Health facility assessment of small and sick newborn care in low- and middle-income countries: systematic tool development and operationalisation with NEST360 and UNICEF.

BACKGROUND: Each year an estimated 2.3 million newborns die in the first 28 days of life. Most of these deaths are preventable, and high-quality neonatal care is fundamental for surviving and thriving. Service readiness is used to assess the capacity of hospitals to provide care, but current health facility assessment (HFA) tools do not fully evaluate inpatient small and sick newborn care (SSNC). METHODS: Health systems ingredients for SSNC were identified from international guidelines, notably World Health Organization (WHO), and other standards for SSNC. Existing global and national service readiness tools were identified and mapped against this ingredients list. A novel HFA tool was co-designed according to a priori considerations determined by policymakers from four African governments, including that the HFA be completed in one day and assess readiness across the health system. The tool was reviewed by > 150 global experts, and refined and operationalised in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania between September 2019 and March 2021. RESULTS: Eight hundred and sixty-six key health systems ingredients for service readiness for inpatient SSNC were identified and mapped against four global and eight national tools measuring SSNC service readiness. Tools revealed major content gaps particularly for devices and consumables, care guidelines, and facility infrastructure, with a mean of 13.2% (n = 866, range 2.2-34.4%) of ingredients included. Two tools covered 32.7% and 34.4% (n = 866) of ingredients and were used as inputs for the new HFA tool, which included ten modules organised by adapted WHO health system building blocks, including: infrastructure, pharmacy and laboratory, medical devices and supplies, biomedical technician workshop, human resources, information systems, leadership and governance, family-centred care, and infection prevention and control. This HFA tool can be conducted at a hospital by seven assessors in one day and has been used in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania. CONCLUSION: This HFA tool is available open-access to adapt for use to comprehensively measure service readiness for level-2 SSNC, including respiratory support. The resulting facility-level data enable comparable tracking for Every Newborn Action Plan coverage target four within and between countries, identifying facility and national-level health systems gaps for action.

Quantifying health facility service readiness for small and sick newborn care: comparing standards-based and WHO level-2 + scoring for 64 hospitals implementing with NEST360 in Kenya, Malawi, Nigeria, and Tanzania.

BACKGROUND: Service readiness tools are important for assessing hospital capacity to provide quality small and sick newborn care (SSNC). Lack of summary scoring approaches for SSNC service readiness means we are unable to track national targets such as the Every Newborn Action Plan targets. METHODS: A health facility assessment (HFA) tool was co-designed by Newborn Essential Solutions and Technologies (NEST360) and UNICEF with four African governments. Data were collected in 68 NEST360-implementing neonatal units in Kenya, Malawi, Nigeria, and Tanzania (September 2019-March 2021). Two summary scoring approaches were developed: a) standards-based, including items for SSNC service readiness by health system building block (HSBB), and scored on availability and functionality, and b) level-2 + , scoring items on readiness to provide WHO level-2 + clinical interventions. For each scoring approach, scores were aggregated and summarised as a percentage and equally weighted to obtain an overall score by hospital, HSBB, and clinical intervention. RESULTS: Of 1508 HFA items, 1043 (69%) were included in standards-based and 309 (20%) in level-2 + scoring. Sixty-eight neonatal units across four countries had median standards-based scores of 51% [IQR 48-57%] at baseline, with variation by country: 62% [IQR 59-66%] in Kenya, 49% [IQR 46-51%] in Malawi, 50% [IQR 42-58%] in Nigeria, and 55% [IQR 53-62%] in Tanzania. The lowest scoring was family-centred care [27%, IQR 18-40%] with governance highest scoring [76%, IQR 71-82%]. For level-2 + scores, the overall median score was 41% [IQR 35-51%] with variation by country: 50% [IQR 44-53%] in Kenya, 41% [IQR 35-50%] in Malawi, 33% [IQR 27-37%] in Nigeria, and 41% [IQR 32-52%] in Tanzania. Readiness to provide antibiotics by culture report was the highest-scoring intervention [58%, IQR 50-75%] and neonatal encephalopathy management was the lowest-scoring [21%, IQR 8-42%]. In both methods, overall scores were low (< 50%) for 27 neonatal units in standards-based scoring and 48 neonatal units in level-2 + scoring. No neonatal unit achieved high scores of > 75%. DISCUSSION: Two scoring approaches reveal gaps in SSNC readiness with no neonatal units achieving high scores (> 75%). Government-led quality improvement teams can use these summary scores to identify areas for health systems change. Future analyses could determine which items are most directly linked with quality SSNC and newborn outcomes.

Investment case for small and sick newborn care in Tanzania: systematic analyses.

