Associated organisationsLiverpool School of Tropical Medicine · Zambia National Public Health InstituteEurope PMC affiliations are not treated as award recipients or mapped locations.
Funding£1.6M
PeriodSept 2025 — Sept 2028
In plain English
AI plain-English summary
Every year, 2.3 million newborns die globally, and nearly a quarter of those deaths are linked to infections—many of them preventable with better detection and treatment. This research tackles a deadly gap in care. In hospitals across sub-Saharan Africa, neonatal sepsis and healthcare-associated infections are major killers, but overstretched staff, limited diagnostics, and fragmented data mean outbreaks often go unnoticed until it is too late. The NeoShield project will generate detailed epidemiological and genomic data on these infections and their antimicrobial resistance patterns in Malawi and Zambia. It will also develop an AI-driven clinical decision support algorithm that combines patient symptoms, bedside test results, and local infection trends to guide antibiotic choices in line with WHO guidelines. If successful, the project will produce open-source digital tools and automated outbreak alerts that help ward staff spot and respond to infection clusters in real time. The same data and algorithms could inform national and global strategies for neonatal infection control and antimicrobial resistance surveillance, quietly strengthening the fragile infrastructure that keeps hospital nurseries safe.
View original technical description
Neonatal healthcare-associated infections (HAIs) are a major cause of mortality and antimicrobial resistance (AMR) in healthcare facilities across sub-Saharan Africa. Of the 2.3 million neonatal deaths annually, an estimated 24% are infection-related, with many linked to outbreaks. Overstretched clinical teams, limited diagnostics, fragmented data, and critical gaps in local pathogen epidemiology and genomics often hinder outbreak detection and response. Integrated, context-appropriate solutions are urgently needed to link local microbiological surveillance to real-time, individual-level care. NeoShield will address these challenges in Malawi and Zambia by generating epidemiological and genomic data on neonatal HAIs and their associated AMR, and by developing and validating an AI-driven Clinical Decision Support Algorithm (CDSA) to support inpatient management of neonatal sepsis. The CDSA will integrate clinical signs, point-of-care diagnostics, and local microbiology trends to support antibiotic treatment decisions aligned with facility, national, and World Health Organisation (WHO) guidelines. Five workstreams will be delivered: (1) Laboratory Strengthening; (2) CDSA Development and Validation; (3) Ward-Level Outbreak Detection with Automated Alerts; (4) Sepsis and Stewardship Intervention Bundle; and (5) Pathogen Whole-Genome Sequencing. NeoShield will produce open-source digital tools, open-access learning resources, peer-reviewed publications, and policy briefs to inform national and global strategies for neonatal infection prevention and AMR surveillance.
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