Association between malaria infection and early childhood development mediated by anemia in rural Kenya

International Journal of Environmental Research and Public Health, Volume 17, No. 3, Year 2020

Interpretação

Malaria is a leading cause of morbidity and mortality among children under five years of age, with most cases occurring in Sub-Saharan Africa. Children in this age group in Africa are at greatest risk worldwide for developmental deficits. There are research gaps in quantifying the risks of mild malaria cases, understanding the pathways linking malaria infection and poor child development, and evaluating the impact of malaria on the development of children under five years. We analyzed the association between malaria infection and gross motor, communication, and personal social development in 592 children age 24 months in rural, western Kenya as part of the WASH Benefits environmental enteric dysfunction sub-study. Eighteen percent of children had malaria, 20% were at risk for gross motor delay, 21% were at risk for communication delay, and 23% were at risk for personal social delay. Having a positive malaria test was associated with increased risk for gross motor, communication, and personal social delay while adjusting for child characteristics, household demographics, study cluster, and intervention treatment arm. Mediation analyses suggested that anemia was a significant mediator in the pathway between malaria infection and risk for gross motor, communication, and personal social development delays. The proportion of the total effect of malaria on the risk of developmental delay that is mediated by anemia across the subscales was small (ranging from 9% of the effect on gross motor development to 16% of the effect on communication development mediated by anemia). Overall, malaria may be associated with short-term developmental delays during a vulnerable period of early life. Therefore, preventative malaria measures and immediate treatment are imperative for children’s optimal development, particularly in light of projections of continued high malaria transmission in Kenya and Africa. These data were collected during the WASH Benefits trial, which is a cluster-randomized controlled trial assessing the impact of WASH and nutrition interventions individually and combined on child health outcomes [44,45,46]. The study was conducted in Bungoma and Kakamega counties in western Kenya. The region is rural and the majority of the population are subsistence farmers. The WASH Benefits trial took place from November 2012 to July 2016. Households were selected to participate in the trial if they were in a rural community (defined as <25% of residents living in a rented home (most families in rural areas own homes compared with urban households in Kenya), with <2 gas stations, and <10 shops in the area) and had limited access to water and sanitation (defined as communities where >80% of residents did not have access to piped water). Female participants were eligible for enrollment into the study if they were pregnant, if they or their partner owned their house, and if they were not planning to move within the next 12 months. The infant that was in utero during the village census was the index child. Households were visited at enrollment and two follow-up periods, one and two years later. A sub-study assessing environmental enteric dysfunction, malaria infection, and hemoglobin concentrations from biological samples enrolled 2,304 households from four arms of the WASH Benefits trial (WASH, WASH and Nutrition, Nutrition, or Active Control) [36,44,47]. The nutrition intervention entailed nutrition education and all children between 6–24 months in the participating household receiving LNS with iron. In the second follow-up, 1,449 children were included in the sub-study [36,44,47]. This sample size was calculated based on having the power to detect differences in environmental enteropathy biomarkers [48] and this sample size was sufficient to determine the association between malaria infection and child development outcomes. An equal proportion of children were selected from each intervention arm. Caregivers brought study children to a central location for sub-study data collection between August 2015 and April 2016. Blood samples for malaria and anemia diagnoses were taken by trained phlebotomists and health surveys were completed. Caregivers provided written informed consent. Consent for blood collection and a sufficient blood sample was obtained for 699 children and therefore malaria and hemoglobin measurements only existed for this subset of children. An average of two to three months later, caregivers brought study children to a central location for main trial data collection, including a child development assessment. Local enumerators conducted most surveys in Kiswahili, the regional language. Surveys and data collection tools were developed from validated measures [49] and locally adapted. Venous blood samples were drawn from sub-study participant children in a central location within villages for biomarker analyses and drops of blood were used to assess malaria parasites and hemoglobin concentrations. Rapid diagnostic tests (RDTs) for P. falciparum, P. vivax, P. ovale, and P. malariae were conducted using rapid diagnostic kits (SD Bioline, Malaria Ag, P.f, P.f, P.v, Alere). The kits can detect parasite concentrations up to 28 days after infection. All children with a positive test result were defined as having malaria in these analyses. Axillary temperatures were taken for all children and if the malaria parasite test was positive and the child’s temperature was 37.5 degrees Celsius or higher, he/she was referred to the nearest clinic for malaria treatment. Hemoglobin concentrations were measured using a Hemocue (Hb 301) machine (Angelholm, Sweden). Anemia was defined as having a hemoglobin concentration below 11.0 g/dL [50]. A medical history form was also completed with caregivers about the child’s recent experiences with illness, prophylaxis, and treatment related to a variety of health conditions, including malaria. Household