Factors associated with malaria care seeking among children under 5 years of age in Mozambique: a secondary analysis of the 2018 Malaria Indicator Survey

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Study Justification:
– Mozambique is ranked fourth among countries with the highest number of malaria cases globally.
– Understanding factors associated with care-seeking for fever among children under 5 can help improve malaria service utilization.
– This study aims to identify barriers to care-seeking and provide insights for targeted interventions.
Study Highlights:
– Care was sought for 69.1% of children aged 0-59 months with fever.
– Younger children, wealthier mothers, and mothers with higher education were more likely to seek care.
– Factors such as distance to health facilities, perception of fever severity, and availability of treatment influenced care-seeking behavior.
– Maternal malaria knowledge and exposure to malaria messages did not significantly impact care-seeking.
Recommendations for Lay Reader:
– Improve access to health facilities, especially in remote areas, to address distance barriers.
– Increase awareness about the importance of seeking care for fever, regardless of perceived severity.
– Ensure availability of treatment at health facilities to address concerns about treatment availability.
Recommendations for Policy Maker:
– Invest in expanding healthcare infrastructure and services in underserved areas.
– Implement targeted health education campaigns to raise awareness about the importance of seeking care for fever.
– Strengthen the supply chain to ensure consistent availability of malaria treatment at health facilities.
Key Role Players:
– Ministry of Health: Responsible for policy development and implementation.
– Healthcare Providers: Deliver healthcare services and provide education to caregivers.
– Community Health Workers: Bridge the gap between communities and healthcare facilities, providing education and referrals.
– Non-Governmental Organizations: Support implementation of interventions and provide resources.
Cost Items for Planning Recommendations:
– Infrastructure Development: Construction and renovation of health facilities.
– Healthcare Workforce: Recruitment, training, and deployment of healthcare professionals.
– Health Education Campaigns: Production of educational materials, media campaigns, and community outreach.
– Supply Chain Management: Procurement and distribution of malaria treatment and diagnostic tools.
– Monitoring and Evaluation: Data collection, analysis, and reporting to assess the impact of interventions.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study is based on a secondary data analysis of the 2018 Malaria Indicator Survey, which provides nationally and provincially representative data. The survey had a high response rate for both the household and women questionnaires. The study used a quantitative, observational design and employed complex sampling logistic regression to identify factors associated with care-seeking behavior. The results show significant associations between age, wealth quintile, and education level of mothers with care-seeking behavior. However, there are some limitations to consider. The study relies on self-reported data from mothers or caregivers, which may introduce bias. Additionally, the study does not provide information on the sample size or the statistical power of the analysis. To improve the evidence, future studies could consider using a larger sample size and incorporating objective measures of care-seeking behavior, such as healthcare facility records. Additionally, conducting qualitative research to explore the reasons behind the reported barriers to care-seeking could provide a more comprehensive understanding of the issue.

Background: Mozambique is ranked fourth in a list of the 29 countries that accounted for 95% of all malaria cases globally in 2019. The aim of this study was to identify factors associated with care seeking for fever, to determine the association between knowledge about malaria and care seeking and to describe the main reasons for not seeking care among children under five years of age in Mozambique. Methods: This is a quantitative, observational study based on a secondary data analysis of the 2018 Malaria Indicator Survey. This weighted analysis was based on data reported by surveyed mothers or caregivers of children aged 0–59 months who had fever in the two weeks prior to the survey. Results: Care was reportedly sought for 69.1% [95% CI 63.5–74.2] of children aged 0–59 months old with fever. Care-seeking was significantly higher among younger children, < 6 months old (AOR = 2.47 [95% CI 1.14–5.31]), 6–11 months old (AOR = 1.75 [95% CI 1.01–3.04]) and 12–23 months old (AOR = 1.85 [95% CI 1.19–2.89]), as compared with older children (48–59 months old). In adjusted analysis, mothers from the middle (AOR = 1.66 [95% CI 0.18–3.37]) and richest (AOR = 3.46 [95% CI 1.26–9.49]) wealth quintiles were more likely to report having sought care for their febrile children than mothers from the poorest wealth quintile. Additionally, mothers with secondary or higher education level were more likely to seek care (AOR = 2.16 [95% CI 1.19–3.93]) than mothers with no education. There was no association between maternal malaria knowledge or reported exposure to malaria messages and care-seeking behaviours. The main reasons reported for not seeking care included distance to health facility (46.3% of respondents), the perception that the fever was not severe (22.4%) and the perception that treatment was not available at the health facility (15%). Conclusion: Health facility access and socioeconomic barriers continue to be important constraints to malaria service utilization in Mozambique.

