Spatial heterogeneity and infection patterns on epidemic transmission disclosed by a combined contact-dependent dynamics and compartmental model.

Epidemics, such as COVID-19, have caused significant harm to human society worldwide. A better understanding of epidemic transmission dynamics can contribute to more efficient prevention and control measures. Compartmental models, which assume homogeneous mixing of the population, have been widely used in the study of epidemic transmission dynamics, while agent-based models rely on a network definition for individuals. In this study, we developed a real-scale contact-dependent dynamic (CDD) model and combined it with the traditional susceptible-exposed-infectious-recovered (SEIR) compartment model. By considering individual random movement and disease spread, our simulations using the CDD-SEIR model reveal that the distribution of agent types in the community exhibits spatial heterogeneity. The estimated basic reproduction number R0 depends on group mobility, increasing logarithmically in strongly heterogeneous cases and saturating in weakly heterogeneous conditions. Notably, R0 is approximately independent of virus virulence when group mobility is low. We also show that transmission through small amounts of long-term contact is possible due to short-term contact patterns. The dependence of R0 on environment and individual movement patterns implies that reduced contact time and vaccination policies can significantly reduce the virus transmission capacity in situations where the virus is highly transmissible (i.e., R0 is relatively large). This work provides new insights into how individual movement patterns affect virus spreading and how to protect people more efficiently.

Behavioral responses of terrestrial mammals to COVID-19 lockdowns.

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.

Mammals responded to reduced road traffic.

COVID-19 restrictions in 2020 reduced traffic worldwide and altered animal movement.

In Australian hospitals and residential aged care facilities, how do we train nursing and direct care staff to assist patients and residents to move? A national survey.

Objective Nursing workplace injuries related to staff-assisted patient/resident movement occur frequently, however, little is known about the programs that aim to prevent these injuries. The objectives of this study were to: (i) describe how Australian hospitals and residential aged care services provide manual handling training to staff and the impact of the coronavirus disease 2019 (COVID-19) pandemic on training; (ii) report issues relating to manual handling; (iii) explore the inclusion of dynamic risk assessment; and (iv) describe the barriers and potential improvements. Method Using a cross-sectional design, an online 20-min survey was distributed by email, social media, and snowballing to Australian hospitals and residential aged care services. Results Respondents were from 75 services across Australia, with a combined 73 000 staff who assist patients/residents to mobilise. Most services provide staff manual handling training on commencement (85%; n = 63/74), then annually (88% n = 65/74). Since the COVID-19 pandemic, training was less frequent, shorter in duration, and with greater online content. Respondents reported issues with staff injuries (63% n = 41), patient/resident falls (52% n = 34), and patient/resident inactivity (69% n = 45). Dynamic risk assessment was missing in part or in whole from most programs (92% n = 67/73), despite a belief that this may reduce staff injuries (93% n = 68/73), patient/resident falls (81% n = 59/73) and inactivity (92% n = 67/73). Barriers included insufficient staff and time, and improvements included giving residents a say in how they move and greater access to allied health. Conclusion Most Australian health and aged care services provide clinical staff with regular manual handling training for staff-assisted patient/resident movement, however, issues with staff injuries, as well as patient/resident falls and inactivity, remain. While there was a belief that dynamic in-the-moment risk assessment during staff-assisted patient/resident movement may improve staff and resident/patient safety, it was missing from most manual handling programs.

Body present... in teaching and health care / Corpo presente... na formação e no cuidado em saúde / Cuerpo presente... en el enseñanza y en cuidado de la salud

A pandemia da COVID-19 nos incitou a produzir uma reflexão a respeito dos conteúdos e modos de sugerir e orientar para a atividade física, haja vista ela não prevenir a infecção e, em ambientes fechados, favorecer a contaminação do vírus. De outra perspectiva, os corpos "das ruas" não se satisfazem com as instruções e respostas dos manuais e guias de atividade física. Nesse sentido, os profissionais de saúde precisam abrir os olhos, os corações e as mentes para a construção de movimentos de composição com as cidades e as lutas em defesa de todas as vidas e não se soltar ou se perder dos estudantes, potenciais cuidadores no futuro próximo. O que propomos para este ensaio é fazer pensar sobre o que nos passa enquanto docente e profissionais-pesquisadoras preocupadas e envolvidas com os processos de formação, especialmente no campo da saúde, a partir de ponderações teórico-conceituais sobre nossas experiências (AU).

