Genomic epidemiology of SARS-CoV-2 infections in The Gambia: an analysis of routinely collected surveillance data between March, 2020, and January, 2022

Kanteh, Abdoulie; Jallow, Haruna S.; Manneh, Jarra; Sanyang, Bakary; Kujabi, Mariama A; Ndure, Sainabou Laye; Jarju, Sheikh; Sey, Alhagie Papa; K, Dabiri Damilare; Bah, Yaya; Sambou, Sana; Jarju, Gibril; Manjang, Buba; Jagne, Abubacarr; Bittaye, Sheikh Omar; Bittaye, Mustapha; Forrest, Karen; Tiruneh, Desta Alamerew; Samateh, Ahmadou Lamin; Jagne, Sheriffo; Hué, Stéphane; Mohammed, Nuredin; Amambua-Ngwa, Alfred; Kampmann, Beate; D’Alessandro, Umberto; Silva, Thushan I. de; Roca, Anna; Sesay, Abdul Karim

doi:10.1016/s2214-109x(22)00553-8

Cited by 8 publications

(16 citation statements)

References 33 publications

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“…However, with our HRM assay, we could identify the infecting variant in many of these samples and describe the variant waves in Kisumu during this time. Our assay has shown three variant replacement events between February 2021 and January 2022, which mirrors the three waves reported during this period from other African countries such as The Gambia (21), Ethiopia (22), and Senegal (23). In the samples analysed from Kenya this study, Alpha was the dominant variant between March 2021-May 2021 and was then replaced by Delta in May 2021, followed by Omicron in mid-December 2021, which is in keeping with epidemiological data from other regions of Kenya (24,25).…”

Section: Discussionsupporting

confidence: 80%

Application of a High-Resolution Melt Assay for Monitoring SARS-CoV-2 Variants in Burkina Faso and Kenya

Greenland-Bews,

Shah,

Achieng

et al. 2024

Preprint

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The rapid emergence and global dissemination of SARS-CoV-2 highlighted a need for robust, adaptable surveillance systems. However, financial and infrastructure requirements for whole genome sequencing (WGS) mean most surveillance data have come from higher-resource geographies, despite unprecedented investment in sequencing in low-middle income countries (LMICs) throughout the SARS-CoV-2 pandemic. Consequently, the molecular epidemiology of SARS-CoV-2 in some LMICs is limited, and there is a need for more cost-accessible technologies to help close data gaps for surveillance of SARS-CoV-2 variants. To address this, we have developed two high-resolution melt curve (HRM) assays that target key variant-defining mutations in the SARS-CoV-2 genome, which give unique signature profiles that define different SARS-CoV-2 variants of concern (VOCs). Extracted RNA from SARS-CoV-2 positive samples collected from 205 participants (112 in Burkina Faso, 93 in Kenya) on the day of enrolment in the MALCOV study (Malaria as a Risk Factor for COVID-19) between February 2021 and February 2022 were analysed using our optimised HRM assays and compared to Next Generation Sequencing (NGS) on Oxford Nanopore MinION . With NGS as a reference, two HRM assays, HRM-VOC-1 and HRM-VOC-2, demonstrated sensitivity/specificity of 100%/99.29% and 92.86/99.39%, respectively, for detecting Alpha, 90.08%/100% and 92.31%/100% for Delta and 93.75%/100% and 100%/99.38% for Omicron. The assays described here provide a lower-cost approach (<$1 per sample) to conducting molecular epidemiology, capable of high-throughput testing. We successfully scaled up the HRM-VOC-2 assay to screen a total of 506 samples from which we were able to show the replacement of Alpha with the introduction of Delta and the replacement of Delta by the Omicron variant in this community in Kisumu, Kenya. These assays are readily adaptable and can focus on local epidemiological surveillance questions or be updated quickly to accommodate the emergence of a novel variant or adapt to novel and emerging pathogens

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Section: Discussionsupporting

confidence: 80%

Application of a High-Resolution Melt Assay for Monitoring SARS-CoV-2 Variants in Burkina Faso and Kenya

