ORTEGA: An object-oriented time-geographic analytical approach to trace space-time contact patterns in movement data

Understanding the effectiveness of infection control methods in reducing and preventing SARS-CoV-2 transmission in healthcare settings is of high importance. We sequenced SARS-CoV-2 genomes for patients and healthcare workers (HCWs) across multiple geographically distinct UK hospitals, obtaining 173 high-quality SARS-CoV-2 genomes. We integrated patient movement and staff location data into the analysis of viral genome data to understand spatial and temporal dynamics of SARS-CoV-2 transmission. We identified eight patient contact clusters (PCC) with significantly increased similarity in genomic variants compared to non-clustered samples. Incorporation of HCW location further increased the number of individuals within PCCs and identified additional links in SARS-CoV-2 transmission pathways. Patients within PCCs carried viruses more genetically identical to HCWs in the same ward location. SARS-CoV-2 genome sequencing integrated with patient and HCW movement data increases identification of outbreak clusters. This dynamic approach can support infection control management strategies within the healthcare setting.

Attachment is central to the development of children’s regulatory processes. It has been associated with developmental and psychiatric health across the life span, especially emotional and behavioral regulation of negative affect when stressed (Schore, 2001; Schore and Schore, 2008). Assessment of attachment patterns provides a critical frame for understanding emerging developmental competencies and formulating treatment and intervention. Play-based attachment assessments provide access to representational models of attachment, which are regarded in attachment theory as the central organizing mechanisms associated with stability or change (Bowlby, 1969/1982; Bretherton and Munholland, 2008). The Attachment Doll Play Assessment (ADPA, George and Solomon, 1990–2016; Solomon et al., 1995) is a prominent established representational attachment measure for children aged early latency through childhood. This study examines the predictive validity of the ADPA to caregiving accessibility and responsiveness assessed from mother-child interaction and maternal representation. Sixty nine mothers and their 5–7-year-old children participated in this study. Mother-child interaction was observed during a pre-separation dyadic interaction task. Caregiving representations were rated from the Caregiving Interview (George and Solomon, 1988/1993/2005/2007). Child security with mother was associated with positive dyadic interaction and flexibly integrated maternal caregiving representations. Child controlling/disorganized attachments were significantly associated with problematic dyadic interaction and dysregulated-helpless maternal caregiving representations. The clinical implications and the use of the ADPA in clinical and educational settings are discussed.

MARKELL, RICHARD A., and ASHER, STEVEN R. Children's Interactions in Dyads: Interpersonal Influence and Sociometric Status. CHILD DEVELOPMENT, 1984, 55, 1412-1424. The purpose of the present study was to investigate whether unpopular children exhibit a bossy interpersonal style in a problem-solving situation. Accordingly, a detailed sequential category coding system was constructed, focusing on patterns of influence among children. Sociometric measures were used to pair 44 thirdand fourth-grade children into 22 dyads. Half of the dyads contained a popular child and an average-status child. The other half contained an unpopular child and an averagestatus child. Dyads were videotaped interacting in a structured problem-solving task for 12 min. The new coding system proved reliable for describing details of interactive behavior. Analyses of interaction patterns, including a new method of data analysis based on the Mantel-Haenszel x2 procedure, revealed relatively little bossy behavior in either type of dyad. However, unpopularaverage dyads showed greater asymmetry in influence and less cohesiveness and comfort than popular-average pairs. They also exhibited more problems in following the task rules. The results are discussed in relation to theories of classroom social structure.

