Attachment_3_FullReportZambiaMIS2012_July2013_withsigs2_(1).pdf

Zambia National Malaria Indicator Survey 2012 ii iii

Zambia National Malaria Indicator Survey 2012

This report summarizes the findings of the 2012 Zambia National Malaria Indicator Survey carried out in April and May 2012 by the Ministry of Health, Central Statistics Office, PATH Malaria Control and Evaluation Partnership in Africa (MACEPA), the United States President’s Malaria Initiative, the World Bank, UNICEF, and the World Health Organization.

iv

Contents

Acronyms ................................................................................................................................ v

Acknowledgments ...................................................................................................................vi

Preface ................................................................................................................................... vii

Executive summary ............................................................................................................... viii

Chapter 1: Introduction

Chapter 2: Characteristics of households and women respondents

Chapter 3: Coverage of key malaria interventions

Chapter 4: Malaria parasite and anaemia prevalence

Chapter 5: General malaria knowledge

Chapter 6: Comparison of malaria indicator survey results, 2006–2012

Chapter 7: Conclusions………………………..…………………………………………………..67

Additional resources

Appendix A: Sample design

Appendix B: Survey personnel

Appendix C: Questionnaires v

Acronyms

ANC Antenatal clinic

ART-LUM Artemether-lumefantrine

CDC US Centers for Disease Control and Prevention

CHW Community health worker

COMBOR Community Malaria Booster Response

CSA Census supervisory areas

CSO Central Statistical Office

DFID UK Department for International Development

DHS Demographic and Health Survey

GFATM The Global Fund to Fight HIV, Tuberculosis and Malaria

Hb Haemoglobin

IPT Intermittent preventive treatment

IRS Indoor residual spraying

ITN Insecticide-treated mosquito net

LLIN Long-lasting insecticidal net

M&E Monitoring and evaluation

MACEPA Malaria Control and Evaluation Partnership in Africa

MERG Monitoring and Evaluation Reference Group

MICS Multiple indicator cluster survey

MIS Malaria indicator survey

MOH Ministry of Health

NMCC National Malaria Control Centre

NMCP National Malaria Control Programme

NMSP National Malaria Strategic Plan

PATH Program for Appropriate Technology in Health

PDA Personal digital assistant

PMI US President’s Malaria Initiative

RBM Roll Back Malaria

RDT Rapid diagnostic test

SEA Standard enumeration areas

SP Sulfadoxine-pyrimethamine

UNICEF United Nations Children’s Fund

WBC White blood cell

WHO World Health Organization

ZISSP Zambia Integrated Services Strengthening Program vi

Acknowledgments

This report presents the results of the Zambia National Malaria Indicator Survey 2012, a comprehensive, nationally representative household survey designed to measure progress toward achieving the goals and targets set forth in the National Malaria Strategic Plan 2011– 2015. It represents the efforts of several agencies and many individuals. The Ministry of Health, namely the National Malaria Control Centre (NMCC), has the major responsibility for conducting the survey. Other agencies have been instrumental in this survey, including the Central Statistical Office (CSO); the Malaria Control and Evaluation Partnership in Africa (MACEPA, a programme at PATH); the Zambia Integrated Services Strengthening Program (ZISSP); the United States (US) President’s Malaria Initiative (PMI); the World Bank;

Comprehensive HIV AIDS Management Programme (CHAMP); First Quantum Minerals, Ltd.; and the World Health Organization (WHO).

At the Ministry of Health, Dr Peter Mwaba, Permanent Secretary, and Dr Elizabeth Chizema Kawesha, Director of Public Health and Research, provided overall survey leadership and guidance. At the NMCC, Dr Mulakwa Kamuliwo, Deputy Director, Public Health and Research, Malaria; Dr Chibesa Wamalume, Case Management Officer; Moonga Hawela, Chief Parasitologist; Mercy Mwanza, Surveillance and Information Officer; Busiku Hamainza, Operations Research Officer; Pauline K. Wamalume, Information Education Communication Officer; and Felix Ngoma, Accountant, took primary responsibility for survey operations and coordination. Also within the Ministry of Health, various members assisted with organization, community sensitization efforts, logistics, ordering of supplies, and training. At CSO, John Kalumbi, Director, and Godwin Sichone, Survey Statistician, provided support for the sample design, sample selection, and analysis. CSO staff also provided support during the field work for identification of cluster boundaries and household listing. At MACEPA, John Miller, Chris Lungu, Kafula Silumbe, Marie Reine Rutagwire, Muleba Mwatafwali, Sosenna Assefa, and Matches Mulenga provided logistics support, survey organization, accounting, support for design and analysis, and report writing. Manny Lewis and and Laura Newman edited and formatted the report. From PMI, Allen Craig of the US Centers for Disease Control and Prevention (CDC) Zambia offices provided support for the design of the survey, Katherine Tan from CDC Atlanta reviewed the protocol, and Anatoly Frolov from CDC Atlanta took responsibility for development of the programming of the questionnaire and data tabulations.

At the ZISSP, Brian Chirwa, Patrick Chewe, and Dayton Makusa provided coordination during the survey planning process and technical support during training and field work. Fred Masaninga from WHO provided support for activities, training, and field work. The Roll Back Malaria Monitoring and Evaluation Reference Group (RBM MERG) developed the questionnaire and survey instruments used. The training materials, methodology, and questionnaires used in the survey were mostly drawn from the work of the RBM MERG, but especially from the work of ORC Macro, which organizes the Demographic and Health Surveys (DHS).

A complete list of the field teams and individuals involved in the survey are presented in Appendix B.