BACKGROUND: Small and sick newborn care (SSNC) is critical for national neonatal mortality reduction targets by 2030. Investment cases could inform implementation planning and enable coordinated resource mobilisation. We outline development of an investment case for Tanzania to estimate additional financing for scaling up SSNC to 80% of districts as part of health sector strategies to meet the country's targets. METHODS: We followed five steps: (1) reviewed national targets, policies and guidelines; (2) modelled potential health benefits by increased coverage of SSNC using the Lives Saved Tool; (3) estimated setup and running costs using the Neonatal Device Planning and Costing Tool, applying two scenarios: (A) all new neonatal units and devices with optimal staffing, and (B) half new and half modifying, upgrading, or adding resources to existing neonatal units; (4) calculated budget impact and return on investment (ROI) and (5) identified potential financing opportunities. RESULTS: Neonatal mortality rate was forecast to fall from 20 to 13 per 1000 live births with scale-up of SSNC, superseding the government 2025 target of 15, and close to the 2030 Sustainable Development Goal 3.2 target of <12. At 85% endline coverage, estimated cumulative lives saved were 36,600 by 2025 and 80,000 by 2030. Total incremental costs were estimated at US$166 million for scenario A (US$112 million set up and US$54 million for running costs) and US$90 million for scenario B (US$65 million setup and US$25 million for running costs). Setup costs were driven by infrastructure (83%) and running costs by human resources (60%). Cost per capita was US$0.93 and the ROI is estimated to be between US$8-12 for every dollar invested. CONCLUSIONS: ROI for SSNC is higher compared to other health investments, noting many deaths averted followed by full lifespan. This is conservative since disability averted is not included. Budget impact analysis estimated a required 2.3% increase in total government health expenditure per capita from US$40.62 in 2020, which is considered affordable, and the government has already allocated additional funding. Our proposed five-step SSNC investment case has potential for other countries wanting to accelerate progress.

Facilitators, barriers, and key influencers of breastfeeding among low birthweight infants: a qualitative study in India, Malawi, and Tanzania.

BACKGROUND: Low birthweight (LBW) infants are at increased risk of morbidity and mortality. Exclusive breastfeeding up to six months is recommended to help them thrive through infection prevention, growth improvements, and enhancements in neurodevelopment. However, limited data exist on the feeding experiences of LBW infants, their caregivers and key community influencers. The qualitative component of the Low Birthweight Infant Feeding Exploration (LIFE) study aimed to understand practices, facilitators, and barriers to optimal feeding options in the first six months for LBW infants in low-resource settings. METHODS: This study was conducted in four sites in India, Malawi, and Tanzania from July 2019 to August 2020. We conducted 37 focus group discussions with mothers and family members of LBW infants and community leaders and 142 in-depth interviews with healthcare providers, government officials, and supply chain and donor human milk (DHM) experts. Data were analyzed using a framework approach. RESULTS: All participants believed that mother's own milk was best for LBW infants. Direct breastfeeding was predominant and feeding expressed breast milk and infant formula were rare. DHM was a new concept for most. Adequate maternal nutrition, lactation support, and privacy in the facility aided breastfeeding and expression, but perceived insufficient milk, limited feeding counseling, and infant immaturity were common barriers. Most believed that DHM uptake could be enabled through community awareness by overcoming misconceptions, safety concerns, and perceived family resistance. CONCLUSION: This study fills an evidence gap in LBW infant feeding practices and their facilitators and barriers in resource-limited settings. LBW infants face unique feeding challenges such as poor latching and tiring at the breast. Similarly, their mothers are faced with numerous difficulties, including attainment of adequate milk supply, breast pain and emotional stress. Lactation support and feeding counseling could address obstacles faced by mothers and infants by providing psychosocial, verbal and physical support to empower mothers with skills, knowledge and confidence and facilitate earlier, more and better breast milk feeding. Findings on DHM are critical to the future development of human milk banks and highlight the need to solicit partnership from stakeholders in the community and health system.

Protecting small and sick newborn care in the COVID-19 pandemic: multi-stakeholder qualitative data from four African countries with NEST360.

BACKGROUND: Health system shocks are increasing. The COVID-19 pandemic resulted in global disruptions to health systems, including maternal and newborn healthcare seeking and provision. Yet evidence on mitigation strategies to protect newborn service delivery is limited. We sought to understand what mitigation strategies were employed to protect small and sick newborn care (SSNC) across 65 facilities Kenya, Malawi, Nigeria and Tanzania, implementing with the NEST360 Alliance, and if any could be maintained post-pandemic. METHODS: We used qualitative methods (in-depth interviews n=132, focus group discussions n=15) with purposively sampled neonatal health systems actors in Kenya, Malawi, Nigeria and Tanzania. Data were collected from September 2021 - August 2022. Topic guides were co-developed with key stakeholders and used to gain a detailed understanding of approaches to protect SSNC during the COVID-19 pandemic. Questions explored policy development, collaboration and investments, organisation of care, human resources, and technology and device innovations. Interviews were conducted by experienced qualitative researchers and data were collected until saturation was reached. Interviews were digitally recorded and transcribed verbatim. A common coding framework was developed, and data were coded via NVivo and analysed using a thematic framework approach. FINDINGS: We identified two pathways via which SSNC was strengthened. The first pathway, COVID-19 specific responses with secondary benefit to SSNC included: rapid policy development and adaptation, new and collaborative funding partnerships, improved oxygen systems, strengthened infection prevention and control practices. The second pathway, health system mitigation strategies during the pandemic, included: enhanced information systems, human resource adaptations, service delivery innovations, e.g., telemedicine, community engagement and more emphasis on planned preventive maintenance of devices. Chronic system weaknesses were also identified that limited the sustainability and institutionalisation of actions to protect SSNC. CONCLUSION: Innovations to protect SSNC in response to the COVID-19 pandemic should be maintained to support resilience and high-quality routine SSNC delivery. In particular, allocation of resources to sustain high quality and resilient care practices and address remaining gaps for SSNC is critical.

Neonatal inpatient dataset for small and sick newborn care in low- and middle-income countries: systematic development and multi-country operationalisation with NEST360.

