Social Contact Rates Research Articles

Loneliness, social support, social isolation and wellbeing among working age adults with and without disability: Cross-sectional study

BackgroundLoneliness is significantly related to health and wellbeing. However, there is little information on the prevalence of loneliness among people with disability or the association between disability, loneliness and wellbeing. Objective/hypothesisFor a nationally representative sample of adults (age 16–64) with/without disability, to examine exposure to three indicators of low social connectedness (loneliness, low perceived social support, social isolation), and to evaluate the association between low social connectedness and wellbeing. To test whether disability status moderated the relationship between low social connectedness and wellbeing. MethodsSecondary analysis of data from three annual rounds of the cross-sectional English Community Life Survey (CLS) 2016–19. ResultsPeople with disability experienced loneliness, low perceived social support and social isolation at significantly higher rates than people without disability. Effect sizes were significantly greater for loneliness. Disability was associated with lower wellbeing. With one exception, low social connectedness was associated with lower wellbeing. Again, effect sizes were significantly greater for loneliness. The prevalence of loneliness was highest among adults with disability who were younger, economically inactive, living in rented or other accommodation, living alone and with low levels of access to environmental assets. There was no evidence that disability status moderated the association between exposure to low social connectedness and low wellbeing. ConclusionsLoneliness was a particularly significant driver of poor wellbeing among people with disability. The relative independence between different indicators of social connectedness suggests that interventions to reduce loneliness will need to do more than simply increase rates of social contact or social support.

Dynamics of social interactions, in the flow of information and disease spreading in social insects colonies: Effects of environmental events and spatial heterogeneity

The relationship between division of labor and individuals’ spatial behavior in social insect colonies provides a useful context to study how social interactions influence the spreading of elements (which could be information, virus or food) across distributed agent systems. In social insect colonies, spatial heterogeneity associated with variations of individual task roles, affects social contacts, and thus the way in which agent moves through social contact networks. We used an Agent Based Model (ABM) to mimic three realistic scenarios of elements’ transmission, such as information, food or pathogens, via physical contact in social insect colonies. Our model suggests that individuals within a specific task interact more with consequences that elements could potentially spread rapidly within that group, while elements spread slower between task groups. Our simulations show a strong linear relationship between the degree of spatial heterogeneity and social contact rates, and that the spreading dynamics of elements follow a modified nonlinear logistic growth model with varied transmission rates for different scenarios. Our work provides important insights on the dual-functionality of physical contacts. This dual-functionality is often driven via variations of individual spatial behavior, and can have both inhibiting and facilitating effects on elements’ transmission rates depending on environment. The results from our proposed model not only provide important insights on mechanisms that generate spatial heterogeneity, but also deepen our understanding of how social insect colonies balance the benefit and cost of physical contacts on the elements’ transmission under varied environmental conditions.

Social‐aware content dissemination through opportunistic D2D communications

AbstractLast decade has witnessed rapid development in wireless network. The traffic demand is driven by enormous application data that have high‐bandwidth requirement. From the operators perspective, device‐to‐device (D2D) communications are expected to provide an efficient way of offloading cellular traffic. Note that, in the high‐density gathering cases, the redundant traffic in the cellular infrastructure can be drastically offloaded by disseminating the duplicated content through D2D communications. According to this observation, we propose a novel social‐aware content dissemination scheme through D2D communications to effectively offload cellular traffic. We base our proposition on the inherent social aspects of user mobility, exploit three social structural metrics, namely, centrality, contact rate, and intercontact time. The contributions of this paper are two‐fold. First, we integrate the carry‐forward mechanism and multihop forwarding into our D2D content dissemination scheme to fully utilize the potential of D2D networks. Second, based on social pattern, we design a two‐stage social‐aware delay prediction scheme (SADP) to improve the D2D offloading utility gain. The two stages are decision‐making stage and content dissemination stage. Based on real trace data set, we evaluate the proposed method through opportunistic D2D communications, which utilizes the aforementioned metrics to enhance offloading performance and D2D transmission utility gain. By comparing with other two well‐known schemes, SA‐Epidemic and SA‐Prophet, it has been shown that our method is superior to them in terms of offloading ratio and message delay and can substantially enhance the content dissemination performance. Since SADP is designed based on a distributed insight, it ensures that it can be adaptive to mobile network. To that end, we also look forward to the future that SADP is a promising approach applied in the application scenario of 5G network.