Dr. Peter Mwaba Permanent Secretary Ministry of Health vii

Preface

The success of the malaria control programme in Zambia continues to inspire similar efforts across the region. Through our strong partnerships and focused efforts, malaria control remains a priority of the Ministry of Health. Key to the success of the program has been the continued emphasis on measurement of progress around key indicators. Measurement is critical to inform our decisions and donors as we continue to strive for malaria-free areas in the country.

The Zambia National Malaria Indicator Survey 2012 represents the fourth large-scale effort to benchmark progress of malaria control efforts—interventions and disease burden—since the launch of the second National Malaria Strategic Plan in 2006–2010. Now well into our third National Malaria Strategic Plan 2011–2015, Zambia continues to lead the way in the African region with four successive malaria indicator surveys.

Managing a malaria control programme is a very dynamic process and the Zambia programme is still heavily dependent on donor aid for its success. In 2010, we reported on the challenges of delayed procurements and reduced insecticide-treated net (ITN) coverage in many malaria-endemic areas of the country. Consequently, in late 2010 and 2011 we prioritized deliveries of ITNs to underserved areas. In this report we are pleased to see progress from these decisions as well as in many other key strategic areas.

Despite these successes, the malaria parasite continues to challenge us. This demands that we continue our efforts to exploit its weaknesses and not look away, but stand firm and continue the assault in new and innovative ways.

With our persistence and good will, we will win this battle. With our emphasis on measurement of our progress and evidenced-based decision-making, we will continue the good fight until we achieve our goal of a malaria-free Zambia.

Hon. Dr. Joseph Kasonde, MP Minister of Health viii

Executive summary

The Ministry of Health, along with its partners, through the National Malaria Control Programme continues to provide quality malaria control prevention and treatment services in an aggressive approach to reducing malaria and malaria-related burden. Monitoring the status of the delivery of these services is critical for understanding progress in the fight against malaria. The Zambia Government and its partners continue to be a driving force for malaria control in the region, and these survey results indicate both the tremendous progress and the challenges that have occurred during the last two to three years.

This report presents the results of the Zambia National Malaria Indicator Survey (MIS) 2012, a nationally representative household survey assessing coverage of key malaria interventions and malaria-related burden among children under age five years. The 2012 MIS report also compares results from previous surveys conducted in 2006–2010. The 2012 survey was developed and conducted by the Ministry of Health and several key malaria partners including the Central Statistical Office (CSO), the Malaria Control and Evaluation Partnership in Africa (MACEPA, a programme at PATH), the World Health Organization (WHO), the United States President’s Malaria Initiative (PMI), the Zambia Integrated Services Strengthening Program (ZISSP), the World Bank, and the University of Zambia.

The MIS was based on a nationally representative two-stage cluster sample of 4,000 households surveyed from 160 standard enumeration areas randomly selected from all ten provinces to provide representative national and urban and rural estimates. Field work was conducted during April and May 2012 by 15 field teams using standardized questionnaires preprogrammed onto hand-held computers (called personal digital assistants or PDAs) to facilitate data entry, extraction, and analysis. Malaria parasite testing was done using First Response® Malaria AG HRP2 rapid diagnostic tests (RDTs) and both thick and thin blood smears. Anaemia testing was done using Hemocue®

Hb 201 analysers and microcuvettes.

Insecticide-treated nets (ITNs) and indoor residual spraying (IRS) are the primary control strategies for preventing malaria transmission in Zambia. Results from the 2012 MIS indicate 72% of Zambian households have at least one mosquito net, and 68% of households have at least one ITN, representing an increase from 2010; substantial progress was made in replenishing ITNs in several provinces that showed decreased coverage in 2010.

Forty-nine percent (49%) of all Zambians slept under a mosquito net the night before the survey, an increase from 2010 despite challenges in increasing overall net availability. Over seventy-five percent (75%) of children under age five years who slept under a net the night before the survey slept under a treated net in Luapula and Eastern provinces, two of the most malarious regions in the country. The number of districts included in the IRS programme increased from 36 to all districts since the 2010 survey, with an increasing number of rural, more malarious areas targeted for spraying. Nationally, in 2012, 25% of households in Zambia reported being sprayed. Seventy four percent (74%) of households nationally reported having either an ITN or being sprayed in the past year.

Nearly three-quarters (72%) of pregnant women reported at least two doses of intermittent preventive treatment (IPT) during recent pregnancies and over half reported at least three doses of IPT. Further, the night before the survey, 58% of all pregnant women 15 to 49 years slept under an ITN.

Since 2004, the national first-line antimalarial treatment has been artemether-lumefantrine (ART-LUM). From 2010 to 2012, reported fever prevalence among children was reduced, and even more of these febrile children who received an antimalarial received the recommended ART-LUM for treatment. More than half of these febrile children seeking care ix reported a finger stick, suggesting tremendous progress in scaling diagnostic testing services for malaria.

Malaria parasite prevalence was found to be 14.9%, and severe anaemia prevalence was found to be 6.8% among children under age five years. This represents a slight decrease in both measures since 2010 and a general trend in decreasing malaria burden nationally since 2006.

The 2012 MIS represents a significant milestone for benchmarking progress for the Zambian Ministry of Health and malaria control partners. The results of this survey will inform the health sector and malaria-specific strategic planning processes for the country in 2012 and beyond.

Chapter 1: Introduction

Zambia has made great strides in improving the coverage and extent of malaria control services offered throughout the country over the past decade. Since the second National Malaria Strategic Plan 2006–2010, the efforts of the Government of the Republic of Zambia, in conjunction with many partners, have been focused on scaling up malaria control interventions, including prevention and treatment services. In order to assess national scale-up efforts, effective monitoring and evaluation are needed to measure progress toward select targets and goals.

