Modeling Intervention Measures and Severity-Dependent Public Response during Severe Acute Respiratory Syndrome Outbreak
Bibliographic record
Abstract
The 2003 severe acute respiratory syndrome (SARS) epidemic came and left swiftly, resulting in more than 8,000 probable cases worldwide and 774 casualties. It is generally believed that quarantine of those individuals suspected of being infected was instrumental in quick containment of the outbreaks. In this work we propose a differential equation model that includes quarantine and other intervention measures implemented by the health authority, including those to prevent nosocomial infections and decrease frequency of contacts among the general public. We also consider the possible behavior change by the general populace to avoid infection, in response to the severity of the outbreak in general and to these intervention measures in particular. Complete analysis is given for the model without quarantine. For the general model with quarantine, a basic reproduction number is derived and full description of its dynamics is provided. We will show that introducing quarantine measures in the model could produce bistability in the system, thus changing the basic dynamics of the model. We give numerical examples of parameter values with which bistable steady states, where one is disease-free and the other endemic, could exist. However, realistic parameter values indicate that, assuming limited imported cases, the occurrence of the stable endemic steady state or bistability is unlikely. The modeling results indicate that for an infectious disease with infectivity and patterns of transmission typical of SARS\@, the outbreak can always be eradicated by implementing border control of imported cases and limited quarantine, along with the public's social response to avoid infections. Moreover, the results also suggest that quarantine measures will be effective in reducing infections only if the quarantined/isolated SARS patients and their potential contacts can successfully reduce their contact rate and/or transmission probabilities. Hence the effectiveness of quarantine for infectious diseases like SARS\@, for which no infection is being prevented during the quarantine period, can only be indirect and therefore must be combined with other intervention measures in order to quickly contain the 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".