Dataset Information

The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities.

ABSTRACT:

Background

Social network analysis can elucidate tuberculosis transmission dynamics outside the home and may inform novel network-based case-finding strategies.

Methods

We assessed the association between social network characteristics and prevalent tuberculosis infection among residents (aged ≥15 years) of 9 rural communities in Eastern Uganda. Social contacts named during a census were used to create community-specific nonhousehold social networks. We evaluated whether social network structure and characteristics of first-degree contacts (sex, human immunodeficiency virus [HIV] status, tuberculosis infection) were associated with revalent tuberculosis infection (positive tuberculin skin test [TST] result) after adjusting for individual-level risk factors (age, sex, HIV status, tuberculosis contact, wealth, occupation, and Bacillus Calmette-Guérin [BCG] vaccination) with targeted maximum likelihood estimation.

Results

Among 3 335 residents sampled for TST, 32% had a positive TST results and 4% reported a tuberculosis contact. The social network contained 15 328 first-degree contacts. Persons with the most network centrality (top 10%) (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.1]) and the most (top 10%) male contacts (1.5 [1.3-1.9]) had a higher risk of prevalent tuberculosis, than those in the remaining 90%. People with ≥1 contact with HIV (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.6]) and ≥2 contacts with tuberculosis infection were more likely to have tuberculosis themselves (2.6 [ 95% confidence interval: 2.2-2.9]).

Conclusions

Social networks with higher centrality, more men, contacts with HIV, and tuberculosis infection were positively associated with tuberculosis infection. Tuberculosis transmission within measurable social networks may explain prevalent tuberculosis not associated with a household contact. Further study on network-informed tuberculosis case finding interventions is warranted.

SUBMITTER: Marquez C

PROVIDER: S-EPMC10169405 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities.

Marquez Carina C Chen Yiqun Y Atukunda Mucunguzi M Chamie Gabriel G Balzer Laura B LB Kironde Joel J Ssemmondo Emmanuel E Mwangwa Florence F Kabami Jane J Owaraganise Asiphas A Kakande Elijah E Abbott Rachel R Ssekyanzi Bob B Koss Catherine C Kamya Moses R MR Charlebois Edwin D ED Havlir Diane V DV Petersen Maya L ML

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 20230201 3

<h4>Background</h4>Social network analysis can elucidate tuberculosis transmission dynamics outside the home and may inform novel network-based case-finding strategies.<h4>Methods</h4>We assessed the association between social network characteristics and prevalent tuberculosis infection among residents (aged ≥15 years) of 9 rural communities in Eastern Uganda. Social contacts named during a census were used to create community-specific nonhousehold social networks. We evaluated whether social ne ...[more]

PMID: 35982635

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Project description:ObjectivesIn this exploratory study we examined the associations between several social network characteristics and lifestyle behaviours in adults at increased risk of diabetes and cardiovascular diseases. In addition, we explored whether similarities in lifestyle between individuals and their network members, or the level of social support perceived by these individuals, could explain these associations.MethodsFrom the control group of the Hoorn Prevention Study, participants with high and low educational attainment were approached for a structured interview between April and August 2010. Inclusion was stopped when fifty adults agreed to participate. Participants and a selection of their network members (e.g. spouses, best friends, neighbours, colleagues) completed a questionnaire on healthy lifestyle that included questions on fruit and vegetable intake, daily physical activity and leisure-time sedentary behaviour. We first examined associations between network characteristics and lifestyle using regression analyses. Second, we assessed associations between network characteristics and social support, social support and lifestyle, and compared the participants' lifestyles to those of their network members using concordance correlation coefficients.ResultsFifty adults (50/83 x 100 = 62% response) and 170 of their network members (170/192 x 100 = 89% response) participated in the study. Individuals with more close-knit relationships, more friends who live nearby, and a larger and denser network showed higher levels of vegetable consumption and physical activity, and lower levels of sedentary behaviour. Perceived social norms or perceived support for behavioural change were not related to healthy lifestyle. Except for spousal concordance for vegetable intake, the lifestyle of individuals and their network members were not alike.ConclusionsStudy results suggest that adults with a larger and denser social network have a healthier lifestyle. Underlying mechanisms for these associations should be further explored, as the current results suggest a minimal role for social support and modelling by network members.

Project description:BackgroundQuality surveillance data used to build tuberculosis (TB) transmission models are frequently unavailable and may overlook community intrinsic dynamics that impact TB transmission. Social network analysis (SNA) generates data on hyperlocal social-demographic structures that contribute to disease transmission.MethodsWe collected social contact data in five villages and built SNA-informed village-specific stochastic TB transmission models in remote Madagascar. A name-generator approach was used to elicit individual contact networks. Recruitment included confirmed TB patients, followed by snowball sampling of named contacts. Egocentric network data were aggregated into village-level networks. Network- and individual-level characteristics determining contact formation and structure were identified by fitting an exponential random graph model (ERGM), which formed the basis of the contact structure and model dynamics. Models were calibrated and used to evaluate WHO-recommended interventions and community resiliency to foreign TB introduction.ResultsInter- and intra-village SNA showed variable degrees of interconnectivity, with transitivity (individual clustering) values of 0.16, 0.29, and 0.43. Active case finding and treatment yielded 67%-79% reduction in active TB disease prevalence and a 75% reduction in TB mortality in all village networks. Following hypothetical TB elimination and without specific interventions, networks A and B showed resilience to both active and latent TB reintroduction, while Network C, the village network with the highest transitivity, lacked resiliency to reintroduction and generated a TB prevalence of 2% and a TB mortality rate of 7.3% after introduction of one new contagious infection post hypothetical elimination.ConclusionIn remote Madagascar, SNA-informed models suggest that WHO-recommended interventions reduce TB disease (active TB) prevalence and mortality while TB infection (latent TB) burden remains high. Communities' resiliency to TB introduction decreases as their interconnectivity increases. "Top down" population level TB models would most likely miss this difference between small communities. SNA bridges large-scale population-based and hyper focused community-level TB modeling.

Project description:IntroductionLoneliness has significant impacts on the health of older adults. Social networks help to improve psychosocial and quality of life outcomes among older adults. A fifth of older adults live in rural communities, where geographic isolation poses challenges to health. The dynamics of social networks of older adults in rural communities has not been explored.ObjectiveTo synthesize the literature related to loneliness and social networks of older adults in rural settings.MethodsA mixed-methods systematic review was conducted through searching six bibliographic databases to retrieve peer-reviewed literature with no time limits. We performed a methodological assessment of each study using a mixed method quality assessment tool. Findings are synthesized thematically.ResultsA total of 50 studies (32 quantitative, 15 qualitative, and 3 mixed methods) were included in this review. Studies were conducted in 17 different countries, the majority from China (n = 12), the UK (n = 9), and USA (n = 9). Findings revealed that social networks of older adults consist of family, friends and neighbors and continue to be developed through participation in various physical and social activities such as walking groups and participation in religious events. Social networks offer informational, functional, psychological and social support to older adults. Through their social networks, older adults feel socially connected and cared for. Successful interventions to improve social networks and address loneliness were those developed in groups or one-on-one with the older adults. The key ingredient to the positive impact of these interventions on reducing social isolation and loneliness was the formation of a social connection and regular engagement with the older adults. However, the review did not find any explicitly reported theory or model on which these interventions are based.ConclusionThe prevalence of loneliness among older adults in rural areas needs urgent attention. Social network theory and methods can help in developing interventions to address social isolation and loneliness among older adults in rural communities.

Dataset Information

The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities.

Background

Methods

Results

Conclusions

Publications

The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities.

Similar Datasets

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