Surveillance data management and transmission

1. Surveillance data management and transmission Integrated Disease Surveillance Programme (IDSP) district surveillance officers (DSO) course

2. Preliminary questions to the group • Were you already involved in a data management and transmission? • If yes, what difficulties did you face? • What would you like to learn about data management and transmission? 2

3. Outline of the session • Warming up case study • Population under surveillance • Reporting units • Data transmission • Closing case study 3

4. Warming up case study • Malaria outbreak, Uttar Pradesh, India, October 1991 • Visit of a primary health centre: • Do you have a problem in your centre? • “No, thank you!, We have sent our people to help the neighbouring facilities where they do have malaria” • Data collected from the malaria form • No compilation of the data • Data compiled by the visitor • Look at the table and observe Case study 4

5. Malaria in primary health centre, Jalalabad, Uttar Pradesh, India, 1988-91 5

6. Observations and some interpretations • People tend to collect more slides from August to October, each year • Collection of slides and positive slides increased in 1991 • Why did the local medical officer did not observe anything? • The medical officer did not compile the data • Failure to do so prevented the medical officer to make any comparisons Case study 6

7. Epilogue • Compiled data presented to the medical officer • Medical officer agreed that there was a problem of malaria • Unless you compile your data, you cannot detect problems • Compiling is the number one step (“Count”) • “Dividing” and “Comparing” with time, place and person analysis further transform data in information • Compile the data before you pass it on Case study 7

8. Surveillance: A systematic, ongoing process • Data collection • Transmission • Analysis • Feedback • Action Population 8

9. Surveillance in the general population • The surveillance system tries to captures events in the whole population • All health care facilities report cases • Census data may be used to: • Estimate population denominators • Calculate rates • Example: • India’s Integrated Disease Surveillance Programme (IDSP) in public health care facilities Population 9

10. Sentinel surveillance • The surveillance system only captures events in selected spots • Chosen health care facilities report cases • Sentinel sites • No population denominators may be used to calculate rates • Example: • Sentinel HIV surveillance • India’s Integrated Disease Surveillance Programme (IDSP) in the private sector Population 10

11. Reporting units for disease surveillance Reporting units 11

12. Passive surveillance • Health care facilities or providers report cases as they present in health care facilities • No specific efforts are made to make sure all cases are reported • Surveillance is integrated to routine health care delivery • Example: • Surveillance of measles in India Active versus passive surveillance 12

13. Stimulated passive surveillance • Health care facilities or providers report cases as they present in health care facilities • Special efforts made to maximize reporting • Reminders, visits • Surveillance remains integrated to routine health care delivery • Example: • Surveillance of acute flaccid paralysis in India • Stimulated surveillance during an outbreak Active versus passive surveillance 13

14. Active surveillance • The system does not wait for: • Case-patients to come to health care facilities • Health care facilities to report cases • Health care workers actively reach out to detect cases • Surveillance comes in addition to routine health care delivery • Example: • Malaria surveillance in India Active versus passive surveillance 14

15. Active and passive reporting • Active reporting • Health workers • House visits • Passive reporting • All other reporting units Reporting units 15

16. Routine data are reported weekly • Email • Electronic • Fax • Messenger • Post • Telephone Data transmission 16

17. Unusual events, outbreaks, clusters are reported immediately • Telephone • Fax • E-mail • Police wireless • Special messenger • Follow with written report Data transmission 17

18. Quality check before reporting • Filling of forms by health care workers • Review by senior staff • Transmission to the higher level • Copy kept in the facility Data transmission 18

19. Zero reporting • Do not mix up: • Zero • Missing information • Zero reporting is mandatory to confirm that the condition was looked for and not found Data transmission 19

20. Case Feedback Reporting unit Immediately Lab slip Outpatient register Inpatient slip Weekly Lab register Weekly Inpatient register Common reporting form P +ve slides + sample -ves Form L Weekly District public health laboratory District surveillance officer Computer(District)

21. Information flow of the weekly surveillance system Sub-centres Programme officers C.S.U. S.S.U. P.H.C.s C.H.C.s D.S.U. Pvt. practitioners Dist. hosp. Nursing homes Private hospitals Med. col. Private labs. P.H. lab. Other Hospitals: ESI, Municipal Rly., Army etc. Corporate hospitals 21

22. Day of the week Required activity Monday • Primary health centre reports to community health centre Tuesday • Community health centre reports to district Regular reporting in Integrated Disease Surveillance Programme (IDSP) Data transmission 22

23. Data manager at the district level • Receives data from reporting units • Enters data into computer • Checks data validity • Generates reports • Submits report to surveillance officer • Prepares a report summarizing the analysis • Submits report to state surveillance officer and state surveillance unit Data transmission 23

24. Reporting units COUNT: Compilation, Detection of thresholds District level DIVIDE: Calculation of rates COMPARE: Time, place and person analysis State levels Advanced analyses Each level analyzes data at its level More complex analyses No need to wait for feedback from the upper level : All levels analyze data Data transmission 24

25. Reporting units Investigate an outbreak District level Focus resources on an area with high incidence State levels Re-design a programme to meet changing needs Each level use the information for action at its level More complex decisions No need to wait for instructions from the upper level : All levels make decisions Data transmission 25

26. Example of decisions made on the basis of surveillance data at each level • Lower level • Outbreak investigation following a cluster detected at the periphery level • Intermediate level • Supplemental immunization campaign following persisting transmission in an area at the intermediate level • Higher level • Programme modifications because of changing epidemiology of a disease in the state Data transmission 26

27. Take home messages • Exhaustive surveillance is connected to denominators, sentinel surveillance is not • Regular, timely data transmission and nil reporting are vital to an effective surveillance system • Analyze the data as you pass it on to make the system alive at all levels 27

28. Closure case study • Typhoid in Galore, Himachal Pradesh • Interesting method of data compilation Case study 28

29. Cases of typhoid fever admitted to primary health centre, Galore, Himachal Pradesh, India May-June 1991 Case study 29

30. So where did the typhoid come from? • What is special about this compilation? • Distribution by sex • Predominance of males in one village, not in another • The data tells something: • But to hear it, you need to compile it • The outbreak was caused by drinking water served at a wedding held in Lanjiana (male and female affected) • Only male family members from the bride groom family who was from Daswin came to the wedding (Local custom) • The sex distribution gives you a clue for the cause of the outbreak Case study 30

31. Additional reading • Section 2 and 3 of IDSP operations manual • Module 5 of training manual • Format and guidelines for reporting of information on disease surveillance (electronic manual) • IDSP manual 31