Association of Respiratory Syncytial Virus Infection and Underlying Risk Factors for Death among Young Infants Who Died at University Teaching Hospital, Lusaka Zambia

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Study Justification:
The study aimed to investigate the association between respiratory syncytial virus (RSV) infection and underlying risk factors for death among young infants who died at University Teaching Hospital in Lusaka, Zambia. This research was important because RSV is a leading cause of acute lower respiratory tract infections and child mortality, particularly in low- and middle-income countries. However, most knowledge about risk factors for fatal RSV disease comes from high-income settings. Therefore, understanding the specific risk factors for RSV-related deaths in low-income settings like Zambia is crucial for developing effective prevention and treatment strategies.
Highlights:
– The study found that among the 720 infant deaths analyzed, 6% were RSV-positive.
– The majority of RSV-positive deaths occurred in infants younger than 4 weeks old, and more males were affected.
– Prematurity/low birth weight and complications of labor and delivery were the most common underlying medical conditions associated with infant deaths.
– Congenital cardiac conditions were significantly associated with an increased risk of RSV infection.
– Other underlying conditions were not significantly associated with RSV.
Recommendations:
Based on the study findings, the following recommendations can be made:
1. Improve neonatal care: Given that birth-related outcomes, such as prematurity and complications of labor and delivery, were the highest mortality risk factors, enhancing neonatal care is crucial in reducing infant mortality.
2. Focus on congenital cardiac conditions: Since congenital cardiac conditions were significantly associated with an increased risk of RSV infection, targeted interventions and preventive measures should be implemented for infants with these conditions.
3. Further research: More studies are needed to explore additional risk factors for RSV-related deaths in low-income settings and to develop comprehensive strategies for prevention and treatment.
Key Role Players:
To address the recommendations, the following key role players are needed:
1. Healthcare providers: Neonatologists, pediatricians, and other healthcare professionals involved in neonatal care.
2. Public health officials: Government officials responsible for implementing public health policies and programs.
3. Researchers: Scientists and researchers specializing in respiratory infections, child health, and epidemiology.
4. Non-governmental organizations (NGOs): Organizations working in the field of child health and providing support for neonatal care.
Cost Items for Planning Recommendations:
While the actual cost may vary, the following budget items should be considered in planning the recommendations:
1. Healthcare infrastructure: Investment in healthcare facilities, equipment, and resources for neonatal care.
2. Training and capacity building: Funding for training healthcare professionals in neonatal care and RSV prevention and treatment.
3. Research funding: Financial support for conducting further research on RSV-related deaths and risk factors.
4. Public health programs: Budget allocation for implementing preventive measures, such as vaccination campaigns and health education initiatives.
5. NGO support: Funding for NGOs working in the field of child health to provide assistance and support for neonatal care programs.
Please note that the above cost items are general considerations and may vary based on the specific context and priorities of the healthcare system in Zambia.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is a prospective cohort study, which is generally considered a strong design for assessing associations. The study includes a large number of infant deaths (720) and uses laboratory testing to identify RSV infection. However, there are a few limitations to consider. First, the study only includes infants who died at University Teaching Hospital in Lusaka, Zambia, which may limit the generalizability of the findings. Second, the study relies on death certificates and hospital records to identify underlying medical conditions, which may introduce some bias or misclassification. Third, the study does not provide detailed information on the methods used for data collection and analysis, which makes it difficult to fully evaluate the study’s methodology. To improve the strength of the evidence, future studies could consider including a more diverse population, using standardized criteria for identifying underlying medical conditions, and providing more transparency in the methods section.

Background: Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infections and child mortality. While RSV disease burden is highest in low- and middle-income countries, most knowledge about risk factors for fatal RSV disease comes from high-income settings. Methods: Among infants aged 4 days to <6 months who died at University Teaching Hospital in Lusaka, Zambia, we tested nasopharyngeal swabs obtained postmortem for RSV using reverse transcriptase-quantitative polymerase chain reaction. Through a systematic review of death certificates and hospital records, we identified 10 broad categories of underlying medical conditions associated with infant deaths. We used backward-selection models to calculate adjusted and unadjusted risk ratios (RRs) for the association between each underlying condition and RSV status. Results: From 720 infant deaths, 6% (44) were RSV-positive, 70% were <4 weeks old, and 54% were male. At least 1 underlying condition was found in 85% of infants, while 63% had ≥2. Prematurity/low birth weight (53% [384]) and complications of labor and delivery (32% [230]) were the most common conditions. Congenital cardiac conditions were significantly associated with an increased risk of RSV infection (4%, 32; adjusted RR: 3.57; 95% CI: 1.71-7.44). No other underlying conditions were significantly associated with RSV. Conclusions: Other than congenital cardiac conditions, we found a lack of association between RSV and underlying risk factors. This differs from high-income settings, where RSV mortality is concentrated among high-risk infants. In this population, birth-related outcomes are the highest mortality risk factors. Improved neonatal care remains crucial in the fight against neonatal mortality.