The COVID-19 pandemic has prompted us to produce thought upon the content and modes of suggesting and directing physical activity, as it does not prevent infection, and, indoors, promotes contamination from the virus. From another perspective, the bodies of the "streets" are not satisfied with the instructions and answers of the manuals and physical activity guides. In this sense, health professionals need to open their eyes, hearts and minds to build compositional movements with the cities and struggles in defense of everybody's lives, holding onto and not getting lost from students, the potential carers in the near future. What we propose for this essay is to make us think about what happens to us as a professor and professionals-researches concerned and involved with the education processes, specially in the field of health, based on theoretical and conceptual considerations about our experiences (AU).

La pandemia COVID-19 nos incitó a reflexionar sobre los contenidos y formas de sugerir y orientar las actividades física, em vista de no prevenir la infección y, en ambientes cerrados, favorecer la contaminación por virus. Desde otra perspectiva, los cuerpos "de las calles" no están satisfechos con las instrucciones y respuestas de los manuales y guías de actividad física. En este sentido, los profesionales de la salud necesitan abrir los ojos, el corazón y la mente para construir movimientos de composición con ciudades y luchas en defensa de todas las vidas y no soltarse o perderse de los estudiantes, potenciales cuidadores en el futuro próximo.Lo que proponemos para este ensayo es hacernos reflexionar sobre lo que nos sucede como profesores-investigadores interesados e involucrados en los procesos de formación, especialmente en el campo de la salud, a partir de consideraciones teórico-conceptuales sobre nuestras experiencias (AU).

Reliability of the Motor Optimality Score-Revised: A study of infants at elevated likelihood for adverse neurological outcomes.

AIM: To assess the inter-assessor reliability of the Motor Optimality Score-Revised (MOS-R) when used in infants at elevated likelihood for adverse neurological outcome. METHODS: MOS-R were assessed in three groups of infants by two assessors/cohort. Infants were recruited from longitudinal projects in Sweden (infants born extremely preterm), India (infants born in low-resource communities) and the USA (infants prenatally exposed to SARS-CoV-2). Intraclass correlation coefficients (ICC) and kappa (κw) were applied. ICC of MOS-R subcategories and total scores were presented for cohorts together and separately and for age-spans: 9-12, 13-16 and 17-25-weeks post-term age. RESULTS: 252 infants were included (born extremely preterm n = 97, born in low-resource communities n = 97, prenatally SARS-CoV-2 exposed n = 58). Reliability of the total MOS-R was almost perfect (ICC: 0.98-0.99) for all cohorts, together and separately. Similar result was found for age-spans (ICC: 0.98-0.99). Substantial to perfect reliability was shown for the MOS-R subcategories (κw: 0.67-1.00), with postural patterns showing the lowest value 0.67. CONCLUSION: The MOS-R can be used in high-risk populations with substantial to perfect reliability, both in regards of total/subcategory scores as well as in different age groups. However, the subcategory postural patterns as well as the clinical applicability of the MOS-R needs further study.

Clinical validation of a contactless respiration rate monitor.

Respiratory rate (RR) is an often underestimated and underreported vital sign with tremendous clinical value. As a predictor of cardiopulmonary arrest, chronic obstructive pulmonary disease (COPD) exacerbation or indicator of health state for example in COVID-19 patients, respiratory rate could be especially valuable in remote long-term patient monitoring, which is challenging to implement. Contactless devices for home use aim to overcome these challenges. In this study, the contactless Sleepiz One+ respiration monitor for home use during sleep was validated against the thoracic effort belt. The agreement of instantaneous breathing rate and breathing rate statistics between the Sleepiz One+ device and the thoracic effort belt was initially evaluated during a 20-min sleep window under controlled conditions (no body movement) on a cohort of 19 participants and secondly in a more natural setting (uncontrolled for body movement) during a whole night on a cohort of 139 participants. Excellent agreement was shown for instantaneous breathing rate to be within 3 breaths per minute (Brpm) compared to thoracic effort band with an accuracy of 100% and mean absolute error (MAE) of 0.39 Brpm for the setting controlled for movement, and an accuracy of 99.5% with a MAE of 0.48 Brpm for the whole night measurement, respectively. Excellent agreement was also achieved for the respiratory rate statistics over the whole night with absolute errors of 0.43, 0.39 and 0.67 Brpm for the 10th, 50th and 90th percentiles, respectively. Based on these results we conclude that the Sleepiz One+ can estimate instantaneous respiratory rate and its summary statistics at high accuracy in a clinical setting. Further studies are required to evaluate the performance in the home environment, however, it is expected that the performance is at similar level, as the measurement conditions for the Sleepiz One+ device are better at home than in a clinical setting.

