Trends, patterns and relationship of antimicrobial use and resistance in bacterial isolates tested between 2015-2020 in a national referral hospital of Zambia.
Misheck ShawaAtmika PaudelHerman ChambaroHarvey KamboyiRuth NakazweLuke AlutuliTuvshinzaya ZorigtTaona SinyawaMulemba SamutelaJoseph ChizimuManyando SimbotweKyoko HayashidaNaganori NaoMasahiro KajiharaYoshikazu FurutaYasuhiko SuzukiHirofumi SawaBernard Hang'ombeHideaki HigashiPublished in: PloS one (2024)
Increased antimicrobial resistance (AMR) among bacteria underscores the need to strengthen AMR surveillance and promote data-based prescribing. To evaluate trends and associations between antimicrobial usage (AMU) and AMR, we explored a dataset of 34,672 bacterial isolates collected between 2015 and 2020 from clinical samples at the University Teaching Hospital (UTH) in Lusaka, Zambia. The most frequently isolated species were Escherichia coli (4,986/34,672; 14.4%), Staphylococcus aureus (3,941/34,672; 11.4%), and Klebsiella pneumoniae (3,796/34,672; 10.9%). Of the 16 drugs (eight classes) tested, only amikacin and imipenem showed good (> 50%) antimicrobial activity against both E. coli and K. pneumoniae, while nitrofurantoin was effective only in E. coli. Furthermore, 38.8% (1,934/4,980) of E. coli and 52.4% (2,079/3,791) of K. pneumoniae isolates displayed multidrug resistance (MDR) patterns on antimicrobial susceptibility tests. Among S. aureus isolates, 44.6% (973/2,181) were classified as methicillin-resistant (MRSA). Notably, all the MRSA exhibited MDR patterns. The annual hospital AMR rates varied over time, while there was a weak positive relationship (r = 0.38, 95% CI = 0.11-0.60) between the monthly use of third-generation cephalosporins (3GCs) and 3GC resistance among Enterobacterales. Overall, the results revealed high AMR rates that fluctuated over time, with a weak positive relationship between 3GC use and resistance. To our knowledge, this is the first report to evaluate the association between AMU and AMR in Zambia. Our results highlight the need to strengthen antimicrobial stewardship programs and optimize AMU in hospital settings.
Keyphrases
- staphylococcus aureus
- escherichia coli
- antimicrobial resistance
- klebsiella pneumoniae
- multidrug resistant
- methicillin resistant staphylococcus aureus
- genetic diversity
- biofilm formation
- healthcare
- adverse drug
- primary care
- acute care
- public health
- emergency department
- quality improvement
- mass spectrometry
- electronic health record
- machine learning
- cystic fibrosis
- respiratory tract
- gas chromatography
- high resolution
- artificial intelligence