Artificial Intelligence Applications in Antimicrobial Stewardship in LMICs: Effectiveness, Implementation Challenges, and Equity Considerations – A Systematic Review

Aser Waleed Mohamed Marzok; Giorgia  Carra; Po-Yu  Liu; Noémie  Boillat-Blanco; Kasim  Allel; Daniele  Roberto Giacobbe; Eric  Dexter; Rasha Abdelsalam Elshenawy

Artificial Intelligence Applications in Antimicrobial Stewardship in LMICs: Effectiveness, Implementation Challenges, and Equity Considerations – A Systematic Review

Aser Waleed Mohamed Marzok
, Giorgia Carra
, Po-Yu Liu
, Noémie Boillat-Blanco
, Kasim Allel
, Daniele Roberto Giacobbe
, Eric Dexter
, Rasha Abdelsalam Elshenawy

Research output: Contribution to conference › Poster › peer-review

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Abstract

Systematic review evaluating artificial intelligence applications in antimicrobial stewardship in LMICs, examining effectiveness, implementation barriers, and equity considerations. Findings demonstrated technical feasibility but highlighted major implementation gaps requiring capacity building, co-design, and sustainable financing.

Original language	English
Number of pages	1
Publication status	Published - 19 Apr 2026
Event	ESCMID Global 2026 – European Society of Clinical Microbiology and Infectious Diseases Congress - Munich, Germany, Munich, Germany Duration: 18 Apr 2026 → 21 Apr 2026

Conference

Conference	ESCMID Global 2026 – European Society of Clinical Microbiology and Infectious Diseases Congress
Country/Territory	Germany
City	Munich
Period	18/04/26 → 21/04/26

Keywords

antimicrobial stewardship
Antimicrobial Stewardship
antimicrobial stewardship (AMS)
Antimicrobial Stewardship (AMS)
antimicrobial stewardship (ASP) intervention
Antimicrobial stewardship competencies
Antimicrobial stewardship programme
Antimicrobial stewardship programs
Artificial intelligence
artificial intelligence (AI)
Artificial Intelligence (AI)
Artificial intelligence drug modelling
Artificial intelligence and machine learning
Artificial intelligence framework
artificial intelligence, business, machine learning, management, systematic literature review, tertiary study
Artificial intelligence tools
antimicrobial resistance
Antimicrobial Resistance
antimicrobial resistance (AMR)
Antimicrobial Resistance (AMR)
Antimicrobial Resistance;
implementation science
LMICs
Implementation science
digital health
Digital health implementation, facilitators, barriers, digital health classification framework, lower- and middle-income countries
Digital health innovation
Digital health tools
digital healthcare

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No. P3063 - AI in AMS(1)Licence: CC BY

Cite this

Mohamed Marzok, A. W., Carra, G., Liu, P.-Y., Boillat-Blanco, N., Allel, K., Roberto Giacobbe, D., Dexter, E., & Abdelsalam Elshenawy, R. (2026). Artificial Intelligence Applications in Antimicrobial Stewardship in LMICs: Effectiveness, Implementation Challenges, and Equity Considerations – A Systematic Review. Poster session presented at ESCMID Global 2026 – European Society of Clinical Microbiology and Infectious Diseases Congress, Munich, Germany.

Mohamed Marzok, Aser Waleed ; Carra, Giorgia ; Liu, Po-Yu et al. / Artificial Intelligence Applications in Antimicrobial Stewardship in LMICs: Effectiveness, Implementation Challenges, and Equity Considerations – A Systematic Review. Poster session presented at ESCMID Global 2026 – European Society of Clinical Microbiology and Infectious Diseases Congress, Munich, Germany.1 p.

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abstract = "Systematic review evaluating artificial intelligence applications in antimicrobial stewardship in LMICs, examining effectiveness, implementation barriers, and equity considerations. Findings demonstrated technical feasibility but highlighted major implementation gaps requiring capacity building, co-design, and sustainable financing.",

keywords = "antimicrobial stewardship, Antimicrobial Stewardship, antimicrobial stewardship (AMS), Antimicrobial Stewardship (AMS), antimicrobial stewardship (ASP) intervention, Antimicrobial stewardship competencies, Antimicrobial stewardship programme, Antimicrobial stewardship programs, Artificial intelligence, artificial intelligence (AI), Artificial Intelligence (AI), Artificial intelligence drug modelling, Artificial intelligence and machine learning, Artificial intelligence framework, artificial intelligence, business, machine learning, management, systematic literature review, tertiary study, Artificial intelligence tools, antimicrobial resistance, Antimicrobial Resistance, antimicrobial resistance (AMR), Antimicrobial Resistance (AMR), Antimicrobial Resistance;, implementation science, LMICs, Implementation science, digital health, Digital health implementation, facilitators, barriers, digital health classification framework, lower- and middle-income countries, Digital health innovation, Digital health tools, digital healthcare",

