Overall, anti-malarial, and non-malarial effect of intermittent preventive treatment during pregnancy with sulfadoxine-pyrimethamine on birthweight: a mediation analysis

The Lancet Global Health, Volume 8, No. 7, Year 2020

Interpretation

Background: Trials of intermittent preventive treatment (IPTp) of malaria in pregnant women that compared dihydroartemisinin-piperaquine with the standard of care, sulfadoxine-pyrimethamine, showed dihydroartemisinin-piperaquine was superior at preventing malaria infection, but not at improving birthweight. We aimed to assess whether sulfadoxine-pyrimethamine shows greater non-malarial benefits for birth outcomes than does dihydroartemisinin-piperaquine, and whether dihydroartemisinin-piperaquine shows greater antimalarial benefits for birth outcomes than does sulfadoxine-pyrimethamine. Methods: We defined treatment as random assignment to sulfadoxine-pyrimethamine or dihydroartemisinin-piperaquine before pooling individual participant-level data from 1617 HIV-uninfected pregnant women in Kenya (one trial; n=806) and Uganda (two trials; n=811). We quantified the relative effect of treatment on birthweight (primary outcome) attributed to preventing placental malaria infection (mediator). We estimated antimalarial (indirect) and non-malarial (direct) effects of IPTp on birth outcomes using causal mediation analyses, accounting for confounders. We used two-stage individual participant data meta-analyses to calculate pooled-effect sizes. Findings: Overall, birthweight was higher among neonates of women randomly assigned to sulfadoxine-pyrimethamine compared with women assigned to dihydroartemisinin-piperaquine (mean difference 69 g, 95% CI 26 to 112), despite placental malaria infection being lower in the dihydroartemisinin-piperaquine group (relative risk [RR] 0·64, 95% CI 0·39 to 1·04). Mediation analyses showed sulfadoxine-pyrimethamine conferred a greater non-malarial effect than did dihydroartemisinin-piperaquine (mean difference 87 g, 95% CI 43 to 131), whereas dihydroartemisinin-piperaquine conferred a slightly larger antimalarial effect than did sulfadoxine-pyrimethamine (8 g, −9 to 26), although more frequent dosing increased the antimalarial effect (31 g, 3 to 60). Interpretation: IPTp with sulfadoxine-pyrimethamine appears to have potent non-malarial effects on birthweight. Further research is needed to evaluate monthly dihydroartemisinin-piperaquine with sulfadoxine-pyrimethamine (or another compound with non-malarial effects) to achieve greater protection against malarial and non-malarial causes of low birthweight. Funding: Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bill & Melinda Gates Foundation, and Worldwide Antimalarial Resistance Network. We collected individual participant-level data from three trials in Siaya County, Kenya (Kenya-STOPMiP),5 Tororo District, Uganda (Uganda-BC1),6 and Busia District, Uganda (Uganda-BC3).7 In Siaya County, around 96% of parasites carry the quintuple antifolate mutation (pfdhfr 51I, 59R, and 108N and pfdhps 437G and 540E) and 5·8% have the sextuple mutation (pfdhps A581G).9 In Tororo, Uganda, around 78% of parasites carry the quintuple mutation, whereas none have the sextuple mutation.14 No data were available on pfdhf/pfdhps mutations in Busia, although Tororo and Busia are adjacent districts. Trial eligibility was restricted to HIV-uninfected pregnant women who were resident in the study region or health facility catchment area with no history of receiving IPTp during their current pregnancy. In the Kenya-STOPMiP trial,5 women between 16 and 32 gestational weeks of pregnancy were enrolled and randomly assigned to receive IPTp with dihydroartemisinin-piperaquine, IPTp with sulfadoxine-pyrimethamine, or intermittent screening and treatment (ISTp) with dihydroartemisinin-piperaquine. Women assigned to IPTp groups received IPTp at enrolment and then at each subsequent antenatal visit at intervals of 4–6 weeks. In the Ugandan studies,6, 7 women between 12 and 20 gestational weeks of pregnancy were enrolled. In Uganda-BC1,6 women were randomly assigned to receive either IPTp with sulfadoxine-pyrimethamine every 8 weeks, IPTp with dihydroartemisinin-piperaquine every 8 weeks, or IPTp with dihydroartemisinin-piperaquine every 4 weeks. In Uganda-BC3,7 women were randomised to either IPTp with sulfadoxine-pyrimethamine or IPTp with dihydroartemisinin-piperaquine every 4 weeks. Women assigned to IPTp every 8 weeks began IPTp at 20 gestational weeks of pregnancy, whereas women assigned to IPTp every 4 weeks began IPTp at 16 or 20 gestational weeks of pregnancy, depending on their gestational age at enrolment. For all studies, each dose of sulfadoxine-pyrimethamine was three tablets of 500 mg sulfadoxine and 25 mg of pyrimethamine given as a single dose. In Kenya-STOPMiP,5 dosing of dihydroartemisinin-piperaquine was based on bodyweight at enrolment (two, three, or four tablets of 40 mg dihydroartemisinin and 320 mg piperaquine per day for bodyweights of 24·0–35·9 kg, 36·0–74·9 kg; or ≥75·0 kg, respectively) and given once a day for 3 days. In the Ugandan studies,6, 7 each dose of dihydroartemisinin-piperaquine was three tablets of 40 mg dihydroartemisinin and 320 mg piperaquine given once a day for 3 days. Single-dose sulfadoxine-pyrimethamine and the first dose of dihydroartemisinin-piperaquine were administered under direct observation at the clinic, and the second and third doses of dihydroartemisinin-piperaquine were self-administered at home. The Ugandan trials were placebo-controlled such that all participants received a three-dose course. Participants in Kenya were visited at home 2 days after enrolment to verify drug adherence, and every fifth