2.1 Overview of the Malaria Indicator Survey (MIS)
The Malaria Indicator Survey (MIS) was devised by the Monitoring and Evaluation Working Group (MERG) of Roll Back Malaria, an international partnership dedicated to coordinating global endeavours against malaria. As an independent household survey, the MIS acquires comprehensive data at both national and regional or provincial levels from a representative sample of respondents. The MERG Survey and Indicator Guidance Task Force, led by the DHS Program, has significantly contributed to the development of the MIS package. This package encompasses questionnaires, manuals, and guidelines, all of which draw on materials from Demographic and Health Surveys. Additionally, The DHS Program actively participates in the implementation of the Malaria Indicator Survey and has established a website to disseminate information and data concerning Malaria Indicator Surveys worldwide. Notably, standardised malaria indicators are readily accessible in nearly 30 countries. The MIS comprehensively captures all internationally recognised malaria indicators, including the ownership and utilisation of insecticide-treated mosquito nets in households, especially among children under five years of age and pregnant women. It also assesses intermittent preventive treatment against malaria during pregnancy, the type and timing of treatment for high fever in children under five, indoor residual spraying of insecticide for mosquito control, and diagnostic blood testing for children under five with fever. Furthermore, the survey gathers supplementary information on indoor residual spraying (IRS) and background data on household member characteristics and ownership of assets such as electricity, bicycles, radios, and indoor plumbing. The majority of questions in the MIS instrument are derived from the Demographic and Health Surveys and the Multiple Indicator Cluster Surveys. Regarding malaria prevalence, the MIS can optionally include the measurement of malaria parasites and anaemia (a common outcome of malaria) among those at higher risk, namely children under five years and pregnant women. Specially trained interviewers collect a small blood sample from eligible respondents who consent to the tests. Anaemia is immediately tested in the field, and the results are promptly provided to respondents. Malaria testing, using both a rapid diagnostic test in the field and microscopy in a laboratory, is recommended in Malaria Indicator Surveys. Anaemia has been examined in over 60 DHS and MIS surveys, while malaria prevalence has been assessed in numerous MIS surveys and some DHS surveys. The timing of the MIS is generally synchronised with the high malaria transmission season, unlike the DHS, which is conducted at various times throughout the year. This alignment is crucial when the MIS includes biomarker testing for malaria. To facilitate the execution of a MIS, the Roll Back Malaria partnership has developed a MIS toolkit. This revised package comprises guidelines, questionnaires, manuals, and recommended tabulations for data analysis to support countries and organisations in conducting the survey ICF (ICF & U.S. Agency for International Development, 2023; Watson et al., 2019).
2.2 Study Design
This study is a quantitative, nationally representative cross-sectional analysis conducted using data from the MIS. By employing this approach, the study aimed to capture a comprehensive snapshot of the malaria situation at the national levels of the included countries, allowing for accurate and insightful assessments of the disease’s prevalence and related indicators.
2.3 Study settings and population
This study involves five SSA countries (Ghana, Nigeria, Niger, Senegal and Mali) (DHS 2021) and focuses specifically on under-five children (i.e., children aged five years or below). The included countries are displayed in Figure 1.
2.4 Data Collection
The primary data source for this study is the 2021 MIS data within the Demographic and Health Survey (DHS) program conducted in the selected countries. Data collection for the MIS involves a well-structured series of steps. First, experts in the field of malaria epidemiology and survey methodologies collaborate to design the survey. During this phase, they determine crucial aspects such as the appropriate sample size, sampling strategy, questionnaire content, and data collection tools. Before the data collection phase, enumerators, who are trained field staff responsible for conducting the survey, undergo comprehensive training. This training equips them with a clear understanding of the survey objectives, the tools used for data collection, how to approach households, and how to administer the questionnaire effectively. During the household data collection phase, enumerators visit the selected households and conduct face-to-face interviews with household members. They utilise structured questionnaires to gather detailed information on various malaria-related topics, including bed net ownership and usage, antimalarial treatment, prevention behaviours, and knowledge about malaria. In addition to the questionnaire, the Malaria Indicator Survey often includes the collection of biological samples, such as blood samples from household members. These samples play a crucial role in testing for malaria infection and confirming reported cases, providing valuable epidemiological data. To ensure the accuracy and reliability of the collected data, data quality assurance measures are implemented during the data collection phase. These measures include close supervision of enumerators, data validation checks, and cross-verification of responses to minimise errors. Once data collection is complete, the information gathered from the questionnaires and biological samples is entered into a database. Specialised statistical software is then used to analyse the data, generating meaningful insights and key indicators related to malaria prevalence and control. The final step involves disseminating the survey results to relevant stakeholders, including government authorities, health agencies, and international organizations. The data collected through the Malaria Indicator Survey is utilised to guide malaria control policies, allocate resources effectively, and monitor progress towards malaria elimination goals (ICF & U.S. Agency for International Development, 2023; Watson et al., 2019).