The Zambian Government has identified malaria control as one of its main public health priorities. This is emphasized in subsequent National Development Plans and National Health Strategic Plans. In line with these efforts, the Ministry of Health (MOH), through the National Malaria Control Centre (NMCC), has developed a further National Malaria Strategic Plan (NMSP) 2011–2015, aimed at significantly sustaining the gains achieved during initial scale-up efforts of malaria control interventions toward the achievement of the national vision of “a malaria-free Zambia.”

The NMCC, in collaboration with its partners, set high targets for coverage of interventions and reductions in malaria burden outlined in the NMSP. Evidence of progress in rolling out malaria interventions to affected communities has come from several partners and sources including the 2001/2002 and 2007 national Demographic and Health Surveys (DHS), the 1999 UNICEF-supported Multiple Indicator Cluster Survey (MICS), and smaller-scale household surveys such as the Roll Back Malaria (RBM) baseline and follow-up surveys in 2001 and 2004, NetMark evaluation surveys in 2000 and 2004, and others.

In 2006, the MOH and partners conducted the first nationally-representative Malaria Indicator Survey (MIS), measuring the coverage of the core RBM interventions and malaria-related disease burden. This was followed by a second MIS in 2008. These surveys were part of a planned, ongoing national evaluation of malaria control efforts implemented under the NMSP 2006–2010 The results of these surveys made it possible to monitor and evaluate progress on population-based coverage of key malaria interventions, including prompt and effective case management, possession and use of insecticide-treated mosquito nets (ITNs), availability of indoor residual spraying (IRS), and intermittent preventive treatment (IPT) for pregnant women. Further, these surveys reported on the national prevalence of malaria parasitaemia (22% in 2006 and 10% in 2008) and severe anaemia (13% in 2006 and 4% in 2008) among children less than five years of age.

The 2006, 2008, and 2010 surveys were based on a standard set of instruments and a protocol developed through the RBM Monitoring and Evaluation Reference Group (MERG), a global technical advisory group providing M&E guidance for malaria control programmes.

These tools were largely based on the collective experience of the DHS and MICS and are presented as a package of materials to promote standardized survey sampling methods, questionnaires, and results tabulations as well as to provide assistance with survey logistics, budgeting, and training of survey teams. The package includes standardized measurement of malaria parasite prevalence and anaemia among target populations to derive malaria-related burden at the community level. The RBM MERG recommends that countries with endemic malaria-transmission patterns, especially those in sub-Saharan Africa, conduct an MIS every two years within six weeks of the end of the rainy season. In Zambia, this corresponds to survey field work during the months of April and May.

Objectives

The goal of the 2012 Zambia MIS was to evaluate progress toward achieving the goals and targets set forth in the NMSP 2011–2015. The specific objectives were:

1. To collect up-to-date information, building on the experience of the MIS 2006, 2008, and 2010 on coverage of the core malaria interventions included in the NMSP 2011– 2015.

2. To assess malaria parasite prevalence among children under age five years.

3. To assess the status of anaemia among the target populations (children ages 6 to 36 months).

4. To assess disparities in malaria intervention coverage and malaria parasite and anaemia prevalence among the surveyed population by location and other background characteristics.

5. To implement standardized, representative household survey methods.

6. To strengthen the capacity of the NMCC and local agencies involved in order to facilitate the implementation of surveys of this type in the future.

Sample design

The MIS 2012 covered household populations in Zambia. The design for the survey was a representative probability sample to produce estimates for the country as a whole, and for rural and urban populations separately. An additional oversample of rural areas aligned with IRS enumerated areas was also included in the sample. This was done to aid in evaluating the impact of IRS.

Zambia is administratively divided into 10 provinces. Each province is in turn subdivided into districts. Each district is further subdivided into constituencies and wards. In total, Zambia has 74 districts, 150 constituencies, and 1,421 wards. For statistical purposes each ward is subdivided into census supervisory areas (CSAs) that, in turn, are subdivided into standard enumeration areas (SEAs). The SEAs, which are geographical areas classified as either rural or urban, have information on the number of households and the population size. This demarcation is done through a mapping exercise.

The MIS 2012 was based on the sampling frame from the 2010 census of population and housing conducted by the Central Statistics Office (CSO 2012). The sampling frame has 25,631 SEAs and 2,815,897 households. The number of households was used as a measure of size for selecting primary sampling units.

Sample sizes have been calculated with the assumption that future cross-sectional surveys will be conducted for comparison with these results. Sample size determination is based on an expected reduction in parasitaemia levels among rural populations from the 2010 MIS results and according to the MIS Sampling Guidelines documentation (RBM 2005). The MIS conducted in Zambia in 2010 provided a national severe anaemia (measured as haemoglobin less than 8 g/dl) prevalence of 9% and a malaria parasite (measured by slide microscopy) prevalence of 16% for children under age 5. For rural areas, the estimates were 10.2% and 20.4%, respectively. With an estimated 77% of households with at least one child under age 5 (and assuming 46% with a children aged 6 to 36 months), the sample size used for the MIS was determined using 95% confidence limits, 80% power, a design effect of 2.00, and 20% adjustment for non-response (from household refusals, or abandoned households). Based on these criteria, a 10% relative standard error requires at least 2,600 households in the rural domain.

The 2012 MIS sampled additional rural households within IRS-targeted areas identified through enumerations carried out by NMCC since 2008. Including these additional households helped determine the extent to which IRS has benefited communities in Zambia through reductions in malaria burden. IRS oversampling was drawn from among the 836 clusters from rural, IRS-targeted areas of districts so that at least 600 total households (24 SEAs) would be included. The remaining allocation of MIS 2012 SEAs were assigned to an urban domain, which accounted for an additional 800 households (32 SEAs).