This is a quantitative, observational study based on a secondary data analysis of the 2018 MIS data. The 2018 MIS collected nationally and provincially representative data from a representative sample of respondents. Consistent with standard MIS methodology, the sampling design had two steps: first selection of a total of 224 enumeration areas (EA) was done for urban and rural areas of each of the eleven provinces using probability proportionate to size, after which 28 households were systematically selected from each included EA. All women aged 15–49 years old who regularly resided or stayed the prior night in included households were included [6]. The survey included a total of 6,196 households and 6184 women aged 15–49 years old. The response rate for the household questionnaire was 99% percent and for the women questionnaire was 98% percent [4]. Data collection took place from March to June 2018. Mozambique is located on the east coast of southern Africa and is divided in 11 provinces, including the country’s capital, Maputo City. Mozambique has a surface of approximately 799,380 km2 [2] and an estimated population of approximately 31 million inhabitants [7]. The two most populous provinces are Nampula and Zambézia, with 6.3 million and 5.7 million inhabitants, respectively. The climate in Mozambique is tropical. The rainy season spans from October to March [2]. There is year-round transmission of malaria with seasonal peaks during the rainy season. This analysis was based on data reported by surveyed mothers or caregivers about their children aged 0–59 months who had fever in the two weeks prior to the survey. The main outcome of this study is care-seeking of children under 5 years who had fever in the two weeks prior to data collection, as reported by mothers/guardians. In this study, care-seeking is defined as a caregiver reporting that he/she sought treatment or counselling for children under 5 years of age with fever, regardless of source of care sought [4]. Potential covariates were identified for inclusion in a predictive model based on variables identified during a literature review of “care seeking” and “treatment seeking” for fever and malaria. A total of 13 socioeconomic and demographic covariates previously shown to be associated with care-seeking [8–12] were identified and used from the 2018 MIS dataset. The covariates included child’s age, sex, place of residence (urban or rural), geographic region (province), household wealth quintile, mother’s level of education, mother’s age, child’s use of a bed net, mothers reporting hearing or seeing a message about malaria in the past 6 months, maternal comprehensive malaria knowledge and three specific questions about malaria knowledge. The following categories were considered for mother’s level of education: no education, primary education, and secondary education or higher. The mother’s level of knowledge was assessed using a composite score based on the following five variables: (i) the mother indicated fever as a symptom of malaria; (ii) the mother indicated mosquito bite as a form of malaria transmission; (iii) The mother knows that should sleep inside a mosquito net to prevent malaria; (iv) The mother knows that malaria has a cure; and (v) The mother indicated correctly at least one medicine to treat malaria. Descriptive statistics were used to summarize socio-economic and demographic characteristics of participants, using the children (KR) dataset. Special (svy) survey commands were used to account for the complex multilevel survey design. Data were weighted using the KR weights (wt = v005/1000000) to account for the differential selection probabilities at the EA, household, and individual levels so that any results with the regional weight factored into it would be representative at the national and regional level. Only weighted survey data are presented in this manuscript. Complex sampling logistic regression model was used to identify factors associated with care-seeking behaviour, with estimated adjusted odds ratio (AOR) and respective 95% confidence intervals (CI). All statistical analysis were performed using STATA, version 15 (Stata Corporation, College Station, Texas).

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

1. Mobile Health (mHealth) Solutions: Implementing mobile health technologies, such as SMS reminders for prenatal care appointments, educational messages about maternal health, and access to telemedicine consultations, can help overcome barriers related to distance and improve access to maternal health services.

2. Community Health Workers (CHWs): Training and deploying CHWs in rural and underserved areas can improve access to maternal health services. CHWs can provide basic prenatal care, health education, and referrals to health facilities when necessary.

3. Transportation Support: Providing transportation support, such as vouchers for transportation or establishing community-based transportation systems, can help pregnant women overcome geographical barriers and reach health facilities for prenatal care and delivery.

4. Maternal Waiting Homes: Establishing maternal waiting homes near health facilities can provide a safe and comfortable place for pregnant women to stay during the final weeks of pregnancy, ensuring they are close to the facility when it’s time to give birth.

