ABSTRACT
ImportanceEstimating the true burden of SARS-CoV-2 infection has been difficult in sub-Saharan Africa due to asymptomatic infections and inadequate testing capacity. Antibody responses from serologic surveys can provide an estimate of SARS-CoV-2 exposure at the population level. ObjectiveTo estimate SARS-CoV-2 seroprevalence, attack rates, and re-infection in eastern Uganda using serologic surveillance from 2020 to early 2022. DesignPlasma samples from participants in the Program for Resistance, Immunology, Surveillance, and Modeling of Malaria in Uganda (PRISM) Border Cohort were obtained at four sampling intervals: October-November 2020; March-April 2021; August-September 2021; and February-March 2022. Setting: Tororo and Busia districts, Uganda. Participants1,483 samples from 441 participants living in 76 households were tested. Each participant contributed up to 4 time points for SARS-CoV-2 serology, with almost half of all participants contributing at all 4 time points, and almost 90% contributing at 3 or 4 time points. Information on SARS-CoV-2 vaccination status was collected from participants, with the earliest reported vaccinations in the cohort occurring in May 2021. Main Outcome(s) and Measure(s)The main outcomes of this study were antibody responses to the SARS-CoV-2 spike protein as measured with a bead-based serologic assay. Individual-level outcomes were aggregated to population-level SARS-CoV-2 seroprevalence, attack rates, and boosting rates. Estimates were weighted by the local age distribution based on census data. ResultsBy the end of the Delta wave and before widespread vaccination, nearly 70% of the study population had experienced SARS-CoV-2 infection. During the subsequent Omicron wave, 85% of unvaccinated, previously seronegative individuals were infected for the first time, and [~]50% or more of unvaccinated, already seropositive individuals were likely re-infected, leading to an overall 96% seropositivity in this population. Our results suggest a lower probability of re-infection in individuals with higher pre-existing antibody levels. We found evidence of household clustering of SARS-CoV-2 seroconversion. We found no significant associations between SARS-CoV-2 seroconversion and gender, household size, or recent Plasmodium falciparum malaria exposure. Conclusions and RelevanceFindings from this study are consistent with very high infection rates and re-infection rates for SARS-CoV-2 in a rural population from eastern Uganda throughout the pandemic.
ABSTRACT
BackgroundCauses of non-malarial fevers in sub-Saharan Africa remain understudied. We hypothesized that metagenomic next-generation sequencing (mNGS), which allows for broad genomic-level detection of infectious agents in a biological sample, can systematically identify potential causes of non-malarial fevers. Methods and FindingsThe 212 participants in this study were of all ages and were enrolled in a longitudinal malaria cohort in eastern Uganda. Between December 2020 and August 2021, respiratory swabs and plasma samples were collected at 313 study visits where participants presented with fever and were negative for malaria by microscopy. Samples were analyzed using CZ ID, a web-based platform for microbial detection in mNGS data. Overall, viral pathogens were detected at 123 of 313 visits (39%). SARS-CoV-2 was detected at 11 visits, from which full viral genomes were recovered from nine. Other prevalent viruses included Influenza A (14 visits), RSV (12 visits), and three of the four strains of seasonal coronaviruses (6 visits). Notably, 11 influenza cases occurred between May and July 2021, coinciding with when the Delta variant of SARS-CoV-2 was circulating in this population. The primary limitation of this study is that we were unable to estimate the contribution of bacterial microbes to non-malarial fevers, due to the difficulty of distinguishing bacterial microbes that were pathogenic from those that were commensal or contaminants. ConclusionsThese results revealed the co-circulation of multiple viral pathogens likely associated with fever in the cohort during this time period. This study illustrates the utility of mNGS in elucidating the multiple causes of non-malarial febrile illness. A better understanding of the pathogen landscape in different settings and age groups could aid in informing diagnostics, case management, and public health surveillance systems.
ABSTRACT
Investment in Africa over the past year with regards to SARS-CoV-2 genotyping has led to a massive increase in the number of sequences, exceeding 100,000 genomes generated to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence within their own borders, coupled with a decrease in sequencing turnaround time. Findings from this genomic surveillance underscores the heterogeneous nature of the pandemic but we observe repeated dissemination of SARS-CoV-2 variants within the continent. Sustained investment for genomic surveillance in Africa is needed as the virus continues to evolve, particularly in the low vaccination landscape. These investments are very crucial for preparedness and response for future pathogen outbreaks. One-Sentence SummaryExpanding Africa SARS-CoV-2 sequencing capacity in a fast evolving pandemic.
