Social Contact Patterns Research Articles

Associations between ethnicity, social contact, and pneumococcal carriage three years post-PCV10 in Fiji

BackgroundPneumococcal carriage is a prerequisite for pneumococcal disease. Little is known about whether social contact frequency and intensity are associated with pneumococcal carriage. In Fiji, indigenous iTaukei have higher prevalence of pneumococcal carriage compared with Fijians of Indian Descent (FID). We hypothesised that contact differences may contribute to ethnic differences in pneumococcal carriage prevalence and density. MethodsIn 2015, young infants (5–8 weeks), toddlers (12–23 months), children (2–6 years), and caregivers from Suva and surrounding areas, participated in a cross-sectional survey (n = 2014), three years post pneumococcal conjugate vaccine introduction. Demographic and contact data, and nasopharyngeal swabs were collected. Pneumococci were detected, and quantified using quantitative real-time PCR, with molecular serotyping by microarray. Associations between ethnicity, contact, and pneumococcal carriage and density were estimated using multivariable generalised estimating equation regression models. ResultsiTaukei participants had larger household sizes, higher pneumococcal carriage rates, more contacts, and more frequent contacts of longer duration, compared with FID. The odds of vaccine-type carriage increased by 28% (95% CI 8–53%) P < 0.01 in association with physical contact with 7–14 year old children. iTaukei ethnicity was associated with vaccine-type carriage (aOR) 1.73; 95% CI 1.06–2.82, P = 0.03) and non-vaccine type carriage (aOR 5.98; 95% CI 4.47–8.00, P < 0.01). Ethnicity and contact were not associated with pneumococcal density. ConclusionsiTaukei had greater frequency and intensity of contact compared with FID. Physical contact was associated with pneumococcal carriage. Observed differences in pneumococcal nasopharyngeal carriage prevalence between iTaukei and FID were not explained by differences in social contact patterns by ethnicity.

Patterns of human social contact and contact with animals in Shanghai, China

East Asia is as a principal hotspot for emerging zoonotic infections. Understanding the likely pathways for their emergence and spread requires knowledge on human-human and human-animal contacts, but such studies are rare. We used self-completed and interviewer-completed contact diaries to quantify patterns of these contacts for 965 individuals in 2017/2018 in a high-income densely-populated area of China, Shanghai City. Interviewer-completed diaries recorded more social contacts (19.3 vs. 18.0) and longer social contact duration (35.0 vs. 29.1 hours) than self-reporting. Strong age-assortativity was observed in all age groups especially among young participants (aged 7–20) and middle aged participants (25–55 years). 17.7% of participants reported touching animals (15.3% (pets), 0.0% (poultry) and 0.1% (livestock)). Human-human contact was very frequent but contact with animals (especially poultry) was rare although associated with frequent human-human contact. Hence, this densely populated area is more likely to act as an accelerator for human-human spread but less likely to be at the source of a zoonosis outbreak. We also propose that telephone interview at the end of reporting day is a potential improvement of the design of future contact surveys.

Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors.

Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.

Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors

Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.

Epidemic threshold and ergodicity of an SIS model in switched networks

Because of individuals' random walk, such as shopping, travel, work, etc., people have different behaviors and thus have different social contact patterns. Therefore, topology of human social contact networks is time-varying. In this paper, we investigate dynamic characteristics of an SIS network epidemic model with Markovian switching. An epidemic threshold is established for the extinction and permanence of the model, which is related to the steady-state distribution of the Markov chain. An interesting result is that when the epidemic is permanent in one network but extinct in another, under network switching mechanisms, it may be either permanent or extinct depending on the steady-state distribution of the Markov chain. This reveals the important role of the Markov chain in epidemic evolution. This work shows that the epidemic propagation in switched networks is quite different from that of static networks. In addition, based on Lyapunov function method, positive recurrence and ergodicity of stochastic spreading processes are also discussed. Finally, numerical simulations are carried out to illustrate our theoretical results.

Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors

Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.