Interaction analysis for moving individuals in space and time can contribute to understanding urban dynamics and human social networks. Recent advancements in trajectory analytics have created methods to identify and extract spatiotemporal patterns of interaction using movement tracking data. However, existing definitions and classifications of interaction between moving individuals are isolated. This research is the first attempt toward developing a taxonomy of human interaction in space and time that are observable from movement data. In the proposed framework, interaction between moving individuals is divided into four categories based on the time when it occurs and the duration of the interaction, including concurrent encounter, concurrent interaction, delayed encounter, and delayed interaction. While the duration of interaction can play a significant role in classifying human interaction, techniques to quantify the duration of interaction are limited. This article incorporates an evaluation of the time‐geographic interaction analysis method to quantify the duration of interaction between moving individuals using human‐generated GPS tracking data in California. The evaluation is a comparison between the existing time‐geographic‐based approach that mainly relies on potential path area computation and polygon intersection and the proximity‐based approach (i.e., based on the intersection of spatial and temporal buffers of two individuals) that is commonly used in digital contact tracing technologies. The results show that the time‐geographic‐based approach can measure the duration of interaction more accurately, whereas the proximity‐based approach underestimates the duration of interactions.

Characterising non-household contact patterns relevant to respiratory transmission in the USA: analysis of a cross-sectional survey

Human motion dataset is an important foundation for researches such as motion data denoising, motion editing, motion synthesis, etc. In order to support more generic studies of multimodal motion data fusion, designing and collecting a public multimodal human motion data set is an urgent problem. First, the acquisition environment is designed for precise motion data collected by sensor-based motion capture devices, rough motion data collected by body sensing devices, and local inertial data collected by inertial measurement units (IMU). Then, temporal synchronization among equipment is applied based on network time protocol (NTP) and spatial synchronization is applied among multi modal data. A full body motion dataset named HFUT-MMD is captured, which contains 6 971 568 frames in 6 types from 12 actors/actresses. The experimental results on the HFUT-MMD dataset using the existing algorithm show that the low precision motion data can be optimized to obtain the motion data similar to the accurate motion data, which corroborates the consistency between the modal data.

The motion capture technique is gathering more and more attention because of its powerful potential for providing life-like motions in computer graphics (CG) animation via sample-based motion creating techniques. Since motion data is multi-dimensional and spatio-temporal data that is difficult to edit as desired, an effective scheme for reusing captured motion sets to create new motion is advantageous. Reusing a motion data set requires effective browsing and extraction techniques that enable the user to look up and capture the relations among the motion contents in the motion data set. We propose a new framework for a motion editing tool by focusing on the connectivity between motions and utilizing it as a filter to extract the desired motion contents from a motion database. The proposed system uses a tree structure for expressing possible connective motion paths in the motion database. The motion connective tree can be a useful user interface to browse and select a motion scenario by exploring the existing motion data sets in the database. Our prototype system demonstrates an easy-to-understand interface to explore and quickly edit a motion data set by selecting icons of the motion tree nodes.

Background:Contact plays a critical role in infectious disease transmission. Characterizing heterogeneity in contact patterns across individuals, time, and space is necessary to inform accurate estimates of transmission risk, particularly to explain superspreading, predict age differences in vulnerability, and inform social distancing policies. Current respiratory disease models often rely on data from the 2008 POLYMOD study conducted in Europe, which is now outdated and potentially unrepresentative of behavior in the US. We seek to understand the variation in contact patterns across time, spatial scales, and demographic and social classifications, and what social behavior looks like at baseline in the absence of an ongoing pandemic.Methods:We analyze spatiotemporal non-household contact patterns across 10.7 million survey responses from June 2020 - April 2021 post-stratified on age and gender to correct for sample representation. To characterize spatiotemporal heterogeneity in respiratory contact patterns at the county-week scale, we use generalized additive models. In the absence of non-pandemic US contact data, we employ a regression approach to estimate baseline contact and address this gap.Findings:Although contact patterns varied over time during the pandemic, contact is relatively stable after controlling for disease. We find that the mean number of non-household contacts is spatially heterogeneous regardless of disease. There is additional heterogeneity across age, gender, race/ethnicity, and contact setting, with mean contact decreasing with age and lower in women. The contacts of White individuals and contacts at work or social events change the most under increased national incidence.Interpretation:We develop the first county-level estimates of non-pandemic contact rates for the US that can fill critical gaps in parameterizing future disease models. Our results identify that spatiotemporal, demographic, and social heterogeneity in contact patterns is highly structured, informing the risk landscape of respiratory infectious disease transmission in the US.

