bThe possible health risks associated with the consumption of harvested rainwater remains one of the major obstacles hampering its large-scale implementation in water limited countries such as South Africa. Rainwater tank samples collected on eight occasions during the low-and high-rainfall periods (March to August 2012) in Kleinmond, South Africa, were monitored for the presence of virulence genes associated with Escherichia coli. The identity of presumptive E. coli isolates in rainwater samples collected from 10 domestic rainwater harvesting (DRWH) tanks throughout the sampling period was confirmed through universal 16S rRNA PCR with subsequent sequencing and phylogenetic analysis. Species-specific primers were also used to routinely screen for the virulent genes, aggR, stx, eae, and ipaH found in enteroaggregative E. coli (EAEC), enterohemorrhagic E. coli (EHEC), enteropathogenic E. coli (EPEC), and enteroinvasive E. coli, respectively, in the rainwater samples. Of the 92 E. coli strains isolated from the rainwater using culture based techniques, 6% were presumptively positively identified as E. coli O157:H7 using 16S rRNA. Furthermore, virulent pathogenic E. coli genes were detected in 3% (EPEC and EHEC) and 16% (EAEC) of the 80 rainwater samples collected during the sampling period from the 10 DRWH tanks. This study thus contributes valuable information to the limited data available regarding the ongoing prevalence of virulent pathotypes of E. coli in harvested rainwater during a longitudinal study in a high-population-density, periurban setting.
Introduction The HPTN 071 (PopART) trial evaluated the impact of an HIV combination prevention package that included “universal testing and treatment” on HIV incidence in 21 communities in Zambia and South Africa during 2013‐2018. The primary study endpoint was based on the results of laboratory‐based HIV testing for> 48,000 participants who were followed for up to three years. This report evaluated the performance of HIV assays and algorithms used to determine HIV status and identify incident HIV infections in HPTN 071, and assessed the impact of errors on HIV incidence estimates. Methods HIV status was determined using a streamlined, algorithmic approach. A single HIV screening test was performed at centralized laboratories in Zambia and South Africa (all participants, all visits). Additional testing was performed at the HPTN Laboratory Center using antigen/antibody screening tests, a discriminatory test and an HIV RNA test. This testing was performed to investigate cases with discordant test results and confirm incident HIV infections. Results HIV testing identified 978 seroconverter cases. This included 28 cases where the participant had acute HIV infection at the first HIV‐positive visit. Investigations of cases with discordant test results identified cases where there was a participant or sample error (mixups). Seroreverter cases (errors where status changed from HIV infected to HIV uninfected, 0.4% of all cases) were excluded from the primary endpoint analysis. Statistical analysis demonstrated that exclusion of those cases improved the accuracy of HIV incidence estimates. Conclusions This report demonstrates that the streamlined, algorithmic approach effectively identified HIV infections in this large cluster‐randomized trial. Longitudinal HIV testing (all participants, all visits) and quality control testing provided useful data on the frequency of errors and provided more accurate data for HIV incidence estimates.
Background Assays and multi-assay algorithms (MAAs) have been developed for population-level cross-sectional HIV incidence estimation. These algorithms use a combination of serologic and/or non-serologic biomarkers to assess the duration of infection. We evaluated the performance of four MAAs for individual-level recency assessments. Methods Samples were obtained from 220 seroconverters (infected <1 year) and 4,396 non-seroconverters (infected >1 year) enrolled in an HIV prevention trial (HPTN 071 [PopART]); 28.6% of the seroconverters and 73.4% of the non-seroconverters had HIV viral loads ≤400 copies/mL. Samples were tested with two laboratory-based assays (LAg-Avidity, JHU BioRad-Avidity) and a point-of-care assay (rapid LAg). The four MAAs included different combinations of these assays and HIV viral load. Seroconverters on antiretroviral treatment (ART) were identified using a qualitative multi-drug assay. Results The MAAs identified between 54 and 100 (25% to 46%) of the seroconverters as recently-infected. The false recent rate of the MAAs for infections >2 years duration ranged from 0.2%-1.3%. The MAAs classified different overlapping groups of individuals as recent vs. non-recent. Only 32 (15%) of the 220 seroconverters were classified as recent by all four MAAs. Viral suppression impacted the performance of the two LAg-based assays. LAg-Avidity assay values were also lower for seroconverters who were virally suppressed on ART compared to those with natural viral suppression. Conclusions The four MAAs evaluated varied in sensitivity and specificity for identifying persons infected <1 year as recently infected and classified different groups of seroconverters as recently infected. Sensitivity was low for all four MAAs. These performance issues should be considered if these methods are used for individual-level recency assessments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.