The Zambia Access to ACT Initiative Survey 2009
Zambia, 2009
Identification
ZMB_2009_ZAAI_v01_M
The Zambia Access to ACT Initiative Survey 2009
| Name | Country code |
|---|---|
| Zambia | ZMB |
Other Household Survey [hh/oth]
Baseline Survey
The Zambia Access to ACT Initiative (ZAAI) is designed to inform the Government of the Republic of Zambia (GRZ) on how to best increase the access to Artemisinin-based Combination Therapy (ACTs) and other essential drugs for treatement of malaria. ZAAI is designed in close collaboration between the GRZ and several Cooperating Partners (CPs) and is co-financed by DFID and USAID.
The ZAAI is designed to implement and evaluate the effectiveness of a combination of public and private sector strategies for improving access to ACTs and diagnostics in the country. The ZAAI has four main objectives:
(1) To enhance public sector supply chain management in order to reduce stock out rates of ACTs and Rapid Diagnostic Tests (RDTs) and improve availability of important medicines and medical supplies at health centres and hospitals throughout Zambia.
(2) To improve access and affordability of ACTs as well as diagnostics through the private sector by introducing a combined ACT and RDT subsidy to private sector wholesalers and other outlets.
(3) To provide access to ACTs and RDTs through Community Health Workers (CHWs), the National Malaria Control Centre (NMCC) has rolled out a CHWs programme in 11 out of the 72 districts. Under the framework of this programme, the NMCC trains CHWs in diagnostics and makes ACTs and RDTs available through the public distribution system. ZAAI will provide funding to further expand the CHWs programme to 2-3 more districts.
(4) To inform policy decisions about the impact and effectiveness of the above interventions. Observing the impact of the three interventions when implemented either separately or co-jointly is a unique opportunity to quantify the relative effect of each intervention as well as their combined effect on the household decision making on malaria treatment.
To achieve the fourth objective the ZAAI will undergo a rigorous impact evaluation, using a randomized design to infer the effect of the interventions. This evaluative research will provide rigorous quantitative evidence on the effectiveness and cost effectiveness of each pilot intervention. The paired public and private sector interventions presents a unique opportunity to measure and evaluate concurrent improvement in both public and private sector accessibility and their joint effect on household access to first line treatment.
A key input into this process will be the collection of high quality, comprehensive, and multi-purpose household survey data, as well as community level data to account for community effects. The ZAAI 2009 is the baseline survey.
Sample survey data [ssd]
Household, Individual, Community
Version
v1.1: Edited Data.
2010-04
Scope
The scope of The Zambia Access to ACT Initiative (ZAAI) survey includes:
HOUSEHOLD:
Household roster, Education, Economic activities, Dwelling characteristics and household amenities, Household assets, Non-farm enterprise, Farm enterprise, Transfers and other income and subjective wealth, Weekly food consumption, Monthly food consumption, Annual non-food consumption, Mosquito nets, Malaria-related knowledge, attitude and practice (KAP), General & health-specific risk pereference, Time preference, Mental health, Health status and utilization, Health care satisfaction, Willingness-to-pay, Willingness-to-pay bid game, Malaria and anemia testing, Height and weight
COMMUNITY:
Direct observation, Composition of interview, Demography, Access to basic services and community characteristics, Social capital and community empowerment, Health, Economic Activities, External Shocks, Prices
| Topic | Vocabulary | URI |
|---|---|---|
| consumption/consumer behaviour [1.1] | CESSDA | http://www.nesstar.org/rdf/common |
| income, property and investment/saving [1.5] | CESSDA | http://www.nesstar.org/rdf/common |
| employment [3.1] | CESSDA | http://www.nesstar.org/rdf/common |
| general health [8.4] | CESSDA | http://www.nesstar.org/rdf/common |
| health care and medical treatment [8.5] | CESSDA | http://www.nesstar.org/rdf/common |
| specific diseases and medical conditions [8.9] | CESSDA | http://www.nesstar.org/rdf/common |
| housing [10.1] | CESSDA | http://www.nesstar.org/rdf/common |
Coverage
Province Level:
The survey was conducted in 3 of Zambia's Provinces: Eastern, Northern and Luapuala Provinces.
District Level:
A total of 8 Districts are covered in these Provinces: Milenge and Mwanse in Luapula Province, Kasama and Chinsali in Northern Province and Nyimba, Chadiza, Lundazi and Chama in Eastern province.
Producers and sponsors
| Name |
|---|
| Jed Friedman and Edit Velenyi, The World Bank |
| Name |
|---|
| The National Malaria Control Center |
| The World Bank |
| Name |
|---|
| Human Development Network |
Sampling
To start the sampling procedure, identify the households that are 'non-contact' and those that refused to cooperate and mark them by writing 'NON CONTACT' or 'REFUSAL' in the margin against them. After this is done, the households that remain are the households from which complete information was collected during listing.
Category 1
The next step is to stratify households according to whether or not there was at least one member of the household who had fever/malaria in the past month. Check question 8 in the listing book to identify such households. All households that had code '1' in question 8, meaning at least a member of that household had fever/malaria in the past month, will be marked with an X in the column indicated as category 1.
Category 2
Make sure you check and are satisfied that all the non-contacts have been indicated as such and those that refused to cooperate have also been identified and marked then all those households that answered 'yes' in question 8 have been put in category 1. If you are sure, then all remaining households will be in category 2. Just like in category 1, put a mark (x) against all the remaining households in the column for category 2.
Assign Sampling Serial Numbers, within each category, following where you put (x). The sampling serial numbers will sequentially be assigned, starting with '1' in each category. In addition assign serial numbers to 'NON CONTACT' and 'REFUSAL' households in the 'NON CONTACT/REFUSAL' column.
