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| Funder | National Institute for Health and Care Research |
|---|---|
| Recipient Organization | Liverpool School of Tropical Medicine |
| Country | United Kingdom |
| Start Date | Aug 01, 2024 |
| End Date | Jul 31, 2028 |
| Duration | 1,460 days |
| Number of Grantees | 3 |
| Roles | Principal Investigator; Co-Principal Investigator; Award Holder |
| Data Source | NIHR Open Data-Funded Portfolio |
| Grant ID | NIHR156297 |
Research Question: Can regular surveillance of antimicrobial resistance (AMR) and antibiotic use (ABU) improve health worker prescribing practices and patient ABU leading to lower AMR prevalence?
Background: Inappropriate ABU are key AMR drivers. Improving ABU is critical to reduce AMR. WHO’s AMR Global Action Plan highlights the need to increase surveillance to improve antimicrobial stewardship. We build on our health systems research in Uganda, Malawi, and Zambia to improve the quality of healthcare (QoC) and model AMR transmission drivers.
Aims: Develop a metric & evidence use process to improve local management of childhood febrile illness.
Objectives: To 1) develop a rapid, recurrent surveillance system of ABU and AMR prevalence and community voices to improve health system strategies, 2) investigate associations of QoC in Health Facilities with AMR to key antibiotics used for childhood febrile illnesses, 3) investigate community ABU and AMR drivers focusing on febrile illnesses and 4) assess AMR risk development by analysing genomic traits from nasal and rectal samples and determine future risk of resistance.
Methods Febrile illness of children <5-years, the most common clinical presentation in Africa, is often empirically treated with antibiotics risking AMR spread. Microbiological surveillance of AMR is unsustainable due to cost and logistics, a more feasible approach is identifying differences in AMR prevalence in local areas to understand and address local AMR drivers and improve ABU. We develop a rapid assessment metric and evidence use process with 4 Research Packages:
RP1) Adapts Lot Quality Assurance Sampling (LQAS) to investigate ABU as a local AMR driver; we assess maternal and clinician ABU for febrile children in urban, peri-urban, and rural areas per country (each area minimum n=44 febrile children). RP2) Microbiological surveillance using LQAS to detect areas with >20% AMR (minimum n=44 swabs, a<0.047,ß<0.092). We validate results (minimum sample n=240). Swabs cultured on chromogenic agar containing antibiotics for MRSA (nasal) and ESBL producing Enterobacteriaceae (rectal). Selected isolates will be whole genome sequenced for contemporary AMR profiles of bacteria enabling informed decisions for ABU based on circulating resistance genes and associated mobile genetic elements.
RP3) Assesses ABU drivers. A probability survey in each area (n>95, max.95%CI ±0.10) measures service coverage, treatment seeking and costs. Ethnographies in a sequential explanatory design explain RP1 and survey results and perceptions of health, illness, and antibiotics.
They advance community-driven solutions to improve ABU. In each countries’ area with the worst QoC, we conduct 12 In-Depth Interviews (clinicians, pharmacists); 1 Community Dialogue (CD) with 3 groups (fathers, mothers, and health workers); and 6 Key Informant Interviews (traditional practitioners, community leaders).
RP4) Intervention development using CDs and national and district stakeholder engagement using the RAPID Outcome Mapping Engagement and Policy-Influence approach.
Timelines: RP1-2 surveillance 1st round: Q1-3 yr1; 2nd round: Q4 yr3 & Q1 yr4. Evolutionary work continuous from Q2 yr2. RP3 Survey Q2-4 yr1; qualitative research Q4 yr1 through yr2. RP4 community dialogue Q3-4 yr1.
Impact & Dissemination: With rapid our AMR/ABU surveillance metric, ABU drivers of AMR are better understood; Health System strategies improve ABU. 3 PhD. Publications, conferences.
Liverpool School of Tropical Medicine
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