BACKGROUND: Every Newborn Action Plan (ENAP) coverage target 4 necessitates national scale-up of Level-2 Small and Sick Newborn Care (SSNC) (with Continuous Positive Airway Pressure (CPAP)) in 80% of districts by 2025. Routine neonatal inpatient data is important for improving quality of care, targeting equity gaps, and enabling data-driven decision-making at individual, district, and national-levels. Existing neonatal inpatient datasets vary in purpose, size, definitions, and collection processes. We describe the co-design and operationalisation of a core inpatient dataset for use to track outcomes and improve quality of care for small and sick newborns in high-mortality settings. METHODS: A three-step systematic framework was used to review, co-design, and operationalise this novel neonatal inpatient dataset in four countries (Malawi, Kenya, Tanzania, and Nigeria) implementing with the Newborn Essential Solutions and Technologies (NEST360) Alliance. Existing global and national datasets were identified, and variables were mapped according to categories. A priori considerations for variable inclusion were determined by clinicians and policymakers from the four African governments by facilitated group discussions. These included prioritising clinical care and newborn outcomes data, a parsimonious variable list, and electronic data entry. The tool was designed and refined by > 40 implementers and policymakers during a multi-stakeholder workshop and online interactions. RESULTS: Identified national and international datasets (n = 6) contained a median of 89 (IQR:61-154) variables, with many relating to research-specific initiatives. Maternal antenatal/intrapartum history was the largest variable category (21, 23.3%). The Neonatal Inpatient Dataset (NID) includes 60 core variables organised in six categories: (1) birth details/maternal history; (2) admission details/identifiers; (3) clinical complications/observations; (4) interventions/investigations; (5) discharge outcomes; and (6) diagnosis/cause-of-death. Categories were informed through the mapping process. The NID has been implemented at 69 neonatal units in four African countries and links to a facility-level quality improvement (QI) dashboard used in real-time by facility staff. CONCLUSION: The NEST360 NID is a novel, parsimonious tool for use in routine information systems to inform inpatient SSNC quality. Available on the NEST360/United Nations Children's Fund (UNICEF) Implementation Toolkit for SSNC, this adaptable tool enables facility and country-level comparisons to accelerate progress toward ENAP targets. Additional linked modules could include neonatal at-risk follow-up, retinopathy of prematurity, and Level-3 intensive care.

Target product profiles for neonatal care devices: systematic development and outcomes with NEST360 and UNICEF.

BACKGROUND: Medical devices are critical to providing high-quality, hospital-based newborn care, yet many of these devices are unavailable in low- and middle-income countries (LMIC) and are not designed to be suitable for these settings. Target Product Profiles (TPPs) are often utilised at an early stage in the medical device development process to enable user-defined performance characteristics for a given setting. TPPs can also be applied to assess the profile and match of existing devices for a given context. METHODS: We developed initial TPPs for 15 newborn product categories for LMIC settings. A Delphi-like process was used to develop the TPPs. Respondents completed an online survey where they scored their level of agreement with each of the proposed performance characteristics for each of the 15 devices. Characteristics with < 75% agreement between respondents were discussed and voted on using Mentimeter™ at an in-person consensus meeting. FINDINGS: The TPP online survey was sent to 180 people, of which 103 responded (57%). The majority of respondents were implementers/clinicians (51%, 53/103), with 50% (52/103) from LMIC. Across the 15 TPPs, 403 (60%) of the 668 performance characteristics did not achieve > 75% agreement. Areas of disagreement were voted on by 69 participants at an in-person consensus meeting, with consensus achieved for 648 (97%) performance characteristics. Only 20 (3%) performance characteristics did not achieve consensus, most (15/20) relating to quality management systems. UNICEF published the 15 TPPs in April 2020, accompanied by a report detailing the online survey results and consensus meeting discussion, which has been viewed 7,039 times (as of January 2023). CONCLUSIONS: These 15 TPPs can inform developers and enable implementers to select neonatal care products for LMIC. Over 2,400 medical devices and diagnostics meeting these TPPs have been installed in 65 hospitals in Nigeria, Tanzania, Kenya, and Malawi through the NEST360 Alliance. Twenty-three medical devices identified and qualified by NEST360 meet nearly all performance characteristics across 11 of the 15 TPPs. Eight of the 23 qualified medical devices are available in the UNICEF Supply Catalogue. Some developers have adjusted their technologies to meet these TPPs. There is potential to adapt the TPP process beyond newborn care.

Blood culture versus antibiotic use for neonatal inpatients in 61 hospitals implementing with the NEST360 Alliance in Kenya, Malawi, Nigeria, and Tanzania: a cross-sectional study.