demographics, including asset ownership and maternal education, were assessed using standardized questionnaires administered at enrollment. Socioeconomic status was defined with an asset index using enrollment survey results for all sub-study participants. The asset index was created using the first principal component from a principal components analysis, which has been shown to be an appropriate proxy for household wealth and is correlated with consumption expenditures [51,52,53]. Items included in the asset index were housing structure, electricity, and ownership of a radio, television, mobile phone, clock, bicycle, motorcycle, gas stove, and car. Maternal education was categorized into the following categories: incomplete primary school, completed primary school, and any secondary school. Three domains of child development were assessed: gross motor, communication, and personal social. The corresponding subscales of the Extended Ages and Stages Questionnaire (EASQ) were used to measure each developmental outcome among all WASH Benefits trial participants during the last data collection round (at approximately age 24 months). The EASQ is a modified version of the Ages and Stages Questionnaire (ASQ), which is widely used for the developmental screening of children under five years of age [54,55,56] and has been used in LMICs [57]. The questionnaires contain a series of age-specific items assessing the achievement of developmental milestones and tracking the child’s progress. The EASQ was piloted to assess respondent bias, maternal accuracy in reporting children’s abilities, cultural appropriateness, and feasibility according to standard procedures [49]. The Gross Motor subscale evaluates body and muscle movement, including tasks like standing, walking, and balancing. The Communication subscale assesses language development and the use of words or sounds to express feelings. The Personal Social subscale reflects emotional responses and social interactions. The EASQ was translated and adapted for this study by using local culturally appropriate items, examples, and tasks, but no substantial changes were made to the original questionnaires. Continuous scores for each subscale were calculated and converted to age-adjusted Z-scores based on the control group within the larger WASH Benefits trial. Children were considered at risk for delay in this population if their Z-scores were below the 25th percentile of control group Z-scores for each domain. This method of defining risk for delay was used as a conservative strategy because there was no prior research informing a culturally appropriate clinical cut-off in this study population. Binary variables were used to incorporate a quantitative definition of poor development and to be consistent with analyses used in the main WASH Benefits publications [46,58]. All statistical analyses were conducted in Stata 14 (StataCorp, College Station, TX, USA, 2015). Three sets of logistic multivariate analyses were undertaken to test the hypotheses corresponding to each child development outcome (gross motor, communication, and personal social). Two regression models were built for each child development outcome to assess the pathways between malaria infection (binary) and being at risk for gross motor, communication, and personal social delays (binary). The first model included malaria infection (binary) and the child development outcomes (three separate binary outcomes). Anemia status (binary; anemia defined as hemoglobin concentration <11.0 g/dL) was added to the second model. The interaction between malaria status and participation in the nutrition intervention was also analyzed in multivariate models to assess whether being in a nutrition treatment arm differentially affected malaria infection. All models were adjusted for child characteristics (sex [binary] and age [continuous, months]), household demographics (asset index [continuous] and maternal education [categorical]), study cluster, and whether the household received the nutrition intervention (binary). Analyses controlled for arms that received nutrition interventions because they were likely confounders. Mediation analyses were then undertaken to assess whether anemia was a mediator along the pathway between malaria infection and being at risk for gross motor, communication, and personal social delays. The binary_mediation method in Stata [59,60,61] was employed. Like the Sobel–Goodman test for continuous outcomes, the binary_mediation method shows that mediation occurred if: 1) malaria infection was significantly associated with the mediator (anemia), 2) malaria infection was significantly associated with developmental delay in the absence of the mediator (anemia), 3) the mediator (anemia) was significantly associated with developmental delay, and 4) the effect of malaria infection on developmental delay decreased upon the addition of the mediator (anemia) to the model. The proportion of the total effect of malaria infection on the risk for gross motor, communication, and personal social delay that is mediated by anemia was also calculated and reported. Children with missing malaria data or child development assessments were removed from analyses. Nine percent of children had missing data from one of these measurements and thus were not included in the final analyses. The final sample size was therefore 592 children. Differences between those who provided consent for blood collection and had a sufficient blood sample, and those who did not were assessed due to the low response rate and no significant differences or systematic attrition were found [36]. The WASH Benefits trial is registered as a clinical trial with the U.S. National Institutes of Health (https://clinicaltrials.gov/ct2/show/{"type":"clinical-trial","attrs":{"text":"NCT01704105","term_id":"NCT01704105"}}NCT01704105). Ethical approval was obtained from the University of California, Berkeley Center for the Protection of Human Subjects and the Kenya Medical Research Institute Ethical Review Committee. Adult participants provided written consent for themselves and their children prior to enrollment.

