Malaria indicator survey 2007, Ethiopia: Coverage and use of major malaria prevention and control interventions

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Study Justification:
The study aimed to assess the coverage, use, and access to major malaria prevention and control interventions in Ethiopia. This was important because in 2005, a nationwide survey showed low ownership of insecticide-treated nets (ITNs), low coverage of indoor residual spraying (IRS), and low use of anti-malarial drugs. The government had set ambitious goals to scale up these interventions, and this study aimed to evaluate the progress and identify areas for improvement.
Highlights:
– The study found that 65.6% of households in malarious areas owned at least one ITN.
– Among ITN-owning households, 53.2% of all persons had slept under an ITN the prior night.
– 20.0% of households reported having IRS in the past 12 months.
– Only 16.3% of children with fever sought medical attention within 24 hours.
– 11.9% of those with fever took an anti-malarial drug, and only 4.7% took it within 24 hours of fever onset.
– The prevalence of parasitaemia was 1.0% among surveyed individuals of all ages.
– 6.6% of children under 5 years of age had moderate-severe anaemia.
Recommendations:
– Sustain and expand malaria intervention coverage.
– Increase intervention access and use.
– Strengthen case management for children with fever, including prompt treatment and referral if needed.
– Improve community awareness and education on malaria prevention and control.
– Enhance monitoring and evaluation of malaria interventions.
Key Role Players:
– Ethiopian National Malaria Control Programme
– Ministry of Health
– Non-governmental organizations (NGOs) working on malaria control
– Community health workers
– Health facility staff
– Researchers and academics
Cost Items for Planning Recommendations:
– Procurement and distribution of insecticide-treated nets
– Indoor residual spraying activities
– Training and capacity building for health workers
– Community mobilization and education campaigns
– Monitoring and evaluation activities
– Research and data collection
– Infrastructure and logistics support
Please note that the cost items provided are general categories and not actual cost estimates. The actual costs will depend on the specific context and implementation strategies.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a nationally representative malaria indicator survey conducted in Ethiopia. The survey used a two-stage random cluster sample of 7,621 households in 319 census enumeration areas, with a total of 32,380 participants. The data collected provides information on coverage, use, and access to malaria prevention and control interventions. The survey methodology follows RBM MERG guidelines with some local modifications. The abstract presents key findings on ITN ownership and usage, indoor residual spraying, treatment seeking behavior, parasite prevalence, and anaemia prevalence. The evidence is based on a large sample size and standardized data collection tools. However, the abstract does not provide information on the sampling strategy, response rate, or representativeness of the sample. To improve the evidence, the abstract should include these details and provide more information on the validity and reliability of the survey findings.