BACKGROUND: Thirty million small and sick newborns worldwide require inpatient care each year. Many receive antibiotics for clinically diagnosed infections without blood cultures, the current 'gold standard' for neonatal infection detection. Low neonatal blood culture use hampers appropriate antibiotic use, fuelling antimicrobial resistance (AMR) which threatens newborn survival. This study analysed the gap between blood culture use and antibiotic prescribing in hospitals implementing with Newborn Essential Solutions and Technologies (NEST360) in Kenya, Malawi, Nigeria, and Tanzania. METHODS: Inpatient data from every newborn admission record (July 2019-August 2022) were included to describe hospital-level blood culture use and antibiotic prescription. Health Facility Assessment data informed performance categorisation of hospitals into four tiers: (Tier 1) no laboratory, (Tier 2) laboratory but no microbiology, (Tier 3) neonatal blood culture use < 50% of newborns receiving antibiotics, and (Tier 4) neonatal blood culture use > 50%. RESULTS: A total of 144,146 newborn records from 61 hospitals were analysed. Mean hospital antibiotic prescription was 70% (range = 25-100%), with 6% mean blood culture use (range = 0-56%). Of the 10,575 blood cultures performed, only 24% (95%CI 23-25) had results, with 10% (10-11) positivity. Overall, 40% (24/61) of hospitals performed no blood cultures for newborns. No hospitals were categorised as Tier 1 because all had laboratories. Of Tier 2 hospitals, 87% (20/23) were District hospitals. Most hospitals could do blood cultures (38/61), yet the majority were categorised as Tier 3 (36/61). Only two hospitals performed > 50% blood cultures for newborns on antibiotics (Tier 4). CONCLUSIONS: The two Tier 4 hospitals, with higher use of blood cultures for newborns, underline potential for higher blood culture coverage in other similar hospitals. Understanding why these hospitals are positive outliers requires more research into local barriers and enablers to performing blood cultures. Tier 3 facilities are missing opportunities for infection detection, and quality improvement strategies in neonatal units could increase coverage rapidly. Tier 2 facilities could close coverage gaps, but further laboratory strengthening is required. Closing this culture gap is doable and a priority for advancing locally-driven antibiotic stewardship programmes, preventing AMR, and reducing infection-related newborn deaths.

Nurses' knowledge, perceived challenges, and recommended solutions regarding premature infant care: A mixed method study in the referral and tertiary hospitals in Dar es salaam, Tanzania.

BACKGROUND: There has been an increase in preterm birth of about 2% in a span of 14 years (2000-2014) mainly from Asia and Sub-Saharan Africa. Nursing care is very crucial and a lack of knowledge of health care providers is a contributing factor to morbidity and mortality. With the increasing number and investment of preterm infants towards attaining sustainable development goals (SDG) 3.2, nurses' knowledge adequacy, challenges and solutions on their care needs to be affirmed. METHODS: A mixed method study was conducted between September 2020 to January 2021 in the neonatal units of four hospitals in Dar es Salaam. Self-administered structured questionnaire was used to assess adequacy of knowledge set at 50% or more for the three main domains 1) Essential newborn Care 2) Infection prevention and management 3) Special care and monitoring. A phenomenological design using a structured interview guide focused on challenges and recommended solutions in acquiring on-the- job training on the care of preterm infants. Quantitative data were analyzed using SPSS version 23 and qualitative data were thematically categorized. RESULTS: Out of 52 of nurses who participated and providing care to preterm infants; 48.1% came from a tertiary hospital, (84.6%) were females, only 28.8% aged more than 40 years and 23.1% had less than one year of experience. Overall, 55.8% of the nurses had never received on job training. Adequate knowledge among nurses was 94% on essential newborn care, 80.8% on infection prevention and management and 36.5% on special care and monitoring of preterm infants. Generally, immediate actions of helping baby breath (HBB) and cord care scored poorest. Components on special care and monitoring which had lowest scores included blood glucose monitoring, temperature monitoring and acceptable daily weight gain. Being more than 41 years old, a female nurse and working in the neonatal unit for at least 1-3 years were more likely to determine adequacy of knowledge on infection prevention and management. Lack of schedule and ways to identify those who require training were among the challenges mentioned in the focus group discussion. CONCLUSION: The findings demonstrate an urgent need of instilling knowledge, skills and competences among nurses providing preterm care in our hospitals. Most nurses had not attended training on the care of premature infant. Special care and monitoring were most poorly performed. The recommended solutions included continuous medical education (CME) for all nurses through hospital and government commitment and encourage mentorship within and between hospitals. Nurses who are female, older than 41 years and those with 1 to 3 years of experience should be considered when planning for CME and mentorship program on infection prevention and management.

Feeding practices and growth patterns of moderately low birthweight infants in resource-limited settings: results from a multisite, longitudinal observational study.

OBJECTIVES: To describe the feeding profile of low birthweight (LBW) infants in the first half of infancy; and to examine growth patterns and early risk factors of poor 6-month growth outcomes. DESIGN: Prospective observational cohort study. SETTING AND PARTICIPANTS: Stable, moderately LBW (1.50 to <2.50 kg) infants were enrolled at birth from 12 secondary/tertiary facilities in India, Malawi and Tanzania and visited nine times over 6 months. VARIABLES OF INTEREST: Key variables of interest included birth weight, LBW type (combination of preterm/term status and size-for-gestational age at birth), lactation practices and support, feeding profile, birthweight regain by 2 weeks of age and poor 6-month growth outcomes. RESULTS: Between 13 September 2019 and 27 January 2021, 1114 infants were enrolled, comprising 4 LBW types. 363 (37.3%) infants initiated early breast feeding and 425 (43.8%) were exclusively breastfed to 6 months. 231 (22.3%) did not regain birthweight by 2 weeks; at 6 months, 280 (32.6%) were stunted, 222 (25.8%) underweight and 88 (10.2%) wasted. Preterm-small-for-gestational age (SGA) infants had 1.89 (95% CI 1.37 to 2.62) and 2.32 (95% CI 1.48 to 3.62) times greater risks of being stunted and underweight at 6 months compared with preterm-appropriate-for-gestational age (AGA) infants. Term-SGA infants had 2.33 (95% CI 1.77 to 3.08), 2.89 (95% CI 1.97 to 4.24) and 1.99 (95% CI 1.13 to 3.51) times higher risks of being stunted, underweight and wasted compared with preterm-AGA infants. Those not regaining their birthweight by 2 weeks had 1.51 (95% CI 1.23 to 1.85) and 1.55 (95% CI 1.21 to 1.99) times greater risks of being stunted and underweight compared with infants regaining. CONCLUSION: LBW type, particularly SGA regardless of preterm or term status, and lack of birthweight regain by 2 weeks are important risk identification parameters. Early interventions are needed that include optimal feeding support, action-oriented growth monitoring and understanding of the needs and growth patterns of SGA infants to enable appropriate weight gain and proactive management of vulnerable infants. TRIAL REGISTRATION NUMBER: NCT04002908.