AI Digest

Study Justification:

– Malaria is a leading cause of morbidity and mortality among children under five years of age in Sub-Saharan Africa.
– Children in this age group in Africa are at the greatest risk worldwide for developmental deficits.
– There are research gaps in understanding the pathways linking malaria infection and poor child development, as well as evaluating the impact of malaria on children under five years.
– This study aims to fill these research gaps by analyzing the association between malaria infection and gross motor, communication, and personal social development in children in rural Kenya.

Study Highlights:

– The study analyzed data from 592 children aged 24 months in rural, western Kenya.
– 18% of children had malaria, and 20%, 21%, and 23% were at risk for gross motor, communication, and personal social delay, respectively.
– Malaria infection was associated with increased risk for all three developmental delays, even after adjusting for various factors.
– Anemia was found to be a significant mediator in the pathway between malaria infection and developmental delays.
– The proportion of the total effect of malaria on developmental delay mediated by anemia ranged from 9% to 16% across the subscales.

Study Recommendations:

– Preventative measures and immediate treatment for malaria are imperative for children’s optimal development.
– Focus on addressing anemia as a mediator in the pathway between malaria infection and developmental delays.
– Implement interventions that target both malaria prevention and anemia management.
– Consider the projected high malaria transmission in Kenya and Africa when planning and implementing these recommendations.

Key Role Players:

– Researchers and scientists in the field of malaria and child development.
– Public health officials and policymakers.
– Healthcare providers and clinics.
– Community health workers and educators.
– Non-governmental organizations (NGOs) working in malaria prevention and child health.

Cost Items for Planning Recommendations:

– Malaria prevention measures: insecticide-treated bed nets, indoor residual spraying, antimalarial medications.
– Anemia management interventions: iron supplementation, nutritional support.
– Training and capacity building for healthcare providers and community health workers.
– Monitoring and evaluation of interventions.
– Health education and awareness campaigns.
– Research and data collection.
– Program management and coordination.
– Infrastructure and logistics support.

Força da prova

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides detailed information about the study design, data collection methods, and statistical analyses. However, it does not mention the specific results or effect sizes, which would provide a clearer understanding of the strength of the evidence. To improve the evidence, the abstract could include a summary of the main findings and effect sizes, as well as any limitations or potential biases in the study.

