Rapid Survey Method

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

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

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. 

• 1985 - 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.

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

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.

Cluster sampling

• 3o cluster sampling

• 30 by 7 cluster sampling method

• WHOs EPI• • is a two-stage cluster sample

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

1. Selection of 30 cluster by PPS

Community Population size

Cumulative Population size

Selection of cluster

1 1000 10002 400 14003 200 16004 300 19005 1200 31006 1000 41007 1600 57008 200 59009 350 625010 450 6700

Table: A cumulative list of community size

Sampling interval = total population of community /no. of clusters to be selected = 6700/3= 2233

SI =2233Random No.= 1814

2nd =RN+ SI

3rd = RN+2SI..30th =RN+29SI

1814 (1st )

4047 (2nd )

6280 (3rd)

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”

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

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.

Advantages:Sampling frame is not needed for selected clusterGood for EPI methodology assumption

Disadvantages:_ Not intended for calculation of estimates from individual clusters._ Less precise than simple random sample.

Disadvantages:-If “Pocket” – Bias estimation-Every individual in household – Bias-Estimates are not for cluster

Application of 30 cluster sampling

1. 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

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.

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)

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.

Analysis

• Overall proportion of defects

• Defective items in each lot

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.

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

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

Selection of study subjects

19 by 5 LQAS contd…. Step 3: Data collection Suppose following is data was collected.

Step 4. Analysis

Add Number Correct in all SAs: 12 + 9 + 16 + 11 +14 = 62 Add all Samples Sizes: 19 + 19 + 19+ 19 + 19 = 95 Knowledge Coverage Estimate = Average Coverage = 62/95 = 65.3% = 70%

Step 5. Use table to find Decision Rule

11

Step 6. Deciding “defect”

Similarly we can study multiple indicators for single area.

Also we can study multiple indicators for 5 areas

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

Advantages• For each lot is binary (acceptable or not):valid for

stratum (lot)• Overall proportion/average• As evaluation & monitoring tool

Constrainsl. 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 needed4. Supervisor is important 5. Logistic management eg Vehicles

Traditional stratified random sample LQASTo see the overall estimation to determine whether individual

lots are acceptable or notto 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.

Sample sizeTypically smaller than that of a traditional stratified sample because, for each lot or stratum, only a binary decision is made.

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 acceptableverdict is possible. there is no measure of the degree of“unacceptability”.

Difference between LQAS and traditional stratified random sample

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

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.

 

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

2. Key informant interviewsE.g. Kilombero District Tanzania

Step 1: QuestionnairesSent by Disrict education officer

Step 2: ValidationUrine 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

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.

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):140-143.• 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. 2002 March.

• R R Frerichs and K T Tar. Computer-assisted rapid surveys in developing countries. Public Health Rep. 1989 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.  

• 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), 98-106, 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. 2008 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)

• Cluster analysis by using EPI6