ePOCT+ and the medAL-suite: Development of an electronic clinical decision support algorithm and digital platform for pediatric outpatients in low- and middle-income countries.

Electronic clinical decision support algorithms (CDSAs) have been developed to address high childhood mortality and inappropriate antibiotic prescription by helping clinicians adhere to guidelines. Previously identified challenges of CDSAs include their limited scope, usability, and outdated clinical content. To address these challenges we developed ePOCT+, a CDSA for the care of pediatric outpatients in low- and middle-income settings, and the medical algorithm suite (medAL-suite), a software for the creation and execution of CDSAs. Following the principles of digital development, we aim to describe the process and lessons learnt from the development of ePOCT+ and the medAL-suite. In particular, this work outlines the systematic integrative development process in the design and implementation of these tools required to meet the needs of clinicians to improve uptake and quality of care. We considered the feasibility, acceptability and reliability of clinical signs and symptoms, as well as the diagnostic and prognostic performance of predictors. To assure clinical validity, and appropriateness for the country of implementation the algorithm underwent numerous reviews by clinical experts and health authorities from the implementing countries. The digitalization process involved the creation of medAL-creator, a digital platform which allows clinicians without IT programming skills to easily create the algorithms, and medAL-reader the mobile health (mHealth) application used by clinicians during the consultation. Extensive feasibility tests were done with feedback from end-users of multiple countries to improve the clinical algorithm and medAL-reader software. We hope that the development framework used for developing ePOCT+ will help support the development of other CDSAs, and that the open-source medAL-suite will enable others to easily and independently implement them. Further clinical validation studies are underway in Tanzania, Rwanda, Kenya, Senegal, and India.

Referral challenges and outcomes of neonates received at Muhimbili National Hospital, Dar es Salaam, Tanzania.

BACKGROUND: Functional referral system including pre referral care, access to emergency transport and ensuring continuity of care between facilities is critical for improved newborn health outcome. The neonatal transport system is quite undervalued in many sub Saharan countries, Tanzania included. This study assessed the pre referral care, transport process, ambulance characteristics, admission clinical status and outcomes of referred neonates at Muhimbili National Hospital Upanga, a tertiary facility in Dar es Salaam, Tanzania. METHODS: A descriptive cross sectional study with a longitudinal follow up was conducted from September 2020 to February 2021 including neonates referred to Muhimbili National Hospital. A structured questionnaire was used to collect demographic characteristics and transport factors including pre referral care extracted from the referral documents and through interviewing caregivers or escorting person/nurse. Ambulances were directly observed using a structured checklist on presence, absence and functionality of supportive equipment. All enrolled neonates had a clinical assessment at admission and 48 hours post admission to determine admission clinical status and 48 hours' clinical outcome as either survived/died. RESULTS: Out of the 348 neonates assessed during the study period, the median gestation age was 38 weeks (IQR 32, 39) with the mean birth weight of 2455 ± 938 g. Pre referral documentation showed that temperature was measured in 176 (57.1%), oxygen saturation and random blood glucose in only 143 (46.6%) and 116 (36.2%) neonates respectively. Ambulance was used as a means of transportation in 308 (88.5%) neonates. While no ambulance had an incubator only 7 (2.0%) neonates were kept on a Kangaroo Mother Care position. Monitoring enroute was done to only 94 (27%) of the transferred neonates with 169 (54.9%) of health care professionals escorting the neonates lacking training on essential newborn care. On arrival, 115 (33%) were hypothermic, 74 (21.3%) hypoxic, 30 (8.6%) with poor perfusion and 49 (14.1%) hypoglycemic. Hypothermic neonates had an increased chance of dying compared to those who were normothermic (OR = 2.09, 95% CI (1.05-4.20), p = 0.037). The chance of dying among those presenting with hypoxia was almost three times (OR = 2.88, 95%CI (1.44-5.74), p = 0.003) while those with poor perfusion was almost five times (OR = 4.76, 95%CI (1.80-12.58), p = 0.002). Additionally, neonates who had hyperglycemia (RBG > 8.3mmol/l) on arrival had a higher probability of dying compared to those who were euglycemic [(OR = 3.10, 95% CI (1.19-8.09) p = 0.021]. Overall mortality was 22.4% within 48 hours of admission and risk of dying increased as the presence of poor clinical status added on. CONCLUSION: Neonatal transportation in Dar es Salaam, Tanzania was observed to be challenging. Pre transfer care and monitoring during transportation was inadequate and this contributed to poor clinical status on admission. Hypothermia, hypoglycemia, hyperglycemia, hypoxia and poor perfusion on admission were associated with increased mortality. Effective referral network is needed for improved neonatal health outcomes. Pre referral supportive care, training of health care professionals, transportation with improved monitoring, clear communication protocol and referral documentation should be invested and effectively utilized.