ABSTRACT
Background: Implementation of appropriate informed consent has become a cornerstone for the use of biological materials and data from clinical care to use in research. During 2017-2018, the Ugandan National Biorepository has since sought prior informed consent for long-term storage and use of remnant clinical human biological materials, where a shortened informed consent form (ICF) was incorporated on the laboratory investigation form. This project aimed at determining the acceptability rate of broad consent from health care users (HCUs) for storage of biological materials and data for research purposes in Uganda. Methods: A cross-sectional study was conducted at three Primary Health Care Facilities. 500 HCUs above 18 years of age seeking health care at outpatient departments between March to December 2020 were invited to enrol. A shortened experimental ICF for this study was developed and attached to the Laboratory investigation form. Results: Overall the acceptability of broad consent for storage of biological materials and data was 86.2% [95% CI: 82.9%-88.9%]. Compared to participants who perceived that the informed consent information is understandable (OR=0.10, CI [0.03-0.32], participants who either partly or totally disagreed were significantly less likely to perceive information as understandable (OR=0.27, CI [0.15-0.46]. 226 out of 431 respondents that accepted storage of biological materials and data, majority (61.7%) preferred to receive feedback on results of relevance to their health. Conclusion: Acceptance of broad consent for storage of biological materials and data for future research purposes was high among HCUs. A shortened and simplified ICF may trigger discussions between participants and health care workers hence increase research participant understanding of study related materials in biobanking. This in turn could enrich ethically collected biobank resources for future research of public health relevance.
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The progression of the SARS-CoV-2 pandemic in Africa has so far been heterogeneous and the full impact is not yet well understood. Here, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations, predominantly from Europe, which diminished following the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1 and C.1.1. Although distorted by low sampling numbers and blind-spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a breeding ground for new variants.
ABSTRACT
Introductory paragraphSARS-CoV-2 genomic surveillance in Uganda provides an opportunity to provide a focused description of the virus evolution in a small landlocked East African country. Here we show a recent shift in the local epidemic with a newly emerging lineage A.23 evolving into A.23.1 which is now dominating the Uganda cases and has spread to 26 other countries. Although the precise changes in A.23.1 as it has adapted are different from the changes in the variants of concern (VOC), the evolution shows convergence on a similar set of proteins. The A.23.1 spike protein coding region has accumulated changes that resemble many of the changes seen in VOC including a change at position 613, a change in the furin cleavage site that extends the basic amino acid motif, and multiple changes in the immunogenic N-terminal domain. In addition, the A.23.1lineage encodes changes in non-spike proteins that other VOC show (nsp6, ORF8 and ORF9). The clinical impact of the A.23.1 variant is not yet clear, however it is essential to continue careful monitoring of this variant, as well as rapid assessment of the consequences of the spike protein changes for vaccine efficacy.
ABSTRACT
BackgroundGlobally response to the SARS-CoV-2 pandemic is highly limited by diagnostic methods. Currently, World Health Organization (WHO) recommends the use of molecular assays for confirmation of SARS-CoV-2 infection which are highly expensive and require specialized laboratory equipment. This is a limitation in mass testing and in low resource settings. SARS CoV-2 IgG/IgM antibody tests have had poor diagnostic performance that do not guarantee their use in diagnostics. In this study we demonstrate a concept of using a combination of RDTs in an algorithm to improve their performance for diagnostics. MethodEighty six (86) EDTA whole blood samples were collected from SARS-CoV-2 positive cases admitted at Masaka and Mbarara Regional Referral Hospitals in Uganda. These were categorized from day when confirmed positive as follows; category A (0-3 days, 10 samples), category B (4-7 days, 20 samples), Category C (8-17 days, 11 samples) and Category D (18-28 days, 20 samples). Plasma was prepared, transported to the testing laboratory and stored at -200C prior to testing. A total of 13 RDTS were tested following manufacturers instructions. Data was entered in Microsoft Excel exported to STATA for computation of sensitivity and specificity. We computed for all possible combinations of 2 of the 13 RDTS (13C2) that were evaluated in parallel algorithm. ResultsThe individual sensitives of the RDTs ranged between 74% and 18% and there was a general increasing trend across the categories with days since PCR confirmation. A total of 78 possible combinations of the RDTs to be used in parallel was computated. The combinations of the 2 RDTS improved the sensitivities to 90%. DiscussionWe demonstrate that use of RDTs in combinations can improve their overall sensitivity. This approach when used on a wider range of combination of RDTs may yield combinations that can give sensitivities that are of diagnostics relevance in mass testing and low resource setting.