ABSTRACTIn social species, the transmission and maintenance of infectious diseases depends on the contact patterns between individuals within groups and on the interactions between groups. In southern Africa, the Cape buffalo (Syncerus caffer caffer) is a vector for many pathogens that can infect sympatric livestock. Although intra‐group contact patterns of Cape buffalo have been relatively well described, how groups interact with each other and risks for pathogen transmission remain poorly understood. We identified and compared spatial behavior and contact patterns between neighboring groups of Cape buffalo under contrasting environments: within the seasonally flooded environment of the Okavango Delta in Botswana and the semi‐arid environment of northern Kruger National Park in South Africa. We used telemetry data collected between 2007 and 2015 from 10 distinct groups. We estimated seasonal overlap and proximity between home ranges of pairwise neighboring groups, and we quantified seasonal contact patterns between these groups. We defined contact patterns within variable spatiotemporal windows compatible with the transmission of diseases carried by the Cape buffalo: bovine tuberculosis, brucellosis, and Rift Valley fever (mosquito‐borne transmission). We examined the effects of habitat and distance to water on contact location. In both study populations, neighboring buffalo groups were highly spatially segregated in the dry and rainy seasons. Inter‐group contact patterns were characterized by very few direct and short‐term indirect (within 0–2 days) contacts, lasting on average 1 hour and 2 hours, respectively. Contact patterns were generally consistent across populations and seasons, suggesting species‐specific behavior. In the drier study site, the probability of indirect and vector‐borne contacts generally decreased during the dry season with increasing distance to water. In the seasonally flooded area, only the probability of vector‐borne contact decreased with increasing distance to water. Our results highlight the importance of dry season water availability in influencing the dynamics of indirectly transmitted Cape buffalo pathogens but only in areas with low water availability. The results from this study have important implications for future modeling of pathogen dynamics in a single host, and the ecology and management of Cape buffalo at the landscape level. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.

Similar to land-based facilities, marine and offshore assets can be exposed to outbreaks of infectious diseases. This is exemplified by the recent COVID-19 outbreak which has had a significant impact on both personnel health and normal operations of the assets. The occurrence and transmission of infectious diseases on marine and offshore assets can, however, be mitigated by appropriate physical arrangements on board and having operational procedures in place. This paper addresses the former. The effectiveness of operational measures can be significantly increased if infectious diseases are considered at the asset’s design stage. ABS has identified a lack of available technical guidance regarding physical arrangements that can help make marine and offshore assets safer for crews and reduce the spread of infectious diseases, such as COVID-19. This paper presents the best practices and recommendations for physical arrangements drawn mainly from the recognized standards for land-based medical facilities and applied to marine and offshore assets. The recommendations focus on specific spaces inside the accommodation block, their number, location, layout, ventilation, and interior surfaces. Isolation cabins with their associated anterooms are proposed as the most reliable way of isolating suspected or confirmed cases of an infectious disease from the rest of the personnel on board. Negative pressure, independent exhaust system, and easy to clean surfaces that are accessible and resistant to deterioration from frequent cleaning and disinfection are effective measures in containing the transmission of infectious diseases that are spread through the air or direct and indirect contact. The paper also emphasizes the need to promote segregation of the visitors from crew and passengers by providing designated spaces for the visitors and gives recommendations on the communication equipment needed for receiving medical advice from land-based medical specialists. If properly implemented and if augmented with robust operational measures, physical arrangement measures have the potential to significantly improve the safety of the crew, passengers, and visitors, as well as minimize the negative consequences of disruptions to normal asset operations.

