Search Results (3)

Background: The Banalia health zone in the Democratic Republic of Congo reported a meningitis epidemic in 2021 that evolved outside the epidemic season. We assessed the effects of the meningitis epidemic response. Methods: The standard case definition was used to identify cases. Care was provided to 2651 in-patients, with 8% of them laboratory tested, and reactive vaccination was conducted. To assess the effects of reactive vaccination and treatment with ceftriaxone, a statistical analysis was performed. Results: Overall, 2662 suspected cases of meningitis with 205 deaths were reported. The highest number of cases occurred in the 30–39 years age group (927; 38.5%). Ceftriaxone contributed to preventing deaths with a case fatality rate that decreased from 70.4% before to 7.7% after ceftriaxone was introduced (p = 0.001). Neisseria meningitidis W was isolated, accounting for 47/57 (82%), of which 92% of the strains belonged to the clonal complex 11. Reactive vaccination of individuals in Banalia aged 1–19 years with a meningococcal multivalent conjugate (ACWY) vaccine (Menactra^®) coverage of 104.6% resulted in an 82% decline in suspected meningitis cases (incidence rate ratio, 0.18; 95% confidence interval, 0.02–0.80; p = 0.041). Conclusion: Despite late detection (two months) and reactive vaccination four months after crossing the epidemic threshold, interventions implemented in Banalia contributed to the control of the epidemic. Full article

Background: There is a growing body of evidence on the potential involvement of coagulase-negative Staphylococci (CoNS) in causing urinary tract infections (UTIs). The aim of this study was to delineate virulence potential, antimicrobial resistance genes, and sequence types of CoNS isolated from patients with UTI symptoms and pyuria in Tanzania. Methods: CoNS from patients with UTI symptoms and more than 125 leucocytes/μL were retrieved, subcultured, and whole-genome sequenced. Results: Out of 65 CoNS isolates, 8 species of CoNS were identified; Staphylococcus haemolyticus, n = 27 (41.5%), and Staphylococcus epidermidis, n = 24 (36.9%), were predominant. The majority of S. haemolyticus were sequence type (ST) 30, with 8 new ST138-145 reported, while the majority of S. epidermidis were typed as ST490 with 7 new ST1184-1190 reported. Sixty isolates (92.3%) had either one or multiple antimicrobial resistance genes. The most frequently detected resistance genes were 53 (21%) dfrG, 32 (12.9%) blaZ, and 26 (10.5%) mecA genes conferring resistance to trimethoprim, penicillin, and methicillin, respectively. Out of 65 isolates, 59 (90.8%) had virulence genes associated with UTI, with a predominance of the icaC 47 (46.5%) and icaA 14 (13.9%) genes. Conclusion:S. haemolyticus and S. epidermidis harboring icaC, dfrG, blaZ, and mecA genes were the predominant CoNS causing UTI in Tanzania. Laboratories should carefully interpret the significant bacteriuria due to CoNS in relation to UTI symptoms and pyuria before labeling them as contaminants. Follow-up studies to document the outcome of the treated patients is needed to add more evidence that CoNS are UTI pathogens. Full article

A multi-mission satellite remote sensing (MSRS) approach is explored to detect and track leaked oil from the Sabiti oil tanker accident that occurred in the central Red Sea on 11 October 2019 (RSOS-2019). The spilled oil spread rapidly and reached the coastal land near Jeddah, the second largest city of KSA, on 17 October. Different oil spill detection algorithms were implemented on SAR and optical sensor-based satellite images to track the oil spill. Sentinel-1 SAR images were most efficient at detecting the spread and thickness of RSOS-2019, but their spatio-temporal coverage greatly limits their use for tracking the oil movement. The spread and propagation of oil were well captured by Sentinel-2 images up to three weeks after the accident day, in agreement with the SAR images. MODIS successfully detected the narrow patch of oil that was leaked on the incident day and the widespread oil patches two days after. Landsat-8 RGB composite and thermal infrared images captured the oil spill on 13 October. By filtering clouds from the Meteosat images through sequential analysis, the spread and movement of the oil patches were efficiently tracked on 13 October. PlanetScope images available between 12 and 17 October enabled tracking of the oil near the coastal waters. The inferred oil spill movements are consistent with the ocean currents as revealed by a high-resolution regional ocean reanalysis. Our results demonstrate the potential of the MSRS approach to detect and track oil spills in the open and coastal waters of the Red Sea in near real-time. Full article