A pandemic within a pandemic? Admission to COVID-19 wards in hospitals is associated with increased prevalence of antimicrobial resistance in two African settings

BACKGROUND: Patients who develop severe illness due to COVID-19 are more likely to be admitted to hospital and acquire bacterial co-infections, therefore the WHO recommends empiric treatment with antibiotics. Few reports have addressed the impact of COVID-19 management on emergence of nosocomial antimicrobial resistance (AMR) in resource constrained settings. This study aimed to ascertain whether being admitted to a COVID-19 ward (with COVID-19 infection) compared to a non-COVID-19 ward (as a COVID-19 negative patient) was associated with a change in the prevalence of bacterial hospital acquired infection (HAI) species or resistance patterns, and whether there were differences in antimicrobial stewardship (AMS) and infection prevention and control (IPC) guidelines between COVID-19 and non-COVID-19 wards. The study was conducted in Sudan and Zambia, two resource constrained settings with differing country-wide responses to COVID-19. METHODS: Patients suspected of having hospital acquired infections were recruited from COVID-19 wards and non-COVID-19 wards. Bacteria were isolated from clinical samples using culture and molecular methods and species identified. Phenotypic and genotypic resistance patterns were determined by antibiotic disc diffusion and whole genome sequencing. Infection prevention and control guidelines were analysed for COVID-19 and non-COVID-19 wards to identify potential differences. RESULTS: 109 and 66 isolates were collected from Sudan and Zambia respectively. Phenotypic testing revealed significantly more multi-drug resistant isolates on COVID-19 wards in both countries (Sudan p = 0.0087, Zambia p = 0.0154). The total number of patients with hospital acquired infections (both susceptible and resistant) increased significantly on COVID-19 wards in Sudan, but the opposite was observed in Zambia (both p = ≤ 0.0001). Genotypic analysis showed significantly more β-lactam genes per isolate on COVID-19 wards (Sudan p = 0.0192, Zambia p = ≤ 0.0001). CONCLUSIONS: Changes in hospital acquired infections and AMR patterns were seen in COVID-19 patients on COVID-19 wards compared to COVID-19 negative patients on non-COVID-19 wards in Sudan and Zambia. These are likely due to a potentially complex combination of causes, including patient factors, but differing emphases on infection prevention and control, and antimicrobial stewardship policies on COVID-19 wards were highlighted

Aetiology of encephalitis and meningitis in children aged 1-59 months admitted to the Children's Hospital, Lusaka, Zambia

Background: Meningitis and encephalitis are important causes of admissions and mortality in Zambia. Apart from bacterial causes, no data is available on viral agents that cause disease at the Children's Hospital, Lusaka, Zambia. We conducted a prospective descriptive study to determine the viral and bacterial causes of encephalitis and meningitis in children aged 1-59 months.Methods: From November 2016 to February 2018, we collected cerebrospinal fluid (CSF) samples and clinical details from children admitted to the inpatient wards with encephalitis and meningitis. Macroscopic examination, microscopy, bacterialculture and real-time (Multiplex) PCR were performed on the CSF samples.Results: A total of 106 patients were enrolled. The median age was 10 months and 81 (76.4%) had meningitis while 25 (23.6%) had encephalitis. One (0.9%) participant had Haemophilus influenzae detected by both culture and PCR. Two (1.9%) had Neisseria meningitidis while 5 (4.7%) had Streptococcus pneumoniae detected only by PCR. Viruses were detected in 26.4% (28/106) and 64% had meningitis. The viral agents detected were: EBV (10%); Parvovirus B19, Human herpes virus type 6, Human herpes virus type 7 and CMV at 2.8% each. A raised CSF WBC was associated with the case definition (P=0.01) of meningitis. Patients with meningitis were more likely to be alive at discharge than those with encephalitis (OR = 3.6, CI = 1.96 – 6.68, P-value <0.001).Conclusions: Viral infections of the central nervous system (CNS) are the commonest causes of both encephalitis and meningitis at the Children's Hospital, Lusaka, Zambia

Extremely Drug-Resistant Salmonella enterica Serovar Senftenberg Infections in Patients in Zambia.

Two cases of extremely drug-resistant Salmonella enterica serovar Senftenberg isolated from patients in Zambia were investigated by utilizing MIC determinations and whole-genome sequencing. The isolates were resistant to, and harbored genes toward, nine drug classes, including fluoroquinolones and extended-spectrum cephalosporins, contained two plasmid replicons, and differed by 93 single-nucleotide polymorphisms

Drug-resistant Acinetobacter species isolated at the University Teaching Hospital, Lusaka, Zambia

