1. Rapid Survey Method

2. Framework: Introduction History of rapid surveys Why rapid surveys?
Approaches of rapid survey methods
Cluster sampling
Lots Quality Assurance Sampling
Qualitative methods
Uses of rapid survey methods
References
Cluster analysis by using EPI6

3. INTRODUCTION Small, community-based surveys
Take 5-7 days to gather field data
2-3 weeks to analyze and prepare a final presentation and report

4. History of rapid surveys
1965- Serfling & Sherman- LOCAL immunization status of 1-4 year old children
Henderson & colleagues to provide community-based information for guiding Smallpox Eradication Program in West Africa. 
Lemeshow & Robinson were commissioned by WHO to statistically describe EPI 30 x 7 survey methodology. 
In 1991 Bennett & colleagues published a seminal article on two-stage cluster surveys which expanded on the 1989 publications by Frerichs.
1965- The notion of rapid surveys as a means to help local health departments learn of the immunization status of 1-4 year old children was first defined and explained in a publication by Serfling and Sherman.

5. Why rapid survey method?
Traditional survey methods- costly & time-consuming, usually provide information at regional or national level only.
Local program manager lacks information on local health needs
Monitoring & Evaluation tool
Low cost, Low resources in short time

6. Approaches of rapid survey method
1. Sampling methods for rapid health survey - 30 cluster sampling (30 by 7 sampling used in EPI evaluation) -Lots quality assurance sampling - Case control methodology 2. Collection, organization and presentation of aggregate-level data - Qualitative methods (FGD, In-depth interview, Key informant interview) 3. Rapid assessment of health needs in mass emergencies.

7. Cluster sampling 3o cluster sampling 30 by 7 cluster sampling method
WHOs EPI
is a two-stage cluster sample

8. Steps in 30 cluster sampling (eg 30 by 7 cluster sampling)
For sample size (c) calculation
c=p(1-p)D/s2 b
where p= proportion
b= expected no. of responses per cluster
D = Design effect= 1+(b-1)roh
Why 210 Sample size in 30 x 7?
P= 50%, 95% CI, allowable error -10%
Sample size =198,
then for each cluster= 198/30 = 6.6
= 7

9. 1. Selection of 30 cluster by PPS
Table: A cumulative list of community size
Community
Population
size
Cumulative
Population size
Selection
of cluster 1
1000 2
400
1400 3
200
1600 4
300
1900 5
1200
3100 6
4100 7
5700 8
5900 9
350
6250 10
450
6700
SI =2233
Random No.
= 1814
2nd =RN+ SI
3rd = RN+2SI .
30th =RN+29SI
1814
(1st )
4047
(2nd )
6280
(3rd)
Sampling interval = total population of community /no. of
clusters to be selected = 6700/3= 2233

10. 2. Selection of subject in each cluster
Sampling unit is individual but sampling is done at household level by Simple Random Sampling
But in 30 X 7 – out of 7, the first sample is selected by randomly, then then surveyer moves to “next household whose front door is closest”

11. Steps in 30 cluster sampling
Analysis (eg EPI)
1. Proportion
pi =y i/xi
2. Mean
3. Weighted analysis in cluster sampling
pi =Σwiyi/Σwixi
Where pi = proportion in ith community
y I = Total number of children vaccinated(y i)
xi = Total number of children whose card were examined
wi = is weight attached to ith cluster

12. Differences between the 30 by 7 cluster sample & generic cluster sample
Cluster sampling
30 by 7 cluster sampling
Clusters are selected by random method
Clusters are selected by Probability proportionate to size of population
Sampling unit is selected by simple random method from sampling frame.
Only first household in each cluster is randomly selected. Then every eligible individual in the household is selected.
Advantages:
_ Only need to obtain list of units in the selected clusters.
_ Cost-effective.
Sampling frame is not needed for selected cluster
Good for EPI methodology assumption
Disadvantages:
_ Not intended for calculation of estimates from individual clusters.
_ Less precise than simple random sample.
If “Pocket” – Bias estimation
Every individual in household – Bias
Estimates are not for cluster

13. Application of 30 cluster sampling
Used in UNICEF’s multiple Indicator cluster survey
2. National Iodine Deficiency Disorders Control Programme
3. A modified cluster-sampling method for post-disaster rapid assessment of needs

14. Lots quality assurance sampling (LQAS)
The LQAS method - type of stratified sampling
Used in manufacturing industry for quality control purposes. – Lot is “defects?” - “acceptable” or “not acceptable”
What is lot in health?
Community that is socially and geographically distinct
Health care delivery area
Health center
Health records in health center.