The Factors and Relationships Influencing Forest Hiking Exercise Characteristics after COVID-19 Occurrence: At Seoul Metropolitan Area and in Hikers' 20s and 30s.

The growing interest and usage of green space during the pandemic relates to why greenery increases enjoyment of daily life and alleviates troubles arising from infectious periods. However, it is necessary to understand what reactions to the degree of COVID-19's spread were expressed in hiking exercise characteristics (hiking frequency, actual movement distance, average speed, total exercise time). To understand the progress of forest usage behavior during the pandemic, we analyzed factors influencing hiking exercise characteristics and relationships between those factors and hiking exercise characteristics. Hiking record data were obtained (2019-2020) from the workout app "Tranggle" pertaining to hikers in their 20s and 30s who visited the 13 mountains in the Seoul Metropolitan Area most frequently. The differences in hiking exercise characteristics (2019 data subtracted from 2020) were linked with factor data that could be related to them, including the degree of COVID-19's spread (Rt). To explore relationships between hiking exercise characteristics and factors, we developed four models with a linear mixed model. We found that Rt, week, weekdays/weekends, and PM10 contributed to explaining the hiking exercise characteristics' differences. As a result of this analysis, the degree of COVID-19's spread (Rt) affected hiking frequency; the week affected hiking frequency and actual movement distance; weekdays or weekends affected hiking frequency, actual movement distance, average speed, and total exercise time; and PM10 affected hiking frequency. These findings indicate that hiking was an alternative way for those looking for a new strategy to replace lost opportunities for physical activity. Therefore, we conclude that it is necessary to induce the usage of green space so that many people can take advantage of the functions and benefits of greenery, which stood out during the pandemic era.

Fitness Movement Types and Completeness Detection Using a Transfer-Learning-Based Deep Neural Network.

Fitness is important in people's lives. Good fitness habits can improve cardiopulmonary capacity, increase concentration, prevent obesity, and effectively reduce the risk of death. Home fitness does not require large equipment but uses dumbbells, yoga mats, and horizontal bars to complete fitness exercises and can effectively avoid contact with people, so it is deeply loved by people. People who work out at home use social media to obtain fitness knowledge, but learning ability is limited. Incomplete fitness is likely to lead to injury, and a cheap, timely, and accurate fitness detection system can reduce the risk of fitness injuries and can effectively improve people's fitness awareness. In the past, many studies have engaged in the detection of fitness movements, among which the detection of fitness movements based on wearable devices, body nodes, and image deep learning has achieved better performance. However, a wearable device cannot detect a variety of fitness movements, may hinder the exercise of the fitness user, and has a high cost. Both body-node-based and image-deep-learning-based methods have lower costs, but each has some drawbacks. Therefore, this paper used a method based on deep transfer learning to establish a fitness database. After that, a deep neural network was trained to detect the type and completeness of fitness movements. We used Yolov4 and Mediapipe to instantly detect fitness movements and stored the 1D fitness signal of movement to build a database. Finally, MLP was used to classify the 1D signal waveform of fitness. In the performance of the classification of fitness movement types, the mAP was 99.71%, accuracy was 98.56%, precision was 97.9%, recall was 98.56%, and the F1-score was 98.23%, which is quite a high performance. In the performance of fitness movement completeness classification, accuracy was 92.84%, precision was 92.85, recall was 92.84%, and the F1-score was 92.83%. The average FPS in detection was 17.5. Experimental results show that our method achieves higher accuracy compared to other methods.

Detecting and Visualizing Stops in Dance Training by Neural Network Based on Velocity and Acceleration.