Investigating the Potential for Clinical Decision Support in Sub-Saharan Africa With AFYA (Artificial Intelligence-Based Assessment of Health Symptoms in Tanzania): Protocol for a Prospective, Observational Pilot Study.

BACKGROUND: Low- and middle-income countries face difficulties in providing adequate health care. One of the reasons is a shortage of qualified health workers. Diagnostic decision support systems are designed to aid clinicians in their work and have the potential to mitigate pressure on health care systems. OBJECTIVE: The Artificial Intelligence-Based Assessment of Health Symptoms in Tanzania (AFYA) study will evaluate the potential of an English-language artificial intelligence-based prototype diagnostic decision support system for mid-level health care practitioners in a low- or middle-income setting. METHODS: This is an observational, prospective clinical study conducted in a busy Tanzanian district hospital. In addition to usual care visits, study participants will consult a mid-level health care practitioner, who will use a prototype diagnostic decision support system, and a study physician. The accuracy and comprehensiveness of the differential diagnosis provided by the diagnostic decision support system will be evaluated against a gold-standard differential diagnosis provided by an expert panel. RESULTS: Patient recruitment started in October 2021. Participants were recruited directly in the waiting room of the outpatient clinic at the hospital. Data collection will conclude in May 2022. Data analysis is planned to be finished by the end of June 2022. The results will be published in a peer-reviewed journal. CONCLUSIONS: Most diagnostic decision support systems have been developed and evaluated in high-income countries, but there is great potential for these systems to improve the delivery of health care in low- and middle-income countries. The findings of this real-patient study will provide insights based on the performance and usability of a prototype diagnostic decision support system in low- or middle-income countries. TRIAL REGISTRATION: ClinicalTrials.gov NCT04958577; http://clinicaltrials.gov/ct2/show/NCT04958577. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34298.

Study protocol for a pilot prospective, observational study investigating the condition suggestion and urgency advice accuracy of a symptom assessment app in sub-Saharan Africa: the AFYA-'Health' Study.

INTRODUCTION: Due to a global shortage of healthcare workers, there is a lack of basic healthcare for 4 billion people worldwide, particularly affecting low-income and middle-income countries. The utilisation of AI-based healthcare tools such as symptom assessment applications (SAAs) has the potential to reduce the burden on healthcare systems. The purpose of the AFYA Study (AI-based Assessment oF health sYmptoms in TAnzania) is to evaluate the accuracy of the condition suggestions and urgency advice provided by a user on a Swahili language Ada SAA. METHODS AND ANALYSIS: This study is designed as an observational prospective clinical study. The setting is a waiting room of a Tanzanian district hospital. It will include patients entering the outpatient clinic with various conditions and age groups, including children and adolescents. Patients will be asked to use the SAA before proceeding to usual care. After usual care, they will have a consultation with a study-provided physician. Patients and healthcare practitioners will be blinded to the SAA's results. An expert panel will compare the Ada SAA's condition suggestions and urgency advice to usual care and study provided differential diagnoses and triage. The primary outcome measures are the accuracy and comprehensiveness of the Ada SAA evaluated against the gold standard differential diagnoses. ETHICS AND DISSEMINATION: Ethical approval was received by the ethics committee (EC) of Muhimbili University of Health and Allied Sciences with an approval number MUHAS-REC-09-2019-044 and the National Institute for Medical Research, NIMR/HQ/R.8c/Vol. I/922. All amendments to the protocol are reported and adapted on the basis of the requirements of the EC. The results from this study will be submitted to peer-reviewed journals, local and international stakeholders, and will be communicated in editorials/articles by Ada Health. TRIAL REGISTRATION NUMBER: NCT04958577.

Measuring coverage and quality of supportive care for inpatient neonatal infections: EN-BIRTH multi-country validation study.

Background: An estimated 7 million episodes of severe newborn infections occur annually worldwide, with half a million newborn deaths, most occurring in low- and middle-income countries. Whilst injectable antibiotics are necessary to treat the infection, supportive care is also crucial in ending preventable mortality and morbidity. This study uses multi-country data to assess gaps in coverage, quality, and documentation of supportive care, considering implications for measurement. Methods: The EN-BIRTH study was conducted in five hospitals in Bangladesh, Nepal, and Tanzania (July 2017-July 2018). Newborns with an admission diagnosis of clinically-defined infection (sepsis, meningitis, and/or pneumonia) were included. Researchers extracted data from inpatient case notes and interviews with women (usually the mothers) as the primary family caretakers after discharge. The interviews were conducted using a structured survey questionnaire. We used descriptive statistics to report coverage of newborn supportive care components such as oxygen use, phototherapy, and appropriate feeding, and we assessed the validity of measurement through survey-reports using a random-effects model to generate pooled estimates. In this study, key supportive care components were assessment and correction of hypoxaemia, hyperbilirubinemia, and hypoglycaemia. Results: Among 1015 neonates who met the inclusion criteria, 89% had an admission clinical diagnosis of sepsis. Major gaps in documentation and care practices related to supportive care varied substantially across the participating hospitals. The pooled sensitivity was low for the survey-reported oxygen use (47%; 95% confidence interval (CI) = 30%-64%) and moderate for phototherapy (60%; 95% CI = 44%-75%). The pooled specificity was high for both the survey-reported oxygen use (85%; 95% CI = 80%-89%) and phototherapy (91%; 95% CI = 82%-97%). Conclusions: The women's reports during the exit survey consistently underestimated the coverage of supportive care components for managing infection. We have observed high variability in the inpatient documents across facilities. A standardised ward register for inpatient small and sick newborn care may capture selected supportive care data. However, tracking the detailed care will require standardised individual-level data sets linked to newborn case notes. We recommend investments in assessing the implementation aspects of a standardised inpatient register in resource-poor settings.