ZPRIME study researchers identified infants aged 4 days to younger than 6 months who died in Lusaka, Zambia, from August 2017 through August 2020. The present analysis utilizes a subset of the full cohort and includes data collected through December 2019. In Zambia, a burial cannot occur without a burial permit. Therefore, all deaths must first be cleared for burial at the medical examiner’s office at the University Teaching Hospital (UTH) or one of a select number of smaller clinics. For this analysis, we focus on deaths that occurred at the University Teaching Hospital in Lusaka, for which we had access to medical history data from the death certificates and clinical charts (Figure 1). In a separate analysis within this issue of Clinical Infectious Diseases, we present explanatory data pertaining to community RSV deaths (see Murphy et al in this Supplement issue). Flowchart showing the entry pathway for final enrollment into ZPRIME including the sources of noninclusion. Between the August 2017 and August 2020 ZPRIME we enrolled 2286 infants aged 4 days to <6 months. For infants enrolled from the UTH morgue, we collected “long form” data, which included demographic and clinical data that we extracted from the medical charts and/or the medical certificate of the cause of death. For this analysis, we focus on facility deaths that were enrolled between August 2017 and December 2019 for which we had collected “long form” data (highlighted in yellow). The present analysis includes ~98% of all these deaths. Abbreviations: UTH, University Teaching Hospital; ZPRIME, Zambia Pertussis Infant Mortality Estimation Study. For all deaths, researchers approached family members accompanying the body to the UTH morgue and, after obtaining informed consent, enrolled them in the study, and noted their age, sex, and date of death. We obtained postmortem nasopharyngeal (NP) samples from each infant using flocked nylon swabs (Copan Diagnostics, Murietta, CA). The swabs were placed in universal transport media on ice, transported to the microbiology laboratory on site at UTH, and stored at −80°C until RSV testing. Nucleic acid extraction was performed using the NucliSens easyMAG system (bioMérieux, Marcy I’Etoile, France), a system for automated isolation of nucleic acids from clinical samples based on silica extraction technology. Screening for RSV used a singleplex reaction specific to the dominant M protein on the virus using reverse transcriptase–quantitative polymerase chain reaction (RT-qPCR), a following the RSV protocol from the respiratory viruses branch at US CDC [7]. In order to demonstrate that the NP swab made effective contact with the respiratory mucosa, each sample run included primers/probes specific to the human constitutive enzyme RNAseP, which is expressed in all human cells (including the nasal epithelium). Its presence, therefore, validates the adequacy of the sample collection process. A positive RSV signal was defined as having a cycle threshold (CT) value of less than 40. All runs included positive and negative controls. Using the death certificates and hospital records of deceased infants, we identified sections of these forms where conditions related to the infants’ health before death were recorded. Fields analyzed from hospital records included 2 free-text fields: “provisional diagnosis” and “clinic diagnosis or reason for referral,” and checkboxes indicating maternal human immunodeficiency virus (HIV) status, prematurity, complications of labor and delivery, low birth weight, and malnutrition. Death certificates in Zambia categorize the cause of death hierarchically with 3 causes of death. All 3 of these fields were included in our analysis. These fields are as follows: “disease or condition directly leading to death,” “antecedent cause,” and “morbid conditions giving rise to the above cause.” We ran frequency tabulations of the data entered into these fields. The frequencies were then reviewed by the principal investigator who is a child survival expert and infectious disease specialist. He collapsed all of the underlying conditions into 1 of the 10 broad categories, as listed in Table 1. These categories were both hypothesis-generating, based on patterns seen in the data themselves, and based on historical precedent, utilizing prior knowledge of risk factors for infant mortality and respiratory disease. To confirm these categorizations, they were then reviewed by 2 additional infectious disease physicians, including a Zambian physician based in Lusaka. Often, the full-text field would list out the condition directly, but conditions were also described idiosyncratically and/or via a variety of different verbatim terms. For example, “low birth weight” was often listed using the acronym LBW, or VLBW (very low birth weight), or ELBW (extremely low birth weight), etc. Similarly, “congenital cardiac conditions” could appear as cyanotic heart disease, congenital heart disease, complex heart disease, or cardiomyopathy. It could also appear using various acronyms, or specifying certain syndromes directly (eg, Tetralogy of Fallot, often abbreviated as TOF). Infants were categorized as having prematurity in cases where the full words “prematurity” or “preterm delivery” were present. In other cases, conditions were described generically without a detailed anatomic explanation. The full list of verbatim terms and how these were collapsed into the 10 final conditions is included in Supplementary Table 1. Demographic Risk Factors, Medical Risk Factors, and Underlying Conditions by Presence of Respiratory Syncytial Virus Data are presented as n (%) unless otherwise indicated. Abbreviations: HIV, human immunodeficiency virus; RSV, respiratory syncytial virus. We then assigned underlying conditions to each infant based on the presence of keywords related to those 10 categories. Each field was analyzed independently of other fields for the same subject to avoid bias based on a full review of a particular infant’s health records. Infants could therefore be assigned 0, 1, or more underlying conditions. Demographic characteristics, such as place of birth (hospital or health facility vs other), parental employment and education, and number of people in the household, were collected via direct interview with the caretaker who accompanied the body to the morgue. Descriptive statistics were calculated to determine the prevalence of each of the above conditions, demographic characteristics, and medical risk factors, stratified by RSV status. Unadjusted log-binomial regression models were used to compute risk ratios (RRs) for each underlying condition and its association with RSV. Given the study design (prospective cohort study), we feel that we were able to capture all infants at risk during the period, and therefore RRs are an appropriate measure of the risk of RSV in the population. In order to determine which underlying factors and covariates were associated with RSV, we used a backward-selection approach. We ran 10 separate models: one for each of the underlying conditions, with the exception of conditions associated with prematurity, as there were zero RSV-positive infants with that condition, plus one for infants with none of the identified conditions. All demographic and medical risk factors shown in Table 1 were included in the original models, and the underlying condition was forced into the final model. We used a P-value threshold of .2 for inclusion in the final model. Last, we ran adjusted and unadjusted models for combinations of conditions which, based on prior medical knowledge, are often related. We created 1 merged condition such that infants with either 1 or both risk factors were classified as yes and infants who did not have either of the risk factors were classified as no. The following merged conditions were used: HIV exposure and/or malnutrition, prematurity and/or congenital cardiac conditions, and prematurity and/or conditions associated with prematurity.