Cardiovascular control is associated with pair-bond success in male prairie voles.

Social support structures reduce mortality and morbidity in humans, but the mechanisms underlying these reductions are not fully understood. The prevailing hypothesis is that social support buffers stress and reduces allostatic load, thereby increasing longevity. However, the possibility that affiliative social interactions confer health benefits independent of stress buffering is understudied. We examined autonomic function in prairie voles - arguably the premier species for modeling human social affiliation - to assess the possibility that the formation of strong social bonds alters autonomic function and contributes to health benefits. We examined cardiovascular measures in male prairie voles before and after two weeks of cohabitation with a female, during a partner preference test, and during social isolation. There were strong correlations between social contact and heart rate (HR) and heart rate variability (HRV), the latter being an index of autonomic nervous system function. Males that successfully pair-bonded with their partners displayed higher HRV prior to pairing than did unsuccessful males, suggesting higher basal parasympathetic tone in the successful males. HRV increased further still when pair-bonded males huddled quietly with their mates during the partner preference test. Non-pair-bonded males not only had lower baseline parasympathetic activity, but showed a further decrease after pairing. HR increased and HRV decreased during social isolation only in pair-bonded males. Since differences in HRV are thought to reflect the relative influences of the parasympathetic and sympathetic nervous systems on cardiac function, these results suggest that autonomic balance may contribute to social bonding and thus to its health benefits.

Efficient estimation of age-specific social contact rates between men and women

Social contact patterns reveal with whom individuals tend to socialize, and therefore to whom they transmit respiratory infections. We infer highly detailed age-specific contact rates between the sexes using a hierarchical Bayesian model that smooths while simultaneously guaranteeing the inherent reciprocity of contact rates. Application of this approach to social contact data from a large prospective survey confirms a tendency that people, especially children and adolescents, mostly contact other people of their own age and sex, and reveals that women have more contact with children than men. These findings imply different exposure patterns between the two sexes for specific age groups, which agrees with available observations.

Social Contact Patterns in an Individual-based Simulator for the Transmission of Infectious Diseases (Stride)

Individual-based models are convenient to study the spread of infectious diseases in combination with heterogeneous social mixing patterns. In this paper, we present an open-source and generic, individual-based simulator for the transmission of infectious diseases (Stride) in which social contact rates are dependent on both the context and the age of the individuals. Using a case study, we illustrate the effect of different social contact hypotheses on disease dynamics.

Influence of social contact patterns and demographic factors on influenza simulation results.

BackgroundThe demographic composition and the frequency and nature of social contacts may affect the spread of influenza virus in a population, resulting in distinct age-dependent immunity patterns. As demography and social contact rates differ strongly between European countries, this may impact infection incidence and vaccine effectiveness and thus limit the extent to which conclusions derived from observations in one country can be generalized to others. In the current study, we aimed to decipher the impact of social contact patterns and demographic factors on simulation results and, thus, to determine to what extent vaccination results can be generalized.MethodsWe simulated the transmission of four influenza strains (A(H1N1), A(H3N2), B/Victoria, B/Yamagata) in Belgium, Finland, Germany, GB, Italy, Luxembourg, Netherlands and Poland, using the simulation tool 4Flu. Individuals were connected in a dynamically evolving age-dependent contact network based on the POLYMOD study.ResultsWhen averaged over 20 years, simulation results without vaccination ranged from annually 20,984 (Germany) to 31,322 infections (Italy) per 100,000 individuals. QIV annually prevented 1758 (Poland) to 7720 infections (Germany) per 100,000. Variability of prevented cases remained high when the country-specific vaccination was replaced by unified coverage, but was reduced considerably if the same demography was used for all countries, or even more so when the same contact matrix was used.ConclusionsContact matrix and demography strongly influence the age-dependent incidence of influenza and the success of vaccination. Projecting simulation results from one country to another can, therefore, lead to erroneous results.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-016-1981-5) contains supplementary material, which is available to authorized users.