participant was visited at home on subsequent visits. For the Ugandan studies, standardised assessments were done to determine adherence. Our mediation analysis included women who had singleton livebirths, received at least one IPTp dose, and a known status of either past or active placental malaria infection. Placental malarial infection was determined by including women who either had a histopathological assessment of placental malaria using placenta tissue or women who tested positive for placental malaria by either microscopy, loop-mediated isothermal amplification, or PCR methods using placental blood. Women were excluded if they were assigned to the Kenya-STOPMiP ISTp group, assigned to the Uganda-BC1 IPTp with dihydroartemisinin-piperaquine every 4 weeks group, or had an unknown status of either past or active placental malaria (ie, missing placental histopathology results and negative for placental malaria by microscopy and molecular methods). Ethics approvals were granted by the Kenya Medical Research Institute, Makerere University School of Biomedical Sciences, the Uganda National Council for Science and Technology, the US Centers for Disease Control and Prevention, and the University of California, San Francisco. We defined treatment as random assignment to IPTp with either sulfadoxine-pyrimethamine or dihydroartemisinin-piperaquine. The mediator in our analysis was defined as the presence of previous or active placental malaria infection. A woman was determined to have a previous or active placental malaria infection if she had pigment or parasites in her placenta determined by histopathology of the placental tissue15 or if she tested positive for parasites by microscopy or molecular methods in her placental blood. Peripherally-detected malaria infection was considered a potential mediator (appendix 2 p 1) but we found that, in our sample of women, parasitaemia without the presence of placental malaria was not associated with lower birthweight, whereas women with placental malaria, regardless of whether they had peripherally-detected malaria, were more likely to have a baby with a lower birthweight. Confounding variables were identified a priori based on causal assumptions represented in a directed acyclic graph (appendix 2 p 2). Because of treatment randomisation, confounders were limited to those that affected mediator–outcome associations. These included gestational age at enrolment, maternal age, maternal parasitaemia at enrolment, gravidity, education, and household wealth. Gravidity was dichotomised as primigravidae (first pregnancy) or multigravidae (one or more previous pregnancies). Household wealth was reported as tertiles and calculated using principal components analysis of common household items. The primary outcome was a continuous measure of birthweight at delivery measured in g. Secondary outcomes were low birthweight (<2500 g) and preterm delivery (<37 gestational weeks). Further details on measurement of these outcomes are reported in the trials.5, 6, 7 We used causal mediation analysis16, 17, 18 to deconstruct the crude differences in birth outcomes between IPTp regimens (ie, overall treatment effect) into the difference in birth outcomes between IPTp regimens that is mediated by preventing placental malaria (ie, indirect or antimalarial effect) and the difference in birth outcomes between IPTp regimens that is not mediated by preventing placental malaria infection (ie, direct or non-malarial effect; appendix 2 pp 2–3). We estimated crude differences in birth outcomes between IPTp regimens using linear or log-binomial regression models with random assignment as the sole predictor. For mediation analyses, we used the mediation R package19 to estimate indirect and direct effects (appendix 2 p 3). We ran separate models to specify the dependence of placental malaria and birth outcomes based on treatment and prespecified confounders (as described in the assumed causal graph; appendix 2 p 2). Predicted values from these models were used in a Monte-Carlo framework to calculate indirect and direct effect estimates and corresponding 95% CIs, which we report as mean differences for birthweight and relative risks for low birthweight and preterm delivery. For all models, treatment–gravidity and treatment–mediator interaction terms were tested wherever possible and incorporated if the p values (pinteraction) of these terms were less than 0·10. We modelled continuous predictors as three-knot restricted cubic splines if the p value of the F test for the joint-effect of the non-linear components was less than 0·05. CIs around mediation effect estimates were generated for each study with a quasi-Bayesian approach using 1000 simulations. Effect modification by gravidity of indirect and direct effect estimates was tested using the test.modmed() function19 with corresponding p values reported as pdifference. For the mediator and primary outcome (placental malaria and birthweight, respectively), we report effect estimates separately for each study and by gravidity, regardless of whether there was evidence of a statistical interaction. Analyses of secondary outcomes (low birthweight and preterm delivery) were not reported separately by gravidity as they were relatively uncommon. We generated pooled-effect estimates using two-stage individual participant data meta-analyses. Individual participant data were used to derive effect estimates for each study and combined using a DerSimonian-Laird random-effects model from the meta R package.20 Between-study heterogeneity was measured using the I2 statistic. Analyses were done using Stata version 14.0 and R version 3.5.0. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.