Progress on the research of social contact pattern and infectious diseases transmission

The pattern of social contact that the connection exists between people in social life tends to have certain rules. Hence, studying the laws of social contact of the population can improve the accuracy of modeling infectious diseases and provide scientific evidences for the spreading and intervention of infectious diseases transmitted by droplets or contact. This paper is a review that summarizes the current research methods of social contact pattern, the law of social contact and its significance to the spreading and prevention of infectious diseases. It finds that the survey methods of social contact mainly include direct observation, contact diaries and proximity sensors and the social contact patterns show regularities in multiple dimensions such as contact time, contact location and contact objects. Moreover, these regularities relevant to social contact patterns can apply to the mathematical model of infectious diseases and the evaluation of the effect of interventions, which provide the effective basis for the prevention and control of infectious diseases.

Social contact patterns can buffer costs of forgetting in the evolution of cooperation.

Analyses of the evolution of cooperation often rely on two simplifying assumptions: (i) individuals interact equally frequently with all social network members and (ii) they accurately remember each partner's past cooperation or defection. Here, we examine how more realistic, skewed patterns of contact-in which individuals interact primarily with only a subset of their network's members-influence cooperation. In addition, we test whether skewed contact patterns can counteract the decrease in cooperation caused by memory errors (i.e. forgetting). Finally, we compare two types of memory error that vary in whether forgotten interactions are replaced with random actions or with actions from previous encounters. We use evolutionary simulations of repeated prisoner's dilemma games that vary agents' contact patterns, forgetting rates and types of memory error. We find that highly skewed contact patterns foster cooperation and also buffer the detrimental effects of forgetting. The type of memory error used also influences cooperation rates. Our findings reveal previously neglected but important roles of contact pattern, type of memory error and the interaction of contact pattern and memory on cooperation. Although cognitive limitations may constrain the evolution of cooperation, social contact patterns can counteract some of these constraints.

Identifying human encounters that shape the transmission of Streptococcus pneumoniae and other acute respiratory infections

Although patterns of social contacts are believed to be an important determinant of infectious disease transmission, it remains unclear how the frequency and nature of human interactions shape an individual’s risk of infection. We analysed data on daily social encounters individually matched to data on S. pneumoniae carriage and acute respiratory symptoms (ARS), from 566 individuals who took part in a survey in South-West Uganda. We found that the frequency of physical (i.e. skin-to-skin), long (≥1 h) and household contacts – which capture some measure of close (i.e. relatively intimate) contact – was higher among pneumococcal carriers than non-carriers, and among people with ARS compared to those without, irrespective of their age. With each additional physical encounter the age-adjusted risk of carriage and ARS increased by 6% (95%CI 2–9%) and 7% (2–13%) respectively. In contrast, the number of casual contacts (<5 min long) was not associated with either pneumococcal carriage or ARS. A detailed analysis by age of contacts showed that the number of close contacts with young children (<5 years) was particularly higher among older children and adult carriers than non-carriers, while the higher number of contacts among people suffering from ARS was more homogeneous across contacts of all ages.Our findings provide key evidence that the frequency of close interpersonal contact is important for transmission of respiratory infections, but not that of casual contacts. Those results are essential for both improving disease prevention and control efforts as well as informing research on infectious disease dynamics and transmission models, and more studies should be undertaken to further validate our results.

Social contact patterns of infants in deciding vaccination strategy: a prospective, cross-sectional, single-centre study.

Social contact between individuals is believed to be a fundamental cause in the transmission of many respiratory tract infections. Because they have not yet been fully vaccinated, infants are at high risk for contracting whooping cough, influenza and their serious complications. Therefore, determining infant social contact patterns is an important step in protecting them from respiratory tract infection. This study included 1200 healthy infants (<12 months of age). Social contact diaries were used to estimate the frequency and nature of the infants' social contacts. This survey also gathered information regarding the infants' respiratory symptoms and their frequency of attendance at crowded places over a period of 1 week. The diary return rate was 83.8% (N = 1006), and there was a total of 4706 contacts reported for these infants. The median daily contact number per capita was 4 (range 1-18). The median number of contacts with adolescents was 0 (range 0-7). Of the infants, 50.3% had contact with non-household individuals. The mothers had the longest contacts with their babies. Contacts with school children, frequency of attendance at crowded places and age were determined to be significant effective factors for reporting respiratory symptoms. Results suggest that school-age siblings and the mothers should be primarily vaccinated, and parents should keep their babies away from crowded places for protecting their infants.

