Background In the context of WHO's End TB strategy, there is a need to focus future control efforts on those interventions and innovations that would be most effective in accelerating declines in tuberculosis burden. Using a modelling approach to link the tuberculosis care cascade to transmission, we aimed to identify which improvements in the cascade would yield the greatest effect on incidence and mortality.Methods We engaged with national tuberculosis programmes in three country settings (India, Kenya, and Moldova) as illustrative examples of settings with a large private sector (India), a high HIV burden (Kenya), and a high burden of multidrug resistance (Moldova). We collated WHO country burden estimates, routine surveillance data, and tuberculosis prevalence surveys from 2011 (for India) and 2016 (for Kenya). Linking the tuberculosis care cascade to tuberculosis transmission using a mathematical model with Bayesian melding in each setting, we examined which cascade shortfalls would have the greatest effect on incidence and mortality, and how the cascade could be used to monitor future control efforts.Findings Modelling suggests that combined measures to strengthen the care cascade could reduce cumulative tuber culosis incidence by 38% (95% Bayesian credible intervals 27-43) in India, 31% (25-41) in Kenya, and 27% (17-41) in Moldova between 2018 and 2035. For both incidence and mortality, modelling suggests that the most important cascade losses are the proportion of patients visiting the private healthcare sector in India, missed diagnosis in health care settings in Kenya, and drug sensitivity testing in Moldova. In all settings, the most influential delay is the interval before a patient's first presentation for care. In future interventions, the proportion of individuals with tuberculosis who are on highquality treatment could offer a more robust monitoring tool than routine notifications of tuberculosis.Interpretation Linked to transmission, the care cascade can be valuable, not only for improving patient outcomes but also in identifying and monitoring programmatic priorities to reduce tuberculosis incidence and mortality.

Crimean-Congo hemorrhagic fever (CCHF) is a tick-borne viral disease that causes a fatal hemorrhagic illness in humans. This disease is asymptomatic in animals. CCHF was first confirmed in a nosocomial outbreak in 2011 in Gujarat State. Another notifiable outbreak occurred in July, 2013, in Karyana Village, Amreli district, Gujarat State. Anti-CCHF virus (CCHFV) immunoglobulin G (IgG) antibodies were detected in domestic animals from the adjoining villages of the affected area, indicating a considerable amount of positivity against domestic animals. The present serosurvey was carried out to determine the prevalence of CCHFV among bovine, sheep, and goat populations from 15 districts of Gujarat State, India. A total of 1226 serum samples from domestic animals were screened for IgG antibodies using a CCHF animal IgG enzyme-linked immunosorbent assay (ELISA) kit from the Centers for Disease Control and Prevention. Antibodies were detected in all the 15 districts surveyed; with positivity of 12.09%, 41.21%, and 33.62% in bovine, sheep, and goat respectively. This necessitates the surveillance of CCHFV IgG antibodies in animals and hemorrhagic fever cases in human.

Background Private providers dominate health care in India and provide most tuberculosis (TB) care. Yet efforts to engage private providers were viewed as unsustainably expensive. Three private provider engagement pilots were implemented in Patna, Mumbai and Mehsana in 2014 based on the recommendations in the National Strategic Plan for TB Control, 2012–17. These pilots sought to improve diagnosis and treatment of TB and increase case notifications by offering free drugs and diagnostics for patients who sought care among private providers, and monetary incentives for providers in one of the pilots. As these pilots demonstrated much higher levels of effectiveness than previously documented, we sought to understand program implementation costs and predict costs for their national scale-up. Methods and findings We developed a common cost structure across these three pilots comprising fixed and variable cost components. We conducted a retrospective, activity-based costing analysis using programmatic data and qualitative interviews with the respective program managers. We estimated the average recurring costs per TB case at different levels of program scale for the three pilots. We used these cost estimates to calculate the budget required for a national scale up of such pilots. The average cost per privately-notified TB case for Patna, Mumbai and Mehsana was estimated to be US$95, US$110 and US$50, respectively, in May 2016 when these pilots were estimated to cover 50%, 36% and 100% of the total private TB patients, respectively. For Patna and Mumbai pilots, the average cost per case at full scale, i.e. 100% coverage of private TB patients, was projected to be US$91 and US$101, respectively. In comparison, the national TB program’s budget for 2015 averages out to $150 per notified TB case. The total annual additional budget for a national scale up of these pilots was estimated to be US$267 million. Conclusions As India seeks to eliminate TB, extensive national engagement of private providers will be required. The cost per privately-notified TB case from these pilots is comparable to that already being spent by the public sector and to the projected cost per privately-notified TB case required to achieve national scale-up of these pilots. With additional funds expected to execute against national TB elimination commitments, the scale-up costs of these operationally viable and effective private provider engagement pilots are likely to be financially viable.

Setting Community based tuberculosis (TB) prevalence surveys in ten sites across India during 2006–2012 Objective To re-analyze data of recent sub-national surveys using uniform statistical methods and obtain a pooled national level estimate of prevalence of TB. Methods Individuals ≥15 years old were screened by interview for symptoms suggestive of Pulmonary TB (PTB) and history of anti-TB treatment; additional screening by chest radiography was undertaken in five sites. Two sputum specimens were examined by smear and culture among Screen-positives. Prevalence in each site was estimated after imputing missing values to correct for bias introduced by incompleteness of data. In five sites, prevalence was corrected for non-screening by radiography. Pooled prevalence of bacteriologically positive PTB was estimated using Random Effects Model after excluding data from one site. Overall prevalence of TB (all ages, all types) was estimated by adjusting for extra-pulmonary TB and Pediatric TB. Results Of 769290 individuals registered, 715989 were screened by interview and 294532 also by radiography. Sputum specimen were examined from 50 852 individuals. Estimated prevalence of smear positive, culture positive and bacteriologically positive PTB varied between 108.4–428.1, 147.9–429.8 and 170.8–528.4 per 100000 populations in different sites. Pooled estimate of prevalence of bacteriologically positive PTB was 350.0 (260.7, 439.0). Overall prevalence of TB was estimated at 300.7 (223.7–377.5) in 2009, the mid-year of surveys. Prevalence was significantly higher in rural compared to urban areas. Conclusion TB burden continues to be high in India suggesting further strengthening of TB control activities.

this varied between tools and type of exposure. Correlations between the measurement results and tool predictions also varied with tool and exposure type. Furthermore, a wide range of exposure estimates were observed when different users were asked to apply the same tools to the same scenario conditions. Conclusion Models to estimate exposure and risk are essential elements of the toolbox of occupational hygienists and risk assessors and managers. However, there is increasing evidence that performance varies between tools, type of exposure and scenario conditions. More importantly, users appear to struggle to apply the tools consistently, leading to wide ranges in estimated exposures. There is an urgent need for the development and implementation of generic quality control procedures for use of exposure tools, to reduce the large uncertainties when applying these tools, both to prevent workers from being excessively exposed and unnecessarily implementation of stringent exposure control measures.