Background. In 2005, a nationwide survey estimated that 6.5% of households in Ethiopia owned an insecticide-treated net (ITN), 17% of households had been sprayed with insecticide, and 4% of children under five years of age with a fever were taking an anti-malarial drug. Similar to other sub-Saharan African countries scaling-up malaria interventions, the Government of Ethiopia set an ambitious national goal in 2005 to (i) provide 100% ITN coverage in malarious areas, with a mean of two ITNs per household; (ii) to scale-up indoor residual spraying of households with insecticide (IRS) to cover 30% of households targeted for IRS; and (iii) scale-up the provision of case management with rapid diagnostic tests (RDTs) and artemisinin-based combination therapy (ACT), particularly at the peripheral level. Methods. A nationally representative malaria indicator survey (MIS) was conducted in Ethiopia between September and December 2007 to determine parasite and anaemia prevalence in the population at risk and to assess coverage, use and access to scaled-up malaria prevention and control interventions. The survey used a two-stage random cluster sample of 7,621 households in 319 census enumeration areas. A total of 32,380 people participated in the survey. Data was collected using standardized Roll Back Malaria Monitoring and Evaluation Reference Group MIS household and women’s questionnaires, which were adapted to the local context. Results. Data presented is for households in malarious areas, which according to the Ethiopian Federal Ministry of Health are defined as being located <2,000 m altitude. Of 5,083 surveyed households, 3,282 (65.6%) owned at least one ITN. In ITN-owning households, 53.2% of all persons had slept under an ITN the prior night, including 1,564/2,496 (60.1%) children <5 years of age, 1,891/3,009 (60.9%) of women 15 – 49 years of age, and 166/266 (65.7%) of pregnant women. Overall, 906 (20.0%) households reported to have had IRS in the past 12 months. Of 747 children with reported fever in the two weeks preceding the survey, 131 (16.3%) sought medical attention within 24 hours. Of those with fever, 86 (11.9%) took an anti-malarial drug and 41 (4.7%) took it within 24 hours of fever onset. Among 7,167 surveyed individuals of all ages, parasitaemia as estimated by microscopy was 1.0% (95% CI 0.5 – 1.5), with 0.7% and 0.3% due to Plasmodium falciparum and Plasmodium vivax, respectively. Moderate-severe anaemia (haemoglobin <8 g/dl) was observed in 239/3,366 (6.6%, 95% CI 4.9-8.3) children <5 years of age. Conclusions. Since mid-2005, the Ethiopian National Malaria Control Programme has considerably scaled-up its malaria prevention and control interventions, demonstrating the impact of strong political will and a committed partnership. The MIS showed, however, that besides sustaining and expanding malaria intervention coverage, efforts will have to be made to increase intervention access and use. With ongoing efforts to sustain and expand malaria intervention coverage, to increase intervention access and use, and with strong involvement of the community, Ethiopia expects to achieve its targets in terms of coverage and uptake of interventions in the coming years and move towards eliminating malaria. © 2010 Jima et al; licensee BioMed Central Ltd.

