Surveillance data management and transmission Integrated Disease Surveillance

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

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

Outline of the session • 1. 2. 3. • Warming up case study Population under surveillance Reporting units Data transmission Closing case study 3

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 4 Case study

Malaria in primary health centre, Jalalabad, Uttar Pradesh, India, 1988 -91 1988 Month Slides 1989 Positive Slides 1990 Positive Slides 1991 Positive Slides Positive Jan 414 0 276 1 273 0 267 0 Feb 337 0 287 0 348 0 234 0 Mar 278 0 263 0 341 0 259 0 Apr 334 2 408 0 252 0 443 0 May 293 0 283 4 229 0 347 0 Jun 211 0 324 0 323 0 372 0 Jul 326 0 345 1 550 0 483 0 Aug 1009 20 1602 8 1440 5 1001 7 Sep 830 22 1492 1 941 9 2036 19 Oct 650 0 862 0 497 0 3187 * 104 Nov 438 0 333 0 289 0 Dec 353 1 279 0 295 0 5473 455 6754 15 5778 14 8629* 130 Total *1227 Slides still to be examined

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 6 Case study

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 7 Case study

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

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 9 Population

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 10 Population

Reporting units for disease surveillance Public sector (Exhaustive) Private (Sentinel) Rural • Sub-centres (SCs) • Primary health centres (PHCs) and block PHCs • Community health centres (CHCs) • Sub-district/district hospitals • Indian medicine units • Practitioners • Hospitals Urban • Dispensaries • Urban hospitals • Public health labs • ESI/Railways/Defence facilities • Medical colleges • Nursing homes • Hospitals • Medical colleges • Laboratories 11 Reporting units

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 12 Active versus passive surveillance

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 13 Active versus passive surveillance

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 14 Active versus passive surveillance

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

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

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

Quality check before reporting 1. Filling of forms by health care workers 2. Review by senior staff 3. Transmission to the higher level § Copy kept in the facility 18 Data transmission

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

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

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

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

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 23 Data transmission

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

Each level use the information for action at its level • 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 25 More complex decisions No need to wait for instructions from the upper level : All levels make decisions Data transmission

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 26 Data transmission

Take home messages 1. Exhaustive surveillance is connected to denominators, sentinel surveillance is not 2. Regular, timely data transmission and nil reporting are vital to an effective surveillance system 3. Analyze the data as you pass it on to make the system alive at all levels 27

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

Cases of typhoid fever admitted to primary health centre, Galore, Himachal Pradesh, India May-June 1991 Cases by sex, village Village Male Female Total Lanjiana 22 31 53 Daswin 17 1 18 Pahal 1 2 3 Halti 2 3 5 Ghirmani 4 0 4 5 other villages 6 12 18 52 49 101 Total 29 Case study

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 30 Case study

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