Enhanced Contact Investigations for Nine Early Travel-Related Cases of SARS-CoV-2 in the United States
Bibliographic record
Abstract
ABSTRACT Background Coronavirus disease 2019 (COVID-19), the respiratory disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in Wuhan, China and has since become pandemic. As part of initial response activities in the United States, enhanced contact investigations were conducted to enable early identification and isolation of additional cases and to learn more about risk factors for transmission. Methods Close contacts of nine early travel-related cases in the United States were identified. Close contacts meeting criteria for active monitoring were followed, and selected individuals were targeted for collection of additional exposure details and respiratory samples. Respiratory samples were tested for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (RT-PCR) at the Centers for Disease Control and Prevention. Results There were 404 close contacts who underwent active monitoring in the response jurisdictions; 338 had at least basic exposure data, of whom 159 had ≥1 set of respiratory samples collected and tested. Across all known close contacts under monitoring, two additional cases were identified; both secondary cases were in spouses of travel-associated case patients. The secondary attack rate among household members, all of whom had ≥1 respiratory sample tested, was 13% (95% CI: 4 – 38%). Conclusions The enhanced contact tracing investigations undertaken around nine early travel-related cases of COVID-19 in the United States identified two cases of secondary transmission, both spouses. Rapid detection and isolation of the travel-associated case patients, enabled by public awareness of COVID-19 among travelers from China, may have mitigated transmission risk among close contacts of these cases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".