The MIS was conducted from October through December 2007. The protocol for the MIS followed RBM MERG guidelines [13] with a few local modifications [14]. To generate nationally representative data, a stratified two-stage cluster sample design with census enumeration areas (EAs; comprising approximately 200 households) as primary sampling units was used, stratified by several domains, including altitude (i.e. <1,500 m vs. 1,500 – 2,500 m) and degree of urbanization (i.e. rural vs. urban). For Amhara and Oromia Regional States, there was over-sampling of EAs so that samples for estimating malaria indicators at regional state level could be generated. This was done to accommodate the needs of The Carter Center and the President's Malaria Initiative, who required regional-level indicator data to monitor implementation and impact of their respective programmes. The Carter Center is implementing comprehensive trachoma, onchocerciasis and malaria programme activities in Amhara Regional State [15], and Oromia is the focus regional state for the President's Malaria Initiative [16]. The sample size was determined using 95% confidence limits, 80% power, a design effect of 1.25, and 20% adjustment for non-response (i.e. from household refusals or abandoned households). In addition, the sample size assumed that 82% of households had children <6 years of age. Based on the above inputs and assumptions, a minimum sample of 5,650 households was determined to be necessary to obtain robust national level information for altitude and urbanization categories. An additional 2,875 households were included in order to get regional state estimates for Amhara and Oromia. Consequently, the total sample size of the survey was estimated to be 8,525 households. Taking into account sample precision, logistics and survey cost, it was decided that a randomly selected sample of 25 households per EA would be optimum; five households per EA could be additionally selected to compensate for absentee or abandoned households. Because of oversampling in some domains (e.g. in Oromia and Amhara) and because the number of sampled households in each EA was fixed, the sample was not self-weighting (i.e. each EA and each household did not have equal probability of selection). Therefore, weights were used to compensate for the resulting differential selection probabilities. Sampling weights were computed based on the implemented survey design as the inverse of the product of the sampling probability and indicator estimates were calculated using those weights. In each selected EA, all households were mapped, and 25 and five alternate households were randomly selected by personal digital assistants (PDAs) (Hewlett -Packard IPAQ HX249X, Palo Alto, CA, and Dell Axim-51, Round Rock, TX) equipped with global positioning systems (GPS). Interviews regarding malaria indicators were conducted in selected households. The MIS questionnaires, household listing, sampling framework, and navigation programmes were directly programmed into the PDAs using Windows Mobile 5.0 (Microsoft Corporation, Seattle) to allow for paper-free data collection. The programme on the PDAs enabled surveyors to enter second stage sampling (i.e. household listing within an EA, random selection of 25 households, household members) and navigate to selected households to complete interviewing and specimen collection and testing (see below). Surveyors were organized in 25 teams, with each survey team consisting of six people: four surveyors, one driver, and one team leader. Upon arrival in a selected community, sub-teams of two surveyors dispersed in different directions to map all the households. Some of the teams (i.e. those assigned to the most remote areas of the country) included one additional laboratory technician to process blood slides in the field. Each team carried a standard lot of supplies and materials, consisting of PDAs with their accessories, a map of selected EAs selected by the Central Statistical Authority, uniforms, reagents and instruments for sample collection, testing, and smear preparation, anti-malarial and anti-helminthic drugs, iron syrup or tablets, sensitization letters, and camping equipment. Teams were visited by supervisors in the field at least twice during the survey period. The objectives of the supervisory visits were to ensure the quality and quantity of data collected by surveyors. Supervisory visits included the following: 1) inspection of teams' PDA records; 2) random inspection of some households by navigating to and visiting completed households; 3) confirmation from the households of the records obtained from the survey; 4) completion of supervisory checklist by direct and indirect observation; and 5) observing a team's overall harmony and performance as well as providing feedback and sharing the experiences of other teams. The questionnaires used included two structured, pre-coded questionnaires with both closed- and open-ended questions: (i) a household questionnaire and (ii) a women's questionnaire. Both were based on RBM MERG MIS Questionnaires [13], modified to local conditions. The questionnaires were translated and printed in Amharic, Afaan Oromoo and Tigrigna languages and field-tested in non-survey EAs to determine the validity of the pre-coded answers. The household questionnaire was administered to the household head or another adult if the household head was absent or unable to respond for any reason, and collected the following data: socio-demographic information and listing of household members; house construction materials and design; ownership of durable assets; availability, source of origin, type, condition and use of household mosquito net(s) (verified by observation); and reported status of IRS. Additionally, the purpose of the household questionnaire was used to identify children <6 years of age for specimen collection as well as women aged 15 – 49 years who were eligible to answer the women's questionnaire. The women's questionnaire was administered to women aged 15 – 49 years identified from the household questionnaire and collected the following data: educational level; reproduction, birth history, and current pregnancy status; knowledge, attitudes and practices (KAP) on malaria preventive and curative aspects; reported history of fever among children <5 years of age (U5) in the previous two weeks; and reported treatment seeking behaviour for children U5 with fever. Blood samples were taken from all children <6 years of age and from all household members in every fourth household. All children <6 years of age were included to ensure that no children U5 were missed during the survey, and only data for children U5 are presented here. The malaria diagnostic tests included RDTs, blood slides for microscopic examination and haemoglobin level testing. RDTs were used in the survey to offer immediate treatment to individuals with a positive test. The RDT used (ParaScreen®, Zephyr Biomedical Systems, India) is a HRP2/pLDH-based antigen test detecting both Plasmodium falciparum and other Plasmodium spp. (in Ethiopia most likely Plasmodium vivax). Sensitivity and specificity of the test in operational conditions in Ethiopia were previously estimated to be 47.5% and 98.5%, respectively [17]. The specimen processing was organized in such a way that all three tests were performed simultaneously from a single finger prick. Two blood slides, thick and thin films (in duplicate), were taken for each participant by a laboratory technician as per standard WHO-approved protocol [18]. Slides were labelled and air-dried horizontally in a carrying case in the field, and stained with Giemsa at the nearest health facility when the team returned from the field usually on the same or the next day. Blood slides were read at a reference laboratory in Addis Ababa and classified qualitatively. One hundred high power fields of the thick film were examined before recording a slide as negative. If positive, the thin film was read to determine the species. To ensure accuracy, all positive slides and a random sample of 5% of the negative slides were re-examined by a second microscopist, who was blinded to the diagnosis of the first slide-reader. The second slide from each participant was used if the first was damaged or unreadable. An error in the auto-generate function of the PDAs led to a mislabelling of some slides, which subsequently could not be matched to their respective RDT results. Most slides, however, were able to be matched to at least the EA or household levels. For individual level analyses, EAs without 100% slide matches were excluded from the analyses. Anaemia testing followed the recommendations of the RBM MERG [19], with haemoglobin concentrations measured using a portable spectrophotometer (HemoCue®, Anglom, Sweden). The following anaemia classification was used: haemoglobin levels below 11 g/dl, 8 g/dl and 5 g/dl were classified as mild, moderate-severe and severe anaemia, respectively [19]. All individuals surveyed with positive RDTs were offered treatment according to the FMOH's National Diagnosis and Treatment Guidelines [20], i.e. artemether-lumefantrine combination therapy (CoArtem®, Novartis, Basel, Switzerland) for P. falciparum infection, chloroquine for other Plasmodium infections, and referral for clinic-based quinine therapy for self-reported pregnant women. For children diagnosed with moderate-severe anaemia (i.e. haemoglobin 24 months of age as per National Protocol for Integrated Maternal and Child Illnesses [21]) and a two-week supply of supplemental iron. All infants under four months with a positive RDT result and children with severe anaemia, haemoglobin <5 g/dl, were referred to the nearest health facility for further evaluation and treatment. Subjects who were found to be severely ill, as determined by the survey nurses, were consulted to immediately visit the nearest possible health facility. Survey data was downloaded from PDAs into a Microsoft ACCESS database (Microsoft Corporation, Seattle). Data management and analysis were carried out in SPSS 16.0 (SPSS, Inc., Chicago, IL), SAS 9.2 (SAS Institute Inc., Cary, NC), and STATA 9.2 (Stata Corporation, College Station, TX). Descriptive statistics were used to describe the characteristics of the sample and calculate coverage, use and access estimates. Point estimates and confidence intervals were derived using the PROC SURVEY (SVY) commands in SAS, which adjusts for clustering in the sampling design, with weighting for household and cluster sampling probability. The MIS 2007 protocol received ethical clearance from the Emory University Institutional Review Board (IRB# 6389), the U.S. Centers for Disease Control and Prevention Ethical Review Committee (IRB# 990132), the PATH Ethical Committee, and the Ethiopian Science and Technology Agency. Verbal informed consent to participate in interviews was sought from the heads of households and each eligible individual in accordance with the tenets of the Declaration of Helsinki. Verbal informed consent was sought from each eligible individual and parents of children <6 years of age for blood films. Additional verbal informed assent was sought from children aged 6-18 years.