AI Digest

Study Justification:

– The study aimed to compare the effects of two different treatments, sulfadoxine-pyrimethamine and dihydroartemisinin-piperaquine, on birthweight in pregnant women.
– Previous trials had shown that dihydroartemisinin-piperaquine was better at preventing malaria infection, but not at improving birthweight.
– The study aimed to determine if sulfadoxine-pyrimethamine had greater non-malarial benefits for birth outcomes than dihydroartemisinin-piperaquine, and if dihydroartemisinin-piperaquine had greater antimalarial benefits for birth outcomes than sulfadoxine-pyrimethamine.

Highlights:

– The study included 1617 HIV-uninfected pregnant women from Kenya and Uganda.
– Overall, birthweight was higher in women assigned to sulfadoxine-pyrimethamine compared to dihydroartemisinin-piperaquine, despite lower rates of placental malaria infection in the dihydroartemisinin-piperaquine group.
– Mediation analyses showed that sulfadoxine-pyrimethamine had a greater non-malarial effect on birthweight, while dihydroartemisinin-piperaquine had a slightly larger antimalarial effect.
– The study suggests that sulfadoxine-pyrimethamine has potent non-malarial effects on birthweight and further research is needed to evaluate monthly dihydroartemisinin-piperaquine with sulfadoxine-pyrimethamine to achieve greater protection against malarial and non-malarial causes of low birthweight.

Recommendations:

– Further research is needed to evaluate the combination of monthly dihydroartemisinin-piperaquine with sulfadoxine-pyrimethamine or another compound with non-malarial effects to achieve better protection against both malarial and non-malarial causes of low birthweight.

Key Role Players:

– Researchers and scientists specializing in malaria prevention and maternal health.
– Healthcare providers and clinicians involved in antenatal care and pregnancy management.
– Public health officials and policymakers responsible for implementing interventions to improve maternal and child health.

Cost Items for Planning Recommendations:

– Research funding for conducting further studies to evaluate the combination of monthly dihydroartemisinin-piperaquine with sulfadoxine-pyrimethamine or other compounds.
– Budget for data collection, analysis, and interpretation.
– Costs associated with recruiting and enrolling pregnant women for the study.
– Funding for training and capacity building of healthcare providers involved in antenatal care.
– Budget for dissemination of research findings and implementation of recommended interventions.

Strength of Evidence

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 design includes three trials with a large sample size, which increases the reliability of the findings. The authors used causal mediation analysis to assess the effects of different treatments on birthweight, considering potential confounders. The results show that sulfadoxine-pyrimethamine has greater non-malarial effects on birthweight, while dihydroartemisinin-piperaquine has a slightly larger antimalarial effect. The study provides valuable insights into the benefits of intermittent preventive treatment during pregnancy. However, to further strengthen the evidence, it would be beneficial to include more details on the methodology, such as the randomization process, data collection methods, and statistical analysis techniques. Additionally, the abstract could provide information on potential limitations of the study and suggestions for future research.

