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?

3
Outline of the session

• Warming up case study
• Population under surveillance
• Reporting units
• Data transmission
• Closing case study

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
5
Malaria in primary health centre, Jalalabad,
Uttar Pradesh, India, 1988-91
1988 1988 1989 1989 1990 1990 1991 1991
Month Slides Positive Slides Positive Slides 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
Total 5473 45 6754 15 5778 14 8629 130
1227 Slides still to be examined 1227 Slides still to be examined 1227 Slides still to be examined 1227 Slides still to be examined 1227 Slides still to be examined 1227 Slides still to be examined 1227 Slides still to be examined 1227 Slides still to be examined 1227 Slides still to be examined
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
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
8
Surveillance A systematic, ongoing process

• Data collection
• Transmission
• Analysis
• Feedback
• Action

Population
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
• Indias Integrated Disease Surveillance Programme
  (IDSP) in public health care facilities

Population
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
• Indias Integrated Disease Surveillance Programme
  (IDSP) in the private sector

Population
11
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
Reporting units
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
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
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
15
Active and passive reporting

• Active reporting
• Health workers
• House visits
• Passive reporting
• All other reporting units

Reporting units
16
Routine data are reported weekly

• Email
• Electronic
• Fax
• Messenger
• Post
• Telephone

Data transmission
17
Unusual events, outbreaks, clusters are reported
immediately

• Telephone
• Fax
• E-mail
• Police wireless
• Special messenger
• Follow with written report

Data transmission
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
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
20
Case
Feedback
Reporting unit
Immediately
Outpatient register
Lab slip
Inpatient slip
Weekly
Lab register
Inpatient register
Weekly
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
22
Regular reporting in Integrated Disease
Surveillance Programme (IDSP)
Data transmission
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
24
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
• State levels
• Advanced analyses

More complex analyses
No need to wait for feedback from the upper
level All levels analyze data
Data transmission
25
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

More complex decisions
No need to wait for instructions from the
upper level All levels make decisions
Data transmission
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
27
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

28
Closure case study

• Typhoid in Galore, Himachal Pradesh
• Interesting method of data compilation

Case study
29
Cases of typhoid fever admitted to primary health
centre, Galore, Himachal Pradesh, India May-June
1991
Cases by sex, village Cases by sex, village Cases by sex, village 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
Total 52 49 101
Case study
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
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