How Long Should GPS Recording Lengths Be to Capture the Community Mobility of An Older Clinical Population? A Parkinson’s Example

Wearable global position system (GPS) technology can help those working with older populations and people living with movement disorders monitor and maintain their mobility level. Health research using GPS often employs inconsistent recording lengths due to the lack of a standard minimum GPS recording length for a clinical context. Our work aimed to recommend a GPS recording length for an older clinical population. Over 14 days, 70 older adults with Parkinson’s disease wore the wireless inertial motion unit with GPS (WIMU-GPS) during waking hours to capture daily “time outside”, “trip count”, “hotspots count” and “area size travelled”. The longest recording length accounting for weekend and weekdays was ≥7 days of ≥800 daily minutes of data (14 participants with 156, 483.9 min recorded). We compared the error rate generated when using data based on recording lengths shorter than this sample. The smallest percentage errors were observed across all outcomes, except “hotspots count”, with daily recordings ≥500 min (8.3 h). Eight recording days will capture mobility variability throughout days of the week. This study adds empirical evidence to the sensor literature on the required minimum duration of GPS recording.

Face mask mandates and risk compensation: an analysis of mobility data during the COVID-19 pandemic in Bangladesh

IntroductionConcerns have been raised about the potential for risk compensation in the context of mask mandates for mitigating the spread of COVID-19. However, the debate about the presence or absence of risk compensation for universal mandatory mask-wearing rules—especially in the context of COVID-19—is not settled yet.MethodsMobility is used as a proxy for risky behaviour before and after the mask mandates. Two sets of regressions are estimated to decipher (any) risk-compensating effect of mask mandate in Bangladesh. These include: (1) intervention regression analysis of daily activities at six types of locations, using pre-mask-mandate and post-mandate data; and (2) multiple regression analysis of daily new COVID-19 cases on daily mobility (lagged) to establish mobility as a valid proxy.Results(1) Statistically, mobility increased at all five non-residential locations, while home stays decreased after the mask mandate was issued; (2) daily mobility had a statistically significant association on daily new cases (with around 10 days of lag). Both significances were calculated at 95% confidence level.ConclusionCommunity mobility had increased (and stay at home decreased) after the mandatory mask-wearing rule, and given mobility is associated with increases in new COVID-19 cases, there is evidence of risk compensation effect of the mask mandate—at least partially—in Bangladesh.

High-Resolution Spatio-Temporal Model for County-Level COVID-19 Activity in the U.S.

We present an interpretable high-resolution spatio-temporal model to estimate COVID-19 deaths together with confirmed cases 1 week ahead of the current time, at the county level and weekly aggregated, in the United States. A notable feature of our spatio-temporal model is that it considers the (1) temporal auto- and pairwise correlation of the two local time series (confirmed cases and deaths from the COVID-19), (2) correlation between locations (propagation between counties), and (3) covariates such as local within-community mobility and social demographic factors. The within-community mobility and demographic factors, such as total population and the proportion of the elderly, are included as important predictors since they are hypothesized to be important in determining the dynamics of COVID-19. To reduce the model’s high dimensionality, we impose sparsity structures as constraints and emphasize the impact of the top 10 metropolitan areas in the nation, which we refer to (and treat within our models) as hubs in spreading the disease. Our retrospective out-of-sample county-level predictions were able to forecast the subsequently observed COVID-19 activity accurately. The proposed multivariate predictive models were designed to be highly interpretable, with clear identification and quantification of the most important factors that determine the dynamics of COVID-19. Ongoing work involves incorporating more covariates, such as education and income, to improve prediction accuracy and model interpretability.

Inflasi dan Mobilitas Masyarakat di Masa Pandemi Covid-19

This study aims to analyze the correlation between the inflation rate by expenditure group and the level of community mobility based on the location of visits in West Java during the Covid-19 pandemic. The research method used is the quantitative method through descriptive analysis and correlation analysis. This study uses secondary data from the Central Bureau of Statistics and the Google Mobility Report. The results of this study explain that the total inflation rate has a strong correlation with people's mobility to the central location of the economy. Inflation of primary commodities found in the Food, Beverage, and Tobacco group and the Housing, Electricity, and Fuel group has a weak correlation with the level of community mobility. The results of this study can be used as a basis for policymakers in the context of controlling inflation and capturing phenomena that occur related to restrictions on mobility during the Covid-19 pandemic.

Theorization the Use of Podcasts as an Alternative Medium of Da’wah and Its Impact on the Audience: The Case of Indonesia

The purpose of this research is to provide novelty in the study of communication science, especially on the role of new media, namely podcasts as a medium of da’wah, which so far has not been widely studied. Through a phenomenological approach and conducted interviews with two uploaders da’wah content of Baha’uddin Nursalim, and two active listeners, the results obtained that podcast as an alternative medium of da’wah is a message about society’s civilization towards the need for auditory media to obtain religious content is increasing. Moreover, users and listeners are considered quite active in choosing an effective medium of da’wah because podcasts provide several advantages during high community mobility and an adaptive and dominative effort to strengthen the existence of Nahdlatul Ulama organizations in the digital era.

