Declining child mortality in northern Malawi despite high rates of infection with HIV

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Study Justification:
The study aimed to determine whether routine surveys, such as the Demographic and Health Surveys (DHS), have underestimated child mortality in Malawi. This is important because accurate data on child mortality is crucial for effective policy-making and resource allocation.
Highlights:
– The study used a continuous-registration demographic surveillance system (DSS) to obtain rates and causes of child mortality in northern Malawi.
– The DSS recorded 38,617 person-years of observation for 20,388 children aged

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 utilized a continuous-registration demographic surveillance system (DSS) with a large population size and comprehensive data collection methods. The study also compared its findings with national estimates from routine surveys. However, to improve the evidence, the abstract could provide more details on the methodology used, such as the specific statistical analyses conducted and any limitations of the study. Additionally, including information on the representativeness of the study population and the generalizability of the findings would further strengthen the evidence.

Objective: To determine whether routine surveys, such as the Demographic and Health Surveys (DHS), have underestimated child mortality in Malawi. Methods: Rates and causes of child mortality were obtained from a continuous-registration demographic surveillance system (DSS) in Malawi for a population of 32 000. After initial census, births and deaths were reported by village informants and updated monthly by project enumerators. Cause of death was established by verbal autopsy whenever possible. The likely impact of human immunodeficiency virus (HIV) infection on child mortality was also estimated from antenatal clinic surveillance data. Overall and age-specific mortality rates were compared with those from the 2004 Malawi DHS. Findings: Between August 2002 and February 2006, 38 617 person-years of observation were recorded for 20 388 children aged < 15 years. There were 342 deaths. Re-census data, follow-up visits at 12 months of age and the ratio of stillbirths to neonatal deaths suggested that death registration by the DSS was nearly complete. Infant mortality was 52.7 per 1000 live births, under-5 mortality was 84.8 per 1000 and under-15 mortality was 99.1 per 1000. One-fifth of deaths by age 15 were attributable to HIV infection. Child mortality rates estimated with the DSS were approximately 30% lower than those from national estimates as determined by routine surveys. Conclusion The fact that child mortality rates based on the DSS were relatively low in the study population is encouraging and suggests that the low mortality rates estimated nationally are an accurate reflection of decreasing rates.