15. Steps of LQAS 1. Selection of Lot from sampling frame
2. Selection of sampling units
3. Sample size and critical number(decision values)
Two types of risk:
(i) Risk of accepting a “bad” lot (Type I, α error)
(ii) Risk of not accepting a “good” lot, (Type II , β Error)

16. Sample size & critical number of permissible “defect” per lot
There are two options:
1.Use of tables, where different upper and lower performance levels are shown for given type I and type II errors.
2. Use of operative characteristics curves, where the probability of acceptance of lot is plotted according to the prevalence of defect in the lot.

17. Analysis
Overall proportion of defects
Defective items in each lot

18. Special case of LQAS: 19 X 5 Divide area in 5 area
19 set of interview is done in each of 5 supervision area (SA)
Why 19?
provides an acceptable level of error for making management decisions; at least 92% of the time it correctly identifies SAs that have reached their coverage target.
Samples larger than 19 have practically the same statistical precision as 19. They do not result in better information, and they cost more.

19. Why 19? Contd…..
Good for deciding which are higher performing supervision areas to learn from
Good for deciding what are the lower performing supervision areas
Good for identifying knowledge/practices that have high coverage from those of low coverage
Good for setting priorities among supervision areas with large differences in coverage
Good for setting priorities among knowledge/practices within an SA
(if one intervention is high but the other is low, we would concentrate on the low coverage intervention)

20. Percent of women (15-49) who know 2 or more ways to prevent HIV transmission in 5 Supervision Areas?
Step 1. Defining Catchment Area and Supervision Areas

21. Selection of study subjects

22. Suppose following is data was collected.
19 by 5 LQAS contd….
Step 3: Data collection
Suppose following is data was collected.
Step 4. Analysis
Add Number Correct in all SAs: = 62
Add all Samples Sizes: = 95
Knowledge Coverage Estimate = Average Coverage = 62/95 = 65.3%
= 70%

23. Step 5. Use table to find Decision Rule11

24. Step 6. Deciding “defect”

25. Similarly we can study multiple indicators for single area.

26. Also we can study multiple indicators for 5 areas

27. Steps to decide lots from larger (>5) areas
Step 1. List communities and total population
Step 2. Calculate the cumulative population
Step 3. Calculate the sampling interval (cumulative population/19)
Step 4. Choose a random number between to sampling interval
Step 5. Beginning with the random number, use the sampling interval
to identify communities for the 19 sets of interviews.
Step 6. Selection of 19 interviewee from household.
Step 7. As above

28. Advantages Constrains
For each lot is binary (acceptable or not):valid for stratum (lot)
Overall proportion/average
As evaluation & monitoring tool
Constrains
l. Sampling frame is needed, therefore it is applies to community level or at small populations.
2. Misclassification (type I and type II error)
3. Dedicated staff is needed
4. Supervisor is important
5. Logistic management eg Vehicles
For large area we go for stratified cluster sampling.

29. To see the overall estimation to determine whether individual
Difference between LQAS and traditional stratified random sample
Traditional stratified random sample
LQAS
To see the overall estimation
to determine whether individual
lots are acceptable or not
to obtain overall population estimates by treating the lots as strata, and combining the samples from all of the lots to create a stratified sample.
Sample size
in each stratum, or lot, is large enough to estimate the sample proportion to within some desired level of precision.
Typically smaller than that of a traditional stratified sample because, for each lot or stratum, only a binary decision is made.

30. Difference between LQAS and traditional stratified random sample
Advantages:
_ Production of estimates & corresponding confidence intervals for each stratum.
_ Increased precision over a SRS.
Advantage
Although the cost of an LQAS sample is lower because of the decreased sample
size, the information gained from such a sample is limited.
-the sampling can be done more frequently
within each lot to assess change because of the smaller sample sizes required.
Disadvantages:
_ A list of all the units with in each stratum required.
Disadvantages
each lot only an acceptable/not acceptable
verdict is possible. there is no measure of the degree of
“unacceptability”.