Badger (Meles meles) contact metrics in a medium-density population

Animal interactions are an important component of sociality in wildlife populations. Recent advances in technological and analytical applications have provided an unprecedented opportunity to understand individual, population and community level interactions. In this study, close-range contact rates within a medium-density badger (Meles meles) population were investigated using proximity collars. Data were available from 15 badgers, across five different social groups with 12,969 interactions recorded. All collared badgers within social groups contacted each other, with mean intra-group contact frequency 7.75±0.16 contacts/day and mean intra-group contact duration 413.70±16.45s/day. Inter-group contacts between badgers only occurred between directly adjacent social groups, at a low frequency (<1% of all contacts). Badger intra-group contacts occurred during every hour of the day and had a bimodal distribution pattern that peaked during early morning and evening. There was significant variation in contact frequency according to individual badger, month, sex and social group, independent of age and minimum daily temperature. Mean social group contact rates were not correlated with estimates of social group size. This study contributes to the growing evidence base for significant individual behaviour components within badger social group dynamics, which has implications not only for the transmission of diseases such as bovine tuberculosis but also in terms of the evolution of sociality itself within this species.

Optimal Intervention Strategies for the Spread of Obesity

The present study considers a deterministic compartmental model for obesity dynamics. The model exhibits forward bifurcation at basic reproduction number,R0=1, that is; forR0&lt;1, obesity is not sustained. However forR0&gt;1the model approaches a locally asymptotically stable endemic equilibrium. To control this epidemic and reduce the obesity at the endemic equilibrium, we considered intervention strategies for the spread of overweight and obesity, where Pontryagin’s Maximum Principle is applied. The numerical technique was used to show that there are effective control strategies that include minimizing the social contact rate with the overweight and obese population and campaigning. Numerical results indicated the effects of the two controls (prevention and education/campaigning) to be different. In societies with lower obesity, the social contact rate with the overweight and obese population plays a more prominent role in spreading obesity than lack of educational programs/campaigns. However, for societies with very high obesity burden, education/campaigning proved to be highly effective strategies. Reducing the social contact rate can result in other results such as a depression and an invasion of their individual rights. The appropriate approach to obesity is needed to lower obese societies.

Quantifying age-related rates of social contact using diaries in a rural coastal population of Kenya.

BackgroundImproved understanding and quantification of social contact patterns that govern the transmission dynamics of respiratory viral infections has utility in the design of preventative and control measures such as vaccination and social distancing. The objective of this study was to quantify an age-specific matrix of contact rates for a predominantly rural low-income population that would support transmission dynamic modeling of respiratory viruses.Methods and FindingsFrom the population register of the Kilifi Health and Demographic Surveillance System, coastal Kenya, 150 individuals per age group (<1, 1–5, 6–15, 16–19, 20–49, 50 and above, in years) were selected by stratified random sampling and requested to complete a day long paper diary of physical contacts (e.g. touch or embrace). The sample was stratified by residence (rural-to-semiurban), month (August 2011 to January 2012, spanning seasonal changes in socio-cultural activities), and day of week. Usable diary responses were obtained from 568 individuals (∼50% of expected). The mean number of contacts per person per day was 17.7 (95% CI 16.7–18.7). Infants reported the lowest contact rates (mean 13.9, 95% CI 12.1–15.7), while primary school students (6–15 years) reported the highest (mean 20.1, 95% CI 18.0–22.2). Rates of contact were higher within groups of similar age (assortative), particularly within the primary school students and adults (20–49 years). Adults and older participants (>50 years) exhibited the highest inter-generational contacts. Rural contact rates were higher than semiurban (18.8 vs 15.6, p = 0.002), with rural primary school students having twice as many assortative contacts as their semiurban peers.Conclusions and SignificanceThis is the first age-specific contact matrix to be defined for tropical Sub-Saharan Africa and has utility in age-structured models to assess the potential impact of interventions for directly transmitted respiratory infections.

