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1.
Lancet Glob Health ; 9(12): e1658-e1666, 2021 12.
Article in English | MEDLINE | ID: mdl-34695371

ABSTRACT

BACKGROUND: Advances in SARS-CoV-2 sequencing have enabled identification of new variants, tracking of its evolution, and monitoring of its spread. We aimed to use whole genome sequencing to describe the molecular epidemiology of the SARS-CoV-2 outbreak and to inform the implementation of effective public health interventions for control in Zimbabwe. METHODS: We performed a retrospective study of nasopharyngeal samples collected from nine laboratories in Zimbabwe between March 20 and Oct 16, 2020. Samples were taken as a result of quarantine procedures for international arrivals or to test for infection in people who were symptomatic or close contacts of positive cases. Samples that had a cycle threshold of less than 30 in the diagnostic PCR test were processed for sequencing. We began our analysis in July, 2020 (120 days since the first case), with a follow-up in October, 2020 (at 210 days since the first case). The phylogenetic relationship of the genome sequences within Zimbabwe and global samples was established using maximum likelihood and Bayesian methods. FINDINGS: Of 92 299 nasopharyngeal samples collected during the study period, 8099 were PCR-positive and 328 were available for sequencing, with 156 passing sequence quality control. 83 (53%) of 156 were from female participants. At least 26 independent introductions of SARS-CoV-2 into Zimbabwe in the first 210 days were associated with 12 global lineages. 151 (97%) of 156 had the Asp614Gly mutation in the spike protein. Most cases, 93 (60%), were imported from outside Zimbabwe. Community transmission was reported 6 days after the onset of the outbreak. INTERPRETATION: Initial public health interventions delayed onset of SARS-CoV-2 community transmission after the introduction of the virus from international and regional migration in Zimbabwe. Global whole genome sequence data are essential to reveal major routes of spread and guide intervention strategies. FUNDING: WHO, Africa CDC, Biotechnology and Biological Sciences Research Council, Medical Research Council, National Institute for Health Research, and Genome Research Limited.


Subject(s)
COVID-19/epidemiology , Epidemics , Genome, Viral , Public Health Surveillance , SARS-CoV-2/genetics , Travel-Related Illness , Adolescent , Adult , COVID-19/transmission , COVID-19/virology , Child , Child, Preschool , Female , Humans , Infant , Male , Middle Aged , Molecular Epidemiology , Retrospective Studies , Whole Genome Sequencing , Young Adult , Zimbabwe/epidemiology
3.
PLoS One ; 14(11): e0223597, 2019.
Article in English | MEDLINE | ID: mdl-31747448

ABSTRACT

BACKGROUND: In Zimbabwe, viral load (VL) testing for people living with HIV on antiretroviral therapy is performed at the National Microbiology Reference Laboratory using a NucliSens machine. Anecdotal evidence has shown that invalid graphs for "Target Not Detectable (TND)" will upon repeat VL testing produce a valid result for virus not detected, therefore removing the need to repeat the test. This needs formal assessment. OBJECTIVES: To determine i) intra- and inter-rater agreement of the visual interpretation of NucliSens graphs (Target Detectable [TD], TND and No Line [NL]) between two laboratory scientists and ii) sensitivity, specificity and predictive values of the NucliSens graphs compared with repeat VL results. METHOD: Cross sectional study using secondary data. Two laboratory scientists independently rated graphs one week apart for intra-rater agreement and compared final ratings with each other for inter-rater agreement. Consensus interpretations of graphs were compared with repeat VL results. Kappa coefficients were used to obtain measures of agreement. RESULTS: There were 562 patients with NucliSens graphs and repeat VL. Kappa scores were: 0.98 (Scientist A); 0.99 (Scientist B); 0.96 (Scientist A versus Scientist B); and 0.65 (NucliSens graphs versus VL). Sensitivity, specificity, positive predictive value and negative predictive value for graphs compared with VL were 71%, 92%, 79% and 89% respectively. CONCLUSION: Intra-and inter-rater agreements were almost perfect. The negative predictive value translates to a false negative rate of 11%. If repeat VL testing is not done, the clinical consequences need to be balanced against cost savings and the risks outweigh the benefits.


Subject(s)
Computer Graphics , Data Interpretation, Statistical , HIV Infections/virology , Viral Load , Virology/instrumentation , Adult , Artifacts , Cross-Sectional Studies , Female , Humans , Male , Observer Variation
4.
Diagnostics (Basel) ; 9(3)2019 Jul 30.
Article in English | MEDLINE | ID: mdl-31366024

ABSTRACT

While reporting human immunodeficiency virus (HIV) viral load (VL) using dried blood spot (DBS) in the BioMerieux NucliSENS platform, application of the hematocrit correction factor has been suggested. In this cross-sectional study from the National Microbiology Reference Laboratory of Zimbabwe, we assessed whether hematocrit correction (individual and/or mean) in DBS results improved the correlation with plasma VL and prediction of VL non-suppression (≥1000 copies per ml in plasma). Of 517 specimens during August-December 2018, 65(12.6%) had non-suppressed plasma VL results. The hematocrit correction factor ranged from 1.3 to 2.0 with a mean of 1.6, standard deviation (SD: 1.5, 1.7). The intraclass correlation (ICC) for mean (0.859, 95% CI: 0.834, 0.880) and individual (0.809, 95% CI: 0.777, 0.837) hematocrit corrected DBS results were not significantly different. The uncorrected DBS results had a significantly lower ICC (0.640, 95% CI: 0.586, 0.688) when compared to corrected DBS results. There were no significant differences in validity, predictive values, and areas under the receiver operating characteristics curves for all three DBS results when predicting VL non-suppression. To conclude, hematocrit correction of DBS VL results improved agreement with the plasma results but did not improve prediction of VL non-suppression. The results were not significantly different for individual and mean corrected results.

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