31. Application of LQAS
1. Used in monitoring of lymphatic filariasis in India. LQAS was applied for rapid monitoring of coverage after every round of mass drug administration (MDA).
2. Used in Sputum Acid-Fast Bacillus Smears for Assessing Sputum Smear Microscopy Centers under RNTCP, TN for quality control.
3. Used in Utilization of antenatal care

33. C. Case-control method for rapid epidemiological assessment
Potential method of sampling for rapid assessment (by choosing appropriate samples of cases and control).
It differs from other technique, as it is retrospective study. Case-control methodology began as means of identifying the risk factors.
Used for rapid assessment for water and environmental sanitation intervention is known.
Also this method can be used rapid assessment tool in epidemic investigation to test hypothesis.

34. 1. Focus group discussion (FGD) 1. As Idea generation tool
D. Use of qualitative research methodology for rapid assessment in social and behavioral research
1. Focus group discussion (FGD)
1. As Idea generation tool
2. In combination with quantitative study
3. As a primary data collection method
2. Key informant interviews
Community perception & priority

35. 2. Key informant interviews E.g. Kilombero District Tanzania
Step 1: Questionnaires
Sent by Disrict education officer
Step 2: Validation
Urine filtration by mobile laboratory
Outcome
77 school (class 1, 3, 5)
Mean – 85/school
Teacher & student questionnaire distributed
Symptoms of schistosomiasis assessed
- Positive children treated

36. Uses of rapid survey methods as monitoring tool in national programs in India
1. Applicability of LQAS, and adopting these modifications for monitoring leprosy elimination in Tamil Nadu state, which was highly endemic for leprosy.
2. Immunization coverage of infants, children and women residing in a primary health centre (PHC) area in Rajasthan was evaluated both by lot quality assurance sampling (LQAS) and by the 30-cluster sampling method.
3. Using LQAS in Polio Eradication Efforts.
4. 30 cluster sampling used as validation of spot-testing kits to determine iodine content in salt in two states: Madhya Pradesh & Delhi.

37. References:
Anker M. Epidemiological and statistical methods for rapid health assessment. World Health Stat Q. 1991;44(3):94-97.
Baltazer JC. The potential of the case-control method for rapid epidemiological assessment. World Health Stat Q. 1991;44(3):
Lanata CF, Black RE. Lot quality assurance sampling techniques in health surveys in developing countries: advantages and current constraints. World Health Stat Q. 1991;44(3):133-9.
Valadez JJ, Weiss W, Leburg C, Davis R. Assessing Community Health Programs: A Participant’s Manual and Workbook, Using LQAS for Baseline Surveys and Regular Monitoring. Core group March.
R R Frerichs and K T Tar. Computer-assisted rapid surveys in developing countries. Public Health Rep Jan–Feb; 104(1): 14–23. {PUBMED}
Serfling RE, Sherman lL, Attribute Sampling Methods for Local Health Departments, Publication No. 1230, U.S. Department of Health and Human Services, Public Health Service, Washington, DC, 1965, 178 pp.  

38. Lemeshow S, and Robinson D: Surveys to measure programme coverage and impact: a review of the methodology used by the Expanded Programme on Immunization. World Health Statistics Quarterly 38, 65-75, 1985.
Frerichs RR, and Tar Tar K: Computer-assisted rapid surveys in developing countries. Public Health Reports 104 (1), 14-23, 1989.
Frerichs RR: Simple analytic procedures for rapid microcomputer-assisted surveys in developing countries. Public Health Reports 104 (1), 24-35, 1989.
Bennett S, Woods T, Liyanage WM, Smith DL: A simplified general method for cluster-sample surveys of health in developing countries. World Health Statistics Quarterly, 44 (3), , 1991.
Sandra MJ, Joia de S, Ralf K, Richard C. A toolkit for rapid assessment of health systems and pandemic influenza preparedness and response. London: London School of Hygiene and Tropical Medicine Sep 26.
Dongre AR, Deshmukh PR, Garg BS. An Approach to Monitor and Initiate Community Led Actions for Antenatal Care in Rural India – A Pilot Study. OJHAS Vol. 8, Issue 2: (2009 Apr-Jun)

39. Cluster analysis by using EPI6