Temporal variation of human encounters and the number of locations in which they occur: a longitudinal study of Hong Kong residents.

Patterns of social contact between individuals are important for the transmission of many pathogens and shaping patterns of immunity at the population scale. To refine our understanding of how human social behaviour may change over time, we conducted a longitudinal study of Hong Kong residents. We recorded the social contact patterns for 1450 individuals, up to four times each between May 2012 and September 2013. We found individuals made contact with an average of 12.5 people within 2.9 geographical locations, and spent an average estimated total duration of 9.1 h in contact with others during a day. Distributions of the number of contacts and locations in which contacts were made were not significantly different between study waves. Encounters were assortative by age, and the age mixing pattern was broadly consistent across study waves. Fitting regression models, we examined the association of contact rates (number of contacts, total duration of contact, number of locations) with covariates and calculated the inter- and intra-participant variation in contact rates. Participant age was significantly associated with the number of contacts made, the total duration of contact and the number of locations in which contact occurred, with children and parental-age adults having the highest rates of contact. The number of contacts and contact duration increased with the number of contact locations. Intra-individual variation in contact rate was consistently greater than inter-individual variation. Despite substantial individual-level variation, remarkable consistency was observed in contact mixing at the population scale. This suggests that aggregate measures of mixing behaviour derived from cross-sectional information may be appropriate for population-scale modelling purposes, and that if more detailed models of social interactions are required for improved public health modelling, further studies are needed to understand the social processes driving intra-individual variation.

Social behaviour and gut microbiota in red-bellied lemurs (Eulemur rubriventer): In search of the role of immunity in the evolution of sociality.

Vertebrate gut microbiota form a key component of immunity and a dynamic link between an individual and the ecosystem. Microbiota might play a role in social systems as well, because microbes are transmitted during social contact and can affect host behaviour. Combining methods from behavioural and molecular research, we describe the relationship between social dynamics and gut microbiota of a group-living cooperative species of primate, the red-bellied lemur (Eulemur rubriventer). Specifically, we ask whether patterns of social contact (group membership, group size, position in social network, individual sociality) are associated with patterns of gut microbial composition (diversity and similarity) between individuals and across time. Red-bellied lemurs were found to have gut microbiota with slight temporal fluctuations and strong social group-specific composition. Contrary to expectations, individual sociality was negatively associated with gut microbial diversity. However, position within the social network predicted gut microbial composition. These results emphasize the role of the social environment in determining the microbiota of adult animals. Since social transmission of gut microbiota has the potential to enhance immunity, microbiota might have played an escalating role in the evolution of sociality.

Predicting Temporal Social Contact Patterns for Data Forwarding in Opportunistic Mobile Networks

In this paper, we predict nodes’ social contact patterns from the temporal perspective, and propose a novel approach to improve the performance of data forwarding in opportunistic mobile networks (OMNs). Specifically, considering both the average separating time and the variance of the separating time, we first introduce the definition of temporal closeness and temporal centrality. Then, several intuitive prediction methods are designed to predict nodes’ future temporal social contact patterns based on the observations from extensive real trace-driven simulation results. Afterward, based on the predicted temporal social contact patterns, we propose an efficient temporal closeness and centrality-based data forwarding strategy named TCCB for OMNs. The core idea of TCCB is to capture and utilize the temporal correlations to infer the future temporal social contact patterns in the remaining valid time of the data. Finally, extensive real trace-driven simulations are conducted to evaluate the performance of TCCB. The results show that TCCB is close to Epidemic in terms of delivery ratio but with significantly reduced delivery cost. Furthermore, TCCB performs much better than Bubble Rap and Prophet in terms of delivery ratio, but the delivery cost of TCCB is very close to that of Bubble Rap.