Abstract

We collected individual participant-level data from three trials in Siaya County, Kenya (Kenya-STOPMiP),5 Tororo District, Uganda (Uganda-BC1),6 and Busia District, Uganda (Uganda-BC3).7 In Siaya County, around 96% of parasites carry the quintuple antifolate mutation (pfdhfr 51I, 59R, and 108N and pfdhps 437G and 540E) and 5·8% have the sextuple mutation (pfdhps A581G).9 In Tororo, Uganda, around 78% of parasites carry the quintuple mutation, whereas none have the sextuple mutation.14 No data were available on pfdhf/pfdhps mutations in Busia, although Tororo and Busia are adjacent districts. Trial eligibility was restricted to HIV-uninfected pregnant women who were resident in the study region or health facility catchment area with no history of receiving IPTp during their current pregnancy. In the Kenya-STOPMiP trial,5 women between 16 and 32 gestational weeks of pregnancy were enrolled and randomly assigned to receive IPTp with dihydroartemisinin-piperaquine, IPTp with sulfadoxine-pyrimethamine, or intermittent screening and treatment (ISTp) with dihydroartemisinin-piperaquine. Women assigned to IPTp groups received IPTp at enrolment and then at each subsequent antenatal visit at intervals of 4–6 weeks. In the Ugandan studies,6, 7 women between 12 and 20 gestational weeks of pregnancy were enrolled. In Uganda-BC1,6 women were randomly assigned to receive either IPTp with sulfadoxine-pyrimethamine every 8 weeks, IPTp with dihydroartemisinin-piperaquine every 8 weeks, or IPTp with dihydroartemisinin-piperaquine every 4 weeks. In Uganda-BC3,7 women were randomised to either IPTp with sulfadoxine-pyrimethamine or IPTp with dihydroartemisinin-piperaquine every 4 weeks. Women assigned to IPTp every 8 weeks began IPTp at 20 gestational weeks of pregnancy, whereas women assigned to IPTp every 4 weeks began IPTp at 16 or 20 gestational weeks of pregnancy, depending on their gestational age at enrolment. For all studies, each dose of sulfadoxine-pyrimethamine was three tablets of 500 mg sulfadoxine and 25 mg of pyrimethamine given as a single dose. In Kenya-STOPMiP,5 dosing of dihydroartemisinin-piperaquine was based on bodyweight at enrolment (two, three, or four tablets of 40 mg dihydroartemisinin and 320 mg piperaquine per day for bodyweights of 24·0–35·9 kg, 36·0–74·9 kg; or ≥75·0 kg, respectively) and given once a day for 3 days. In the Ugandan studies,6, 7 each dose of dihydroartemisinin-piperaquine was three tablets of 40 mg dihydroartemisinin and 320 mg piperaquine given once a day for 3 days. Single-dose sulfadoxine-pyrimethamine and the first dose of dihydroartemisinin-piperaquine were administered under direct observation at the clinic, and the second and third doses of dihydroartemisinin-piperaquine were self-administered at home. The Ugandan trials were placebo-controlled such that all participants received a three-dose course. Participants in Kenya were visited at home 2 days after enrolment to verify drug adherence, and every fifth participant was visited at home on subsequent visits. For the Ugandan studies, standardised assessments were done to determine adherence. Our mediation analysis included women who had singleton livebirths, received at least one IPTp dose, and a known status of either past or active placental malaria infection. Placental malarial infection was determined by including women who either had a histopathological assessment of placental malaria using placenta tissue or women who tested positive for placental malaria by either microscopy, loop-mediated isothermal amplification, or PCR methods using placental blood. Women were excluded if they were assigned to the Kenya-STOPMiP ISTp group, assigned to the Uganda-BC1 IPTp with dihydroartemisinin-piperaquine every 4 weeks group, or had an unknown status of either past or active placental malaria (ie, missing placental histopathology results and negative for placental malaria by microscopy and molecular methods). Ethics approvals were granted by the Kenya Medical Research Institute, Makerere University School of Biomedical Sciences, the Uganda National Council for Science and Technology, the US Centers for Disease Control and Prevention, and the University of California, San Francisco. We defined treatment as random assignment to IPTp with either sulfadoxine-pyrimethamine or dihydroartemisinin-piperaquine. The mediator in our analysis was defined as the presence of previous or active placental malaria infection. A woman was determined to have a previous or active placental malaria infection if she had pigment or parasites in her placenta determined by histopathology of the placental tissue15 or if she tested positive for parasites by microscopy or molecular methods in her placental blood. Peripherally-detected malaria infection was considered a potential mediator (appendix 2 p 1) but we found that, in our sample of women, parasitaemia without the presence of placental malaria was not associated with lower birthweight, whereas women with placental malaria, regardless of whether they had peripherally-detected malaria, were more likely to have a baby with a lower birthweight. Confounding variables were identified a priori based on causal assumptions represented in a directed acyclic graph (appendix 2 p 2). Because of treatment randomisation, confounders were limited to those that affected mediator–outcome associations. These included gestational age at enrolment, maternal age, maternal parasitaemia at enrolment, gravidity, education, and household wealth. Gravidity was dichotomised as primigravidae (first pregnancy) or multigravidae (one or more previous pregnancies). Household wealth was reported as tertiles and calculated using principal components analysis of common household items. The primary outcome was a continuous measure of birthweight at delivery measured in g. Secondary outcomes were low birthweight (<2500 g) and preterm delivery (<37 gestational weeks). Further details on measurement of these outcomes are reported in the trials.5, 6, 7 We used causal mediation analysis16, 17, 18 to deconstruct the crude differences in birth outcomes between IPTp regimens (ie, overall treatment effect) into the difference in birth outcomes between IPTp regimens that is mediated by preventing placental malaria (ie, indirect or antimalarial effect) and the difference in birth outcomes between IPTp regimens that is not mediated by preventing placental malaria infection (ie, direct or non-malarial effect; appendix 2 pp 2–3). We estimated crude differences in birth outcomes between IPTp regimens using linear or log-binomial regression models with random assignment as the sole predictor. For mediation analyses, we used the mediation R package19 to estimate indirect and direct effects (appendix 2 p 3). We ran separate models to specify the dependence of placental malaria and birth outcomes based on treatment and prespecified confounders (as described in the assumed causal graph; appendix 2 p 2). Predicted values from these models were used in a Monte-Carlo framework to calculate indirect and direct effect estimates and corresponding 95% CIs, which we report as mean differences for birthweight and relative risks for low birthweight and preterm delivery. For all models, treatment–gravidity and treatment–mediator interaction terms were tested wherever possible and incorporated if the p values (pinteraction) of these terms were less than 0·10. We modelled continuous predictors as three-knot restricted cubic splines if the p value of the F test for the joint-effect of the non-linear components was less than 0·05. CIs around mediation effect estimates were generated for each study with a quasi-Bayesian approach using 1000 simulations. Effect modification by gravidity of indirect and direct effect estimates was tested using the test.modmed() function19 with corresponding p values reported as pdifference. For the mediator and primary outcome (placental malaria and birthweight, respectively), we report effect estimates separately for each study and by gravidity, regardless of whether there was evidence of a statistical interaction. Analyses of secondary outcomes (low birthweight and preterm delivery) were not reported separately by gravidity as they were relatively uncommon. We generated pooled-effect estimates using two-stage individual participant data meta-analyses. Individual participant data were used to derive effect estimates for each study and combined using a DerSimonian-Laird random-effects model from the meta R package.20 Between-study heterogeneity was measured using the I2 statistic. Analyses were done using Stata version 14.0 and R version 3.5.0. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Materials