To achieve the sample’s total requirement of 4,000 households, 25 households were selected from each of 160 SEAs. A first-stage selection of the SEAs was conducted by the CSO according to the specified domains. A second-stage sampling was conducted at the time of field work using personal digital assistants (PDAs) fitted with geo-positioning units. All households within an SEA were digitally listed, and a random sample of 25 households per SEA was selected for interviewing from all households listed. Every attempt was made to conduct interviews in the 25 selected households and, if any eligible interviewee was absent, up to three visits were made to complete the interview. This was done to minimize potential bias from non-response.

Questionnaires

Two questionnaires were used for the Zambia MIS 2012: the household questionnaire and the women’s questionnaire. The content of each was based on model questionnaires developed by the MEASURE DHS+ programme and adopted and recommended for use by the RBM MERG Task Force on Household Surveys.

The household questionnaire was used to list all usual members and visitors of the selected households. Some basic characteristics of each person were collected, including his or her age, sex, education level, and relationship to the head of the household. The main purpose of the household questionnaire was to identify women who were eligible to answer the women’s questionnaire (all women 15 to 49 years of age were eligible). Malaria-specific issues covered in the household questionnaire included:

Fever prevalence and treatment-seeking behaviour for all household members.

IRS.

ITNs, including household possession, net treatment status, and use of nets among all household members.

The women’s questionnaire was used to collect information from all women aged 15 to 49. It included the following topics:

Background characteristics (e.g., education level, asset-based wealth index).

Reproductive and birth history, pregnancy status.

General malaria knowledge.

IPT for pregnant women.

Fever prevalence among children under five years of age and fever treatment with antimalarial drugs.

Questionnaires were programmed into PDAs to eliminate the need for paper transcribing, to allow quicker data tabulation, and to facilitate faster interviewing from available skip patterns.

For the purposes of the household listing, each individual was assigned a unique identification code at the time of questionnaire administration.

Malaria parasite and anaemia testing

All health professionals recruited from the MOH received standardized training to conduct finger pricks for anaemia and malaria parasitaemia testing among children under six years of age in every household sampled. Sampling in children under age six years ensured that all children under age five years—the target population—were captured. Every effort was made to prevent secondary infection from the finger stick by using new disposable lancets for each child and by cleaning the finger with an alcohol swab. Field teams were provided with sufficient supplies for this throughout the field work. In addition, the field staff were provided with a fresh pair of latex gloves for each child receiving a finger stick. The purpose of the MIS was explained and, only if parental consent was given, a finger prick was conducted.

The first drop of blood was wiped from the finger, the second drop was used to prepare a thick blood smear, the third drop was used in the HemoCue® photometer to determine the child's haemoglobin level, and the fourth drop was applied to a rapid diagnostic test (RDT)— First Response® Malaria AG HPR2, Premier Medical Corp., Ltd. A final drop was placed on filter paper for later molecular confirmation of diagnosis and parasite species if needed.

Results from the anaemia testing and RDTs were available immediately to the parents or caregivers of the child. Thick blood smears were fixed after drying and the blood smears were stained with Giemsa stain. All stained slides were read by two independent microscopists masked from RDT results. Slides with discrepant reader results or with discrepant RDT results were reanalysed by a third microscopist for final validation.

Diagnosis and treatment algorithm

Zambia’s NMCC has a policy of expanding the use of RDTs for malaria diagnosis in conjunction with the use of Coartem® (a fixed dose combination of artemether 20mg and lumefantrine 120mg) for primary treatment of malaria in those with a positive RDT result; the Zambian-approved ICT Malaria Pf RDT was used to guide treatment of parasitaemic children during the survey.

Haemoglobin results were shared with the parent/guardian. If a child had a haemoglobin level of less than 7g/dl and a negative RDT, the parent/guardian was given written results, and the child was given an appropriate two-week dosage of daily iron and folate and chewable mebendazole and referred to a health centre. Medendazole is given as a presumptive treatment of helminthic infections and is only given to children at least 12 months of age as per the Integrated Management of Childhood Illnesses (IMCI) guidelines.

Children with a positive RDT result who did not clinically fit into the severe malaria classification (severe anaemia, prostration, impaired consciousness, respiratory distress, convulsions, circulatory collapse, abnormal bleeding, jaundice, and passing black/brown [dark] urine) received immediate treatment for malaria using Coartem®, an artemisinin-containing combination antimalarial treatment, according to Zambia national treatment guidelines. Treatment was administered by the MOH nurses who were members of each field team. Further, children with a positive RDT result who were classified as having simple malaria with mild to moderate anaemia (Hb between 8–11.5 g/dL) were treated with Coartem® and given a two-week course of folic acid ONLY and no ferrous sulphate. Children clinically assessed by the survey nurse as having severe malaria were transported immediately to the nearest health centre. Children already treated with Coartem® within the past two weeks were referred to the nearest facility for additional evaluation. Children who were found to be seriously ill, as determined by the survey nurses, were provided transportation to the nearest health facility.

HemoCue® and RDT testing were done according to manufacturer recommendations. Blood smears were stained with Giemsa stain prepared in advance of the field work by the NMCC.

Parasite densities were calculated by counting the number of asexual-stage parasites per 200+ white blood cells (WBCs) and assuming 8,000 WBCs per decilitre of blood. Where there were fewer than 10 parasites per 100 fields, the slides were read up to a threshold of 500+ WBCs. Blood smears were considered negative if no parasites were found after counting 200 fields.

