Detection of SARS-CoV-2 Variants Imported Through Land Borders at the Height of the COVID-19 Pandemic in Ghana, 2022
Bibliographic record
Abstract
Background The World Health Organization recommends surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at points of entry to systematically collect and analyze data to inform decisions about the effective and appropriate use of resources needed for interventions. This study sought to determine the prevalence of SARS-CoV-2 and its variants imported into Ghana by travelers entering the country via land borders from February to July 2022. Methods A cross-sectional approach was employed, where recruited participants consented to the collection of oropharyngeal and nasopharyngeal samples. Specimens were analyzed for the presence of SARS-CoV-2 ribonucleic acid (RNA) using a commercially available VeriQ nCoV-OM COVID-19 Multiplex Detection kit. Amplicon sequencing protocols (ARTIC network, Oxford Nanopore Technologies (ONT), New England Biolabs, British Columbia Centre for Disease Control (BCCDC), COVID-19 Genomics UK (COG-UK), Canadian COVID-19 Genomics Network (CanCOGen), and ONT MinION) were used for SARS-CoV-2 sequencing. Logistic regression and phylogenetic analyses were conducted on the generated data. Results We detected a SARS-CoV-2 prevalence of 3.6% (170/4,621) among a total of 4,621 travelers screened. The average age of travelers was 32.11 ± 11.77, with the majority being male (68%, 3,132/4,621). After adjusting for educational status, household size, vaccination status, and study site, those with primary and tertiary education levels had 1.74 (95% CI: 1.16-2.62, P = 0.007) and 2.27 (95% CI: 1.27-4.05, P = 0.006) higher odds of testing positive for SARS-CoV-2 compared to those with no education. Vaccinated travelers had 0.65 odds (95% CI: 0.48-0.89, P = 0.007) of testing positive for SARS-CoV-2. The Omicron variant (B.1.1.529) emerged as the predominant lineage, constituting 77% (27/35) of isolates, compared to Alpha, Delta, and Recombinant variants. Phylogenetic analysis corroborated this finding, highlighting Delta and Omicron as the dominant circulating SARS-CoV-2 variants. Notably, Ghanaian strains from this study clustered with global variants, suggesting multiple introductions, likely through land borders. Conclusion A low prevalence of SARS-CoV-2 was recorded in this study, prompting the decision to reopen land borders and ease pandemic-related travel restrictions. Omicron was identified as the dominant variant. These findings emphasize the crucial role of routine surveillance at port health and advocate for a collaborative approach to addressing public health crises, preventing unnecessary travel and trade restrictions through data-based decision-making.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".