4 research outputs found
Supplemental files_Paul Katongole et al.XLSX
No full textIntroduction: Uropathogenic E.coli (UPEC) remains the most common cause of urinary tract
infections (UTIs). They account for over 80-90% of all community acquired and
30-50% of all hospital acquired UTIs. E.coli
strains have been found to belong to evolutionary origins known as phylogenetic
groups. In 2013, Clermont classified E. coli strains
into eight phylogenetic groups using quadruplex PCR method. The aim of this
study was to identify the phylogenetic groups of UPEC strains in Uganda using
Clermont’s quadruplex PCR method and to assess their antibiotic susceptibility
patterns in Uganda.
Methods:
In this cross-sectional study, 140 stored
Uropathogenic E.coli isolates from the clinical microbiology laboratory,
department of Medical Microbiology, College of Health sciences Makerere
University were subjected to phylogenetic typing by a quadruplex PCR method.
Antimicrobial susceptibility testing was performed by disk diffusion method
according to CLSI 2014. Phenotypic detection of ESBL, AmpC and Carbapenemases
was done according to CLSI guidelines and Laboratory SOPs.
Results:
Phylogenetic group B2 (40%) was the most
predominant followed by A (6.23%), Clade I and II (5%), D and E (each 2.14%),
B1 (1.43%) and F and C (each 0.71%). The most common resistant antibiotic was
Trimethoprim sulphamethoxazole (90.71%) and the least was imipenem (1.43%).
73.57% of isolates were multiple drug resistant (MDR). Antibiotic resistance
was mainly detected in phylogenetic group B2 (54%).
Conclusions: Our findings showed
the high prevalence of MDR E. coli isolates with dominance of
phylogenetic group B2. About 9 % of E. coli isolates belonged to the
newly described phylogroups C, E, F, and clade I and I
Progress on implementing the WHO-GLASS recommendations on priority pathogen-antibiotic sensitivity testing in Africa: A scoping review [version 1; peer review: 2 approved]
No full textIntroduction The World Health Organization global antimicrobial resistance surveillance system (GLASS) was rolled out in 2015 to guide antimicrobial resistance (AMR) surveillance. However, its implementation in Africa has not been fully evaluated. We conducted a scoping review to establish the progress of implementing the WHO 2015 GLASS manual in Africa. Methods We used MeSH terms to comprehensively search electronic databases (MEDLINE and Embase) for articles from Africa published in English between January 2016 and December 2023. The Arksey and O'Malley's methodological framework for scoping reviews was employed. Data were collected on compliance with WHO GLASS recommendations for AMR surveillance-priority samples, pathogens, and pathogen-antibiotic combinations and analysed using Microsoft Excel. Results Overall, 13,185 articles were identified. 7,409 were duplicates, and 5,141 articles were excluded based on titles and abstracts. 609 full-text articles were reviewed, and 147 were selected for data extraction. Of the 147 selected articles, 78.9% had been published between 2020 and 2023; 57.8% were from Eastern Africa. 93.9% of articles were on cross-sectional studies. 96.6% included only one priority sample type; blood (n=56), urine (n=64), and stool (n=22). Of the 60 articles that focused on blood as a priority sample type, 71.7%, 68.3%, 68.3%, 36.7%, 30%, and 10% reported recovery of Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Salmonella species and Streptococcus pneumoniae, respectively. Salmonella and Shigella species were reported to have been recovered from 91.3% and 73.9% of the 23 articles that focused on stool. E. coli and K. pneumoniae recoveries were also reported from 94.2% and 68.1% of the 69 articles that focused on urine. No article in this review reported having tested all the recommended WHO GLASS pathogen-antibiotic combinations for specific pathogens. Conclusion Progress has been made in implementing the GLASS recommendations in Africa, but adoption varies across countries limiting standardisation and comparability of data
Continental concerted efforts to control the seventh outbreak of Ebola Virus disease in Uganda: The first 90 days of the response
No full textOn 20th September 2022, Uganda declared the 7th outbreak of Ebola virus disease (EVD) caused by the Sudan Ebola strain following the confirmation of a case admitted at Mubende Regional Referral Hospital. Upon confirmation, the Government of Uganda immediately activated the national incident management system to initiate response activities. Additionally, a multi‑country emergency stakeholder meeting was held in Kampala; convening Ministers of Health from neighbouring Member States to undertake cross‑border preparedness and response actions. The outbreak spanned 69 days and recorded 164 cases (142 confirmed, 22 probable), 87 recoveries and 77 deaths (case fatality ratio of 47%). Nine out of 136 districts were affected with transmission taking place in 5 districts but spilling over in 4 districts without secondary transmission. As part of the response, the Government galvanised robust community mobilisation and initiated assessment of medical counter measures including therapeutics, new diagnostics and vaccines. This paper highlights the response actions that contributed to the containment of this outbreak in addition to the challenges faced with a special focus on key recommendations for better control of future outbreaks
Sudan virus disease super-spreading, Uganda, 2022
No full textAbstract Background On 20 September 2022, Uganda declared its fifth Sudan virus disease (SVD) outbreak, culminating in 142 confirmed and 22 probable cases. The reproductive rate (R) of this outbreak was 1.25. We described persons who were exposed to the virus, became infected, and they led to the infection of an unusually high number of cases during the outbreak. Methods In this descriptive cross-sectional study, we defined a super-spreader person (SSP) as any person with real-time polymerase chain reaction (RT-PCR) confirmed SVD linked to the infection of ≥ 13 other persons (10-fold the outbreak R). We reviewed illness narratives for SSPs collected through interviews. Whole-genome sequencing was used to support epidemiologic linkages between cases. Results Two SSPs (Patient A, a 33-year-old male, and Patient B, a 26-year-old male) were identified, and linked to the infection of one probable and 50 confirmed secondary cases. Both SSPs lived in the same parish and were likely infected by a single ill healthcare worker in early October while receiving healthcare. Both sought treatment at multiple health facilities, but neither was ever isolated at an Ebola Treatment Unit (ETU). In total, 18 secondary cases (17 confirmed, one probable), including three deaths (17%), were linked to Patient A; 33 secondary cases (all confirmed), including 14 (42%) deaths, were linked to Patient B. Secondary cases linked to Patient A included family members, neighbours, and contacts at health facilities, including healthcare workers. Those linked to Patient B included healthcare workers, friends, and family members who interacted with him throughout his illness, prayed over him while he was nearing death, or exhumed his body. Intensive community engagement and awareness-building were initiated based on narratives collected about patients A and B; 49 (96%) of the secondary cases were isolated in an ETU, a median of three days after onset. Only nine tertiary cases were linked to the 51 secondary cases. Sequencing suggested plausible direct transmission from the SSPs to 37 of 39 secondary cases with sequence data. Conclusion Extended time in the community while ill, social interactions, cross-district travel for treatment, and religious practices contributed to SVD super-spreading. Intensive community engagement and awareness may have reduced the number of tertiary infections. Intensive follow-up of contacts of case-patients may help reduce the impact of super-spreading events