Age Trends in Daily Social Contact Patterns

Research on older adults’ social integration usually focuses on time-indefinite access to social support, community involvement, and network connectedness. Little research has examined the actual amount of social contact older adults have on a typical day. The author uses nationally representative data on 92,698 adults—collected in the 2003-2009 American Time Use Surveys—to examine age-related trends in rates of everyday contact. Zero-inflated negative binomial regression analyses reveal nonlinear relationships between age and rates of social contact. Older adults have substantially lower rates of social contact than younger and middle-aged adults—especially among women. A significant portion, but not all, of the age-related variation in contact patterns is attributable to life-course factors like living arrangements. The author closes by considering several potential explanations for these trends and by urging social gerontologists to pay closer attention to the causes and consequences of microsocial contact patterns among older adults.

Types of drinkers and drinking settings: an application of a mathematical model

US college drinking data and a simple population model of alcohol consumption are used to explore the impact of social and contextual parameters on the distribution of light, moderate and heavy drinkers. Light drinkers become moderate drinkers under social influence, moderate drinkers may change environments and become heavy drinkers. We estimate the drinking reproduction number, R(d) , the average number of individual transitions from light to moderate drinking that result from the introduction of a moderate drinker in a population of light drinkers. Ways of assessing and ranking progression of drinking risks and data-driven definitions of high- and low-risk drinking environments are introduced. Uncertainty and sensitivity analyses, via a novel statistical approach, are conducted to assess R(d) variability and to analyze the role of context on drinking dynamics. Our estimates show R(d) well above the critical value of 1. R(d) estimates correlate positively with the proportion of time spent by moderate drinkers in high-risk drinking environments. R(d) is most sensitive to variations in local social mixing contact rates within low-risk environments. The parameterized model with college data suggests that high residence times of moderate drinkers in low-risk environments maintain heavy drinking. With regard to alcohol consumption in US college students, drinking places, the connectivity (traffic) between drinking venues and the strength of socialization in local environments are important determinants in transitions between light, moderate and heavy drinking as well as in long-term prediction of the drinking dynamics.

Engineering responses to pandemics

Focusing on pandemic influenza, this chapter approaches the planning for and response to such a major worldwide health event as a complex engineering systems problem. Action-oriented analysis of pandemics requires a broad inclusion of academic disciplines since no one domain can cover a significant fraction of the problem. Numerous research papers and action plans have treated pandemics as purely medical happenings, focusing on hospitals, health care professionals, creation and distribution of vaccines and anti-virals, etc. But human behavior with regard to hygiene and social distancing constitutes a first-order partial brake or control of the spread and intensity of infection. Such behavioral options are non-pharmaceutical interventions. (NPIs) The chapter employs simple mathematical models to study alternative controls of infection, addressing a well-known parameter in epidemiology, $R_{0}$, the reproductive number, defined as the mean number of new infections generated by an index case. Values of $R_{0}$ greater than 1.0 usually indicate that the infection begins with exponential growth, the generation-to-generation growth rate being $R_{0}$. $R_{0}$ is broken down into constituent parts related to the frequency and intensity of human contacts, both partially under our control. It is suggested that any numerical value for $R_{0}$ has little meaning outside the social context to which it pertains. Difference equation models are then employed to study the effects of heterogeneity of population social contact rates, the analysis showing that the disease tends to be driven by high frequency individuals. Related analyses show the futility of trying geographically to isolate the disease. Finally, the models are operated under a variety of assumptions related to social distancing and changes in hygienic behavior. The results are promising in terms of potentially reducing the total impact of the pandemic.

Information-related changes in contact patterns may trigger oscillations in the endemic prevalence of infectious diseases

It is well known that behavioral changes in contact patterns may significantly affect the spread of an epidemic outbreak. Here we focus on simple endemic models for recurrent epidemics, by modelling the social contact rate as a function of the available information on the present and the past disease prevalence. We show that social behavior change alone may trigger sustained oscillations. This indicates that human behavior might be a critical explaining factor of oscillations in time-series of endemic diseases. Finally, we briefly show how the inclusion of seasonal variations in contacts may imply chaos.