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Based on the information provided, here are some potential innovations that could improve access to maternal health:

1. Mobile Health (mHealth) Solutions: Develop mobile applications or text messaging services to provide pregnant women with information on prenatal care, nutrition, and reminders for appointments and medication.

2. Community Health Workers: Train and deploy community health workers to provide education, counseling, and basic healthcare services to pregnant women in rural areas, where access to healthcare facilities may be limited.

3. Telemedicine: Implement telemedicine programs to connect pregnant women in remote areas with healthcare providers through video consultations, allowing them to receive prenatal care and advice without having to travel long distances.

4. Transportation Solutions: Develop transportation systems or partnerships to ensure that pregnant women have access to reliable and affordable transportation to healthcare facilities for prenatal visits and delivery.

5. Maternal Health Vouchers: Introduce voucher programs that provide pregnant women with subsidized or free access to prenatal care, delivery services, and postnatal care, reducing financial barriers to accessing maternal healthcare.

6. Maternal Waiting Homes: Establish maternal waiting homes near healthcare facilities to provide accommodation and support for pregnant women who live far away, allowing them to stay closer to the facility as they approach their due dates.

7. Integration of Services: Integrate maternal health services with other healthcare programs, such as family planning and immunization, to provide comprehensive care and improve access for pregnant women.

8. Public-Private Partnerships: Foster collaborations between the government, private sector, and non-profit organizations to leverage resources and expertise in improving access to maternal health services.

9. Health Education Campaigns: Conduct targeted health education campaigns to raise awareness about the importance of prenatal care, safe delivery practices, and postnatal care, addressing cultural and social barriers that may prevent women from seeking care.