Infection prevention and care bundles addressing health care-associated infections in neonatal care in low-middle income countries: a scoping review.

BACKGROUND: Health care-associated infections (HCAI) in neonatal units in low- and middle-income countries (LMIC) are a major cause of mortality. This scoping review aimed to synthesise published literature on infection prevention and care bundles addressing neonatal HCAI in LMICs and to construct a Classification Framework for their components (elements). METHODS: Five electronic databases were searched between January 2001 and July 2020. A mixed-methods approach was applied: qualitative content analysis was used to build a classification framework to categorise bundle elements and the contents of the classification groups were then described quantitatively. FINDINGS: 3619 records were screened, with 44 eligible studies identified. The bundle element Classification Framework created involved: (1) Primary prevention, (2) Detection, (3) Case management, and Implementation (3 + I). The 44 studies included 56 care bundles with 295 elements that were then classified. Primary prevention elements (128, 43%) predominated of which 71 (55%) focused on central line catheters and mechanical ventilators. Only 12 elements (4%) were related to detection. A further 75 (25%) elements addressed case management and 66 (88%) of these aimed at outbreak control. INTERPRETATION: The 3 + I Classification Framework was a feasible approach to reporting and synthesising research for infection-relevant bundled interventions in neonatal units. A shift towards the use in infection prevention and care bundles of primary prevention elements focused on the neonate and on commonly used hospital devices in LMIC (e.g., self-inflating bags, suctioning equipment) would be valuable to reduce HCAI transmission. Detection elements were a major gap. FUNDING: This work was made possible in part by the John D. and Catherine T. MacArthur Foundation, the Bill & Melinda Gates Foundation, ELMA Philanthropies, The Children's Investment Fund Foundation UK, The Lemelson Foundation, and the Ting Tsung and Wei Fong Chao Foundation under agreements to William Marsh Rice University. The project leading to these results has also received the support of a fellowship from the "la Caixa" Foundation (ID 100010434). The fellowship code is LCF/BQ/EU19/11710040. EJAF is an Academic Clinical Fellow whose salary is funded by the UK National Institute for Health Research (NIHR). NES receives a Research Training Program Scholarship (Australian Commonwealth Government).

Malaria hospitalisation in East Africa: age, phenotype and transmission intensity.

BACKGROUND: Understanding the age patterns of disease is necessary to target interventions to maximise cost-effective impact. New malaria chemoprevention and vaccine initiatives target young children attending routine immunisation services. Here we explore the relationships between age and severity of malaria hospitalisation versus malaria transmission intensity. METHODS: Clinical data from 21 surveillance hospitals in East Africa were reviewed. Malaria admissions aged 1 month to 14 years from discrete administrative areas since 2006 were identified. Each site-time period was matched to a model estimated community-based age-corrected parasite prevalence to provide predictions of prevalence in childhood (PfPR2-10). Admission with all-cause malaria, severe malaria anaemia (SMA), respiratory distress (RD) and cerebral malaria (CM) were analysed as means and predicted probabilities from Bayesian generalised mixed models. RESULTS: 52,684 malaria admissions aged 1 month to 14 years were described at 21 hospitals from 49 site-time locations where PfPR2-10 varied from < 1 to 48.7%. Twelve site-time periods were described as low transmission (PfPR2-10 < 5%), five low-moderate transmission (PfPR2-10 5-9%), 20 moderate transmission (PfPR2-10 10-29%) and 12 high transmission (PfPR2-10 ≥ 30%). The majority of malaria admissions were below 5 years of age (69-85%) and rare among children aged 10-14 years (0.7-5.4%) across all transmission settings. The mean age of all-cause malaria hospitalisation was 49.5 months (95% CI 45.1, 55.4) under low transmission compared with 34.1 months (95% CI 30.4, 38.3) at high transmission, with similar trends for each severe malaria phenotype. CM presented among older children at a mean of 48.7 months compared with 39.0 months and 33.7 months for SMA and RD, respectively. In moderate and high transmission settings, 34% and 42% of the children were aged between 2 and 23 months and so within the age range targeted by chemoprevention or vaccines. CONCLUSIONS: Targeting chemoprevention or vaccination programmes to areas where community-based parasite prevalence is ≥10% is likely to match the age ranges covered by interventions (e.g. intermittent presumptive treatment in infancy to children aged 2-23 months and current vaccine age eligibility and duration of efficacy) and the age ranges of highest disease burden.

Mixed-methods, descriptive and observational cohort study examining feeding and growth patterns among low birthweight infants in India, Malawi and Tanzania: the LIFE study protocol.