Various genres of dance, such as Yosakoi Soran, have contributed to the health of many people and contributed to their sense of belonging to a community. However, due to the effects of COVID-19, various face-to-face activities have been restricted and group dance practice has become difficult. Hence, there is a need to facilitate remote dance practice. In this paper, we propose a system for detecting and visualizing the very important dance motions known as stops. We measure dance movements by motion capture and calculate the features of each movement based on velocity and acceleration. Using a neural network to learn motion features, the system detects stops and visualizes them using a human-like 3D model. In an experiment using dance data, the proposed method obtained highly accurate stop detection results and demonstrated its effectiveness as an information and communication technology support for remote group dance practice.

Human Movement Quality Assessment Using Sensor Technologies in Recreational and Professional Sports: A Scoping Review.

The use of sensor technology in sports facilitates the data-driven evaluation of human movement not only in terms of quantity but also in terms of quality. This scoping review presents an overview of sensor technologies and human movement quality assessments in ecologically-similar environments. We searched four online databases to identify 16 eligible articles with either recreational and/or professional athletes. A total of 50% of the studies used inertial sensor technology, 31% vision-based sensor technology. Most of the studies (69%) assessed human movement quality using either the comparison to an expert's performance, to an exercise definition or to the athletes' individual baseline performance. A total of 31% of the studies used expert-based labeling of the movements to label data. None of the included studies used a control group-based study design to investigate impact on training progress, injury prevention or behavior change. Although studies have used sensor technology for movement quality assessment, the transfer from the lab to the field in recreational and professional sports is still emerging. Hence, research would benefit from impact studies of technology-assisted training interventions including control groups as well as investigating features of human movement quality in addition to kinematic parameters.

Infants prenatally exposed to SARS-CoV-2 show the absence of fidgety movements and are at higher risk for neurological disorders: A comparative study.

Congenital viral infections are believed to damage the developing neonatal brain. However, whether neonates exposed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) show manifestations of such damage remains unclear. For neurodevelopment evaluation, general movement assessments have been shown to be effective in identifying early indicators of neurological dysfunction, including the absence of fidgety movements. This study compared the early motor repertoire by general movement assessment at three to five months of age in neonates who were or were not prenatally exposed to SARS-CoV-2 to determine whether infants prenatally exposed to SARS-CoV-2 are at risk of developing neurological disorders. Fifty-six infants, including 28 in the exposed group of mothers without vaccination who had no need for intensive care and likely had SARS-CoV-2 infection close to the time of pregnancy resolution and 28 infants in the nonexposed group, were videotaped to compare their detailed early motor repertoires, in which a motor optimality score-revised (MOS-R) was calculated using Prechtl's method by using the chi-square or Mann-Whitney U tests. In the exposed group, 3 (11%) infants showed the absence of fidgety movements with a total MOS-R<14 points, and 3 (11%) other infants showed abnormal fidgety movements. Between groups, atypical body symmetry (p = 0.009) and MOS-R values were significantly lower (Z = -3.08, p = 0.002), with a large size effect (Cohen's d = 0.97). The consequences of this new virus go beyond the health of the pregnant mother, and these consequences in some of the infants in the exposed group are likely not transitory because of the absence of fidgety movements between 3-5 months; thus, these babies are at increased risk of developing a serious neurological disorder.

Moving towards intelligent telemedicine: Computer vision measurement of human movement.

BACKGROUND: Telemedicine video consultations are rapidly increasing globally, accelerated by the COVID-19 pandemic. This presents opportunities to use computer vision technologies to augment clinician visual judgement because video cameras are so ubiquitous in personal devices and new techniques, such as DeepLabCut (DLC) can precisely measure human movement from smartphone videos. However, the accuracy of DLC to track human movements in videos obtained from laptop cameras, which have a much lower FPS, has never been investigated; this is a critical gap because patients use laptops for most telemedicine consultations. OBJECTIVES: To determine the validity and reliability of DLC applied to laptop videos to measure finger tapping, a validated test of human movement. METHOD: Sixteen adults completed finger-tapping tests at 0.5 Hz, 1 Hz, 2 Hz, 3 Hz and at maximal speed. Hand movements were recorded simultaneously by a laptop camera at 30 frames per second (FPS) and by Optotrak, a 3D motion analysis system at 250 FPS. Eight DLC neural network architectures (ResNet50, ResNet101, ResNet152, MobileNetV1, MobileNetV2, EfficientNetB0, EfficientNetB3, EfficientNetB6) were applied to the laptop video and extracted movement features were compared to the ground truth Optotrak motion tracking. RESULTS: Over 96% (529/552) of DLC measures were within +/-0.5 Hz of the Optotrak measures. At tapping frequencies >4 Hz, there was progressive decline in accuracy, attributed to motion blur associated with the laptop camera's low FPS. Computer vision methods hold potential for moving us towards intelligent telemedicine by providing human movement analysis during consultations. However, further developments are required to accurately measure the fastest movements.

