.png){kind=icon}
返回
Estimating true prevalence through questionnaire data
.png){kind=icon}
OA
AI
DOI：10.1002/jmv.28908.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We present a general analytical method for obtaining unbiased prevalence estimates based on data from regional or national testing programs, where individual participation in the testing program is voluntary but where additional questionnaire data is collected regarding the individual-level reason/motivation for being tested. The approach is based on re-writing the conditional probabilities for being tested, being infected, and having symptoms, so that a series of equations can be defined that relate estimable quantities (from test data and questionnaire data) to the result of interest (an unbiased estimate of prevalence). The final estimates appear to be robust based on prima-facie examination of the temporal dynamics estimated, as well as agreement with an independent estimate of prevalence. Our approach demonstrates the potential strength of incorporating questionnaires when testing a population during an outbreak, and can be used to help obtain unbiased estimates of prevalence in similar settings.
Keyword:
biostatistics & bioinformatics
coronavirus
data processing
epidemiology
pandemics
SARS coronavirus
time series analysis
virus classification
期刊
IF:
4.6
论文数:
1.2W
被引数:
2.0W
机构
引用论文
Global Percentage of Asymptomatic SARS-CoV-2 Infections Among the Tested Population and Individuals With Confirmed COVID-19 Diagnosis A Systematic Review and Meta-analysis.png)
JAMA NETWORK OPEN
OAAI
JAMA NETWORK OPENIF9.7
OAAI分享收藏Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methodsBMC PUBLIC HEALTHOAAI
BMC PUBLIC HEALTHIF3.6
OAAI分享收藏分享收藏Household transmission of SARS-CoV-2 Omicron variant of concern subvariants BA.1 and BA.2 in DenmarkNATURE COMMUNICATIONSOAAI
NATURE COMMUNICATIONSIF15.7
OAAI分享收藏
查看更多内容