Seasonality and the dynamics of infectious diseases

Seasonal variations in temperature, rainfall and resource availability are ubiquitous and can exert strong pressures on population dynamics. Infectious diseases provide some of the best-studied examples of the role of seasonality in shaping population fluctuations. In this paper, we review examples from human and wildlife disease systems to illustrate the challenges inherent in understanding the mechanisms and impacts of seasonal environmental drivers. Empirical evidence points to several biologically distinct mechanisms by which seasonality can impact host-pathogen interactions, including seasonal changes in host social behaviour and contact rates, variation in encounters with infective stages in the environment, annual pulses of host births and deaths and changes in host immune defences. Mathematical models and field observations show that the strength and mechanisms of seasonality can alter the spread and persistence of infectious diseases, and that population-level responses can range from simple annual cycles to more complex multiyear fluctuations. From an applied perspective, understanding the timing and causes of seasonality offers important insights into how parasite-host systems operate, how and when parasite control measures should be applied, and how disease risks will respond to anthropogenic climate change and altered patterns of seasonality. Finally, by focusing on well-studied examples of infectious diseases, we hope to highlight general insights that are relevant to other ecological interactions.

Similarities in affiliation and aggression between cross-fostered rhesus macaque females and their biological mothers.

In female-bonded primate species, there is cross-generational consistency in female affiliative and aggressive behavior. This consistency could be the result of maternal effects, offspring learning, shared environment, and/or direct genetic inheritance of behavioral or psychological traits. In this study, I investigated possible similarities in affiliation and aggression between cross-fostered rhesus macaque females and their biological mothers. Ten female infants were cross-fostered at birth, and selected aspects of their affiliative and agonistic behavior over the course of their first 3 years of life were compared to the behavior of their foster and biological mothers. Average offspring rates of social contact and aggression across the 3 years, and in particular in Years 2 and 3, resembled those of their biological mothers whereas no clear behavioral similarities between offspring and foster mothers were observed at any age. Heritable variation in female social behavior may be maintained by natural selection and leads to adaptation to different socioecological niches within macque populations.

Intragroup and Intergroup Social Interactions in White-Handed Gibbons

One of the least studied aspects of the Hylobatidae is their social behavior. In the past, researchers have attributed this to a general lack of affiliative social interactions due to small group size and the hostile nature of intergroup encounters. Data collected on white-handed gibbons (Hylobates lar) in Khao Yai National Park, Thailand, indicate that gibbons engage in higher rates of social behavior than had previously been appreciated. In addition to relatively high rates of intragroup social contact, gibbons engaged in social behavior, including play and grooming, with members of neighboring groups. These findings obligate a renewed consideration of the nature and function of territoriality in primates.

Socioeconomic differences in general practice consultation rates in patients aged 65 and over: prospective cohort study

Objective: To examine socioeconomic differences in general practice consultation rates among patients aged 65 years and over.Design: Secondary analysis of data from the fourth national survey of morbidity in general...

SOCIAL INTERACTIONS IN THREE SUPPORTED EMPLOYMENT OPTIONS: A COMPARATIVE ANALYSIS

Controversy exists over the benefits that workers with severe disabilities accrue under different supported employment options. This study focused upon one benefit of supported employment: social integration. Direct observation procedures were used to assess the social interactions of 37 adults with severe disabilities in 18 employment programs representing three different supported employment contexts (individual, enclave, and work crew). Results indicated that workers employed in individual and enclave programs had significantly more contact with nondisabled persons than did members of work crews. No differences were detected in the social contact rate between disabled and nondisabled workers in individual versus enclave sites. Furthermore, few differences in type of interactions across the three different work options were revealed. Results suggest that both individual and enclave models are capable of facilitating social integration. However, characteristics of specific job sites, more so than the employment model per se, may determine whether a particular employment setting is conducive to social integration.