Variations in Manual Dexterity in 11- and 12-Year-Old Children in the North of Spain in the SARS-CoV-2 Lockdown.

Between March and June 2019, the SARS-CoV-2 virus broke out in Spain. The lockdown in response entailed the modification of certain habits in the infant-juvenile population, such as those related to the practice of physical activity and the implications derived from it. The aim of this study was to learn the impacts that lockdown had on manual dexterity in children aged 11-12 years. METHODS: A total of 50 Spanish children aged 11-12 years (M = 11.40; SD = 0.50) participated, 33 (66%) boys and 17 (34%) girls. The Movement Assessment Battery for Children 2 (Movement ABC-2) and an ad hoc questionnaire for socio-demographic data and other relevant information were administered for the data collection. RESULTS: There are significant differences (p < 0.05) in the results for the manual dexterity variables measured by the peg turning and line drawing tests as well as by the measured, scalar and percentile dimension scores for manual dexterity between before and after the lockdown in both boys and girls. No significant differences were found in measurements related to the triangle assembly variable (p = 0.125). CONCLUSIONS: A significant negative impact of SARS-CoV-2 lockdown on manual dexterity values was evident in boys and girls aged 11-12 years.

Combination of survival movement strategies in cyclic game systems during an epidemic.

Disease outbreaks affect many ecosystems threatening species that also fight against other natural enemies. We investigate a cyclic game system with 5 species, whose organisms outcompete according to the rules of a generalised spatial rock-paper-scissors game, during an epidemic. We study the effects of behavioural movement strategies that allow individuals of one out of the species to move towards areas with a low density of disease vectors and a high concentration of enemies of their enemies. We perform a series of stochastic simulations to discover the impact of self-preservation strategies in pattern formation, calculating the species' spatial autocorrelation functions. Considering organisms with different physical and cognitive abilities, we compute the benefits of each movement tactic to reduce selection and infection risks. Our findings show that the maximum profit in terms of territorial dominance in the cyclic game is achieved if both survival movement strategies are combined, with individuals prioritising social distancing. In the case of an epidemic causing symptomatic illness, the drop in infection risk when organisms identify and avoid disease vectors does not render a rise in the species population because many refuges are disregarded, limiting the benefits of safeguarding against natural enemies. Our results may be helpful to the understanding of the behavioural strategies in ecosystems where organisms adapt to face living conditions changes.

Anthropomorphic Robotic Eyes: Structural Design and Non-Verbal Communication Effectiveness.

This paper shows the structure of a mechanical system with 9 DOFs for driving robot eyes, as well as the system's ability to produce facial expressions. It consists of three subsystems which enable the motion of the eyeballs, eyelids, and eyebrows independently to the rest of the face. Due to its structure, the mechanical system of the eyeballs is able to reproduce all of the motions human eyes are capable of, which is an important condition for the realization of binocular function of the artificial robot eyes, as well as stereovision. From a kinematic standpoint, the mechanical systems of the eyeballs, eyelids, and eyebrows are highly capable of generating the movements of the human eye. The structure of a control system is proposed with the goal of realizing the desired motion of the output links of the mechanical systems. The success of the mechanical system is also rated on how well it enables the robot to generate non-verbal emotional content, which is why an experiment was conducted. Due to this, the face of the human-like robot MARKO was used, covered with a face mask to aid in focusing the participants on the eye region. The participants evaluated the efficiency of the robot's non-verbal communication, with certain emotions achieving a high rate of recognition.

Automated assessment of hyoid movement during normal swallow using ultrasound.