Based on the provided information, it is difficult to identify specific innovations for improving access to maternal health. The information provided focuses on a study conducted in Lusaka, Zambia, regarding respiratory syncytial virus (RSV) infection and underlying risk factors for infant mortality. The study analyzes data from death certificates and hospital records to identify underlying medical conditions associated with infant deaths.

To improve access to maternal health, it is important to consider a range of potential innovations. Some possible recommendations could include:

1. Telemedicine: Implementing telemedicine services to provide remote consultations and support for pregnant women, allowing them to access healthcare professionals without the need for physical visits.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information, reminders, and guidance on prenatal care, nutrition, and maternal health, making it easier for women to access important resources and track their health during pregnancy.

3. Community health workers: Expanding the role of community health workers to provide education, support, and basic healthcare services to pregnant women in remote or underserved areas, improving access to maternal health services.

4. Maternal health clinics: Establishing dedicated maternal health clinics in areas with limited healthcare infrastructure, providing comprehensive prenatal care, delivery services, and postnatal care to ensure women have access to essential maternal health services.

5. Transportation solutions: Implementing transportation solutions, such as mobile clinics or transportation vouchers, to help pregnant women in remote areas reach healthcare facilities for prenatal care, delivery, and postnatal care.

6. Maternal health education programs: Developing and implementing educational programs that focus on maternal health, including prenatal care, nutrition, breastfeeding, and newborn care, to empower women with knowledge and promote healthy practices.