Innovations

Based on the provided information, it seems that the study is focused on comparing the effects of two different treatments, sulfadoxine-pyrimethamine and dihydroartemisinin-piperaquine, on birth outcomes in pregnant women. The study aims to assess whether sulfadoxine-pyrimethamine has greater non-malarial benefits for birthweight compared to dihydroartemisinin-piperaquine, and whether dihydroartemisinin-piperaquine has greater antimalarial benefits for birth outcomes compared to sulfadoxine-pyrimethamine.

In terms of potential innovations to improve access to maternal health, here are a few recommendations:

1. Mobile Health (mHealth) Solutions: Develop mobile applications or text messaging services to provide pregnant women with information, reminders, and guidance on prenatal care, medication adherence, and healthy lifestyle practices.

2. Telemedicine: Implement telemedicine programs that allow pregnant women in remote or underserved areas to have virtual consultations with healthcare providers, reducing the need for travel and improving access to prenatal care.

3. Community Health Workers: Train and deploy community health workers to provide education, support, and basic prenatal care services to pregnant women in their communities, particularly in areas with limited access to healthcare facilities.

4. Supply Chain Management: Improve supply chain management systems to ensure the availability and timely delivery of essential maternal health medications, such as sulfadoxine-pyrimethamine and dihydroartemisinin-piperaquine, to healthcare facilities in remote areas.

5. Health Financing Models: Explore innovative health financing models, such as microinsurance or conditional cash transfer programs, to reduce financial barriers and increase access to maternal health services, including antenatal care and medication.

