RESUMO
BACKGROUND: The emergence of COVID-19 precipitated containment policies (e.g., lockdowns, school closures, etc.). These policies disrupted healthcare, potentially eroding gains for Sustainable Development Goals including for neonatal mortality. Our analysis aimed to evaluate indirect effects of COVID-19 containment policies on neonatal admissions and mortality in 67 neonatal units across Kenya, Malawi, Nigeria, and Tanzania between January 2019 and December 2021. METHODS: The Oxford Stringency Index was applied to quantify COVID-19 policy stringency over time for Kenya, Malawi, Nigeria, and Tanzania. Stringency increased markedly between March and April 2020 for these four countries (although less so in Tanzania), therefore defining the point of interruption. We used March as the primary interruption month, with April for sensitivity analysis. Additional sensitivity analysis excluded data for March and April 2020, modelled the index as a continuous exposure, and examined models for each country. To evaluate changes in neonatal admissions and mortality based on this interruption period, a mixed effects segmented regression was applied. The unit of analysis was the neonatal unit (n = 67), with a total of 266,741 neonatal admissions (January 2019 to December 2021). RESULTS: Admission to neonatal units decreased by 15% overall from February to March 2020, with half of the 67 neonatal units showing a decline in admissions. Of the 34 neonatal units with a decline in admissions, 19 (28%) had a significant decrease of ≥ 20%. The month-to-month decrease in admissions was approximately 2% on average from March 2020 to December 2021. Despite the decline in admissions, we found no significant changes in overall inpatient neonatal mortality. The three sensitivity analyses provided consistent findings. CONCLUSION: COVID-19 containment measures had an impact on neonatal admissions, but no significant change in overall inpatient neonatal mortality was detected. Additional qualitative research in these facilities has explored possible reasons. Strengthening healthcare systems to endure unexpected events, such as pandemics, is critical in continuing progress towards achieving Sustainable Development Goals, including reducing neonatal deaths to less than 12 per 1000 live births by 2030.
Assuntos
COVID-19 , Mortalidade Infantil , Análise de Séries Temporais Interrompida , Humanos , COVID-19/epidemiologia , COVID-19/prevenção & controle , COVID-19/mortalidade , Recém-Nascido , Tanzânia/epidemiologia , Quênia/epidemiologia , Mortalidade Infantil/tendências , Malaui/epidemiologia , Nigéria/epidemiologia , Admissão do Paciente/estatística & dados numéricos , Unidades de Terapia Intensiva Neonatal , Hospitalização/estatística & dados numéricos , Pandemias , LactenteRESUMO
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.
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Instalações de Saúde , Hospitais , Recém-Nascido , Humanos , Tanzânia , Malaui , Quênia , Nigéria , Organização Mundial da SaúdeRESUMO
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.
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Países em Desenvolvimento , Pacientes Internados , Criança , Recém-Nascido , Gravidez , Humanos , Feminino , Qualidade da Assistência à Saúde , Parto , TanzâniaRESUMO
New strategies are needed to improve HIV testing rates in Tanzania, particularly among adult men. We sought to investigate if HIV oral self-testing would increase HIV testing uptake in Tanzanian rural community homes. The study design was a prospective community-randomized pilot study, in two matched villages with similar characteristics (intervention and control villages) Before data collection, we trained village health workers and research assistants for one week. We recruited male and female adults from 50 representative households in each of two villages in eastern Tanzania. We collected data at baseline and we followed-up the enrolled households after a one-month period. There was a high interest in testing for HIV, with all participants from both arms (100%; n = 259) reporting that they would like to test for HIV. After the one-month follow-up, overall, 66.1% (162/245) of study participants reported to have tested for HIV in both arms. In the intervention arm, 97.6% (124/127) reported that they tested for HIV versus in the control arm, 32.2% (38/118) tested for HIV, p-value < 0.001. In Tanzania, we found that availability of HIV self-testing was associated with an enormous increase in HIV testing uptake in a rural population.