7. Maternal health financing initiatives: Implementing innovative financing mechanisms, such as health insurance schemes or conditional cash transfer programs, to reduce financial barriers and improve access to maternal health services.

It is important to note that these recommendations are general and may need to be tailored to the specific context and needs of the population in Lusaka, Zambia, or any other location. Additionally, further research and analysis would be required to determine the feasibility and effectiveness of these innovations in improving access to maternal health.
AI Innovations Description
Based on the information provided, the recommendation to improve access to maternal health and address the underlying risk factors identified in the study is to implement the following strategies:

1. Strengthen neonatal care: Given that birth-related outcomes were identified as the highest mortality risk factors, improving neonatal care is crucial. This can be achieved by enhancing the training and capacity of healthcare providers in managing complications during labor and delivery, as well as providing adequate support and resources for neonatal care units.

2. Improve access to antenatal care: Early and regular antenatal care plays a vital role in identifying and managing underlying medical conditions that can contribute to maternal and infant mortality. Efforts should be made to increase access to antenatal care services, particularly in low-income and rural areas, through the establishment of more healthcare facilities, mobile clinics, and community outreach programs.

3. Enhance screening and management of congenital cardiac conditions: The study found a significant association between congenital cardiac conditions and an increased risk of respiratory syncytial virus (RSV) infection. Therefore, it is important to strengthen screening programs to detect congenital cardiac conditions early in pregnancy and provide appropriate interventions and management strategies to reduce the risk of RSV infection and associated complications.

4. Promote maternal education and awareness: Educating expectant mothers about the importance of antenatal care, healthy lifestyle choices, and recognizing warning signs during pregnancy can empower them to seek timely medical assistance and make informed decisions regarding their health and the health of their infants.

5. Strengthen healthcare infrastructure and resources: Adequate healthcare infrastructure, including well-equipped facilities, sufficient medical supplies, and trained healthcare professionals, is essential for providing quality maternal and neonatal care. Investments should be made to improve healthcare infrastructure and ensure the availability of essential resources in both urban and rural areas.

6. Collaborate with international organizations and stakeholders: Engaging with international organizations, such as the World Health Organization (WHO) and non-governmental organizations (NGOs), can provide additional support, expertise, and resources to implement innovative solutions and interventions to improve access to maternal health.

By implementing these recommendations, it is possible to enhance access to maternal health services, reduce maternal and infant mortality rates, and improve overall maternal and neonatal outcomes.
AI Innovations Methodology
To improve access to maternal health, here are some potential recommendations:

1. Telemedicine: Implementing telemedicine services can provide remote access to healthcare professionals for prenatal care, postpartum check-ups, and consultations. This can be particularly beneficial for women in rural or underserved areas who may have limited access to healthcare facilities.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information on maternal health, track pregnancy progress, and send reminders for appointments and medication can empower women to take control of their own health. These apps can also provide access to educational resources and connect women with healthcare providers.

3. Community health workers: Training and deploying community health workers who can provide basic maternal healthcare services, education, and support in remote or underserved areas can help bridge the gap in access to maternal health services.

4. Transportation support: Establishing transportation services or subsidies specifically for pregnant women can help overcome barriers related to distance and transportation costs, ensuring that women can access healthcare facilities for prenatal care, delivery, and postpartum care.

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 that would benefit from the recommendations, such as pregnant women in rural areas or low-income communities.

2. Collect baseline data: Gather data on the current access to maternal health services, including the number of women receiving prenatal care, the distance to healthcare facilities, and any existing barriers.

3. Define indicators: Determine key indicators to measure the impact of the recommendations, such as the number of women accessing prenatal care, the reduction in travel time to healthcare facilities, or the increase in knowledge about maternal health.

4. Simulate the implementation: Use modeling techniques to simulate the implementation of the recommendations. This could involve creating scenarios where telemedicine services, mHealth applications, community health workers, or transportation support are introduced and estimating the potential increase in access to maternal health services based on the defined indicators.

5. Analyze the results: Evaluate the simulated impact of the recommendations on improving access to maternal health by comparing the baseline data with the simulated outcomes. Assess the changes in the defined indicators and determine the effectiveness of each recommendation.

6. Refine and iterate: Based on the analysis, refine the recommendations and simulation methodology if necessary. Iterate the process to further optimize the impact on improving access to maternal health.

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of different innovations and make informed decisions on implementing strategies to improve access to maternal health.

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