Resumo

These data were collected during the WASH Benefits trial, which is a cluster-randomized controlled trial assessing the impact of WASH and nutrition interventions individually and combined on child health outcomes [44,45,46]. The study was conducted in Bungoma and Kakamega counties in western Kenya. The region is rural and the majority of the population are subsistence farmers. The WASH Benefits trial took place from November 2012 to July 2016. Households were selected to participate in the trial if they were in a rural community (defined as <25% of residents living in a rented home (most families in rural areas own homes compared with urban households in Kenya), with <2 gas stations, and 80% of residents did not have access to piped water). Female participants were eligible for enrollment into the study if they were pregnant, if they or their partner owned their house, and if they were not planning to move within the next 12 months. The infant that was in utero during the village census was the index child. Households were visited at enrollment and two follow-up periods, one and two years later. A sub-study assessing environmental enteric dysfunction, malaria infection, and hemoglobin concentrations from biological samples enrolled 2,304 households from four arms of the WASH Benefits trial (WASH, WASH and Nutrition, Nutrition, or Active Control) [36,44,47]. The nutrition intervention entailed nutrition education and all children between 6–24 months in the participating household receiving LNS with iron. In the second follow-up, 1,449 children were included in the sub-study [36,44,47]. This sample size was calculated based on having the power to detect differences in environmental enteropathy biomarkers [48] and this sample size was sufficient to determine the association between malaria infection and child development outcomes. An equal proportion of children were selected from each intervention arm. Caregivers brought study children to a central location for sub-study data collection between August 2015 and April 2016. Blood samples for malaria and anemia diagnoses were taken by trained phlebotomists and health surveys were completed. Caregivers provided written informed consent. Consent for blood collection and a sufficient blood sample was obtained for 699 children and therefore malaria and hemoglobin measurements only existed for this subset of children. An average of two to three months later, caregivers brought study children to a central location for main trial data collection, including a child development assessment. Local enumerators conducted most surveys in Kiswahili, the regional language. Surveys and data collection tools were developed from validated measures [49] and locally adapted. Venous blood samples were drawn from sub-study participant children in a central location within villages for biomarker analyses and drops of blood were used to assess malaria parasites and hemoglobin concentrations. Rapid diagnostic tests (RDTs) for P. falciparum, P. vivax, P. ovale, and P. malariae were conducted using rapid diagnostic kits (SD Bioline, Malaria Ag, P.f, P.f, P.v, Alere). The kits can detect parasite concentrations up to 28 days after infection. All children with a positive test result were defined as having malaria in these analyses. Axillary temperatures were taken for all children and if the malaria parasite test was positive and the child’s temperature was 37.5 degrees Celsius or higher, he/she was referred to the nearest clinic for malaria treatment. Hemoglobin concentrations were measured using a Hemocue (Hb 301) machine (Angelholm, Sweden). Anemia was defined as having a hemoglobin concentration below 11.0 g/dL [50]. A medical history form was also completed with caregivers about the child’s recent experiences with illness, prophylaxis, and treatment related to a variety of health conditions, including malaria. Household demographics, including asset ownership and maternal education, were assessed using standardized questionnaires administered at enrollment. Socioeconomic status was defined with an asset index using enrollment survey results for all sub-study participants. The asset index was created using the first principal component from a principal components analysis, which has been shown to be an appropriate proxy for household wealth and is correlated with consumption expenditures [51,52,53]. Items included in the asset index were housing structure, electricity, and ownership of a radio, television, mobile phone, clock, bicycle, motorcycle, gas stove, and car. Maternal education was categorized into the following categories: incomplete primary school, completed primary school, and any secondary school. Three domains of child development were assessed: gross motor, communication, and personal social. The corresponding subscales of the Extended Ages and Stages Questionnaire (EASQ) were used to measure each developmental outcome among all WASH Benefits trial participants during the last data collection round (at approximately age 24 months). The EASQ is a modified version of the Ages and Stages Questionnaire (ASQ), which is widely used for the developmental screening of children under five years of age [54,55,56] and has been used in LMICs [57]. The questionnaires contain a series of age-specific items assessing the achievement of developmental milestones and tracking the child’s progress. The EASQ was piloted to assess respondent bias, maternal accuracy in reporting children’s abilities, cultural appropriateness, and feasibility according to standard procedures [49]. The Gross Motor subscale evaluates body and muscle movement, including tasks like standing, walking, and balancing. The Communication subscale assesses language development and the use of words or sounds to express feelings. The Personal Social subscale reflects emotional responses and social interactions. The EASQ was translated and adapted for this study by using local culturally appropriate items, examples, and tasks, but no substantial changes were made to the original questionnaires. Continuous scores for each subscale were calculated and converted to age-adjusted Z-scores based on the control group within the larger WASH Benefits trial. Children were considered at risk for delay in this population if their Z-scores were below the 25th percentile of control group Z-scores for each domain. This method of defining risk for delay was used as a conservative strategy because there was no prior research informing a culturally appropriate clinical cut-off in this study population. Binary variables were used to incorporate a quantitative definition of poor development and to be consistent with analyses used in the main WASH Benefits publications [46,58]. All statistical analyses were conducted in Stata 14 (StataCorp, College Station, TX, USA, 2015). Three sets of logistic multivariate analyses were undertaken to test the hypotheses corresponding to each child development outcome (gross motor, communication, and personal social). Two regression models were built for each child development outcome to assess the pathways between malaria infection (binary) and being at risk for gross motor, communication, and personal social delays (binary). The first model included malaria infection (binary) and the child development outcomes (three separate binary outcomes). Anemia status (binary; anemia defined as hemoglobin concentration <11.0 g/dL) was added to the second model. The interaction between malaria status and participation in the nutrition intervention was also analyzed in multivariate models to assess whether being in a nutrition treatment arm differentially affected malaria infection. All models were adjusted for child characteristics (sex [binary] and age [continuous, months]), household demographics (asset index [continuous] and maternal education [categorical]), study cluster, and whether the household received the nutrition intervention (binary). Analyses controlled for arms that received nutrition interventions because they were likely confounders. Mediation analyses were then undertaken to assess whether anemia was a mediator along the pathway between malaria infection and being at risk for gross motor, communication, and personal social delays. The binary_mediation method in Stata [59,60,61] was employed. Like the Sobel–Goodman test for continuous outcomes, the binary_mediation method shows that mediation occurred if: 1) malaria infection was significantly associated with the mediator (anemia), 2) malaria infection was significantly associated with developmental delay in the absence of the mediator (anemia), 3) the mediator (anemia) was significantly associated with developmental delay, and 4) the effect of malaria infection on developmental delay decreased upon the addition of the mediator (anemia) to the model. The proportion of the total effect of malaria infection on the risk for gross motor, communication, and personal social delay that is mediated by anemia was also calculated and reported. Children with missing malaria data or child development assessments were removed from analyses. Nine percent of children had missing data from one of these measurements and thus were not included in the final analyses. The final sample size was therefore 592 children. Differences between those who provided consent for blood collection and had a sufficient blood sample, and those who did not were assessed due to the low response rate and no significant differences or systematic attrition were found [36]. The WASH Benefits trial is registered as a clinical trial with the U.S. National Institutes of Health (https://clinicaltrials.gov/ct2/show/{"type":"clinical-trial","attrs":{"text":"NCT01704105","term_id":"NCT01704105"}}NCT01704105). Ethical approval was obtained from the University of California, Berkeley Center for the Protection of Human Subjects and the Kenya Medical Research Institute Ethical Review Committee. Adult participants provided written consent for themselves and their children prior to enrollment.

