RAMP Rollout in Kenya

Rapid Mobile Phone-based survey (RAMP)in

KenyaPresented by

Kioko Kiilu (KRCS)

Jenny Cervinskas (IFRC)Nairobi, February 1st, 2011

Introduction to Rapid Mobile Phone-based (RAMP) survey

RAMP experience with KRCS volunteers◦ Site and project identification◦ Survey methods, training, fieldwork◦ Lessons learnt

Preliminary results

Plenary

Outline

To provide a survey methodology and operations protocol so that governments and NGOs can:◦conduct health surveys at reduced cost ◦with limited external technical assistance◦and achieve high standards of data quality

Dramatically decrease the time from data collection to having data available for decision making

RAMP: Purpose

Technical Reference Manual Standardized questionnaires for malaria Questionnaires designed on the internet using

EpiSurveyor Data collected using cell phones Training manual and tools adaptable to local settings Standard survey methods Rapid analysis and reporting of results

RAMP survey tool: Features

The traditional data cycle

Mobile technology can drastically reduce the time between data collection and action.

Weeks to Months (sometimes continuous)

Weeks to Months to Years

Weeks to Months to Years

Weeks to Months to Years (or never)

Weeks to Months (sometimes continuous)

Questionnaire Design

Data Entry

Data Analysis

Data Reporting

ACTION

Data Collection

The SMT data cycle EpiSurveyor has:

◦ eliminated the need for data entry and is now automating many analysis and reporting functions

◦ shortened the time and reduced the costs between collection and action

Anyone can create a username and password at www.episurveyor.org and start using these tools for free

Questionnaire Design

Data Entry

Data Analysis

Data Reporting

ACTION

Data Collection

Questionnaire design in Episurveyor (internet) Real-time data entry on cell phones Daily upload of data from cell phone over 2G cell

network to internet database Real-time data cleaning Real-time data analysis Rapid production of preliminary survey results bulletin

within 24 hours of last interview Rapid production of preliminary feedback survey

report in 72 hours

Cell phone-enabled innovations

Aim is to simplify and improve the timeliness of the entire data collection cycle

RAMP experience with Kenya Red Cross Society (KRCS)

volunteers

Ongoing operational research project in malaria

Hard-to-reach areas/Long data cycle

Mobile network coverage

Project: Home Management of Malaria (HMM) in Malindi district, Coast province

Site and project identification

Malindi - Survey site

1st stage: standard probability-proportional-to-estimated-size (PPES) selection of PSUs◦ Sampling frame: 106 villages of the HMM project

2nd stage: segmentation of PSU; choose 1 segment using PPES

SRS to choose 10 households Precision:

+/- 6% for each key indicator from household questions +/- 3% using roster/individual data

30 PSUs, 10 households per PSU, 1500 persons, all ages

Survey methods

Household questionnaire◦ Usual household characteristics (wealth asset questions, distance

to health facility, etc.)◦ Summary questions (innovation)

Duplicated nearly all key indicators that are in the person & net register

Eg., no. of persons: all ages & children <5 yo No. of any nets, ITNs No. of persons/children <5 yo slept under ITN last night

Person roster Net roster

◦ Number of persons that slept under each net

Three survey instruments

HMM volunteers (Interviewers)

HMM Coaches /MOH Public Health Officers (PHOs) (Supervisors)

Training – 4 days (January 19-22, 2011)

Recruitment and training

Content ◦ Cellphone basics◦ Questionnaires◦ Informed consent◦ Interview techniques◦ Field procedures ◦ Field logistics/reporting◦ Supervisor training

Methodology◦ Presentations, role play, group discussion, demonstrations,

field tests (2)

Training content & methodology

Survey teams: ◦ 6 teams

1 Team supervisor and 2-4 interviewers/team)

Survey supervisory team (KRC, IFRC, WHO, MOH, DataDyne):◦ Planning, logistic & financial

responsibilities, field support, daily “quality” rounds, and remote monitoring of data quality

Field work (January 24th-28th, 2011)

Morning briefing (“quality round”)

Meeting with community leaders, reviewing sketch

maps, segmentation, selection of HHs

Conduct interviews at HH level

Supervisor will send data to server

Debriefing at day’s end with support team in Malindi

Data cleaning and analysis

A day’s schedule

Data entry: worked well, all teams were able to collect data using the cellphone and send to server

Survey conducted with reasonable adherence to correct field procedures

KRC volunteers were able to prepare the sketch maps, carry out segmentation, and apply SRS to select HHs

Preliminary results were available within 24 hrs. of the return of the last team from the field

Lessons learnt

Preliminary results

Results: key indicators, HH questionnaire

HH ownership at least one

ITN

Access, % pop. with access to

ITN

Use, all persons

Use, children <5 years

Use in children <5y, given at least 1 ITN

Of <5y fever cases, treated

ACT

Of <5y fever cases, treated ACT within 24

hr

Of <5y fever cases, blood

taken (testing)

0

10

20

30

40

50

60

70

80

90

100

78

68

55

65

7977

69

14

Percentage

Access: Two-thirds of ITNs to reach universal coverage are present. Gap is 32%.

Key indicators

Target population 68 753

Persons per net 2.47

ITNs needed 27 835

Survey-estimated ITNs in HH of target pop

18 931 (68%)

ITN/LLIN need/gap 8 904 (32%)

Results: High percentage of ITNs are being used. Use gap is due to insufficient ownership of ITNs

Key indicators Point estimate

% ITNs that were slept under last night 87%

% ITNs that were hung last night 86%

ITN use, all ages 55%

ITN use, <5 yo 65%

* 47% of nets had 3 or 4 persons sleeping under them

ITN use by age group

<1y 1 2-4 5-9 10-14 15-24 25-44 45-59 60+0

10

20

30

40

50

60

70

80

90

100

Age groups (years)

Age in months Cumulative %

<12 months 28

12-23 months 59

24-36 months 80

Age of ITNs

* 88% of nets were LLINs

Number of persons sleeping under a single net last night

%, nets

1 person 15

2 persons 39

3 persons 32

4 persons 15

Key results from roster-only data

Treatment & diagnosis, <5 yo

Key indicators %

Treated ACT, <5 yo 77

Treated ACT within 24 hours, <5 yo 69

Received finger/heal stick for blood 14

- Denominator for all indicators was % of children <5y with fever in the previous two weeks

Survey results bulletin & report

Using the cellphones

No major problems: all cellphones were operational

No calls to the Datadyne “hotline”

Data entry: worked well

Data was sent to the server by all teams, every day

Daily/immediate upload of data if 2G/GPRS available

Potential difficulties: initial connection of cell phone to

data network

So, does the RAMP “work”?

Conducted by secondary-school graduates with no previous survey experience

Survey was completed within two weeks◦ 1 week training, 4.5 days field work

Daily data cleaning accomplished Preliminary survey results bulletin finished within

24 hours Preliminary report finished within 72 hours Provided excellent management information on

the key indicators

Cost component USD

Local operational costs (e.g., personnel costs: avg. $40 per interviewer & supervisor/day * 20 persons * 10 days, training hall, stationary)

13 429

Phones + accessories 5 416

Transport (drivers, fuel) 3 950

Total 22 795

Approx Kshs 1.7m

Analysis + Report Free (WHO)

Costs

• Kenya Red Cross Volunteers• Kenya Ministry of Public Health and Sanitation• IFRC• Datadyne• WHO• Kenya Bureau of Statistics

A special thanks to the survey team and the many families who agreed to be interviewed for this survey

Acknowledgements

Thank-you for your attention