Unravelling patient pathways in the context of antibacterial resistance in East Africa
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Date
2022Author
Keenan, Katherine
Fredricks, Kathryn J.
Ahad, Mary Abed Al
Neema, Stella
Mwanga, Joseph R.
Kesby, Mike
Mushi, Martha F.
Aduda, Annette
Green, Dominique L.
Lynch, Andy G.
Huque, Sarah I.
Mmbaga, Blandina T.
Worthington, Hannah
Kansiime, Catherine
Olamijuwon, Emmanuel
Ntinginya, Nyanda E.
Loza, Olga
Bazira, Joel
Barragán, Antonio Maldonado
Smith, V Anne
Decano, Arun Gonzales
Mwaniki, John Njeru
Sandeman, Alison
Stelling, John
Elliott, Alison
Aanensen, David
Gillespie, Stephen H.
Kibiki, Gibson
Sabiiti, Wilber
Sloan, Derek J.
Asiimwe, Benon B.
Kiiru, John
Mshana, Stephen E.
Holden, Matthew T. G.
Consortium, HATUA
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Background: A key factor driving the development and maintenance of antibacterial resistance (ABR) is individuals’ use of antibiotics (ABs) to treat illness. It is therefore crucial to understand the dynamics of patient treatment-seeking - where patients go when unwell, what motivates choice, and treatments they obtain. Developing a better understanding of social inequalities of antibiotic use in low resource settings has been identified as a research priority, as has understanding pluralistic healthcare landscapes, but so far robust multi-country mixed methods data has been lacking. This paper aims to investigate patterns and determinants of patient treatment-seeking pathways, and how they intersect with AB use in East Africa, a region where ABR-attributable deaths are exceptionally high.
Methods: The Holistic Approach to Unravelling Antimicrobial Resistance (HATUA) Consortium collected quantitative data from 6,827 adult outpatients presenting with urinary tract infection (UTI) symptoms in Kenya, Tanzania, and Uganda, and conducted qualitative in-depth patient interviews with a subset (n=116). We described patterns of treatment-seeking visually using Sankey plots and elucidated explanations using mixed-methods. Using Bayesian hierarchical regression modelling, we investigated the associations between socio-demographic, economic, healthcare, and attitudinal factors and three outcomes related to ABR: self-treatment as a first step, having a multi-step treatment pathway, and consuming ABs.
Results: Despite patients predominantly seeking help from medical facilities as a first step, many described complex and repetitive treatment-seeking pathways, which increased the likelihood of consuming ABs. Higher socio-economic status patients were more likely to consume ABs and multi-step pathways. Reasons for choosing providers (e.g., cost, location, time) were conditioned by wider structural factors such as healthcare systems and AB availability.
Conclusion: There is likely to be a reinforcing cycle between complex, repetitive treatment pathways, AB consumption and ABR, which could become more common as ABR evolves. A focus on individual behaviours obscures the contextual challenges patients face when treatment seeking. Pluralistic healthcare landscapes may promote more complex treatment seeking and therefore inappropriate AB use. We recommend intervening on aspects of the treatment cycle amenable to change, focussing on medical facilities (e.g., accessible diagnostics, patient-doctor interactions, information flows), and community AB access points (e.g., drug sellers).
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