BACKGROUND: The potential for using ultrasound by speech and language therapists (SLTs) as an adjunct clinical tool to assess swallowing function has received increased attention during the COVID-19 pandemic, with a recent review highlighting the need for further research on normative data, objective measurement, elicitation protocol and training. The dynamic movement of the hyoid, visible in ultrasound, is crucial in facilitating bolus transition and protection of the airway during a swallow and has shown promise as a biomarker of swallowing function. AIMS: To examine the kinematics of the hyoid during a swallow using ultrasound imaging and to relate the patterns to the different stages of a normal swallow. To evaluate the accuracy and robustness of two different automatic hyoid tracking methods relative to manual hyoid position estimation. METHODS & PROCEDURES: Ultrasound data recorded from 15 healthy participants swallowing a 10 ml water bolus delivered by cup or spoon were analysed. The movement of the hyoid was tracked using manually marked frame-to-frame positions, automated hyoid shadow tracking and deep neural net (DNN) tracking. Hyoid displacement along the horizontal image axis (HxD) was charted throughout a swallow, and the maximum horizontal displacement (HxD max) and maximum hyoid velocity (HxV max) along the same axis were automatically calculated. OUTCOMES & RESULTS: The HxD and HxV of 10 ml swallows are similar to values reported in the literature. The trajectory of the hyoid movement and its location at significant swallow event time points showed increased hyoid displacement towards the peak of the swallow. Using an interclass correlation coefficient, HxD max and HxV max values derived from the DNN tracker and shadow tracker are shown to be in high agreement and moderate agreement, respectively, when compared with values derived from manual tracking. CONCLUSIONS & IMPLICATIONS: The similarity of the hyoid tracking results using ultrasound to previous reports based on different instrumental tools supports the possibility of using hyoid movement as a measure of swallowing function in ultrasound. The use of machine learning to automatically track the hyoid movement potentially provides a reliable and efficient way to quantify swallowing function. These findings contribute towards improving the clinical utility of ultrasound as a swallowing assessment tool. Further research on both normative and clinical populations is needed to validate hyoid movement metrics as a means of differentiating normal and abnormal swallows and to verify the reliability of automatic tracking. WHAT THIS PAPER ADDS: What is already known on this subject There is growing interest in the use of ultrasound as an adjunct tool for assessing swallowing function. However, there is currently insufficient knowledge about the patterning and timing of lingual and hyoid movement in a typical swallow. We know that movement of the hyoid plays an essential role in bolus transition and airway protection. However, manual tracking of hyoid movement is time-consuming and restricts the extent of large-scale normative studies. What this study adds We show that hyoid movement can be tracked automatically, providing measurable continuous positional data. Measurements derived from this objective data are comparable with similar measures previously reported using videofluoroscopy and of the two automatic trackers assessed, the DNN approach demonstrates better robustness and higher agreement with manually derived measures. Using this kinematic data, hyoid movement can be related to different stages of swallowing. Clinical implications of this study This study contributes towards our understanding of the kinematics of a typical swallow by evaluating an automated hyoid tracking method, paving the way for future studies of typical and disordered swallow. The challenges of image acquisition highlight issues to be considered when establishing clinical protocols. The application of machine learning enhances the utility of ultrasound swallowing assessment by reducing the labour required and permitting a wider range of hyoid measurements. Further research in normative and clinical populations is facilitated by automatic data extraction allowing the validity of prospective hyoid measures in differentiating different types of swallows to be rigorously assessed.

Identifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement.

BACKGROUND: Despite commercial airlines mandating masks, there have been multiple documented events of COVID-19 superspreading on flights. Conventional models do not adequately explain superspreading patterns on flights, with infection spread wider than expected from proximity based on passenger seating. An important reason for this is that models typically do not consider the movement of passengers during the flight, boarding, or deplaning. Understanding the risks for each of these aspects could provide insight into effective mitigation measures. METHODS: We modeled infection risk from seating and fine-grained movement patterns - boarding, deplaning, and inflight movement. We estimated infection model parameters from a prior superspreading event. We validated the model and the impact of interventions using available data from three flights, including cabin layout and seat locations of infected and uninfected passengers, to suggest interventions to mitigate COVID-19 superspreading events during air travel. Specifically, we studied: 1) London to Hanoi with 201 passengers, including 13 secondary infections among passengers; 2) Singapore to Hangzhou with 321 passengers, including 12 to 14 secondary infections; 3) a non-superspreading event on a private jet in Japan with 9 passengers and no secondary infections. RESULTS: Our results show that the inclusion of passenger movement better explains the infection spread patterns than conventional models do. We also found that FFP2/N95 mask usage would have reduced infection by 95-100%, while cloth masks would have reduced it by only 40-80%. Results indicate that leaving the middle seat vacant is effective in reducing infection, and the effectiveness increases when combined with good quality masks. However, with a good mask, the risk is quite low even without the middle seats being empty. CONCLUSIONS: Our results suggest the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.