Materiais

N/A

Inovações

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 that provide information and reminders about prenatal care, vaccinations, and other important aspects of maternal health. These tools can help educate and empower pregnant women, especially in rural areas with limited access to healthcare facilities.

2. Telemedicine: Implement telemedicine programs that allow pregnant women to consult with healthcare providers remotely. This can help overcome geographical barriers and provide access to specialized care for high-risk pregnancies.

3. Community Health Workers: Train and deploy community health workers to provide basic prenatal care, health education, and referrals to pregnant women in underserved areas. These workers can bridge the gap between communities and formal healthcare systems, improving access to maternal health services.

4. Maternal Health Vouchers: Introduce voucher programs that provide pregnant women with subsidized or free access to prenatal care, delivery services, and postnatal care. These vouchers can be distributed through community health centers or local organizations, ensuring that financial constraints do not prevent women from accessing essential maternal health services.

5. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve leveraging private sector resources, such as clinics, pharmacies, and transportation services, to enhance the availability and affordability of maternal healthcare in underserved areas.

6. Maternal Health Education Campaigns: Launch targeted education campaigns to raise awareness about the importance of prenatal care, nutrition, and hygiene practices during pregnancy. These campaigns can be conducted through various channels, including radio, television, community meetings, and social media, to reach a wide audience.

7. Infrastructure Development: Invest in improving healthcare infrastructure, including the construction and renovation of healthcare facilities, especially in rural areas. This can help ensure that pregnant women have access to well-equipped facilities for safe deliveries and emergency obstetric care.

8. Maternity Waiting Homes: Establish maternity waiting homes near healthcare facilities to accommodate pregnant women who live far away. These homes provide a safe and comfortable place for women to stay during the final weeks of pregnancy, ensuring timely access to skilled birth attendants and emergency obstetric care.

9. Transportation Support: Develop transportation initiatives, such as ambulance services or community transport networks, to facilitate the timely and safe transportation of pregnant women to healthcare facilities. This can be particularly beneficial in remote areas with limited transportation options.

10. Maternal Health Financing: Explore innovative financing models, such as microinsurance or community-based health financing schemes, to make maternal health services more affordable and accessible to low-income women.

