Background Contact tracing data of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is used to estimate basic epidemiological parameters. Contact tracing data could also be potentially used for assessing the heterogeneity of transmission at the individual patient level. Characterization of individuals based on different levels of infectiousness could better inform the contact tracing interventions at field levels. Methods Standard social network analysis methods used for exploring infectious disease transmission dynamics was employed to analyze contact tracing data of 1959 diagnosed SARS-CoV-2 patients from a large state of India. Relational network data set with diagnosed patients as “nodes” and their epidemiological contact as “edges” was created. Directed network perspective was utilized in which directionality of infection emanated from a “source patient” towards a “target patient”. Network measures of “ degree centrality” and “betweenness centrality” were calculated to identify influential patients in the transmission of infection. Components analysis was conducted to identify patients connected as sub- groups. Descriptive statistics was used to summarise network measures and percentile ranks were used to categorize influencers. Results Out-degree centrality measures identified that of the total 1959 patients, 11.27% (221) patients have acted as a source of infection to 40.19% (787) other patients. Among these source patients, 0.65% (12) patients had a higher out-degree centrality (> = 10) and have collectively infected 37.61% (296 of 787), secondary patients. Betweenness centrality measures highlighted that 7.50% (93) patients had a non-zero betweenness (range 0.5 to 135) and thus have bridged the transmission between other patients. Network component analysis identified nineteen connected components comprising of influential patient’s which have overall accounted for 26.95% of total patients (1959) and 68.74% of epidemiological contacts in the network. Conclusions Social network analysis method for SARS-CoV-2 contact tracing data would be of use in measuring individual patient level variations in disease transmission. The network metrics identified individual patients and patient components who have disproportionately contributed to transmission. The network measures and graphical tools could complement the existing contact tracing indicators and could help improve the contact tracing activities.
Background Evidence on the extra-household contacts of TB patients who drive disease transmission is scarce. Methods We conducted a cross-sectional personal social network survey among 300 newly diagnosed index pulmonary TB patients to identify their first-degree extra-household contacts. Results A significantly higher proportion of neighbourhood (3.5; 95% CI 1.3 to 7.5), occupational (3.2; 95% CI 1.3 to 9.2) and friendship contacts (2.2; 95% CI 0.8 to 4.5) developed TB within 1 y of the index patient's diagnosis than their household contacts (0.7; 95% CI 0.3 to 1.3). Similarly, a higher proportion of extra-household contacts had TB at different time points before the index patient was diagnosed. Conclusion Extra-household contacts of TB patients could be a potential source of TB or could be at increased risk of TB.
Background Disclosure of tuberculosis (TB) status by patients is a critical step in their treatment cascade of care. There is a lack of systematic assessment of TB disclosure patterns and its positive outcomes which happens dynamically over the disease period of individual patients with their family and wider social network relations. Methods This prospective observational study was conducted in Chennai Corporation treatment units during 2019–2021. TB patients were recruited and followed-up from treatment initiation to completion. Information on disease disclosures made to different social members at different time points, and outcomes were collected and compared. Bivariate and multi variate analysis were used to identify the patients and contact characteristics predictive of TB disclosure status. Results A total of 466 TB patients were followed-up, who listed a total of 4039 family, extra familial and social network contacts of them. Maximum disclosures were made with family members (93%) and half of the relatives, occupational contacts and friendship contacts (44–58%) were disclosed within 15 days of treatment initiation. Incremental disclosures made during the 150–180 days of treatment were highest among neighbourhood contacts (12%), and was significantly different between treatment initiation and completion period. Middle aged TB patients (31 years and 46–55 years) were found less likely to disclose (AOR 0.56 and 0.46 respectively; p<0.05) and illiterates were found more likely to disclose their TB status (AOR 3.91; p<0.05). Post the disclosure, family contacts have mostly provided resource support (44.90%) and two third of all disclosed contacts have provided emotional support for TB patients (>71%). Conclusion Findings explain that family level disclosures were predominant and disclosures made to extra familial network contacts significantly increased during the latter part of treatment. Emotional support was predominantly received by TB patients from all their contacts post disclosure. Findings could inform in developing interventions to facilitate disclosure of disease status in a beneficial way for TB patients.
Individuals who consume alcohol have a higher chance of contracting tuberculosis (TB) due to their social mixing patterns. We aimed to study the social mixing patterns of TB patients who consume alcohol on a regular basis using a quantitative social network approach. In a high-TB prevalence context in India, a social network survey of 300 newly diagnosed pulmonary drug-sensitive TB patients was done. The survey found 52 (17%) male TB patients who shared alcohol on a regular basis with 106 (4%) of their first-degree social contacts. Alcohol sharing happened in 16 neighborhood venues. When compared to contacts who did not use alcohol, a higher proportion of contacts with regular alcohol use were diagnosed with TB (12.3%; 95% CI: 6.6–20.00 vs. 3.5%; 95% CI: 2.8–4.3). Social network analysis showed that the network consisting of patients and contacts was less dense and less connected (with density ratio of 0.009, and degree centrality of 1.3, and betweenness centrality of 0.5), indicating weaker transmission potential of the network. Comparatively the network consisting of patients, contacts and their alcohol sharing venues was more dense and more connected (with density ratio of 0.018, higher degree centrality of 3.1 and betweenness centrality of 154.2) indicating stronger transmission potential of the network. Regular alcohol sharing in four venues created a giant network component, that linked a higher proportion of contacts without TB (72.3%) to a higher proportion of TB patients (67.3%) and their contacts with TB (38.4%). When examined from a network perspective, the pooled TB transmission exposure of contacts with regular alcohol use grew by a factor of 10, which helped explain the unfavorable social mixing of patients and contacts with regular alcohol use.
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