Bibliographic record
Abstract
AIM: To describe the epidemiological characteristics of Middle East respiratory syndrome coronavirus (MERS-CoV) human cases since the first reported case in 2012. METHODS: This is a retrospective descriptive epidemiological analysis of all laboratory-confirmed MERS-CoV human cases reported to the World Health Organization (WHO) from 2012 to May 2025. Cumulative cases globally, along with their demographics, comorbidities, epidemiological exposure, symptoms, hospital admissions, and mortality, were included. Descriptive analysis was used for the data. RESULTS: Between March 2012 and May 2025, a total of 2,626 laboratory-confirmed MERS-CoV human cases were reported to the WHO, with 947 (36.1%) resulting in deaths. The majority of cases occurred in the Kingdom of Saudi Arabia (KSA), with 2,217 (84.4%) human cases and 866 (39.1%) deaths. Twenty-six other countries reported human cases, with the highest number occurring in South Korea, which reported 186 cases (7.1%). The highest number of cases occurred in 2014, with 662 (29.9%) cases, followed by 2015, with 453 (20.4%) cases. Almost half of the cases in KSA (44.7%) were secondary infections, and most (83%) required hospital admission, with 39.7% requiring admission to intensive care unit. The most common comorbidities were diabetes mellitus, chronic heart disease, and chronic renal failure. Between 2020 and the end of May 2025, 113 new human cases of MERS-CoV infection (4.3%) were reported, with the majority occurring in KSA. In 2025 alone, 10 new cases were reported, with two deaths. Secondary transmission occurred in 60% of these cases. Seven of the 10 cases were reported in April 2025 alone. CONCLUSION: Between 2012 and May 2025, the majority of MERS-CoV infections occurred in the Kingdom of Saudi Arabia and had a high mortality, reaching 40%. Although most cases were reported between 2014 and 2015, new human cases are still ongoing and are increasing in 2025. Continued epidemiological investigation and surveillance are needed.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".