Increased outbreaks of monkeypox highlight gaps in actual disease burden in Sub-Saharan Africa and in animal reservoirs
Bibliographic record
Abstract
We explain research gaps on Monkeypox (MPX) virus epidemiology in endemic countries and present hypotheses for the recent increase of MPX cases in West Africa as a possible explanation for the current epidemic in Europe, America, and Australia. The detection of >400 MPX cases in less than a month in May 2022, across many countries underscores the epidemic potential of MPX in humans and demonstrates several important research gaps. First, the true burden of MPX in West and Central Africa is poorly understood, although it is critical for prevention and control of future outbreaks. Second, the diversity and extent of the animal reservoir remain unknown. We hypothesize that the synanthropic rodent population has increased in recent years in Africa leading to more human-rodent interactions and thus increased transmission of MPXV. We further hypothesise that nearly 45 years after the end of routine smallpox vaccination, the larger and more interconnected immune-naïve population has crossed a threshold resulting in more sustainable human-to-human transmission of MPXV. The current epidemic in the Western World is possibly a consequence of increased local transmission of MPXV in Africa. A new estimation of the basic and effective reproduction rate ( R 0 and R e ) in different populations is required. National, regional, and international collaborations are needed to address research gaps related to MPX outbreaks.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".