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.