Personal digital assistants

PDAs were used for the second-stage sampling and recording of questionnaires and for malaria parasite and anaemia testing results. Dell Axim X51s PDAs were used for data collection. Programming of the questionnaire was done for the Windows Mobile 5.0 operating system using Visual Basic and SQL Mobile by the US Centers for Disease Control and Prevention (CDC), Atlanta, USA. A further programme was used for second-stage household sampling and included a navigation component to facilitate field staff returning to selected households for interviewing.

Community sensitization

To prepare surveyed communities for impending field work including a finger stick for anaemia and parasite testing, a series of community sensitization measures were undertaken. These included a general informational letter and accompanying flyer distributed to districts and local communities. These documents included information about the purpose, the procedures, and the importance of household participation. Further, a series of radio spots was developed in seven local languages and aired on both national and local community radio stations with service areas matching the selected SEAs. The radio spot contained a 45-second message from the MOH introducing the survey, describing the importance of doing finger sticks to determine parasitaemia and anaemia among children, and encouraging participation.

Training, pretest activities, and field work

Data collection for the MIS took place in April and May 2012. Fifteen interviewing teams carried out the field work. Each team included at least two health professionals and two lab technicians. Health professionals were selected by district health management teams from districts represented within the sampling frame, with the intent of having field staff from within, or close to, selected SEAs. These health professionals, primarily female registered nurses, were responsible for conducting household interviews. Teams were assigned to each of the ten provinces, with additional teams allocated for working among the larger provinces as the selection determined.

Training was conducted in Lusaka during the last two weeks of March 2012. The training was coordinated by NMCC, MACEPA, WHO, and other partners as appropriate. The training schedule included sessions on survey background, questioning methods, the questionnaire, testing procedures, and the second-stage cluster-level sampling of households. PDAs were introduced to the field staff on the first day of training and used through all the training sessions to familiarize participants with each procedure. Central and provincial statistical officers were called upon to provide support in identifying local cluster boundaries.

A field pretest of all survey procedures was conducted at the end of the training week in a set of clusters near the training centre. All participants in the training exercise were pre-arranged into groups corresponding to their field work assignments. During the pretest, full enumeration areas (SEAs not otherwise included in the survey sample) were listed and interviewed. Each team practiced performing the household listing, joining listed households from several PDAs into one PDA, and conducting interviews and testing procedures.

Ethical approval

Individual consent was obtained before starting the household and women’s questionnaires and blood draws. The attached questionnaire and consent forms were used to obtain consent. The attached consent form was previously used in the MIS 2008.

The Research Ethics Committees of the University of Zambia (Ref: 002-03-12), on behalf of the MOH in Zambia, PATH on behalf of the MACEPA project, and the CDC reviewed and either approved the protocol or approved it as non-research evaluation.

Chapter 2: Characteristics of households and women respondents

Characteristics of households

The Zambia MIS 2012 collected data on basic demographic and socioeconomic characteristics of the population in the sampled households as well as information on housing facilities and conditions. This information was used in constructing an asset-based wealth index for interpretation of survey results. The criteria used to form the wealth index were based on work done previously by the World Bank and ORC Macro through the MEASURE DHS project.

For this survey, a household was defined as a person or group of persons, related or unrelated, who live together in the same dwelling unit (under one household head) and share a common source of food. The household questionnaire collected information on all usual residents and visitors who spent the night preceding the survey in the household.

Table 1 presents the de facto household population by five-year age groups according to sex and residence. The data show that there are slightly more women in Zambia than men, comprising 52.4% and 47.6%) of the population, respectively. The population under age 15 years makes up about 46.8% of the total population. One important finding is the gap between the percentage of males and females at the 20–24 and the 25–29 age groups (Figure 1), especially in urban areas. The gap indicates there are more women than men in both of these age groups.

Table 1. Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to gender and residence (Zambia 2012)

Urban Rural Total

Age Male Female Total Male Female Total Male Female Total

(1) (2) (3) (4) (5) (6) (7) (8) (9)

0–4 16.3 15.5 15.9 23.2 21.0 22.0 20.4 18.7 19.5

5–9 12.1 13.3 12.7 16.5 16.0 16.3 14.7 14.9 14.8

10–14 12.3 12.9 12.6 11.9 12.8 12.4 12.1 12.8 12.5

15–19 10.9 10.4 10.7 7.0 7.7 7.4 8.6 8.9 8.7

20–24 8.1 10.7 9.5 6.2 8.0 7.2 7.0 9.2 8.1

25–29 9.1 10.3 9.7 6.6 6.7 6.7 7.8 8.2 7.9

30–34 7.3 7.2 7.3 6.1 6.6 6.4 6.6 6.9 6.8

35–39 6.7 5.8 6.2 5.7 4.9 5.3 6.1 5.3 5.7

40–44 5.6 3.2 4.3 4.6 3.4 4.0 5.0 3.3 4.1

45–49 3.7 2.9 3.3 3.2 2.9 3.1 3.4 2.9 2.8

50–54 2.9 3.4 3.2 2.5 2.6 2.6 2.7 2.9 2.8

55–59 2.5 1.6 2.0 1.6 1.8 1.7 2.0 1.7 1.8

60–64 1.2 1.1 1.1 1.7 1.5 1.6 1.5 1.3 1.4

65–69 0.4 0.5 0.4 1.0 1.6 1.3 0.7 1.1 0.9

70–74 0.4 0.5 0.4 0.7 0.9 0.8 0.6 0.7 0.7

75–79 0.4 0.4 0.4 0.7 0.9 0.8 0.6 0.7 0.6

80+ 0.2 0.2 0.2 0.7 0.6 0.6 0.5 0.4 0.5

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Table 1. Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to gender and residence (Zambia 2012)

Urban Rural Total

Age Male Female Total Male Female Total Male Female Total

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Number 1,587 1,838 3,425 6,467 7,036 13,503 8,054 8,874 16,928

Figure 1. Age pyramid of sampled population of Malaria Indicator Survey (Zambia 2012)

222018161412108642024681012141618202224

0–4

5–9

10–14

15–19

20–24

25–29

30–34

35–39

40–44

45–49

50–54

55–59

60–64

65–69

70–74

75–79

80+

Percentage

A ge

Male Female continued

Table 2 presents the household composition among those surveyed. The percent of households headed by men was similar for both rural and urban areas. In the distribution of the number of usual household members, rural and urban areas are also very similar, except for households with two or three members.