Seasonal variation in daily patterns of social contacts in the European badger Meles meles.

Social interactions among hosts influence the persistence and spread of infectious pathogens. Daily and seasonal variation in the frequency and type of social interactions will play an important role in disease epidemiology and, alongside other factors, may have an influence on wider disease dynamics by causing seasonal forcing of infection, especially if the seasonal variation experienced by a population is considerable. We explored temporal variation in within‐group contacts in a high‐density population of European badgers Meles meles naturally infected with Mycobacterium bovis (the causative agent of bovine tuberculosis). Summer contacts were more likely and of longer duration during the daytime, while the frequency and duration of winter contacts did not differ between day and night. In spring and autumn, within‐group contacts peaked at dawn and dusk, corresponding with when they were of shortest duration with reduced potential for aerosol transmission of pathogens. Summer and winter could be critical for transmission of M. bovis in badgers, due to the high frequency and duration of contacts during resting periods, and we discuss the links between this result and empirical disease data. This study reveals clear seasonality in daily patterns of contact frequency and duration in species living in stable social groups, suggesting that changes in social contacts could drive seasonal forcing of infection in wildlife populations even when the number of individuals interacting remains similar.

Social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong

The spread of many respiratory infections is determined by contact patterns between infectious and susceptible individuals in the population. There are no published data for quantifying social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong which is a hotspot for emerging infectious diseases due to its high population density and connectivity in the air transportation network. We adopted a commonly used diary-based design to conduct a social contact survey in Hong Kong in 2015/16 using both paper and online questionnaires. Participants using paper questionnaires reported more contacts and longer contact duration than those using online questionnaires. Participants reported 13 person-hours of contact and 8 contacts per day on average, which decreased over age but increased with household size, years of education and income level. Prolonged and frequent contacts, and contacts at home, school and work were more likely to involve physical contacts. Strong age-assortativity was observed in all age groups. We evaluated the characteristics of social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong. Our findings could help to improve the design of future social contact surveys, parameterize transmission models of respiratory infectious diseases, and inform intervention strategies based on model outputs.

Probabilistic forecasting in infectious disease epidemiology: the 13th Armitage lecture.

Routine surveillance of notifiable infectious diseases gives rise to daily or weekly counts of reported cases stratified by region and age group. From a public health perspective, forecasts of infectious disease spread are of central importance. We argue that such forecasts need to properly incorporate the attached uncertainty, so they should be probabilistic in nature. However, forecasts also need to take into account temporal dependencies inherent to communicable diseases, spatial dynamics through human travel and social contact patterns between age groups. We describe a multivariate time series model for weekly surveillance counts on norovirus gastroenteritis from the 12 city districts of Berlin, in six age groups, from week 2011/27 to week 2015/26. The following year (2015/27 to 2016/26) is used to assess the quality of the predictions. Probabilistic forecasts of the total number of cases can be derived through Monte Carlo simulation, but first and second moments are also available analytically. Final size forecasts as well as multivariate forecasts of the total number of cases by age group, by district and by week are compared across different models of varying complexity. This leads to a more general discussion of issues regarding modelling, prediction and evaluation of public health surveillance data. Copyright © 2017 John Wiley & Sons, Ltd.

An Opportunistic Push Scheme for Online Social Networking Services in Heterogeneous Wireless Networks

Article synchronization is one of the most fundamental issues in online social networking services (SNSs). In particular, when deploying multiple access networks with different transmission costs, an efficient synchronization scheme should be devised for users to enjoy SNSs in heterogeneous wireless networks. In this paper, we propose an opportunistic push scheme (OPS) that aggregates published articles, opportunistically pushing them through low-cost access networks (e.g., open Wi-Fi networks). To balance the reduced transmission costs and the increased page loading time, we formulate a Markov decision process problem that considers a mobility model based on the users’ social contact pattern. Evaluation results demonstrate that OPS with the optimal policy can reduce the number of transmissions in high-cost access networks, while satisfying users’ quality of experience in terms of the page loading time.

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.