Tackling antimicrobial resistance through monitoring of quality of care and antibiotics use in Malawi: A mixed method and geographic information system approach

Abstract

Study type
This is a mixed methods study using ethnographic approaches in a sequential explanatory design.
Research Questions
1. Can LQAS be used as a tool for AMR and ABU surveillance in local health facilities?
2. What are the AMR prevalence variations in districts in Malawi?
3. What is the link between quality of clinical care, prescribing practices in health facility and communities, and local ABU as drivers of AMR
4. How can GIS techniques be used to support AMR surveillance and improve policy for AMR control?
5. What are the community perception of health, illness and ABU for childhood fevers?
Background
Inappropriate antibiotic prescribing and patient use are key AMR drivers. Addressing both are critical to reduce AMR and protect healthcare systems. The World Health Organisation (WHO) AMR Global Action Plan highlights the need to increase surveillance in Low and Middle Income Countries (LMIC) to improve antimicrobial stewardship. This study seeks to measurably improve the quality of care (QoC) and ABU and to model AMR transmission drivers amongst bacteria. Furthermore, the usefulness of geographical information system (GIS) in AMR surveillance will be explored.
Objectives
Main objective
To interrupt AMR in communities by identifying factors that optimise ABU and developing affordable strategies with Ministries of Health.
Specific objectives
1. To investigate associations of quality of care (QoC) in a sample of Health Care Facilities (HCF) with AMR to key antibiotics used for febrile illnesses in children
2. To assess the risk of AMR development through analysis of genomic traits from samples collected in study sites; determine future risk of resistance development
3. To investigate community level health system drivers of ABU and AMR at the sub-district level with particular focus on febrile illnesses using mixed methods including GIS approach.
4. To develop a rapid and sustainable approach to assessing ABU and AMR in the community in Blantyre, in order to facilitate evidence-based improvement of quality of febrile illness care
5. To develop solutions to tackling QoC, ABU and AMR informed by community voices

Methods in Brief
The focus is febrile illness in children <5-years, the most common clinical presentation in sub-Saharan Africa. Children are often empirically treated with antibiotics which risks unnecessary or inadequate treatment for the individual and spreading AMR. Whilst recommended, microbiological surveillance of AMR is unsustainable due to cost and logistical challenges. A rapid healthcare assessment metric and evidence use process for AMR, ABU, and QoC will be developed through 4 research packages (RP):
RP1) Investigates ABU as a local AMR driver by adapting Lot Quality Assurance Sampling (LQAS) to rapidly assess ABU amongst febrile children in urban, peri-urban, and rural areas with a minimum sample in each area of n=44 febrile children. We will assess the clinician-patient dyad for each sampled case for QoC and ABU using a Health Facility Assessment tool.
RP2) Uses LQAS for microbiological surveillance to detect areas with >20% AMR in a minimum of n=44 nasal and rectal swabs of febrile children (a<0.047,ß<0.092). Swabs will be cultured on chromogenic agar containing appropriate antibiotics for Methicillin Resistant Staphylococcus aureus (MRSA) (nasal) and Extended Spectrum Beta-Lactamase (ESBL). Selected resulting isolates will be whole genome sequenced, providing contemporary AMR profiles of bacteria enabling informed decisions for ABU based on circulating resistance genes and associated mobile genetic elements.
RP3) Assesses drivers of ABU using mixed methods. A probability household survey in each area (n>95, max.95%CI ±0.10) measures service coverage, treatment seeking, and costs. Ethnographic approaches in a sequential explanatory design explain 1) RP1 and household survey results, 2) how people make sense of health, illness, and antibiotics, and 3) serves as a resource for community driven solution development to address ABU. In the area with the worst QoC score, we will conduct 12 In-Depth Interviews (IDI) (6 clinicians, 6 pharmacists); 1 Community Dialogue (CD) comprising 3 break-out groups (10-12 fathers, 10-12 mothers and 10-12 health care providers); and 6 Key Informant Interviews (KII) (3 traditional healers/herbalists, 3 community leaders).
RP4) Intervention development will be supported using the CD approach in combination with national and district stakeholder engagement using the RAPID Outcome Mapping Engagement and Policy-Influence approach. Ethnographic non-participant observation of the engagement, result analysis and intervention development process will lead to a deeper understanding of the strategy development process.

Expected outcome
Through this research, we expect improved quality of care and strengthening of the health system to track health system changes that optimises ABU and monitors AMR prevalence. Furthermore, this will lead to sustained health system reforms. Our findings will be disseminated to Kamuzu University of Health Sciences and other stakeholders through briefing papers, presentations and scientific presentations.

Where does this project lie in the translational pathway? T2 - Human /Clinical Research,T3 - Evidence into Practice ,T4 - Practice to Policy/Population
Expected Outputs This research is sponsored by LSTM through funding from National Institute of Health and Care Research (£424,646). Through this research, we expect improved quality of care and strengthening of the health system to track health system changes that optimises ABU and monitors AMR prevalence. Furthermore, this will lead to sustained health system reforms. Our findings will be disseminated to Kamuzu University of Health Sciences, the ministry of health and other stakeholders through briefing papers, presentations, scientific publications and conference presentations.
Training Opportunities 1. Training on LQAS approach and how to analyse LQAS data
2. Statistical methods and modeling in health research
3. Qualitative methods and analysis of qualitative data
4. Strategies to influence policy change or development
5. The advance use of mapping software (QGIS)
6. Manuscript and thesis writing
Skills Required 1. Proficiency in the use of Microsoft office packages (word, excel, powerpoint, sharepoint)
2. Project management experience
3. Previous research experience

Key Publications associated with this project

Ginting F, Sugianli AK, et al. Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling. Am J Epidemiol. 2019;188(4):734-42.
  Rath RS, Solanki HK. Review of Lot Quality Assurance Sampling, Methodology and its Application in Public Health. Nepal J Epidemiol. 2019 Sep 30;9(3):781-787. doi: 10.3126/nje.v9i3.24507. PMID: 31687252; PMCID: PMC6824847.
  Leger A, Lambraki I, et al. AMR-Intervene: a social-ecological framework to capture the diversity of actions to tackle antimicrobial resistance from a One Health perspective. J Antimicrob Chemother. 2021;76(1):1-21.
  Valadez JJ. Assessing Child Survival Programs in Developing Countries: Testing Lot Quality Assurance Sampling. Cambridge: Harvard University Press; 1991
  Chokshi A, Sifri Z, Cennimo D, Horng H. Global Contributors to Antibiotic Resistance. Journal of Global Infectious Diseases [Internet]. 2019;11(1):36–42. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6380099/