INTRODUCTION: Ending preventable deaths of newborns and children under 5 will not be possible without evidence-based strategies addressing the health and care of low birthweight (LBW, <2.5 kg) infants. The majority of LBW infants are born in low- and middle-income countries (LMICs) and account for more than 60%-80% of newborn deaths. Feeding promotion tailored to meet the nutritional needs of LBW infants in LMICs may serve a crucial role in curbing newborn mortality rates and promoting growth. The Low Birthweight Infant Feeding Exploration (LIFE) study aims to establish foundational knowledge regarding optimal feeding options for LBW infants in low-resource settings throughout infancy. METHODS AND ANALYSIS: LIFE is a formative, multisite, observational cohort study involving 12 study facilities in India, Malawi and Tanzania, and using a convergent parallel, mixed-methods design. We assess feeding patterns, growth indicators, morbidity, mortality, child development and health system inputs that facilitate or hinder care and survival of LBW infants. ETHICS AND DISSEMINATION: This study was approved by 11 ethics committees in India, Malawi, Tanzania and the USA. The results will be disseminated through peer-reviewed publications and presentations targeting the global and local research, clinical, programme implementation and policy communities. TRIAL REGISTRATION NUMBERS: NCT04002908 and CTRI/2019/02/017475.

Birthweight: EN-BIRTH multi-country validation study.

BACKGROUND: Accurate birthweight is critical to inform clinical care at the individual level and tracking progress towards national/global targets at the population level. Low birthweight (LBW) < 2500 g affects over 20.5 million newborns annually. However, data are lacking and may be affected by heaping. This paper evaluates birthweight measurement within the Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) study. METHODS: The EN-BIRTH study took place in five hospitals in Bangladesh, Nepal and Tanzania (2017-2018). Clinical observers collected time-stamped data (gold standard) for weighing at birth. We compared accuracy for two data sources: routine hospital registers and women's report at exit interview survey. We calculated absolute differences and individual-level validation metrics. We analysed birthweight coverage and quality gaps including timing and heaping. Qualitative data explored barriers and enablers for routine register data recording. RESULTS: Among 23,471 observed births, 98.8% were weighed. Exit interview survey-reported weighing coverage was 94.3% (90.2-97.3%), sensitivity 95.0% (91.3-97.8%). Register-reported coverage was 96.6% (93.2-98.9%), sensitivity 97.1% (94.3-99%). Routine registers were complete (> 98% for four hospitals) and legible > 99.9%. Weighing of stillbirths varied by hospital, ranging from 12.5-89.0%. Observed LBW rate was 15.6%; survey-reported rate 14.3% (8.9-20.9%), sensitivity 82.9% (75.1-89.4%), specificity 96.1% (93.5-98.5%); register-recorded rate 14.9%, sensitivity 90.8% (85.9-94.8%), specificity 98.5% (98-99.0%). In surveys, "don't know" responses for birthweight measured were 4.7%, and 2.9% for knowing the actual weight. 95.9% of observed babies were weighed within 1 h of birth, only 14.7% with a digital scale. Weight heaping indices were around two-fold lower using digital scales compared to analogue. Observed heaping was almost 5% higher for births during the night than day. Survey-report further increased observed birthweight heaping, especially for LBW babies. Enablers to register birthweight measurement in qualitative interviews included digital scale availability and adequate staffing. CONCLUSIONS: Hospital registers captured birthweight and LBW prevalence more accurately than women's survey report. Even in large hospitals, digital scales were not always available and stillborn babies not always weighed. Birthweight data are being captured in hospitals and investment is required to further improve data quality, researching of data flow in routine systems and use of data at every level.

Antibiotic use for inpatient newborn care with suspected infection: EN-BIRTH multi-country validation study.

BACKGROUND: An estimated 30 million neonates require inpatient care annually, many with life-threatening infections. Appropriate antibiotic management is crucial, yet there is no routine measurement of coverage. The Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) study aimed to validate maternal and newborn indicators to inform measurement of coverage and quality of care. This paper reports validation of reported antibiotic coverage by exit survey of mothers for hospitalized newborns with clinically-defined infections, including sepsis, meningitis, and pneumonia. METHODS: EN-BIRTH study was conducted in five hospitals in Bangladesh, Nepal, and Tanzania (July 2017-July 2018). Neonates were included based on case definitions to focus on term/near-term, clinically-defined infection syndromes (sepsis, meningitis, and pneumonia), excluding major congenital abnormalities. Clinical management was abstracted from hospital inpatient case notes (verification) which was considered as the gold standard against which to validate accuracy of women's report. Exit surveys were conducted using questions similar to The Demographic and Health Surveys (DHS) approach for coverage of childhood pneumonia treatment. We compared survey-report to case note verified, pooled across the five sites using random effects meta-analysis. RESULTS: A total of 1015 inpatient neonates admitted in the five hospitals met inclusion criteria with clinically-defined infection syndromes. According to case note verification, 96.7% received an injectable antibiotic, although only 14.5% of them received the recommended course of at least 7 days. Among women surveyed (n = 910), 98.8% (95% CI: 97.8-99.5%) correctly reported their baby was admitted to a neonatal ward. Only 47.1% (30.1-64.5%) reported their baby's diagnosis in terms of sepsis, meningitis, or pneumonia. Around three-quarters of women reported their baby received an injection whilst in hospital, but 12.3% reported the correct antibiotic name. Only 10.6% of the babies had a blood culture and less than 1% had a lumbar puncture. CONCLUSIONS: Women's report during exit survey consistently underestimated the denominator (reporting the baby had an infection), and even more so the numerator (reporting known injectable antibiotics). Admission to the neonatal ward was accurately reported and may have potential as a contact point indicator for use in household surveys, similar to institutional births. Strengthening capacity and use of laboratory diagnostics including blood culture are essential to promote appropriate use of antibiotics. To track quality of neonatal infection management, we recommend using inpatient records to measure specifics, requiring more research on standardised inpatient records.