Greenland-Bews,

Shah,

Achieng

et al. 2024

Preprint

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“…By December 2021, The Gambia had registered three SARS-CoV-2 transmission waves dated: first, July-September 2020; second, January 2021; and third, July 2021 (Figure 1). The first and third waves were more intense, with higher peaks of official daily cases [18] with the delta variant being the most frequent during the third wave [19]. The second wave concurred with the global transmission of the delta/B.1.617.2 subtype variant, described in The Gambia at the time [19].…”

Section: Covid-19 and The National Response In The Gambiamentioning

confidence: 64%

“…The first and third waves were more intense, with higher peaks of official daily cases [18] with the delta variant being the most frequent during the third wave [19]. The second wave concurred with the global transmission of the delta/B.1.617.2 subtype variant, described in The Gambia at the time [19].…”

Section: Covid-19 and The National Response In The Gambiamentioning

confidence: 64%

“…For the SARS-CoV-2 seroprevalence study presented here, we considered five sera collection time periods that corresponded to the SARS-CoV-2 waves observed in The Gambia [19]: (i)…”

Section: Sars-cov-2 Sero-prevalence Studymentioning

confidence: 99%

“…PeriCOVID: SARS-CoV-2 seroprevalence in pregnant women from Farafenni, The Gambia SARS-CoV-2, the causative agent of the coronavirus disease 2019 (COVID- 19), was first identified in December 2019 in Wuhan, China [1]. SARS-CoV-2 was rapidly transmitted globally, disrupting structures and systems; and causing millions of deaths.…”

Section: Introductionmentioning

confidence: 99%

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SARS-CoV-2 seroprevalence in pregnant women during the first three COVID-19 waves in The Gambia

Janha,

Bah,

Jah

et al. 2023

Preprint

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Objectives SARS-CoV-2 transmission in Sub-Saharan Africa has probably been underestimated. Population-based seroprevalence studies are needed to determine the extent of transmission in the continent. Methods Blood samples from a cohort of Gambian pregnant women were tested for SARS-CoV-2 total IgM/IgG before (Pre-pandemic1: October-December 2019 and Pre-pandemic2: February-June 2020) and during the pandemic (Post-wave1: October-December 2020, Post-wave2: May-June 2021; and Post-wave3: October-December 2021). Samples positive for total SARS-CoV-2 IgM/IgG were tested for protein-specific antibodies. Results SARS-CoV-2 total IgM/IgG seroprevalence was 0.9% 95%CI (0.2, 4.9) in Pre-pandemic1; 4.1% (1.4, 11.4) in Pre-pandemic2; 31.1% (25.2, 37.7) in Post-wave1; 62.5% (55.8, 68.8) in Post-wave2 and 90.0% (85.1, 93.5) in Post-wave3. S-protein IgG and NCP-protein IgG seroprevalence also increased at each Post-wave period. Although S-protein IgG and NCP-protein IgG seroprevalence was similar at Post-wave1, S-protein IgG seroprevalence was higher at Post-wave2 and Post-wave3, [prevalence difference (PD) 13.5 (0.1, 26.8) and prevalence ratio (PR) 1.5 (1.0, 2.3) in Post-wave2; and 22.9 (9.2, 36.6) and 1.4 (1.1, 1.8) in Post-wave3 respectively, p<0.001]. Conclusion SARS-CoV-2 transmission in The Gambia during the first three COVID-19 waves was high, differing significantly from official numbers of COVID-19 cases reported. Our findings are important for policy makers in managing the near-endemic COVID-19.

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Integrative genomics would strengthen AMR understanding through ONE health approach

Liu,

Pandey

2024

Heliyon

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Genomic epidemiology of SARS-CoV-2 infections in The Gambia: an analysis of routinely collected surveillance data between March, 2020, and January, 2022

Cited by 8 publications

References 33 publications

Application of a High-Resolution Melt Assay for Monitoring SARS-CoV-2 Variants in Burkina Faso and Kenya

Application of a High-Resolution Melt Assay for Monitoring SARS-CoV-2 Variants in Burkina Faso and Kenya

SARS-CoV-2 seroprevalence in pregnant women during the first three COVID-19 waves in The Gambia

Integrative genomics would strengthen AMR understanding through ONE health approach

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