Bidirectional screening for DM and TB is feasible and produces a high yield for DM among TB patients. The yield of TB among DM patients was low and needs future research using new, improved TB diagnostic tools.

We used social network analysis (SNA) to study the novel coronavirus (COVID-19) outbreak in Karnataka, India, and to assess the potential of SNA as a tool for outbreak monitoring and control. We analysed contact tracing data of 1147 COVID-19 positive cases (mean age 34.91 years, 61.99% aged 11-40, 742 males), anonymised and made public by the Karnataka government. Software tools, Cytoscape and Gephi, were used to create SNA graphics and determine network attributes of nodes (cases) and edges (directed links from source to target patients). Outdegree was 1-47 for 199 (17.35%) nodes, and betweenness, 0.5-87 for 89 (7.76%) nodes. Men had higher mean outdegree and women, higher mean betweenness. Delhi was the exogenous source of 17.44% cases. Bangalore city had the highest caseload in the state (229, 20%), but comparatively low cluster formation. Thirty-four (2.96%) 'super-spreaders' (outdegree ⩾ 5) caused 60% of the transmissions. Real-time social network visualisation can allow healthcare administrators to flag evolving hotspots and pinpoint key actors in transmission. Prioritising these areas and individuals for rigorous containment could help minimise resource outlay and potentially achieve a significant reduction in COVID-19 transmission.

Objective To estimate the burden of active infection and anti-SARS-CoV-2 IgG antibodies in Karnataka state jointly and to assess variation across geographical regions and risk groups. Methods A cross-sectional survey of 16416 people covering three risk groups was done between 3-16 September 2020 using the state of Karnataka’s infrastructure of 290 healthcare facilities across all 30 districts. Participants were further classified into risk subgroups and were sampled using stratified sampling. All participants were subjected to simultaneous detection of SARS-CoV-2 IgG using a commercial ELISA kit, SARS-CoV-2 antigen using a rapid antigen detection test (RAT), and reverse transcription-polymerase chain reaction (RT-PCR) for RNA detection. Maximum-likelihood estimation was used for joint estimation of the adjusted IgG, active, and total prevalence (either IgG or active or both), while multinomial regression identified predictors. Results Overall adjusted total prevalence of COVID-19 in Karnataka was 27.7% (95% CI: 26.1 to 29.3), IgG 16.8% (15.5 to 18.1) and active infection fraction 12.6% (11.5 to 13.8). Case-to-infection ratio 1:40, and infection fatality rate 0.05%. Influenza-like-symptoms or contact with COVID-19 positive patient are good predictors of active infection. RAT kits had higher sensitivity (68%) in symptomatics compared to 47% asymptomatic. Conclusion Our sentinel-based population survey is the first comprehensive survey to provide accurate estimates of the COVID-19 burden. Our findings provide a reasonable approximation of the population immunity threshold levels. Leveraging existing surveillance platforms, coupled with syndromic approach and sampling framework, renders our model replicable.

Background:Lymphatic Filariasis is a mosquito transmitted disease, caused by parasitic worm Wuchereria bancrofti. Global Programme for Elimination of Lymphatic Filariasis was established in early 2000. The strategy recommended by the World Health Organization is annual Mass Drug Administration (MDA) of single-dose of Diethylcarbamazine 6 mg/kg (DEC), distributed to inhabitants of Filariasis endemic areas, excluding children below 2 years of age, pregnant women, and seriously ill persons, and Morbidity Management. The health system distributes the drugs by a door-to-door strategy.Objective:To assess the coverage and compliance of MDA in Bidar district during the campaign in November 2008.Materials and Methods:Cross-sectional population-based house-to-house visit. Outcome is assessed as actual coverage and compliance, in Percentage and proportions.Results:Eight clusters, total eligible population of 1 131 individuals were interviewed. The coverage rate was 78% with variation across different areas. The compliance with drug ingestion was 68%.Conclusion:The effective coverage was below the target (85%). Side effects of DEC were minimum, the overall coverage was better in rural areas compared with urban areas.

Background: Occupational stress can impair one’s health and reduce the efficiency and productivity of work. Delivering health services in rural areas is a tedious job for healthcare workers due to various factors. Inadequate staffing of workers leading to overloaded work and many other factors make them less motivated and experience work stress. Methods: A cross sectional study done in Nelamangla, rural field practice area of BMCRI. A multi stage random sampling technique was applied for the study. 5 PHCs were randomly chosen. Healthcare workers (such as LHV, ANM, Health Assistants, ASHA workers and AWWs) were recruited by probability proportion to sample size. 140 study participants were interviewed using pre tested semi structured questionnaire to collect socio demographic details and work related details; validated professional life stress scale was used to assess stress levels. Descriptive statistics and chi square test were used. Results: 37.1% (52) had mild stress, 52.1% (73) were moderately stressed, 10.7% (15) were severely stressed and none of them were very severely stressed that needed immediate intervention. Working hours, job satisfaction, clarity about work, amount of work exceeding stipulated time, loss of interest at work, not being rewarded and valued for their work are few of the factors that are found to be associated with stress levels. Conclusions: Work related factors have been the main stressors and higher stress levels might impede the performance of the workers and hence addressing this is necessary.