Table 2. Household composition Percent distribution by sex of head of household and by household size, according to residence (Zambia 2012)

Residence

Characteristic Urban Rural Total

(1) (2) (3)

Sex of head of household

Male 75.6 74.4 74.9

Female 24.4 25.6 24.1

Number of usual members

1 8.9 9.6 9.3

2 11.5 12.9 12.3

3 13.5 15.1 14.4

4 18.3 17.8 18.0

5 15.6 14.9 15.2

6 12.7 12.1 12.4

7 9.3 7.6 8.3

8 5.1 5.1 5.1

9+ 5.0 5.0 5.0

Total 100.0 100.0 100.0

Number 750 3,050 3,800

Table 3 shows that nearly two-thirds (63.0%) of urban households reported having electricity, compared to 5.3% of rural households. Nationally, the most common sources of drinking water were unprotected wells (23.4%), public taps or standpipes (14.7%), protected wells (13.4%), and water piped into yard or plot (13.3%). In rural areas, the most common sources of drinking water were unprotected wells (33.3%) and tube wells or boreholes (19.0%), while urban households mostly reported using water sources piped into yard or plot (30.7%), public taps or standpipes (29.3%), or water piped into the dwelling (19.1%). The most common toilet facilities reported in households were open pits or pit latrines without slabs (37.3%) or pit latrines with slabs (23.4%). The majority of both urban and rural households surveyed had earth, sand, or dung floors (55.4%) or cement floors (40.5%).

Table 3. Household characteristics Percent distribution of households by household characteristics, according to residence (Zambia 2012)

Residence

Household characteristic Urban Rural Total

(1) (2) (3)

Electricity

Yes 63.0 5.3 28.7

No 37.0 94.7 71.3

Source of drinking water

Piped into dwelling 19.1 0.4 7.9

Piped into yard/plot 30.7 1.4 13.3

Public tap/standpipe 29.3 4.8 14.7

Tube well or borehole 2.0 19.0 12.1

Protected well 8.0 17.1 13.4

Unprotected well 8.8 33.3 23.4

Protected spring 0.2 0.9 0.6

Unprotected spring 0.3 10.7 6.4

Rainwater 0.0 0.1 0.0

Surface water (river/dam/lake/spring/pond)

1.1 12.0 7.6

Bottled water 0.0 0.0 0.0

Other 0.5 0.4 0.4

Sanitation facilities

Flushed to pipe sewer system

21.4 0.6 9.0

Flushed to septic tank 12.7 0.5 5.5

Flushed to pit latrine 1.2 0.1 0.5

Flushed to somewhere else 0.3 0.1 0.2

Ventilated improved pit latrine

3.5 0.9 1.9

Pit latrine with slab 39.9 12.1 23.4

Pit latrine without slab/open pit

17.7 50.6 37.3

Hanging toilet/hanging latrine

0.0 0.4 0.3

No facility/bush/field 2.9 33.8 21.3

Other 0.4 0.8 0.6

Flooring material

Earth/sand/dung 13.9 83.6 55.4

Wood planks 0.0 0.0 0.0

Parquet or polished wood 0.0 0.0 0.0

Vinyl or asphalt strips 0.4 0.0 0.2

Ceramic tiles 5.5 0.2 2.4

Table 3. Household characteristics Percent distribution of households by household characteristics, according to residence (Zambia 2012)

Residence

Household characteristic Urban Rural Total

(1) (2) (3)

Flooring material (continued)

Cement 77.9 15.0 40.5

Carpet 0.8 0.2 0.4

Other 1.5 1.0 1.1

Total 100.0 100.0 100.0

Table 4 shows that nearly 60% of Zambian households possess a radio. Just over half (50.5%) of households have either a landline telephone or a cell phone, including more than three-quarters (76.1%) of households in urban areas.

Table 4. Household durable goods, livestock, and land ownership Percent of households possessing various durable consumer goods, any livestock, and land ownership, by residence (Zambia 2012)

Residence

Household characteristic Urban Rural Total

(1) (2) (3)

Radio 77.9 47.4 59.8

Television 65.6 13.3 34.5

Telephone or cell phone 76.1 33.1 50.5

Refrigerator 41.9 2.7 18.6

Bicycle 46.8 20.4 36.1

Motorcycle 1.4 0.7 1.0

Car/truck 10.2 1.3 4.9

Any livestock 87.4 42.4 60.6

Owns land 76.9 13.6 39.2

None of the above 23.1 3.4 15.4

Wealth index

The “wealth index” is used to present results in this survey and is a proxy measure of the relative standard of living. In the MIS 2012, the wealth index is based on the reported household ownership of consumer goods and assets, household characteristics such as the type of household toilet facilities and available source of drinking water, and other characteristics that may relate to the household’s relative socioeconomic status. The wealth index was created by assigning a factor weight to each asset or characteristic generated through principal component analysis. The factors were summed for each household, creating a total score, which was subsequently ranked and divided into quintiles from one (lowest) to five (highest). The index was based on data from each household for the entire sample and the wealth index is presented for each set of indicators in the report.

