoskeleton workout was compared to a session they did with free weights. Each squat workout entailed a four-set, four-repetition paradigm with 60-second rest periods. Sets for each workout involved progressively heavier (22.5, 34, 45.5, 57 kg) loads. The same physiological, perceptual, and exercise performance dependent variables were measured and collected from both workouts. Per dependent variable, Pearson correlation coefficients, t-tests, and Cohen's d effect size compared the degree of similarity between values obtained from the exoskeleton and free weight workouts. Results show peak O2, heart rate, and peak force data produced the least variability. In contrast, far more inter-workout variability was noted for peak velocity, peak power, and electromyography (EMG) values. Overall, an insufficient amount of comparative similarity exists for data collected from both workouts. Due to the limited data similarity, the exoskeleton does not exhibit an acceptable degree of validity. Likely the cause for the limited similarity was due to the brief amount of familiarization subjects had to the exoskeleton prior to actual data collection. A familiarization session that accustomed subjects to squats done with the exoskeleton prior to actual data collection may have considerably improved the validity of data obtained from that device.

Leader-Member Exchange (LMX) Impact on Work-Home Interference in a South African Commuter Transport Engineering Company

2019 ◽  
Vol 43 ◽  
Author(s):  
Jan Christoff Visagie ◽  
Michael M. Jones ◽  
Herman L. Linde
Keyword(s):  
South African ◽  
Structural Equation ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Leader Member Exchange ◽  
Negative Consequences ◽  
Dyadic Relationship ◽  
Cross Sectional ◽  
Engineering Company ◽  
Member Exchange

The South African workplace is confronted with many leadership challenges, specifically those relating to the employment relationship between subordinates and their supervisors. A high-quality relationship is essential, considering the work-family spillovers employees experience. Limited research has been conducted on the potential positive and negative consequences of the leader-member exchange (LMX) dyadic relationship. In this study, we used a cross-sectional research design, and drew an employee sample (N = 120) from a commuter transport engineering company. A five-point Likert scale was employed and statistical analyses were carried out using the SAS statistical program. We calculated Pearson correlation coefficients and used structural equation modelling to test the proposed conceptual model to indicate possible correlations between the different variables. The main finding of the study was that the nature of the LMX relationship quality in the relevant company appeared to be high and positively related to work-home enrichment but negatively related to work-home conflict and role overload. The article concludes by making a number of suggestions to respond to challenges.

Enhanced context-aware recommendation using topic modeling and particle swarm optimization

2021 ◽  
pp. 1-16
Author(s):  
Ibtissem Gasmi ◽  
Mohamed Walid Azizi ◽  
Hassina Seridi-Bouchelaghem ◽  
Nabiha Azizi ◽  
Samir Brahim Belhaouari
Keyword(s):  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
State Of The Art ◽  
Weighting Function ◽  
Contextual Factors ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Pso Algorithm ◽  
Context Aware ◽  
Proposed Model

Context-Aware Recommender System (CARS) suggests more relevant services by adapting them to the user’s specific context situation. Nevertheless, the use of many contextual factors can increase data sparsity while few context parameters fail to introduce the contextual effects in recommendations. Moreover, several CARSs are based on similarity algorithms, such as cosine and Pearson correlation coefficients. These methods are not very effective in the sparse datasets. This paper presents a context-aware model to integrate contextual factors into prediction process when there are insufficient co-rated items. The proposed algorithm uses Latent Dirichlet Allocation (LDA) to learn the latent interests of users from the textual descriptions of items. Then, it integrates both the explicit contextual factors and their degree of importance in the prediction process by introducing a weighting function. Indeed, the PSO algorithm is employed to learn and optimize weights of these features. The results on the Movielens 1 M dataset show that the proposed model can achieve an F-measure of 45.51% with precision as 68.64%. Furthermore, the enhancement in MAE and RMSE can respectively reach 41.63% and 39.69% compared with the state-of-the-art techniques.

scholarly journals The patellofemoral morphology and the normal predicted value of tibial tuberosity-trochlear groove distance in the Chinese population

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhe Li ◽  
Guanzhi Liu ◽  
Run Tian ◽  
Ning Kong ◽  
Yue Li ◽  
...  
Keyword(s):  
Individual Differences ◽  
Chinese Population ◽  
Pearson Correlation ◽  
Three Dimensional ◽  
Correlation Coefficients ◽  
Tibial Tuberosity ◽  
Trochlear Groove ◽  
Lasso Regression ◽  
Cross Sectional ◽  
Anterior Posterior

Abstract Background Our objective was to obtain normal patellofemoral measurements to analyse sex and individual differences. In addition, the absolute values and indices of tibial tuberosity-trochlear groove (TT-TG) distances are still controversial in clinical application. A better method to enable precise prediction is still needed. Methods Seventy-eight knees of 78 participants without knee pathologies were included in this cross-sectional study. A CT scan was conducted for all participants and three-dimensional knee models were constructed using Mimics and SolidWorks software. We measured and analysed 19 parameters including the TT-TG distance and dimensions and shapes of the patella, femur, tibia, and trochlea. LASSO regression was used to predict the normal TT-TG distances. Results The dimensional parameters, TT-TG distance, and femoral aspect ratio of the men were significantly larger than those of women (all p values < 0.05). However, after controlling for the bias from age, height, and weight, there were no significant differences in TT-TG distances and anterior-posterior dimensions between the sexes (all p values > 0.05). The Pearson correlation coefficients between the anterior femoral offset and other indexes were consistently below 0.3, indicating no relationship or a weak relationship. Similar results were observed for the sulcus angle and the Wiberg index. Using LASSO regression, we obtained four parameters to predict the TT-TG distance (R2 = 0.5612, p < 0.01) to achieve the optimal accuracy and convenience. Conclusions Normative data of patellofemoral morphology were provided for the Chinese population. The anterior-posterior dimensions of the women were thicker than those of men for the same medial-lateral dimensions. More attention should be paid to not only sex differences but also individual differences, especially the anterior condyle and trochlea. In addition, this study provided a new method to predict TT-TG distances accurately.

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