Human-to-human contact plays a leading role in the transmission of infectious diseases, and the contact pattern between individuals has an important influence on the intensity and trend of disease transmission. In this paper, we define regular contacts and random contacts. Then, taking the COVID-19 outbreak in Yangzhou City, China as an example, we consider age heterogeneity, household structure and two contact patterns to establish discrete dynamic models with switching between daytime and nighttime to depict the transmission mechanism of COVID-19 in population. We studied the changes in the reproduction number with different age groups and household sizes at different stages. The effects of the proportion of two contacts patterns on reproduction number were also studied. Furthermore, taking the final size, the peak value of infected individuals in community and the peak value of quarantine infected individuals and nucleic acid test positive individuals as indicators, we evaluate the impact of the number of random contacts, the duration of the free transmission stage and summer vacation on the spread of the disease. The results show that a series of prevention and control measures taken by the Chinese government in response to the epidemic situation are reasonable and effective, and the young and middle-aged adults (aged 18-59) with household size of 6 have the strongest transmission ability. In addition, the results also indicate that increasing the proportion of random contact is beneficial to the control of the infectious disease in the phase with interventions. This work enriches the content of infectious disease modeling and provides theoretical guidance for the prevention and control of follow-up major infectious diseases.

New technologies to trace infection

Benefiting from recent advantages in location-aware technologies, movement data are becoming ubiquitous. Hence, numerous research topics with respect to movement data have been undertaken. Yet, the research of dynamic interactions in movement data is still in its infancy. In this paper, we propose a hybrid approach combining the multi-temporal scale spatio-temporal network (MTSSTN) and the continuous triangular model (CTM) for exploring dynamic interactions in movement data. The approach mainly includes four steps: first, the relative trajectory calculus (RTC) is used to derive three types of interaction patterns; second, for each interaction pattern, a corresponding MTSSTN is generated; third, for each MTSSTN, the interaction intensity measures and three centrality measures (i.e., degree, betweenness and closeness) are calculated; finally, the results are visualized at multiple temporal scales using the CTM and analyzed based on the generated CTM diagrams. Based on the proposed approach, three distinctive aims can be achieved for each interaction pattern at multiple temporal scales: (1) exploring the interaction intensities between any two individuals; (2) exploring the interaction intensities among multiple individuals, and (3) exploring the importance of each individual and identifying the most important individuals. The movement data obtained from a real football match are used as a case study to validate the effectiveness of the proposed approach. The results demonstrate that the proposed approach is useful in exploring dynamic interactions in football movement data and discovering insightful information.

The dynamic, reciprocal, and bidirectional relationships in encounters between infants and their caregivers are called early interactions. Evidence shows that these interactions influence cognitive, emotional, and social development beyond the early years. While some studies have examined these interactions in dyads with infants with Down syndrome, they have mostly focused on parents in small samples. This study explores these interactions by considering parental, infant, and interaction variables. A total of 128 dyads participated, with 64 infants with Down syndrome and 64 typically developing infants, matched one-by-one by developmental age. During home visits, socio-demographic and developmental information was collected, development and dyadic interactions were assessed using standardised instruments. Descriptive analyses, MANOVAs, and ANOVAs were conducted comparing the group of dyads that included infants and toddler with Down syndrome and those with typical development. Infant and toddler gender showed significant differences and was included as a relevant factor in the analyses. Key findings include lower scores in parental sensitivity and non-directiveness in dyads with children with Down syndrome. Children with Down syndrome also showed lower scores in attention to the caregiver. Interactions with children with Down syndrome exhibited less mutuality and engagement. Significant gender-based interactions were found, showing that parents are more sensitive and less directive with girls with Down syndrome, who also show greater expression of negative affect and better attention to the caregiver. This study suggests different qualities in early interactions when a child with Down syndrome is involved. These interactions are characterised by lower sensitivity and greater directiveness, possibly in response to the lower attention towards the caregiver observed in these children. This results in less mutual interaction. The findings' alignment with previous research and implications for clinical work are discussed. Given the observed effect of the child's gender, future research should further explore this aspect.

Contact patterns as a risk factor for bovine tuberculosis infection in a free-living adult brushtail possum Trichosurus vulpecula population