Epidemiological findings, estimates of the instantaneous reproduction number, and control strategies of the first Mpox outbreak in Latin America
Bibliographic record
Abstract
BACKGROUND: The 2022-2023 period marked the largest global Mpox outbreak, with Latin America's situation notably underexplored. This study aims to estimate Mpox's instantaneous reproduction number (R(t)), analyze epidemiological trends, and map vaccination efforts in six Latin American countries. METHODS: Utilizing Pan American Health Organization Mpox surveillance data, we examined demographic characteristics, cumulative incidence rates, and epidemic curves, calculated R(t) with weekly sliding windows for each country, alongside a review of vaccination initiatives. RESULTS: From 2022 to 2023, 25,503 Mpox cases and 71 deaths were reported across Argentina, Brazil, Chile, Colombia, Mexico and Peru, with a significant majority (91.8%-98.5%) affecting men, with a mean age of 32-35 years. Maximum R(t) values varied across countries: Argentina (2.63; 0.85 to 5.39), Brazil (3.13; 2.61 to 3.69), Chile (2.91; 1.55 to 4.70), Colombia (3.15; 2.07 to 4.44), Mexico (2.28; 1.18 to 3.75), and Peru (2.84; 2.33 to 3.40). The epidemic's peak occurred between August and September 2022 with R(t) values subsequently dropping below 1. From November 2022, and as of February 2024, only Chile, Peru, and Brazil had initiated Mpox vaccination campaigns, with Colombia launching a Clinical Trial. CONCLUSION: The peak of the Mpox epidemic in the studied countries occurred before the commencement of vaccination programs. This trend may be then partly attributed to a combination of behavioral modifications in key affected communities and contact tracing local programs. Therefore, the proportion of the at-risk population that remains susceptible is still uncertain, highlighting the need for continued surveillance and evaluation of vaccination strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".