5. Financial Incentives: Introducing financial incentives, such as conditional cash transfers or maternity vouchers, can encourage pregnant women to seek and utilize maternal health services.

6. Strengthening Health Infrastructure: Investing in the improvement and expansion of health facilities, particularly in rural areas, can enhance access to quality maternal health services.

7. Health Education and Awareness Campaigns: Conducting targeted health education and awareness campaigns can help address misconceptions and increase knowledge about the importance of maternal health, encouraging more women to seek care.

It’s important to note that the specific implementation and effectiveness of these innovations would require further research and evaluation.
AI Innovations Description
Based on the information provided, the study identified several factors associated with care-seeking for fever among children under five years of age in Mozambique. These factors include:

1. Age of the child: Care-seeking was higher among younger children (less than 6 months old, 6-11 months old, and 12-23 months old) compared to older children (48-59 months old).

2. Socioeconomic status: Mothers from the middle and richest wealth quintiles were more likely to seek care for their febrile children compared to mothers from the poorest wealth quintile.

3. Education level: Mothers with secondary or higher education were more likely to seek care for their children compared to mothers with no education.

The study also found that there was no association between maternal malaria knowledge or reported exposure to malaria messages and care-seeking behaviors. The main reasons reported for not seeking care included distance to health facility, the perception that the fever was not severe, and the perception that treatment was not available at the health facility.

Based on these findings, a recommendation to improve access to maternal health could be to focus on addressing the barriers identified in the study. This could include:

1. Improving access to healthcare facilities: Efforts should be made to increase the number of healthcare facilities, particularly in rural areas, and to improve transportation infrastructure to reduce the distance and travel time to these facilities.

2. Increasing awareness and education: Health education programs should be implemented to raise awareness about the importance of seeking care for febrile children, particularly among mothers with lower education levels. These programs should also provide information on the availability of treatment options for malaria.

3. Addressing socioeconomic disparities: Interventions should be targeted towards addressing the socioeconomic barriers that prevent mothers from seeking care for their children. This could include providing financial support or subsidies for healthcare services, particularly for mothers from the poorest wealth quintile.

By implementing these recommendations, it is expected that access to maternal health will be improved, leading to better care-seeking behaviors and ultimately reducing the burden of malaria in Mozambique.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Strengthening Health Facility Infrastructure: Investing in the improvement of health facility infrastructure, including the construction or renovation of clinics and hospitals, can help increase access to maternal health services. This can include ensuring the availability of essential equipment, supplies, and trained healthcare professionals.

2. Mobile Health Clinics: Implementing mobile health clinics can help reach remote or underserved areas where access to maternal health services is limited. These clinics can provide essential prenatal care, postnatal care, and emergency obstetric services to pregnant women who may not have easy access to a fixed healthcare facility.

3. Community Health Workers: Training and deploying community health workers can improve access to maternal health services, especially in rural areas. These workers can provide basic prenatal and postnatal care, health education, and referrals to appropriate healthcare facilities.

4. Telemedicine and Telehealth Services: Utilizing technology such as telemedicine and telehealth can help overcome geographical barriers and improve access to maternal health services. Pregnant women can receive virtual consultations, access health information, and receive remote monitoring, reducing the need for physical travel to healthcare facilities.

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

1. Define the Outcome Measure: Determine the specific outcome measure that represents improved access to maternal health, such as the percentage of pregnant women receiving prenatal care within the recommended timeframe.

2. Collect Baseline Data: Gather data on the current access to maternal health services, including the percentage of pregnant women receiving prenatal care, distance to the nearest healthcare facility, and other relevant factors.

3. Introduce the Innovations: Simulate the implementation of the recommended innovations, such as strengthening health facility infrastructure, deploying mobile health clinics, training community health workers, and implementing telemedicine services.

4. Analyze the Impact: Compare the baseline data with the simulated data after the introduction of the innovations. Calculate the changes in the outcome measure (e.g., the increase in the percentage of pregnant women receiving prenatal care) and assess the impact of each innovation on improving access to maternal health.

5. Consider External Factors: Take into account any external factors that may influence the impact of the innovations, such as changes in government policies, socio-economic conditions, or healthcare system capacity.

6. Refine and Iterate: Based on the analysis, refine the innovations and simulation methodology as needed. Repeat the simulation process to further optimize the impact on improving access to maternal health.

It is important to note that this is a general methodology and the specific details and data requirements may vary depending on the context and scope of the simulation study.

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