We set up a continuous-registration demographic surveillance system (DSS), covering a population of 32 000, in Karonga district (northern Malawi) in 2002.15 An initial house-to-house census (baseline census) recorded personal identifiers and sociodemographic data for all individuals, and economic data and physical location for every household. Demographic surveillance was started in 230 geographically-defined clusters, each containing 15–60 households, immediately after completion of the baseline census in a given cluster. Within each cluster, one village informant was trained to record births, deaths and migrations. Project field staff followed up and recorded births and deaths monthly and migrations annually. To check completeness of infant death registration, all babies whose birth was recorded in the DSS and who were not known to have died or migrated out of the area were visited at 12 months of age. This follow-up visit detected only one extra infant death among 662 eligible babies. The total DSS population was re-censused after 2 years. This showed that the monthly and annual reporting system had registered 99% of deaths, 97% of births and 92% of migrations.15 This report includes data from the beginning of the DSS in August 2002 until February 2006. Although the initial protocol was limited to live births, fetal deaths were also reported. To encourage reporting of early infant deaths, from March 2003 village informants were asked to report fetal deaths routinely, including miscarriages (fetal death before 7 months of gestation) and stillbirths (babies born dead after 7 months of gestation). Verbal autopsy interviews were conducted, if consent was given, by a medical assistant in the local language (Chitumbuka) with the most immediate caregiver who could be traced. Interviewers used standard semistructured questionnaires developed for neonatal deaths (ages 0–28 days) or child deaths (ages 29 days–14 years). Both instruments were similar to the INDEPTH verbal autopsy tool,16 an adaptation of the World Health Organization (WHO) verbal autopsy questionnaire.17 Additionally, whenever available, patient-held health documents were reviewed together with any hospital records for children for whom the cause of death was unclear from other information. Three individuals (physicians or experienced clinical officers) independently reviewed each verbal autopsy to assign the likely underlying cause of death. Any information on maternal HIV infection status from other research studies was made available to the reviewers. In accordance with WHO verbal autopsy standards,18 HIV/AIDS was assigned as a cause of death if symptoms suggested immunosuppression in the absence of other obvious causes, taking into account any available information on maternal HIV infection or AIDS death and any prior diagnoses of suspected HIV infection. Discrepantly-coded cases were discussed and resolved if possible, or coded as “nonspecifiable” if consensus could not be reached. HIV status was not routinely determined during the study. We estimated the number of children born to HIV-infected mothers in the study population and applied the probabilities of death in this group found in other studies without antiretroviral therapy (ART) or cotrimoxazole.19–22 Unlinked anonymous HIV serosurveillance was done at two antenatal care clinics within the DSS area.23–25 Birth registration in the DSS included information on antenatal clinic attendance; this information allowed us to estimate the proportion of mothers who attended these two clinics. Antenatal clinic registers showed that the rates of attendance varied little with time, so we assumed the pattern of antenatal clinic access was the same before the start of demographic surveillance. Maternal HIV infection rates were estimated from the age-specific HIV infection prevalence at the two antenatal clinics, applied to the mother’s age group at the time of giving birth. Maternal HIV prevalence was approximately 11% at the larger clinic and approximately 7% at the smaller, more rural clinic. Prophylaxis to prevent mother-to-child transmission was not generally available during the study period, but 44 HIV+ women identified at one of the antenatal clinics in another study received the maternal and paediatric dose of nevirapine. The free national ART programme started in June 2004, with the first clinic opening in Karonga district in June 2005, 80 km from the study area. At that time children were only treated at specialized facilities. No pregnant women were started on ART during this period, making it unlikely that vertical transmission and HIV-related infant mortality were reduced by ART roll-out. Cotrimoxazole prophylaxis became available in ART clinics in late 2005, but it is unlikely that any children in the study population had received this by February 2006. Overall and cause-specific mortality rates were calculated. Observation time for each child began when the child was first seen in the baseline census, at birth or at the time of migration into the area after the baseline census. Observation time ended at the time of death (if the child was still a member in a household in the area at the time of death) or at the time of migration out of the surveillance area. Multiple episodes of observation and gaps were allowed if the child moved out of the surveillance area and later returned. All analyses were done with Stata 10.0 software (Stata Corporation, College Station, United States of America). To estimate AIDS mortality, the failure event was death from AIDS or “tuberculosis or AIDS”. Deaths from all other known or unknown causes were censored. To estimate non-AIDS mortality, the failure event was death from causes other than AIDS or “tuberculosis or AIDS”. Deaths from AIDS or from “tuberculosis or AIDS” were censored, along with deaths from unknown causes. Standard child mortality indicators were calculated from the Kaplan–Meier function as the cumulative risks of death at the age of 28 days, 12 months, 24 months, 5 years and 15 years. The probability of dying between ages x and [x + n] (known as nqx) was calculated from the Kaplan–Meier survival function as This yielded the risk of death before the age of [x + n], conditional on having survived to age x. The completeness of ascertainment of deaths was assessed from the distribution of age at death. Stillbirths were included, since stillbirths and early infant deaths were more likely to be missed than deaths of older children26–29 and the number of stillbirths was expected to exceed the number of neonatal deaths in the population.29 Overall and age-specific mortality rates were compared with those estimated by the 2004 Malawi DHS.30

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

1. Implementing a continuous-registration demographic surveillance system (DSS): This system allows for the collection of accurate and up-to-date data on births, deaths, and migrations in a specific population. By implementing a DSS, healthcare providers can have a better understanding of the maternal health situation in a particular area, which can help in identifying areas for improvement and targeting interventions.

2. Conducting routine surveys: Routine surveys, such as the Demographic and Health Surveys (DHS), can provide valuable information on child mortality rates and causes of death. These surveys can help identify trends and patterns in maternal health and guide the development of targeted interventions.

3. Verbal autopsy interviews: Verbal autopsy interviews can be conducted to establish the likely cause of death when a formal medical diagnosis is not available. This can help in identifying specific causes of maternal mortality and inform strategies for prevention and treatment.

4. Antenatal clinic surveillance: Monitoring maternal HIV infection rates and providing access to antenatal care clinics can help in identifying and managing HIV-related complications during pregnancy. This can contribute to reducing maternal and child mortality rates.