Lessons In Customizing Virtual Communities To Meet The Needs Of Older Adults

GetSetUp started as a technology learning platform for older adults. During Covid-19 we realized that many adults not only wanted to learn technology but were eager for lifelong learning opportunities. Our specially designed technology platform offered a safe, welcoming space that fosters growth, learning, and community for older adults over 60,000 Michiganders over 60 joined in just 4 months. Case studies show how older adults can benefit from technology to feel empowered, reduce social isolation, and improve wellbeing through a job or volunteer opportunities and new friendships. Reports highlight this ongoing need for those with limited community, mobility issues, or those looking to diversify their communities. A trusted virtual community helps connect the physical world digitally to assure older adults understand processes like vaccine enrollment procedures. Virtual communities will not replace physical communities but offer research opportunities, reach more remote communities, and allow for collaboration with state and aging networks.

Association Between Dual-Task Gait and Cognitive Function in Older Adults

Community mobility involves walking with physical and cognitive challenges. In older adults (N=116; results here from initial analyses: N=29, Age=75±5 years, 51% females), we assessed gait speed and smoothness (harmonic-ratio) while walking on even and uneven surfaces, with or without an alternate alphabeting dual-task (ABC). ANOVA assessed surface and dual-task effects; Pearson correlations compared gait with global cognition and executive function composite z-scores. The four conditions (even, uneven, even-ABC and uneven-ABC) affected speed(m/s) (0.97±0.14 vs 0.90±0.15 vs 0.83±0.17 vs 0.79±0.16). Smoothness (2.19±0.48 vs 1.89±0.38 vs 1.92±0.53 vs 1.7±0.43) was affected by only surface (controlled for speed). Greater speed was associated with better global cognition(ρ=0.47 to 0.49, p<0.05) for all conditions and with better executive function for even-ABC(ρ=0.39, p=0.04) and uneven-ABC(ρ=0.40, p=0.03). Executive function was associated with smoothness during even(ρp=-0.42, p=0.03) and uneven(ρp=-0.39, p=0.04) walking. Type of walking challenge differentially affects gait quality and associations with cognitive function.

Methods and Rationale for Using GPS-Derived Objective Technologies to Examine Community Mobility in Older Adults

Objective measures of community mobility are advantageous for capturing life-space activity. In contrast to subjective, self-reported approaches, GPS-derived objective measures leverage passive, real-time data collection techniques to mitigate recall bias and minimize participant burden. We present methods to quantify community mobility among a sample of 164 community-dwelling older adults (Mean age=77.3±6.5) from a physical therapy intervention aimed at improving walking ability. We characterized community mobility using activity space metrics (e.g., standard deviation ellipse (SDE) area), timing (e.g., time outside home), and shape (e.g., SDE compactness). We will discuss challenges and solutions to generating these metrics as well as their associations with physical and cognitive performance. Time outside of home and SDE area, but not SDE compactness, were correlated with better performance on the 6-Minute Walking Test and Trail-Making Test (Part B) (ρ=.20-.23, p’s<.05). These findings will aid in understanding which community mobility measures are associated with functional capacity.

Community Mobility in Older Adults: Novel Methodologies, Risk Factors, and Interventions

Community mobility is an individual’s movement outside the home. It is essential for the completion of many instrumental activities of daily living, such as shopping and healthcare, and promotes physical function, social engagement, independent living, and quality of life. Mobility research often focuses on gait speed measured in clinical settings, a critical but not sufficient determinant of community mobility. Here we present four talks that assess community mobility and its determinants using novel methodologies to enhance our understanding of how to maintain independence in older ages. First, Andrea Rosso presents characteristics of individuals with the strongest associations between environmental walkability, as assessed by virtual audits, and walking. Second, Kyle Moored demonstrates associations of self-reported fatigability with life space among older men, independent of their physical functioning. Breanna Crane introduces GPS-based objective measures of community mobility and their associations with cognitive and physical function of older adults. Finally, Pam Dunlap presents results of a randomized clinical trial of a physical therapy intervention to improve walking in older adults on subjective and objective measures of life space. These talks will provide a better understanding of the factors related to community mobility, introduce attendees to novel methodologies in the assessment of both community mobility and risk factors associated with the loss of community mobility, and demonstrate approaches to improve community mobility in at-risk older adults. The discussant, Jana Hirsch, will provide perspectives on how these data inform our current view of community mobility and will lead a discussion with the audience.

Strategizing COVID-19 lockdowns using mobility patterns

During the COVID-19 pandemic, governments have attempted to control infections within their territories by implementing border controls and lockdowns. While large-scale quarantine has been the most successful short-term policy, the enormous costs exerted by lockdowns over long periods are unsustainable. As such, developing more flexible policies that limit transmission without requiring large-scale quarantine is an urgent priority. Here, the dynamics of dismantled community mobility structures within US society during the COVID-19 outbreak are analysed by applying the Louvain method with modularity optimization to weekly datasets of mobile device locations. Our networks are built based on individuals' movements from February to May 2020. In a multi-scale community detection process using the locations of confirmed cases, natural break points from mobility patterns as well as high risk areas for contagion are identified at three scales. Deviations from administrative boundaries were observed in detected communities, indicating that policies informed by assumptions of disease containment within administrative boundaries do not account for high risk patterns of movement across and through these boundaries. We have designed a multi-level quarantine process that takes these deviations into account based on the heterogeneity in mobility patterns. For communities with high numbers of confirmed cases, contact tracing and associated quarantine policies informed by underlying dismantled community mobility structures is of increasing importance.