NOTE: (a) The sum of the last sampling serial numbers in categories 1 and 2 must be equal to the total number of households that gave complete information during listing of the SEA.
(b) The sum of the last serial numbers in the column for category 1,2 and non-contact/refusal must be equal to the last total number of households listed in the SEA.
The next step is to select a Sample, and it is done as follows. A total of 15 households in each SEA will be selected. Seven (7) households will come from category 1 and 8 households will come from category 2. In cases where there are shortfalls in any category get the shortfall form the other category.
The allocated number of sample households to each category will be selected independently using the following procedure:
- Divide the total number of households listed in the category by the number of households to be selected (according to sample allocation) to give the Sampling Interval (SI). Calculate this to two (2) decimal places.
- From the table of random numbers, get a random number (RS) between '1' and the SI, inclusive. The random number obtained will give the first household that will be in the sample.
- Add the SI to the random number (RS), and the integer part of the sum will give the second household to be in the sample.
- Continue with the procedure, adding SI to each successive sum until you have all the allocated sample size for the category.
- Put a circle round each sampling serial number (column 11), in the listing book, corresponding to the numbers you have worked out for each category. The sampling serial numbers circled will indicate the households selected for the sample.
- Transcribe onto the 'LIST OF SELECTED HOUSEHOLDS' sheet, now copying the household serial numbers (column 2) of the selected households.
In category 1, households bearing sampling serial numbers 7, 15, 23,31, 39, 47 and 55 are selected. In category B, households bearing sampling serial numbers 3, 10, 18, 26, 34, 42, 50 and 58 are selected. For each of these households in the SEA, a detailed questionnaire will be administered. With the above sampling method, there will be no replacement for any household. The selected household must be interviewed.
Survey instrument
The household questionnaire include Household roster, Education, Economic activities, Dwelling characteristics and household amenities, Household assets, Non-farm enterprise, Farm enterprise, Transfers and other income and subjective wealth, Weekly food consumption, Monthly food consumption, Annual non-food consumption, Mosquito nets, Malaria-related knowledge, attitude and practice (KAP), General & health-specific risk pereference, Time preference, Mental health, Health status and utilization, Health care satisfaction, Willingness-to-pay, Willingness-to-pay bid game, Malaria and anemia testing, Height and weight.
The community questionnaire include Direct observation, Composition of interview, Demography, Access to basic services and community characteristics, Social capital and community empowerment, Health, Economic Activities, External Shocks, Prices.
All questionnaires and modules are provided as external resources.
Data collection
| Start | End |
|---|---|
| 2009-05-01 | 2009-11-30 |
| Name |
|---|
| Palm Associates Limited |
| Geo-Hydro Consulting |
To offset these limitations, the evaluation will include a household survey. A combined malaria indicator and socioeconomic household survey will be administered in randomly selected households in both the control and intervention districts prior to the intervention (baseline), and one year following the baseline survey (follow up).
• The household survey modules will provide data on: household composition (age, gender, etc.), consumption, assets, education, labor supply, health seeking behavior, fever/malaria episode-related KAP, history of malaria within the household, treatment seeking behavior, WTP for anti-malarials, fever/malaria related expenditures, and opportunity costs of illness.
• In addition, the survey will collect biomarker tests: parasite prevalence, hemoglobin, and anthropometry will be collected from all household residents. Upon consent from the household member or his/her guardian, parasite prevalence will be tested using rapid diagnostic test kits (RDTs). The procedure is mildly intrusive, whereby a small sample of blood is taken by standard finger-prick methods using a sterile lancet (the same sample will be used for hemoglobin assessment). Trained public health technicians will be responsible for all blood collections.
All surveys will be performed according to the international guidelines for human experimentation in clinical research. Ethical clearance for the surveys will be obtained from the MOH prior to fielding the surveys.
Complementary data will also be collected to track and understand the effect of potential confounders, and to, ideally, ensure lack of contamination between treatments and control groups, or, if unavoidable, to best mitigate these effects during the analytical work. Complementary data includes: i) monthly weather statistics; ii) community factors, including changes in behavior communication related to fever/malaria prevention and treatment, etc.; and iii) specialized agency consultations (MOH, NMCC, NRA, MLS, DHMT, etc.) to track/control for confounding interventions, such as introduction of new programs (e.g. additional preventive intervention ITNs, IRS etc. through other donors; changes in the regulatory regime, etc.)
In addition to tracking operational progress and the impact of the interventions on the population, the study includes a rigorous costing and cost effectiveness component. The cost-effectiveness analysis will provide evidence on the relative costs and consequences of different interventions in order to assist in priority-setting and budget allocation. Costing will inform on accounting and economic costs of the interventions. Cost effectiveness will inform on the gross (incremental cost of intervention only) and net costs (incorporating potential cost savings as a result of the intervention, measured e.g. as cases averted, reduction in productivity loss, etc.) of the interventions.
Distributor information
| Organization name |
|---|
| Health |
Data Access
Jed Friedman and Edit Velenyi. The Zambia Access to ACT Initiative Survey 2009. Ref. ZMB_2009_ZAAI_v01_M. Dataset downloaded from <www.microdata.worldbank.org> on [date].
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
(c) 2010, The World Bank
Contacts
| Name | Affiliation |
|---|---|
| Edit Velenyi | The World Bank |
Metadata production
DDI_ZMB_2009_ZAAI_v01_M
| Name | Affiliation | Role |
|---|---|---|
| Akiko Sagesaka | The World Bank | Documentation of the study |
2010-03-25
Metadata version
version 1.0