author = "\{Mohamed Marzok\}, \{Aser Waleed\} and Giorgia Carra and Po-Yu Liu and No{\'e}mie Boillat-Blanco and Kasim Allel and \{Roberto Giacobbe\}, Daniele and Eric Dexter and \{Abdelsalam Elshenawy\}, Rasha",

note = "Poster presented at ESCMID Global 2026, Munich, Germany (Poster P3063).; ESCMID Global 2026 – European Society of Clinical Microbiology and Infectious Diseases Congress ; Conference date: 18-04-2026 Through 21-04-2026",

year = "2026",

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day = "19",

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Mohamed Marzok, AW, Carra, G, Liu, P-Y, Boillat-Blanco, N, Allel, K, Roberto Giacobbe, D, Dexter, E & Abdelsalam Elshenawy, R 2026, 'Artificial Intelligence Applications in Antimicrobial Stewardship in LMICs: Effectiveness, Implementation Challenges, and Equity Considerations – A Systematic Review', ESCMID Global 2026 – European Society of Clinical Microbiology and Infectious Diseases Congress, Munich, Germany, 18/04/26 - 21/04/26.

Artificial Intelligence Applications in Antimicrobial Stewardship in LMICs: Effectiveness, Implementation Challenges, and Equity Considerations – A Systematic Review. / Mohamed Marzok, Aser Waleed; Carra, Giorgia ; Liu, Po-Yu et al.
2026. Poster session presented at ESCMID Global 2026 – European Society of Clinical Microbiology and Infectious Diseases Congress, Munich, Germany.

Research output: Contribution to conference › Poster › peer-review

TY - CONF

T1 - Artificial Intelligence Applications in Antimicrobial Stewardship in LMICs: Effectiveness, Implementation Challenges, and Equity Considerations – A Systematic Review

AU - Mohamed Marzok, Aser Waleed

AU - Carra, Giorgia

AU - Liu, Po-Yu

AU - Boillat-Blanco, Noémie

AU - Allel, Kasim

AU - Roberto Giacobbe, Daniele

AU - Dexter, Eric

AU - Abdelsalam Elshenawy, Rasha

N1 - Poster presented at ESCMID Global 2026, Munich, Germany (Poster P3063).

PY - 2026/4/19

Y1 - 2026/4/19

N2 - Systematic review evaluating artificial intelligence applications in antimicrobial stewardship in LMICs, examining effectiveness, implementation barriers, and equity considerations. Findings demonstrated technical feasibility but highlighted major implementation gaps requiring capacity building, co-design, and sustainable financing.

AB - Systematic review evaluating artificial intelligence applications in antimicrobial stewardship in LMICs, examining effectiveness, implementation barriers, and equity considerations. Findings demonstrated technical feasibility but highlighted major implementation gaps requiring capacity building, co-design, and sustainable financing.

KW - antimicrobial stewardship

KW - Antimicrobial Stewardship

KW - antimicrobial stewardship (AMS)

KW - Antimicrobial Stewardship (AMS)

KW - antimicrobial stewardship (ASP) intervention

KW - Antimicrobial stewardship competencies

KW - Antimicrobial stewardship programme

KW - Antimicrobial stewardship programs

KW - Artificial intelligence

KW - artificial intelligence (AI)

KW - Artificial Intelligence (AI)

KW - Artificial intelligence drug modelling

KW - Artificial intelligence and machine learning

KW - Artificial intelligence framework

KW - artificial intelligence, business, machine learning, management, systematic literature review, tertiary study

KW - Artificial intelligence tools

KW - antimicrobial resistance

KW - Antimicrobial Resistance

KW - antimicrobial resistance (AMR)

KW - Antimicrobial Resistance (AMR)

KW - Antimicrobial Resistance;

KW - implementation science

KW - LMICs

KW - Implementation science

KW - digital health

KW - Digital health implementation, facilitators, barriers, digital health classification framework, lower- and middle-income countries

KW - Digital health innovation

KW - Digital health tools

KW - digital healthcare

M3 - Poster

T2 - ESCMID Global 2026 – European Society of Clinical Microbiology and Infectious Diseases Congress

Y2 - 18 April 2026 through 21 April 2026

ER -

Mohamed Marzok AW, Carra G, Liu PY, Boillat-Blanco N, Allel K, Roberto Giacobbe D et al.. Artificial Intelligence Applications in Antimicrobial Stewardship in LMICs: Effectiveness, Implementation Challenges, and Equity Considerations – A Systematic Review. 2026. Poster session presented at ESCMID Global 2026 – European Society of Clinical Microbiology and Infectious Diseases Congress, Munich, Germany.

Artificial Intelligence Applications in Antimicrobial Stewardship in LMICs: Effectiveness, Implementation Challenges, and Equity Considerations – A Systematic Review

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