Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Sub-Saharan Africa: Longitudinal Trend Analysis
Bibliographic record
Abstract
BACKGROUND: This study updates the initial COVID-19 pandemic surveillance in sub-Saharan Africa (SSA) from 2020 by providing 2 additional years of data for the region. OBJECTIVE: First, we aimed to measure whether there was an expansion or contraction in the pandemic in SSA when the World Health Organization (WHO) declared an end to the public health emergency for the COVID-19 pandemic on May 5, 2023. Second, we used dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aimed to provide historical context for the course of the pandemic in SSA. METHODS: In addition to updates of traditional surveillance data and dynamic panel estimates from the original study by Post et al (2021), this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and used Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t-test to assess whether regional weekly speed was greater than an outbreak threshold of 10. We ran the test iteratively with a rolling 6-month window of data across the sample period. RESULTS: Speed for the region remained well below the outbreak threshold before and after the WHO declaration. Acceleration and jerk were also low and stable. The 7-day persistence coefficient remained somewhat large (1.11) and statistically significant. However, both shift parameters for the weeks around the WHO declaration were negative, meaning the clustering effect of new COVID-19 cases had become recently smaller. From November 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t-test of speed equal to 10 was insignificant for the entire sample period. CONCLUSIONS: While COVID-19 continues to circulate in SSA, the region never reached outbreak status, and the weekly transmission rate remained below 1 case per 100,000 population for well over 1 year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold for its classification as a pandemic. Both standard and enhanced surveillance metrics confirm that the pandemic ended in SSA by the time the WHO made its declaration.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".