Characteristics of women respondents

Eligible women ages 15 to 49 years were interviewed using the women’s questionnaire.

Table 5 shows that a majority (58.5%) of women were ages 15 to 29 years, and more than half of them lived in rural areas (52.6%). More than half of the women reported less than a secondary-level education (56.0%). The women surveyed were mainly Protestants (62.5%) or Catholics (19.5%), and women most often cited belonging to either the Bemba (33.4%), Nyanja (13.7%), or Tonga (12.6%) ethnic groups.

Table 5. Background characteristics of women respondents Distribution of women ages 15 to 49 years by background characteristics (Zambia 2012)

Characteristic Percent Number

(1) (2)

Age

15–19 17.8 581

20–24 21.5 657

25–29 19.2 586

30–34 16.2 527

35–39 11.9 380

40–44 7.5 276

45–49 5.9 193

Residence

Rural 52.6 2,450

Urban 47.4 750

Province

Central 6.4 306

Copperbelt 17.8 318

Eastern 12.8 512

Luapula 7.8 366

Lusaka 19.5 384

Muchinga 6.6 193

Northern 8.5 373

North-Western 4.8 181

Southern 12.2 392

Western 3.7 175

Education

No education 10.3 450

Primary 45.7 1,678

Table 5. Background characteristics of women respondents Distribution of women ages 15 to 49 years by background characteristics (Zambia 2012)

Characteristic Percent Number

(1) (2)

Secondary 39.2 974

Higher 4.8 98

Religion

Catholic 19.5 635

Protestant 62.5 1,950

Muslim 0.3 7

Traditional 0.4 17

Other 17.2 591

Ethnic group

Bemba 33.4 1,065

Tonga 12.6 437

North-Western 8.0 243

Baroste 6.4 227

Nyanja 13.7 382

Mambwe 2.9 87

Tumbuka 5.6 172

Other 17.4 587

Total 100.0 3,200

Chapter 3: Coverage of key malaria interventions

Malaria control efforts in Zambia are focused around selected interventions. These include providing prompt, effective treatment with artemether-lumefantrine (ART-LUM) within 24 hours of symptom onset. Malaria transmission is prevented through two primary means:

1) the use of ITNs, targeted in rural areas, and 2) IRS, targeted in urban or peri-urban areas in 36 districts during 2008–2009 (up from 15 during 2005–2007). These efforts are complemented by specific interventions for pregnant women—namely provision of ITNs at no cost to beneficiaries at antenatal clinics (ANCs) and provision of IPT with sulfadoxine-pyrimethamine (SP).

Ownership of mosquito nets and ITNs

The national vision for ITN distribution is to have universal coverage for all people where the potential exists for malaria transmission. In Zambia, universal coverage is defined as ensuring that all sleeping spaces in all households are covered by an ITN. In order to achieve high coverage, various delivery methods have been adopted. These include mass distribution campaigns, malaria in pregnancy, equity which targets vulnerable groups (orphans, aged, chronically ill), Community Malaria Booster Response (COMBOR), Malaria School Health Programme, and commercial market distribution for sustainability. The mass distribution campaigns have been implemented since late 2005 with expected replacements after approximately three years of use. These campaigns have been conducted in all districts in all ten provinces over the past several years as funding for ITNs has become available.

The ownership and use of mosquito nets, whether insecticide-treated or not,1 is the primary prevention strategy for reducing malaria transmission in areas of Zambia where IRS is not targeted. Table 6 shows that 72.1% of households in Zambia had a mosquito net, with 69.5% of households having a net that had been treated with insecticide at some time. More importantly, 68.1% of households had an ITN and 56.9% had more than one ITN. The average number of ITNs per household was 2.4. Ownership of nets (all categories) was typically higher in rural than urban areas, suggesting the prioritization of rural areas through mass distribution has been largely successful. For example, average number of ITNs per urban household was 2.10, compared to 2.56 in rural areas. In Luapula Province, 93.5% of households reported having at least one mosquito net, and 90.0% of households reported owning at least one ITN. This is the highest percentage of mosquito net and ITN ownership reported among the provinces, owing partly to distribution efforts in 2011 by STEPS-OVC and the MOH of ITNs provided by the UK Department for International Development (DFID).

Northern and Eastern provinces also benefited from large ITN distributions in 2011, distributed by the MOH, STEPS OVC, and other local partners, with ITNs supplied by financing from the Global Fund to Fight HIV, TB and Malaria (GFATM) and the World Bank.

Malaria control programme partners place the largest emphasis of ITN distribution on the mass distribution strategy. This promotes full coverage of vulnerable populations, such as children and pregnant women, but also seeks to prevent transmission among other household members. The mass distribution is a ‘pro-poor’ strategy in that poorer households reported larger number of ITNs across all indicators of ownership than wealthier households.

1 An insecticide-treated net (ITN) is 1) a factory-treated net that does not require any treatment, 2) a pretreated net obtained within the past 12 months, or 3) a net that has been soaked with insecticide within the past 12 months.