5. Access to antiretroviral therapy (ART) and prophylaxis: Ensuring access to ART for HIV-positive pregnant women and providing prophylaxis to prevent mother-to-child transmission of HIV can significantly reduce maternal and child mortality rates associated with HIV infection.

6. Availability of cotrimoxazole prophylaxis: Providing cotrimoxazole prophylaxis to HIV-positive individuals, including pregnant women, can help prevent opportunistic infections and reduce mortality rates.

These innovations can contribute to improving access to maternal health services and reducing maternal and child mortality rates, particularly in areas with high rates of HIV infection like northern Malawi.
AI Innovations Description
Based on the information provided, the recommendation to improve access to maternal health in northern Malawi is to strengthen and expand the continuous-registration demographic surveillance system (DSS) that was implemented in Karonga district. This system has proven to be effective in accurately recording births, deaths, and migrations within the population.

To further enhance the DSS, the following steps can be taken:

1. Increase coverage: Expand the DSS to cover a larger population, including more villages and households. This will provide a more comprehensive picture of maternal health indicators and enable better tracking of maternal mortality rates.

2. Improve data collection: Train more village informants and project enumerators to ensure accurate and timely reporting of births, deaths, and migrations. Regular follow-up visits should be conducted to verify the completeness of data and detect any discrepancies.

3. Enhance cause of death determination: Continue conducting verbal autopsy interviews to establish the likely cause of death for children. This can help identify specific factors contributing to maternal mortality and guide targeted interventions.

4. Incorporate HIV surveillance: Strengthen the integration of HIV surveillance within the DSS. This can be done by collecting data on maternal HIV infection status and estimating the impact of HIV on child mortality rates. This information will be crucial in developing strategies to address the high rates of HIV-related deaths among children.

5. Collaborate with healthcare facilities: Establish partnerships with local healthcare facilities, particularly antenatal clinics, to gather additional data on maternal health indicators. This can include information on antenatal care attendance, HIV testing, and access to preventive measures such as antiretroviral therapy and cotrimoxazole prophylaxis.

By implementing these recommendations, the DSS can provide more accurate and comprehensive data on maternal health, leading to targeted interventions and innovations to improve access to maternal healthcare services in northern Malawi.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Strengthening healthcare infrastructure: Investing in healthcare facilities, equipment, and trained healthcare professionals in areas with limited access to maternal health services can improve access and quality of care.

2. Mobile health clinics: Implementing mobile health clinics that travel to remote areas can provide essential maternal health services, including prenatal care, vaccinations, and postnatal care, to women who may not have easy access to healthcare facilities.

3. Community health workers: Training and deploying community health workers can help bridge the gap between healthcare facilities and communities. These workers can provide education, counseling, and basic healthcare services to pregnant women and new mothers in their own communities.

4. Telemedicine: Utilizing telemedicine technology can connect pregnant women in remote areas with healthcare professionals who can provide virtual consultations, monitor their health, and offer guidance throughout their pregnancy.

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

1. Define the target population: Identify the specific population or region where the recommendations will be implemented.

2. Collect baseline data: Gather data on the current state of maternal health access in the target population, including indicators such as maternal mortality rates, prenatal care coverage, and distance to healthcare facilities.

3. Model the interventions: Use mathematical modeling techniques to simulate the implementation of the recommended interventions. This could involve estimating the number of healthcare facilities needed, the coverage and impact of mobile health clinics, the number of community health workers required, or the potential reach of telemedicine services.

4. Simulate the impact: Apply the modeled interventions to the baseline data and simulate the potential impact on maternal health access indicators. This could include estimating changes in maternal mortality rates, improvements in prenatal care coverage, or reductions in travel distances to healthcare facilities.

5. Evaluate the results: Analyze the simulated results to assess the effectiveness of the recommended interventions in improving access to maternal health. Compare the simulated outcomes with the baseline data to determine the potential impact of the interventions.

6. Refine and iterate: Based on the evaluation results, refine the interventions and repeat the simulation process to further optimize the recommendations and assess their potential long-term impact on maternal health access.

It’s 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 maternal health and utilizing appropriate statistical and modeling techniques will be crucial in conducting an accurate and comprehensive simulation.

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