Assessment of Functional Mobility After COVID-19 in Adults Aged 50 Years or Older in the Canadian Longitudinal Study on Aging.

Importance: The association of COVID-19 not requiring hospitalization with functional mobility in community-dwelling adults above and beyond the impact of the pandemic control measures implemented in 2020 remains to be elucidated. Objective: To evaluate the association between a COVID-19 diagnosis and change in mobility and physical function of adults in Canada aged 50 years or older during the initial pandemic lockdown. Design, Setting, and Participants: This population-based cohort study used data from the Canadian Longitudinal Study on Aging (CLSA) COVID-19 study. This study was launched on April 15, 2020, and the exit questionnaires were completed between September and December 2020. Prepandemic data from the first CLSA follow-up (2015-2018) were also used. Respondents included middle-aged and older community-dwelling participants residing in Canadian provinces. Data were analyzed from February to May 2021. Exposures: The assessment for self-reported COVID-19 status was adapted from the Public Health Agency of Canada and the Centers for Disease Control and Prevention case definition available at the time of data collection; cases were classified as confirmed or probable, suspected, or non-COVID-19. Main Outcomes and Measures: Changes in mobility since the start of the COVID-19 pandemic were assessed using global rating of change in mobility scales at the COVID-19 exit questionnaire. Participant-reported new onset of difficulty in 3 physical function tasks was also examined. Results: Among 51 338 participants at baseline, 21 491 participants (41.9%) were 65 years or older and 26 155 participants (51.0%) were women and 25 183 (49.1%) were men. Of 2748 individuals with confirmed or probable or suspected COVID-19, 113 (94.2%) were not hospitalized. Individuals with confirmed or probable COVID-19 had higher odds of worsening mobility in terms of ability to engage in household activity (odds ratio [OR], 1.89; 95% CI, 1.11-3.22), physical activity (OR, 1.91; 95% CI, 1.32-2.76), and standing up after sitting in a chair (OR, 2.33; 95% CI, 1.06-5.11) compared with adults without COVID-19 during the same pandemic time period. Similar results were found for suspected COVID-19 status (eg, household activity: OR, 2.09; 95% CI, 1.82-2.41). Conclusions and Relevance: This cohort study among older adults in Canada found that receiving a COVID-19 diagnosis was significantly associated with worse mobility and functioning outcomes even in the absence of hospitalization. These findings suggest that interventions may be needed for individuals with mild to moderate COVID-19 who do not require hospitalization.

A single-agent extension of the SIR model describes the impact of mobility restrictions on the COVID-19 epidemic.

Mobility restrictions are successfully used to contain the diffusion of epidemics. In this work we explore their effect on the epidemic growth by investigating an extension of the Susceptible-Infected-Removed (SIR) model in which individual mobility is taken into account. In the model individual agents move on a chessboard with a Lévy walk and, within each square, epidemic spreading follows the standard SIR model. These simple rules allow to reproduce the sub-exponential growth of the epidemic evolution observed during the Covid-19 epidemic waves in several countries and which cannot be captured by the standard SIR model. We show that we can tune the slowing-down of the epidemic spreading by changing the dynamics of the agents from Lévy to Brownian and we investigate how the interplay among different containment strategies mitigate the epidemic spreading. Finally we demonstrate that we can reproduce the epidemic evolution of the first and second COVID-19 waves in Italy using only 3 parameters, i.e , the infection rate, the removing rate, and the mobility in the country. We provide an estimate of the peak reduction due to imposed mobility restrictions, i. e., the so-called flattening the curve effect. Although based on few ingredients, the model captures the kinetic of the epidemic waves, returning mobility values that are consistent with a lock-down intervention during the first wave and milder limitations, associated to a weaker peak reduction, during the second wave.