Non-communicable disease care and physical activity promotion in India: analysis of recent policies, guidelines and workplans.

Burden statements on non-communicable diseases (NCDs) across the globe suggest that they pose a constant threat to human development. There are two different types of NCD interventions: population-based interventions addressing NCD risk factors and individual-based interventions addressing NCDs in the primary care setting. Most of the individual-based interventions are based on NCD-care models, as opposed to population-based interventions targeting risk factors through independent vertical programmes. We explored the relevant Indian policy documents including the recent National Health Policy 2017, to get an overview of the Indian NCD-care model and to find out how physical activity (PA) promotion stands in the year 2019 in the current policy documents on NCDs. We conducted a review with two perspectives; first to capture the NCD-care models and second to document the PA promotion and its integration in the current NCD-care model specific to the Indian context. Indian NCD programme is an evolving healthcare programme with a definite NCD-care model, where the individual-based and population-based care are thoroughly linked. Despite having good NCD-care policy and methodical planning, PA promotion seems to be lacking in the policy perspective and currently physical inactivity as a risk factor is not considered seriously. The structure of the NCD-care model should be detailed and strengthened by incorporating lessons from other successful NCD models from across the globe. Indian NCD model must provide sufficient scope of interfacing individual care to that of population-based risk factor strategies like physical activity promotion.

Monitoring data quality in syndromic surveillance: learnings from a resource limited setting.

BACKGROUND: India is in the process of integrating all disease surveillance systems with the support of a World Bank funded program called the Integrated Disease Surveillance System. In this context the objective of the study was to evaluate the components of the Orissa Multi Disease Surveillance System. MATERIALS AND METHODS: Multistage sampling was carried out, starting with four districts, followed by sequentially sampling two blocks; and in each block, two sectors and two health sub-centers were selected, all based on the best and worst performances. Two study instruments were developed for data validation, for assessing the components of the surveillance and diagnostic algorithm. The Organizational Ethics Group reviewed and approved the study. RESULTS: In all 178 study subjects participated in the survey. The case definition of suspected meningitis in disease surveillance was found to be difficult, with only 29.94%, who could be correctly identified. Syndromic diagnosis following the diagnostic algorithm was difficult for suspected malaria (28.1%), 'unusual syndrome' (28.1%), and simple diarrhea (62%). Only 17% could correctly answer questions on follow-up cases, but only 50% prioritized diseases. Our study showed that 54% cross-checked the data before compilation. Many (22%) faltered on timeliness even during emergencies. The constraints identified were logistics (56%) and telecommunication (41%). The reason for participation in surveillance was job responsibility (34.83%). CONCLUSIONS: Most of the deficiencies arose from human errors when carrying out day-to-day processes of surveillance activities, hence, should be improved by retraining. Enhanced laboratory support and electronic transmission would improve data quality and timeliness. Validity of some of the case definitions need to be rechecked. Training Programs should focus on motivating the surveillance personnel.