Sampling
The sampling process in the MIS aims to gather data from a representative sample of households within the target population. This is achieved through a two-stage cluster sampling approach. In the first stage, clusters, which are typically villages or enumeration areas, are randomly selected. Then, in the second stage, households within the chosen clusters are also randomly selected (ICF & U.S. Agency for International Development, 2023; Watson et al., 2019).
2.5 Variables
2.5.1 Dependent Variable
The dependent variable for this study is “under-five children who slept under ITN last night”, measured as a binary outcome (utilised/not utilised). It is derived from the statement “children under 5 slept under mosquito bed net last night”. Responses for the original variable were categorised as ‘no’, if no child from the household used ITN the previous night, ‘some children’ if at least one child used ITN the previous night, ‘all children’ if all the children in the household used ITN the previous night, and ‘no net in household’ to denote no ownership of a bed net in the household. This variable was recategorised as ‘utilised’ to cover the responses ‘all children’ and ‘some children’, and ‘not utilised’ to include the ‘no’ response. While the ‘no net in household’ response was dropped to ensure data quality and relevance. Additionally, cases with missing or incomplete data on key variables of interest were also dropped from the analysis to promote valid and reliable analysis.
2.5.2 Independent Variables
The main independent variables were household characteristics: gender of household head, age of household head, marital status of household head, household size, and the number of rooms used for sleeping. Additionally, the influence of socio-demographic factors, such as mother’s educational level, wealth index, and type of residence (urban/rural) on ITN use was also examined.
The gender of the household head variable captures the gender of the head of the household, indicating whether the household is headed by a male or female. The age of the household head (<20, 20-29, 30-39, 40-49, 50-59, and 60+) refers to the chronological age of the individual who is considered the primary decision-maker or leader of a household. Household head’s marital status refers to information on the marital status of the household head. It places the household head into one of either never married, married, divorced or widowed categories. Household size (1-3, 4-6, 7-9, and 10+) referred to the total number of individuals living in the household, including children, adults, and elderly members. The number of rooms used for sleeping (1-2, 2-4, 5-6, 7-9, and 10+) denotes the total number of rooms in the household designated for sleeping purposes and provides insights into the living conditions and overcrowding within the households. Mother’s educational level (No education, Primary, Secondary, and Higher) represents the educational attainment of the mother in the household. It can range from no formal education to varying levels of formal education, such as primary, secondary, or higher education. Wealth index (Poorest, Poorer, Middle, Richer, and Richest) is a composite measure used to assess the economic status of households and was constructed based on various indicators, such as household assets, access to basic services, and living conditions. Type of residence (Urban/Rural) categorises households based on their location, indicating whether they are situated in urban or rural areas.
2.6 Statistical Analysis
Pre-analysis data quality checks were conducted, where a multicollinearity analysis was conducted to identify potential risk factors that might exhibit collinear relationships, thereby impacting the regression model. However, the results of the multicollinearity analysis indicated that the variables related to ITN usage among children under-5 exhibited a variance inflation factor below 3. Thus, the data did not provide any indication of multicollinearity among the variables included in the model.
Descriptive statistics was used to summarise the characteristics of the study sample and the prevalence of ITN utilisation. Multivariate logistic regression analysis was performed to assess the independent effect of each variable on ITN utilisation while controlling for potential confounding factors. Adjusted odds ratios (AORs) and their corresponding 95% confidence intervals (CIs) were reported to measure the strength and significance of the associations.
2.7 Ethical Considerations
This study obtained permission from the Demographic and Health Survey program and adhered to the ethical guidelines outlined by the DHS to maintain the confidentiality and anonymity of survey participants. Since the data used is secondary and publicly available, ethical approval was not required for this study.