Identifying and addressing challenges to antimicrobial use surveillance in the human health sector in low- and middle-income countries: experiences and lessons learned from Tanzania and Uganda
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Abstract
Background
Antimicrobial resistance (AMR) is a global health security threat and is associated
with increased morbidity and mortality. One of the key drivers of AMR is the inappropriate
use of antibiotics. A key component of improving antibiotic use is conducting antimicrobial
use (AMU) surveillance.
Methods
USAID Medicines Technologies and Pharmaceutical Services Program has supported the
implementation of antimicrobial stewardship activities, including setting up systems
for AMU surveillance in Tanzania and Uganda. Results from both countries have been
previously published. However, additional implementation experience and lessons learned
from addressing challenges to AMU surveillance have not been previously published
and are the subject of this narrative article.
Results
The team identified challenges including poor quality data, low digitalization of
tools, and inadequate resources including both financial and human resources. To address
these gaps, the Program has supported the use of continuous quality improvement approaches
addressing gaps in skills, providing tools, and developing guidelines to fill policy
gaps in AMU surveillance. Recommendations to fill these gaps, based on the Potter
and Brough systematic capacity building model have been proposed.
Conclusions
Strengthening AMU surveillance through using a capacity-building approach will fill
gaps and strengthen efforts for AMR control in both countries.
Summary Background Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen–drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. Methods We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen–drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. Findings On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62–6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911–1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000–1 270 000) deaths attributable to AMR and 3·57 million (2·62–4·78) deaths associated with AMR in 2019. One pathogen–drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000–100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae. Interpretation To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen–drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat. Funding Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.
'Capacity building' is the objective of many development programmes and a component of most others. However, satisfactory definitions continue to elude us, and it is widely suspected of being too broad a concept to be useful. Too often it becomes merely a euphemism referring to little more than training. This paper argues that it is more important to address systemic capacity building, identifying a pyramid of nine separate but interdependent components. These form a four-tier hierarchy of capacity building needs: (1) structures, systems and roles, (2) staff and facilities, (3) skills, and (4) tools. Emphasizing systemic capacity building would improve diagnosis of sectoral shortcomings in specific locations, improve project/programme design and monitoring, and lead to more effective use of resources. Based on extensive action research in 25 States, experience from India is presented to illustrate how the concept of the capacity building pyramid has been put to practical use.
Journal ID (nlm-ta): Antimicrob Resist Infect Control
Journal ID (iso-abbrev): Antimicrob Resist Infect Control
Title:
Antimicrobial Resistance and Infection Control
Publisher:
BioMed Central
(London
)
ISSN
(Electronic):
2047-2994
Publication date
(Electronic):
9
February
2023
Publication date PMC-release: 9
February
2023
Publication date Collection: 2023
Volume: 12
Electronic Location Identifier: 9
Affiliations
[1
]USAID Medicines, Technologies, and Pharmaceutical Services (MTaPS) Program, Management
Sciences for Health, Kampala, Uganda
[2
]USAID Medicines, Technologies, and Pharmaceutical Services (MTaPS) Program, Management
Sciences for Health, Dar Es Salaam, Tanzania
[3
]GRID grid.411961.a, ISNI 0000 0004 0451 3858, Weill Bugando School of Medicine, , Catholic University of Health and Allied Sciences, ; Mwanza, Tanzania
[4
]GRID grid.11194.3c, ISNI 0000 0004 0620 0548, Infectious Diseases Institute, , Makerere University College of Health Sciences, ; Kampala, Uganda
[5
]GRID grid.436296.c, ISNI 0000 0001 2203 2044, USAID Medicines, Technologies, and Pharmaceutical Services (MTaPS) Program, Management
Sciences for Health, ; Arlington, VA 22203 USA
[6
]USAID Medicines, Technologies, and Pharmaceutical Services (MTaPS) Program, Management
Sciences for Health, Nairobi, Kenya
[7
]GRID grid.34477.33, ISNI 0000000122986657, Department of Pharmacy, School of Pharmacy, , University of Washington, ; Seattle, WA 98105 USA
[8
]GRID grid.34477.33, ISNI 0000000122986657, Department of Global Health, School of Public Health, , University of Washington, ; Seattle, WA 98105 USA
[9
]GRID grid.11194.3c, ISNI 0000 0004 0620 0548, Sustainable Pharmaceutical Systems (SPS) Unit, Pharmacy Department, , Makerere University School of Health Sciences, ; P.O. Box 10217, Kampala, Uganda
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History
Date
received
: 28
June
2022
Date
accepted
: 26
January
2023
Funding
Funded by: FundRef http://dx.doi.org/10.13039/100000200, United States Agency for International Development;
Award ID: 7200AA18C00074
Award ID: 7200AA18C00074
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Award ID: 7200AA18C00074
Award ID: 7200AA18C00074
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Award ID: 7200AA18C00074
Award Recipient
:
Reuben KiggunduEdgar LusayaJeremiah SeniJ. P. WaswaFrancis KakoozaDinah TjipuraKate KikuleCecilia MuivaMohan P. JoshiAndy StergachisFreddy Eric KitutuNiranjan Konduri
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