It is important to note that the implementation of these innovations should be context-specific and tailored to the needs and resources of the target population.

AI Innovations Description

Based on the description provided, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Implement integrated malaria prevention and treatment programs: Given the association between malaria infection and developmental delays in children, it is crucial to prioritize malaria prevention and treatment measures in maternal health programs. This can include providing insecticide-treated bed nets, indoor residual spraying, and antimalarial medications to pregnant women and young children.

2. Strengthen antenatal care services: Antenatal care visits provide an opportunity to screen for and manage malaria infections in pregnant women. By strengthening antenatal care services, healthcare providers can ensure early detection and prompt treatment of malaria in pregnant women, reducing the risk of adverse outcomes for both the mother and the child.

3. Improve access to diagnostic testing and treatment: Enhancing access to malaria diagnostic testing and treatment services in rural areas is essential for early detection and effective management of malaria infections. This can be achieved by training healthcare workers in remote areas to perform rapid diagnostic tests and administer appropriate antimalarial medications.

4. Increase awareness and education: Conducting community-based awareness campaigns and educational programs can help raise awareness about the risks of malaria infection during pregnancy and early childhood. This can empower communities to take preventive measures, seek timely treatment, and adhere to recommended interventions.

5. Strengthen health systems: To improve access to maternal health, it is important to strengthen health systems in rural areas. This includes ensuring an adequate supply of essential medicines, improving infrastructure for healthcare facilities, and training healthcare workers to provide quality maternal and child health services.

By implementing these recommendations, it is possible to develop innovative strategies that address the association between malaria infection and early childhood development, ultimately improving access to maternal health and reducing the burden of malaria-related developmental delays.

AI Innovations Methodology

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

1. Strengthening Antenatal Care (ANC) Services: Enhance the quality and availability of ANC services to ensure that pregnant women receive comprehensive care, including early detection and management of malaria infection, anemia screening, and appropriate treatment.

2. Integrated Maternal and Child Health Programs: Implement integrated programs that address both maternal and child health, focusing on interventions that can prevent and treat malaria infection, anemia, and other common health issues during pregnancy and early childhood.

3. Community-Based Interventions: Engage community health workers and volunteers to provide education, counseling, and support to pregnant women and their families, emphasizing the importance of preventive measures, such as insecticide-treated bed nets, antimalarial medication, and proper nutrition.

4. Mobile Health (mHealth) Solutions: Utilize mobile technology to deliver health information, reminders, and appointment notifications to pregnant women, enabling them to access timely and relevant maternal health services.

5. Strengthening Health Systems: Improve the capacity and infrastructure of health facilities in rural areas, ensuring the availability of essential supplies, trained healthcare providers, and reliable diagnostic and treatment services for malaria and anemia.

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 that reflect access to maternal health, such as the number of pregnant women receiving ANC services, the proportion of women screened and treated for malaria and anemia, and the percentage of women delivering in a health facility.

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

3. Develop a simulation model: Create a mathematical or statistical model that simulates the impact of the recommended interventions on the selected indicators. The model should consider factors such as population size, coverage of interventions, and potential barriers to access.

4. Input intervention scenarios: Define different scenarios that represent the implementation of the recommended interventions. This could include variations in coverage, timing, or intensity of the interventions.

5. Run simulations: Use the simulation model to generate projections of the indicators under each intervention scenario. This will provide estimates of the potential impact of the interventions on improving access to maternal health.

6. Analyze results: Compare the simulation results across different scenarios to identify the most effective interventions in terms of improving access to maternal health. Consider factors such as cost-effectiveness, feasibility, and sustainability.

7. Refine and validate the model: Incorporate feedback from stakeholders, experts, and additional data sources to refine the simulation model and validate its accuracy. This may involve adjusting parameters, assumptions, or data inputs.

8. Communicate findings: Present the simulation results in a clear and concise manner, highlighting the potential benefits of the recommended interventions and their implications for policy and practice.

Autor

Dima Health

Statistics:

Citations: 3

Identifiers:

DOI: 10.3390/ijerph17030902

ISSN: 16617827

Research Areas:

Community Interventions, Environmental, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care, Social Determinants

Study Countries:

Kenya

Study Design:

Cohort Study, Cross Sectional Study, Grounded Theory, randomised-control-trial

Study Approach:

Quantitative

Participants Gender:

Female

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