Acinetobacter species have emerged as one of the leading causative agents of Hospital-Acquired Infections (HAIs). Acinetobacter baumannii, the most commonly isolated clinical subspecies among the Acinetobacter species, is known to cause a wide range of HAIs, with an increased risk of mortality ranging from 8% to 40% in hospitalized patients. This study aimed to evaluate the clinical significance of Acinetobacter species isolated from admitted patients, ward environmental surfaces and instruments at the University Teaching Hospital, (UTH) in Lusaka, Zambia.This was a facility-based cross-sectional study that involved collecting clinical samples (cerebrospinal fluid, sputum, pus swabs, blood culture, urine, synovial fluid, pericardial fluid, and pleural fluid) that were submitted to the Microbiology Laboratory at UTH as part of the routine diagnosis and patient care between July and December 2021. Environmental specimens were also collected from surfaces and equipment in contact with patients, such as beds, beddings, suction machines, ventilators, ward gowns and endotracheal tubes.Sixty Acinetobacter isolates were recovered, 40 (66.7%) from clinical specimens and 20 (33.3%) from environmental samples, respectively. Among the clinical isolates, the admission ward had the highest (21.7%; 95% CI: 10.9–32.4) while the main ICU had the least (1.7%; 95% CI: 0.0–5.0%); for environmental samples, the highest isolation was from taps (25%) and sinks (20%). Among the sixty Acinetobacter isolates, A. baumannii was the most prevalent subspecies (n = 43). Highest resistance was observed to tetracycline (98%; 95% CI: 94–100) and co-trimoxazole (70%; 95% CI: 58–82) while the lowest resistance was seen in imipenem (17%; 95% CI: 7.3–28.3), tobramycin (20%; 95%CI: 11.7–36) and cefotaxime (22%; 95% CI: 24–22). The AdeB gene (efflux pump) was detected in 82.5% of the clinical isolates. The frequency of clinical isolates that showed resistance to at least three classes of antibiotics (aminoglycosides, fluoroquinolones and sulphonamides) translated into being Multidrug-resistant (MDR) and Extensive drug resistance (XDR) in the clinical isolates was 75% (30/40) and 52.5% (21/30), respectively. These findings intimate the clinical significance of HAI Acinetobacter infections and need for continuous AMR surveillance to inform treatment guidelines and regular infection prevention processes

Multivariable logistic regression model for risk factors associated with treatment outcome (death/recovery) in patients at UTH.

Multivariable logistic regression model for risk factors associated with treatment outcome (death/recovery) in patients at UTH.</p

Genomic Signature of Multidrug-Resistant Salmonella enterica Serovar Typhi Isolates Related to a Massive Outbreak in Zambia between 2010 and 2012.

Retrospectively, we investigated the epidemiology of a massive Salmonella enterica serovar Typhi outbreak in Zambia during 2010 to 2012. Ninety-four isolates were susceptibility tested by MIC determinations. Whole-genome sequence typing (WGST) of 33 isolates and bioinformatic analysis identified the multilocus sequence type (MLST), haplotype, plasmid replicon, antimicrobial resistance genes, and genetic relatedness by single nucleotide polymorphism (SNP) analysis and genomic deletions. The outbreak affected 2,040 patients, with a fatality rate of 0.5%. Most (83.0%) isolates were multidrug resistant (MDR). The isolates belonged to MLST ST1 and a new variant of the haplotype, H58B. Most isolates contained a chromosomally translocated region containing seven antimicrobial resistance genes, catA1, bla(TEM-1), dfrA7, sul1, sul2, strA, and strB, and fragments of the incompatibility group Q1 (IncQ1) plasmid replicon, the class 1 integron, and the mer operon. The genomic analysis revealed 415 SNP differences overall and 35 deletions among 33 of the isolates subjected to whole-genome sequencing. In comparison with other genomes of H58, the Zambian isolates separated from genomes from Central Africa and India by 34 and 52 SNPs, respectively. The phylogenetic analysis indicates that 32 of the 33 isolates sequenced belonged to a tight clonal group distinct from other H58 genomes included in the study. The small numbers of SNPs identified within this group are consistent with the short-term transmission that can be expected over a period of 2 years. The phylogenetic analysis and deletions suggest that a single MDR clone was responsible for the outbreak, during which occasional other S. Typhi lineages, including sensitive ones, continued to cocirculate. The common view is that the emerging global S. Typhi haplotype, H58B, containing the MDR IncHI1 plasmid is responsible for the majority of typhoid infections in Asia and sub-Saharan Africa; we found that a new variant of the haplotype harboring a chromosomally translocated region containing the MDR islands of IncHI1 plasmid has emerged in Zambia. This could change the perception of the term “classical MDR typhoid” currently being solely associated with the IncHI1 plasmid. It might be more common than presently thought that S. Typhi haplotype H58B harbors the IncHI1 plasmid or a chromosomally translocated MDR region or both

Distribution of GNB isolated from blood cultures at UTH (2020 to 2021).

Distribution of GNB isolated from blood cultures at UTH (2020 to 2021).</p

Distribution of GNB per ward and MDR, XDR and PDR data.

Distribution of GNB per ward and MDR, XDR and PDR data.</p

Flowchart of the enrolled patients and selection criteria.

Flowchart of the enrolled patients and selection criteria.</p