1. Collaborator: ICMR/RMRC Mobile based Surveillance Quest using IT MoSQuIT

2. Track, monitor the status of malaria in the community Detect changes in trend, distribution of malaria in order to initiate investigative, control measures Measure the effectiveness of antimalaria programme Prevention & control Objectives

3. UN-Millenium Development Goals (MDG)‏ MOHFW National Health Programs, India National Vector Borne Disease Control Programme (NVBDCP)‏ Prevention & Control of Non Communicable Diseases Pilot Programme on Prevention and Control of Diabetes, CVD and Stroke National Programme for Prevention and Control of Deafness Universal Immuization Programme National Cancer Control Programme National Aids Control Programme National Mental Health Programme National Iodine Deficiency Disorders Control Programme National Programme for Control of Blindness Revised National TB Control Programme National Leprosy Eradication Programme National Filaria Control Programme National Tobacco Control Program Thrust on Malaria

4. Trend of Malaria Cases and Deaths 2001-2009 http://nvbdcp.gov.in/malaria3.html

5. Surveillance as per WHO is the systematic process of collection, transmission, analysis and feedback of public health data for decision-making Surveillance

6. Conventional Malaria Surveillance flow Data transfer takes 15 days to one month‏ Epidemiological Analysis takes 2-3 years

7.  Prevents delay in dissemination of data from field to decision-makers Early diagnosis reduces morbidity and mortality Early detection of epidemic situation Fast reporting, close to real time  Improves accuracy of decision making  Facilitates better treatment and care of patients Vs Mobile basedConventional Benefits

8. Flow of MoSQuIT system

9.  Statistical analysis based on Malaria indicators (Annual Blood Examination Rate, Annual Parasite Incidence, Annual Falciparum Incidence...)‏  Trend analysis based on Person, Place, Time  Outbreak analysis, Predictive analysis  Efficiency analysis to measure time-lag in various system components Data Analysis

10. Mobile based Data collection Transfer data Collect data(M1, M2)‏ Mechanism (any one is used)‏ GPRSSMSDirect load Store data (local)‏ Physical Data load (3)‏ Mobile Service provider GSM modem Data Transformation Data transfer – SMS (2)‏ Data transfer – GPRS (1)‏ Data Analysis Mobile Data validation Epidemiological studies Health worker Supervisor, Lab technician (PHC)‏ Researcher Lab result updation (M2)‏Data validation Alerts J2ME based s/w ASP.NET based Computation eng., PostgreSQL DB ASP.NET based Webservice Deployment Architecture

11. Mobile Selection Parameters  Low price  Mobile Hardware Requirement/Specifications for MoSQuIT application- Real QWERTY keypad Long Lasting Battery backup Expandable Memory Card Robust Design Wider Screen Size Bluetooth GPRS Enabled Data Cable  Software Requirement of mobile for MoSQuIT- J2me enabled Provision to enable /disable file Access Permission  Service centre availability in NE  Mobiles within the price range of Rs.10000 tested while finalizing- LG KP 500, Samsung Champ, Samsung Chat, Blackberry Curve 852, Motorokr E6, Nokia 5130, Nokia 5350, Nokia 5223, Nokia C3  Mobile satisfying all the parameters- Nokia C3

12. Case, Stock info, Slide dispatch Epidemic alert Lab report Data Transfer: GPRS, SMS, Manual Update record: Treatment info Delete record Reports: Cases, Lab, Stock Data entry (Lab)‏ Send report to HW Reports: Lab Data validation Modify/Update data Information about death of patient Reports: Stock related data, Case, Lab, Epidemiological indices, Reports: Cases,Stock, Lab, Epidemiological indices, Case analysis: Predefined queries, queries Trend, Predictive Analysis Stakeholders Master Data Entry User Registration: Rights allocation Admin: Data Back up Alerts, Login, Data Mart

13. Accredited Social Health Activists Team

14. Future Plan Key Partner: ICMR Replication in several other states Enhance to cover surveillance of more diseases (eg. Diarrhea, Tuberculosis,...) in line with nation's health programme thrust areas