6. Public-Private Partnerships: Foster collaborations between public and private sectors to leverage resources, expertise, and technology for the development and implementation of innovative solutions to improve access to maternal health.

These are just a few examples of potential innovations that can be considered to improve access to maternal health. It is important to conduct further research and evaluation to determine the effectiveness and feasibility of these recommendations in specific contexts.

AI Innovations Description

The recommendation that can be developed into an innovation to improve access to maternal health based on the provided description is to further evaluate the use of monthly dihydroartemisinin-piperaquine with sulfadoxine-pyrimethamine (or another compound with non-malarial effects) to achieve greater protection against both malarial and non-malarial causes of low birthweight. This recommendation is based on the findings that sulfadoxine-pyrimethamine has potent non-malarial effects on birthweight, while dihydroartemisinin-piperaquine has a slightly larger antimalarial effect. By combining these two treatments and potentially adding another compound with non-malarial effects, it may be possible to improve birth outcomes and reduce the risk of low birthweight in pregnant women. Further research and evaluation are needed to determine the effectiveness and safety of this approach.

AI Innovations Methodology

Based on the provided description, it seems that the study is focused on comparing the effects of two different treatments (sulfadoxine-pyrimethamine and dihydroartemisinin-piperaquine) on birthweight and placental malaria infection in pregnant women. The study aims to assess whether sulfadoxine-pyrimethamine has greater non-malarial benefits for birth outcomes compared to dihydroartemisinin-piperaquine, and whether dihydroartemisinin-piperaquine has greater antimalarial benefits for birth outcomes compared to sulfadoxine-pyrimethamine.

To improve access to maternal health, it is important to consider innovations that can address the challenges faced by pregnant women in accessing healthcare services. Here are a few potential recommendations:

1. Mobile Health (mHealth) Solutions: Develop mobile applications or SMS-based systems that provide pregnant women with information, reminders for prenatal visits, and access to teleconsultations with healthcare providers. This can help overcome geographical barriers and improve communication between pregnant women and healthcare professionals.

2. Community Health Workers (CHWs): Train and deploy CHWs in remote or underserved areas to provide prenatal care, education, and support to pregnant women. CHWs can conduct regular check-ups, provide health education, and refer women to healthcare facilities when necessary.

3. Telemedicine: Establish telemedicine services that allow pregnant women to consult with healthcare providers remotely. This can be particularly beneficial for women in rural or isolated areas who may have limited access to healthcare facilities.

4. Transportation Support: Implement transportation programs that provide pregnant women with affordable or free transportation to healthcare facilities for prenatal visits, delivery, and postnatal care. This can help overcome transportation barriers that prevent women from accessing timely and appropriate care.

5. Maternal Health Vouchers: Introduce voucher programs that provide pregnant women with subsidized or free access to essential maternal health services, including prenatal care, delivery, and postnatal care. Vouchers can be distributed to vulnerable or low-income women to ensure equitable access to care.

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

1. Define the target population: Identify the specific group of pregnant women who would benefit from the innovation, such as those in remote areas or with limited access to healthcare facilities.

2. Collect baseline data: Gather data on the current access to maternal health services, including prenatal care utilization rates, distance to healthcare facilities, transportation availability, and other relevant factors.

3. Model the impact: Use mathematical modeling or simulation techniques to estimate the potential impact of the recommended innovations on improving access to maternal health. This could involve simulating scenarios with and without the innovations and comparing the outcomes, such as increased utilization of prenatal care, reduced travel time to healthcare facilities, or improved health outcomes for mothers and babies.

4. Sensitivity analysis: Conduct sensitivity analyses to assess the robustness of the results and explore the potential variations in the impact of the innovations under different assumptions or scenarios.

5. Policy recommendations: Based on the simulation results, provide evidence-based recommendations to policymakers and stakeholders on the implementation of the innovations to improve access to maternal health. Consider factors such as cost-effectiveness, scalability, and sustainability.

It is important to note that the specific methodology for simulating the impact may vary depending on the available data, resources, and expertise. Consulting with experts in the field of health systems research or health economics can provide further guidance on designing and conducting the simulation study.

Author

Dima Health

Statistics:

Citations: 26

Identifiers:

DOI: 10.1016/S2214-109X(20)30119-4

Research Areas:

Cancer, Community Interventions, Genetics and Genomics, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Sexual and Reproductive Health, Technology and Innovations

Study Countries:

Kenya, Multi-Countries, Uganda

Study Design:

Grounded Theory, Quasi Experimental Study

Study Approach:

Quantitative

Participants Gender:

Female