The Sivagangai District (Tamil Nadu, India) Deputy Director of Health Services (DDHS), Dr. Raghupathy, compared the Real-Time Biosurveillance Program (RTBP) to a comprehensive machine with multiple flavors that can give the required surveillance results with the touch of a button. Kurunegala RE (Region Epidemiologist, Sri Lanka), Dr. Hemachandra’s words were “RTBP will give a booster to surveillance in our region”.
Evaluation planning workshops took place in Karraikudi, Tamil Nadu and Kurunegala, Sri Lanka. This was to present the lessons to date and get a common consensus on the evaluation methodology. Participants were health officials and health workers (medical officers and nurses) belonging to the jurisdictions the project is being pilot tested. Besides the workshops, the researchers held meetings with health workers and officials to understand other elements towards evaluating the project.
Click to view the Indian Workshop report and Sri Lanka workshop report.
The medical officers in both countries agree that they cannot enter data while attending to 100 patients in a morning. The Real-Time Biosurveillance Program (RTBP) in India and Sri Lanka have, to date, collected 46,000+ and 76,000+ patient records since June 2009, respectively. This data comes from health facilities submitted through the m-HealthSurvey. Dr. M. Ganesan (Senior Project Officer, RTBI – Rural Technology and Business Incubator) discussed the progress of the data submission patterns and the associated shortcomings in the newly introduced process. While in India the challenge lies in getting the health workers to send data in real-time in Sri Lanka it is finding an incentive for the health workers submit reliable data. Analyst programmers: Vincy Pushpa Mary and Sheebha Ryer at RTBI are placed with the challenge of enhancing the mobile phone application: m-HealthSurvey to overcome the user induced challenges.
Prof. Artur Dubrawski (Director, Auton Lab) was able to show the workshop participants in both countries, live, real data subject to detection analysis through the T-Cube Web Interface. Although the data is quite noisy and somewhat unreliable signals of Acute Diarrheal Disease in India and Common Cold in Sri Lanka were detected, which were confirmed by Medical Officers attending the workshops. Karen Chen (Research Analyst, Auton Lab) mined the Sri Lanka Epidemiology Unit published Weekly Epidemiological Report data and exemplified propagation patterns of Dengue over a 6 month period; where the disease first started in Kandy District, then moved east to Ampara District, eventually moving south of the country at which time the disease in Kandy District seems to have been contained. Another set of analysis showed Dengue to emerge each year in the months of May (i.e. seasonal trend); however, an exceptional case of Dengue emerging in August; illustrated in presentation slides (Dubrawski, 2009).
Project came to learn of two main use cases for detection analysis that both health departments (DDHS Sivagangai and RE Kurunegala) require: 1) investigate the temporal scan and spatial scan of a suspected disease outbreak 2) regularly monitor the Group A, Group B, Sentential disease in Sri Lanka (i.e. what’s reported through H-544) and S-form and P-form diseases, part of the Integrated Disease Surveillance Program (IDSP), in India. While, the full fledged T-Cube with all functions remain available, the team at Auton Lab will reduce the present TCWI to a minimal set of functions to fit the requirements (i.e. two use cases) suggested by the health departments in Tamil Nadu and Sri Lanka; instead of going through the tedious process of setting of parameters to run the statistical methods and estimations. The process will be automated to a single push of a button.
Users of T-Cube agreed to participating in the frequent periodic on-line assessment on utilization, usability, effectiveness. Moreover, the project is interested in assessing the Receiver Operation Characteristics (ROC), Activity Monitoring Operating Characteristics (AMOC), and RECALL (commonly known as sensitivity). For this, the project will, periodically, submit a set of high probability events (disease outbreaks) detected through T-Cube to the health departments. They will tell us whether those alerts were true or false, as well as tell us those events that were not detected by T-Cube.
The Sahana Messaging/Alerting Module with CAP messaging was presented. In an alert message, the Medical Officers in Tamil Nadu want to know the disease name, effective date, when, where, and what to do. This would transforms to receiving the Common Alerting Protocol (CAP) elements: info.event, info.description (disease names), info.effective, info.onset, area.area description, via SMS. However, the full CAP message will be posted on the web and the xml file emailed as an attachment with the short CAP message in the body. The users are interested in both upstream and downstream alerting.