The probability of failing in detecting an infectious disease at entry points into a country.
Identifieur interne : 002672 ( PubMed/Corpus ); précédent : 002671; suivant : 002673The probability of failing in detecting an infectious disease at entry points into a country.
Auteurs : M. Dell'Omodarme ; M C PratiSource :
- Statistics in medicine [ 0277-6715 ] ; 2005.
English descriptors
- KwdEn :
- Bayes Theorem, Communicable Diseases (diagnosis), Communicable Diseases (epidemiology), Confidence Intervals, Diagnostic Tests, Routine (methods), Diagnostic Tests, Routine (standards), Disease Outbreaks (prevention & control), Humans, Predictive Value of Tests, Quarantine, SARS Virus (genetics), SARS Virus (growth & development), Sensitivity and Specificity, Severe Acute Respiratory Syndrome (diagnosis), Travel.
- MESH :
- diagnosis : Communicable Diseases, Severe Acute Respiratory Syndrome.
- epidemiology : Communicable Diseases.
- genetics : SARS Virus.
- growth & development : SARS Virus.
- methods : Diagnostic Tests, Routine.
- prevention & control : Disease Outbreaks.
- standards : Diagnostic Tests, Routine.
- Bayes Theorem, Confidence Intervals, Humans, Predictive Value of Tests, Quarantine, Sensitivity and Specificity, Travel.
Abstract
In a group of N individuals, carrying an infection with prevalence pi, the exact probability P of failing in detecting the infection is evaluated when a diagnostic test of sensitivity s and specificity s' is carried out on a sample of n individuals extracted without replacement from the group. Furthermore, the minimal number of individuals that must be tested if the probability P has to be lower than a fixed value is determined as a function of pi. If all n tests result negative, confidence intervals for pi are given both in the frequentistic and Bayesian approach. These results are applied to recent data for severe acute respiratory syndrome (SARS). The conclusion is that entry screening with a diagnostic test is rarely an efficacious tool for preventing importation of a disease into a country.
DOI: 10.1002/sim.2131
PubMed: 15977301
Links to Exploration step
pubmed:15977301Le document en format XML
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Furthermore, the minimal number of individuals that must be tested if the probability P has to be lower than a fixed value is determined as a function of pi. If all n tests result negative, confidence intervals for pi are given both in the frequentistic and Bayesian approach. These results are applied to recent data for severe acute respiratory syndrome (SARS). 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