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Filename: drivers/Session_files_driver.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
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Purpose: The U.S. response to the SARS-CoV-2 epidemic has been hampered by early and ongoing delays in testing for infection; without data on where infections were occurring and the magnitude of the epidemic, early public health responses were not data-driven. Understanding the prevalence of SARS-CoV-2 infections and immune response is critical to developing and implementing effective public health responses. Most serological surveys have been limited to localities that opted to conduct them and/or were based on convenience samples. Moreover, results of antibody testing might be subject to high false positive rates in the setting of low prevalence of immune response and imperfect test specificity.
Methods: We will conduct a national serosurvey for SARS-CoV-2 PCR positivity and immune experience. A probability sample of U.S. addresses will be mailed invitations and kits for the self-collection of anterior nares swab and finger prick dried blood spot specimens. Within each sampled household, one adult 18 years or older will be randomly selected and asked to complete a questionnaire and to collect and return biological specimens to a central laboratory. Nasal swab specimens will be tested for SARS-CoV-2 RNA by RNA PCR; dried blood spot specimens will be tested for antibodies to SARS-CoV-2 (i.e., immune experience) by enzyme-linked immunoassays. Positive screening tests for antibodies will be confirmed by a second antibody test with different antigenic basis to improve predictive value of positive (PPV) antibody test results. All persons returning specimens in the baseline phase will be enrolled into a follow-up cohort and mailed additional specimen collection kits 3 months after baseline. A subset of 10% of selected households will be invited to participate in full household testing, with tests offered for all household members aged ≥3 years. The main study outcomes will be period prevalence of infection with SARS-CoV-2 and immune experience, and incidence of SARS-CoV-2 infection and antibody responses.
Results: Power calculations indicate that a national sample of 4000 households will facilitate estimation of national SARS-CoV-2 infection and antibody prevalence with acceptably narrow 95% confidence intervals across several possible scenarios of prevalence levels. Oversampling in up to seven populous states will allow for prevalence estimation among subpopulations. Our 2-stage algorithm for antibody testing produces acceptable PPV at prevalence levels ≥1.0%. Including oversamples in states, we expect to receive data from as many as 9156 participants in 7495 U.S. households.
Conclusions: In addition to providing robust estimates of prevalence of SARS-CoV-2 infection and immune experience, we anticipate this study will establish a replicable methodology for home-based SARS-CoV-2 testing surveys, address concerns about selection bias, and improve positive predictive value of serology results. Prevalence estimates of SARS-CoV-2 infection and immune experience produced by this study will greatly improve our understanding of the spectrum of COVID-19 disease, its current penetration in various demographic, geographic, and occupational groups, and inform the range of symptoms associated with infection. These data will inform resource needs for control of the ongoing epidemic and facilitate data-driven decisions for epidemic mitigation strategies.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7417272 | PMC |
http://dx.doi.org/10.1016/j.annepidem.2020.07.015 | DOI Listing |
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