Comparison of DNA concentration and bacterial pathogen PCR detection when using two DNA extraction kits for nasopharyngeal/oropharyngeal samples.

INTRODUCTION: Several important human pathogens that cause life-threatening infections are asymptomatically carried in the Nasopharynx/Oropharynx (NP/OP). DNA extraction is a prerequisite for most culture-independent techniques used to identify pathogens in the NP/OP. However, components of DNA extraction kits differ thereby giving rise to differences in performance. We compared the DNA concentration and the detection of three pathogens in the NP/OP using the discontinued DNeasy PowerSoil Kit (Kit DP) and the DNeasy PowerLyzer PowerSoil Kit (Kit DPP). METHODS: DNA was extracted from the same set of 103 NP/OP samples using the two kits. DNA concentration was measured using the Qubit 2.0 Fluorometer. Real-time Polymerase Chain reaction (RT-PCR) was done using the QuantStudio 7-flex system to detect three pathogens: S. pneumoniae, H. influenzae, and N. meningitidis. Bland-Altman statistics and plots were used to determine the threshold cycle (Ct) value agreement for the two kits. RESULTS: The average DNA concentration from kit DPP was higher than Kit DP; 1235.6 ng/ml (SD = 1368.3) vs 884.9 ng/ml (SD = 1095.3), p = 0.002. Using a Ct value cutoff of 40 for positivity, the concordance for the presence of S. pneumoniae was 82% (84/102); 94%(96/103) for N. meningitidis and 92%(95/103) for H. influenzae. Kit DP proportionately resulted in higher Ct values than Kit DPP for all pathogens. The Ct value bias of measurement for S. pneumoniae was +2.4 (95% CI, 1.9-3.0), +1.4 (95% CI, 0.9-1.9) for N. meningitidis and +1.4 (95% CI, 0.2-2.5) for H. influenzae. CONCLUSION: The higher DNA concentration obtained using kit DPP could increase the chances of recovering low abundant bacteria. The PCR results were reproducible for more than 90% of the samples for the gram-negative H. influenzae and N. meningitidis. Ct value variations of the kits must be taken into consideration when comparing studies that have used the two kits

Phylogeography and resistome of pneumococcal meningitis in West Africa before and after vaccine introduction.

Despite contributing to the large disease burden in West Africa, little is known about the genomic epidemiology of Streptococcus pneumoniae which cause meningitis among children under 5 years old in the region. We analysed whole-genome sequencing data from 185 S. pneumoniae isolates recovered from suspected paediatric meningitis cases as part of the World Health Organization (WHO) invasive bacterial diseases surveillance from 2010 to 2016. The phylogeny was reconstructed, accessory genome similarity was computed and antimicrobial-resistance patterns were inferred from the genome data and compared to phenotypic resistance from disc diffusion. We studied the changes in the distribution of serotypes pre- and post-pneumococcal conjugate vaccine (PCV) introduction in the Central and Western sub-regions separately. The overall distribution of non-vaccine, PCV7 (4, 6B, 9V, 14, 18C, 19F and 23F) and additional PCV13 serotypes (1, 3, 5, 6A, 19A and 7F) did not change significantly before and after PCV introduction in the Central region (Fisher's test P value 0.27) despite an increase in the proportion of non-vaccine serotypes to 40 % (n=6) in the post-PCV introduction period compared to 21.9 % (n=14). In the Western sub-region, PCV13 serotypes were more dominant among isolates from The Gambia following the introduction of PCV7, 81 % (n=17), compared to the pre-PCV period in neighbouring Senegal, 51 % (n=27). The phylogeny illustrated the diversity of strains associated with paediatric meningitis in West Africa and highlighted the existence of phylogeographical clustering, with isolates from the same sub-region clustering and sharing similar accessory genome content. Antibiotic-resistance genotypes known to confer resistance to penicillin, chloramphenicol, co-trimoxazole and tetracycline were detected across all sub-regions. However, there was no discernible trend linking the presence of resistance genotypes with the vaccine introduction period or whether the strain was a vaccine or non-vaccine serotype. Resistance genotypes appeared to be conserved within selected sub-clades of the phylogenetic tree, suggesting clonal inheritance. Our data underscore the need for continued surveillance on the emergence of non-vaccine serotypes as well as chloramphenicol and penicillin resistance, as these antibiotics are likely still being used for empirical treatment in low-resource settings. This article contains data hosted by Microreact

SARS-CoV-2 seroprevalence in pregnant women in Kilifi, Kenya from March 2020 to March 2022

BackgroundSeroprevalence studies are an alternative approach to estimating the extent of transmission of SARS-CoV-2 and the evolution of the pandemic in different geographical settings. We aimed to determine the SARS-CoV-2 seroprevalence from March 2020 to March 2022 in a rural and urban setting in Kilifi County, Kenya.MethodsWe obtained representative random samples of stored serum from a pregnancy cohort study for the period March 2020 to March 2022 and tested for antibodies against the spike protein using a qualitative SARS-CoV-2 ELISA kit (Wantai, total antibodies). All positive samples were retested for anti-SARS-CoV-2 anti-nucleocapsid antibodies (Euroimmun, ELISA kits, NCP, qualitative, IgG) and anti-spike protein antibodies (Euroimmun, ELISA kits, QuantiVac; quantitative, IgG).ResultsA total of 2,495 (of 4,703 available) samples were tested. There was an overall trend of increasing seropositivity from a low of 0% [95% CI 0–0.06] in March 2020 to a high of 89.4% [95% CI 83.36–93.82] in Feb 2022. Of the Wantai test-positive samples, 59.7% [95% CI 57.06–62.34] tested positive by the Euroimmun anti-SARS-CoV-2 NCP test and 37.4% [95% CI 34.83–40.04] tested positive by the Euroimmun anti-SARS-CoV-2 QuantiVac test. No differences were observed between the urban and rural hospital but villages adjacent to the major highway traversing the study area had a higher seroprevalence.ConclusionAnti-SARS-CoV-2 seroprevalence rose rapidly, with most of the population exposed to SARS-CoV-2 within 23 months of the first cases. The high cumulative seroprevalence suggests greater population exposure to SARS-CoV-2 than that reported from surveillance data

COVID 19 kap survey tool questionnaires.

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Covid19 kap information sheet & consent form.

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Sampling framework.

Sampling framework.</p