10. Strengthening Health Systems: Invest in strengthening healthcare infrastructure, training healthcare providers, and ensuring the availability of essential medicines and equipment to improve the quality and accessibility of maternal health services.
AI Innovations Description
Based on the information provided, the recommendation to improve access to maternal health would be to focus on scaling up the coverage and use of major malaria prevention and control interventions in Ethiopia. This can be achieved through the following steps:

1. Increase ownership and distribution of insecticide-treated nets (ITNs): The survey showed that 65.6% of households owned at least one ITN. Efforts should be made to increase this coverage to ensure that all households in malarious areas have access to ITNs. Distribution campaigns and targeted interventions can be implemented to reach vulnerable populations, such as pregnant women and children under five years of age.

2. Scale up indoor residual spraying (IRS): Only 20% of households reported having IRS in the past 12 months. This intervention should be expanded to cover a larger proportion of households targeted for IRS. This can be achieved through increased funding, training of personnel, and community engagement to ensure acceptance and participation.

3. Improve case management with rapid diagnostic tests (RDTs) and artemisinin-based combination therapy (ACT): The survey showed that only 16.3% of children with fever sought medical attention within 24 hours, and only 11.9% took an anti-malarial drug. Efforts should be made to increase access to RDTs and ACT, particularly at the peripheral level. This can be achieved through training of healthcare providers, strengthening supply chains, and community education on the importance of early diagnosis and treatment.

4. Enhance community involvement: Strong involvement of the community is crucial for the success of malaria prevention and control interventions. Community members can be engaged through awareness campaigns, community health workers, and community-based distribution of ITNs and other interventions. This will help increase access and utilization of maternal health services.

By implementing these recommendations, Ethiopia can improve access to maternal health by reducing the burden of malaria and its impact on pregnant women and children. This will contribute to achieving the national goal of eliminating malaria and improving maternal and child health outcomes.
AI Innovations Methodology
To improve access to maternal health, here are some potential recommendations:

1. Increase the availability and distribution of insecticide-treated nets (ITNs) in malarious areas: This can be done through targeted distribution campaigns, partnerships with local communities and organizations, and ensuring sustainable supply chains for ITNs.

2. Scale-up indoor residual spraying (IRS) of households with insecticide: This involves spraying insecticides on the walls and ceilings of households to kill mosquitoes and reduce malaria transmission. Increasing the coverage of IRS can be achieved through government-led initiatives, community engagement, and training of local health workers.

3. Improve case management with rapid diagnostic tests (RDTs) and artemisinin-based combination therapy (ACT): This includes increasing the availability and accessibility of RDTs and ACTs at peripheral health facilities. Training healthcare providers on the use of RDTs and ACTs, as well as promoting community awareness and education on malaria diagnosis and treatment, can also contribute to improving case management.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the indicators: Identify key indicators related to access to maternal health, such as the percentage of pregnant women who receive antenatal care, the percentage of pregnant women who receive skilled birth attendance, and the percentage of pregnant women who receive postnatal care.

2. Collect baseline data: Gather data on the current status of these indicators in the target population. This can be done through surveys, interviews, and data analysis from existing health records.

3. Develop a simulation model: Create a mathematical or statistical model that incorporates the potential impact of the recommendations on the selected indicators. This model should take into account factors such as population size, geographical distribution, and existing healthcare infrastructure.

4. Input data and parameters: Input the baseline data and parameters related to the recommendations into the simulation model. This includes data on the coverage and use of ITNs, IRS, RDTs, and ACTs, as well as information on the target population and healthcare facilities.

5. Run simulations: Use the simulation model to run different scenarios that reflect the potential impact of the recommendations. This can involve adjusting the coverage and use of the interventions and observing the resulting changes in the selected indicators.

6. Analyze results: Analyze the simulation results to determine the potential impact of the recommendations on improving access to maternal health. This can include comparing the indicators before and after the implementation of the recommendations, as well as assessing the magnitude of the changes observed.

7. Validate and refine the model: Validate the simulation model by comparing the simulated results with real-world data, if available. Refine the model based on feedback and additional data to improve its accuracy and reliability.

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of the recommendations on improving access to maternal health. This can inform decision-making and resource allocation to prioritize interventions that are most likely to have a positive impact.

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