Table 6. Ownership of mosquito nets Households with at least one and more than one mosquito net (treated or untreated), ever-treated mosquito net, and insecticide-treated net (ITN), and average number of nets by each type per household, by background characteristics (Zambia 2012)

Background characteristic

Percentage of households that have at least one net

Percentage of households that have more than one net

Average number of nets per household

Percentage of households that have at least one ever-treated net

Percentage of households that have more than one ever-treated net

Average number of ever-treated nets per household

Percentage of households that have at least one

ITN1

Percentage of households that have more than one ITN

Average number of ITNs per household Number of households

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Residence

Urban 67.0 56.7 2.32 64.4 54.1 2.19 62.3 52.2 2.10 750

Rural 75.6 62.8 2.68 73.0 61.0 2.59 71.9 60.2 2.56 3,050

Province

Central 58.6 45.7 1.73 55.7 42.7 1.56 55.7 42.7 1.56 241

Copperbelt 68.4 60.3 2.40 68.1 60.2 2.39 62.4 55.4 2.39 358

Eastern 88.0 80.1 3.52 87.6 79.7 3.51 87.5 79.5 3.50 571

Luapula 93.5 85.3 3.88 90.2 82.6 3.76 90.0 82.6 3.76 410

Lusaka 58.1 47.7 1.87 55.8 44.9 1.74 55.4 44.6 1.74 416

Muchinga 74.3 65.5 2.75 62.7 54.0 2.25 62.2 53.6 2.23 254

Northern 83.9 69.0 3.03 83.1 69.0 3.01 83.1 69.0 3.01 415

North- Western

77.8 67.1 2.77 77.8 67.1 2.77 77.8 67.1 2.77 212

Southern 68.3 46.5 2.03 65.3 45.3 1.96 63.7 43.5 1.88 506

Western 63.2 48.7 2.01 55.9 45.4 1.84 51.9 41.9 1.70 242

Table 6. Ownership of mosquito nets Households with at least one and more than one mosquito net (treated or untreated), ever-treated mosquito net, and insecticide-treated net (ITN), and average number of nets by each type per household, by background characteristics (Zambia 2012)

Background characteristic

Percentage of households that have at least one net

Percentage of households that have more than one net

Average number of nets per household

Percentage of households that have at least one ever-treated net

Percentage of households that have more than one ever-treated net

Average number of ever-treated nets per household

Percentage of households that have at least one

ITN1

Percentage of households that have more than one ITN

Average number of ITNs per household Number of households

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Wealth index

Lowest 76.5 64.8 2.66 74.5 63.4 2.61 73.6 62.8 2.58 759

Second 76.3 61.2 2.59 73.9 59.8 2.52 72.6 58.7 2.48 763

Middle 71.3 60.5 2.51 67.6 57.7 2.40 66.7 56.6 2.35 758

Fourth 71.3 57.0 2.46 68.3 55.0 2.36 66.9 53.8 2.30 758

Highest 69.3 59.8 2.51 67.0 57.3 2.37 65.1 55.6 2.30 762

Total 72.1 60.3 2.53 69.5 58.2 2.43 68.1 56.9 2.38 3,800 1 An insecticide-treated net (ITN) is 1) a factory-treated net that does not require any treatment, 2) a pretreated net obtained within the past 12 months, or 3) a net that has been soaked with insecticide within the past 12 months.

Table 7 presents the household-level possession of long-lasting insecticidal nets (LLINs) that were obtained through mass distribution, dispensed at ANCs in the Malaria in Pregnancy programme, or purchased through the commercial sector. Of the available nets in households, most of the ITNs were LLINs across all areas and provinces.

Table 7. Household possession of long-lasting insecticidal nets (LLINs) Percentage of households with at least one and more than one LLIN, and average number of LLINs per household, by background characteristics (Zambia 2012)

Background characteristic

Percentage of households that have at least one

LLIN1

Percentage of households that have more than one LLIN

Average number of LLINs per household

Number of households

(1) (2) (3) (4)

Residence

Urban 59.1 49.3 1.99 750

Rural 71.5 59.8 2.55 3,050

Province

Central 55.7 42.7 1.54 241

Copperbelt 52.9 47.0 1.86 358

Eastern 87.4 79.5 3.50 571

Luapula 90.0 82.6 3.76 410

Lusaka 55.4 44.6 1.73 416

Muchinga 62.2 53.6 2.23 254

Northern 83.1 67.0 3.01 415

North-Western 77.8 67.1 2.77 212

Southern 63.6 43.3 1.88 506

Western 51.4 41.6 1.69 242

Wealth index

Lowest 73.6 62.8 2.58 759

Second 72.5 58.7 2.48 763

Middle 64.8 55.0 2.30 758

Fourth 64.6 51.8 2.23 758

Highest 62.7 53.4 2.21 762

Total 66.5 55.6 2.32 3,800

1A long-lasting insecticidal net (LLIN) is a factory-manufactured net that does not require any treatment.

Use of mosquito nets and insecticide-treated nets by children and pregnant women

In malaria-endemic areas, studies have shown that the use of ITNs, especially among the target populations of children under age five years and pregnant women, can result in a reduction in the occurrence of malaria episodes, all-cause child mortality, and complications associated with malaria during pregnancy. Zambia’s NMSP 2011–2015 set targets of 100% coverage and 85% usage among these populations. Attaining and maintaining high usage of ITNs is essential for reducing malaria transmission and malaria-related burden in Zambia.

In the MIS 2012, the use of ITNs was identified in each household by means of a complete net roster. The net roster identifies and lists each mosquito net available in the house, asks questions to ascertain its treatment status, and then asks about each individual that slept under that net the night before the survey. From this net roster method, the questionnaire gathers data on the use of nets the night before the survey for children, pregnant women, and all other household members.

Table 8 presents information on the use of mosquito nets by children. The results show that 59.9% of children under age five years were reported to have slept under a mosquito net the night before the survey, and 57.0% of children were reported to have slept under an ITN. In general, the results showed a higher net usage among younger (one year old) compared to older (two years old) age groups (Figure 2). This trend has been consistent as ITN use has increased among children under five over the past several years. Usage of ITNs was higher for children in rural areas (60.1%) than in urban areas (50.9%). Also, male children under age five years were equally as likely as females to have slept under a net or ITN.