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Background: Avian influenza A (H7N9) remains circulating in China. For countries at risk of introduction of H7N9, such as Vietnam, early detection of H7N9 virus is essential for the early containment of the virus. Insulated isothermal reverse transcriptase PCR (iiRT‐PCR) is a portable PCR system that can be deployed under field conditions to identify pathogens at the sampling site. Applying PCR at the sampling site will greatly reduce the time to obtain a diagnostic result which allows the veterinary authority to take immediate action to contain disease spreading. Objective: To determine analytical and diagnostic sensitivity and specificity of the portable iiRT‐PCR for H7N9 virus detection. Methods: A panel of 59 virus isolates, including H7N9, avian influenza viruses of subtype H1 to H13, swine and human influenza viruses, Newcastle disease virus, and infectious bursal disease virus, were tested by H7 and N9 iiRT‐PCR reagents, using probes and primers specific to H7 or N9, in comparison with laboratory‐based real‐time RT‐PCR assays to determine analytical sensitivity and specificity. Fifty oropharyngeal samples from experimentally infected chicken and ducks with H7N9 and 50 non‐infected control swabs were tested by the H7 iiRT‐PCR to determine diagnostic sensitivity and specificity. Results: The H7 and N9 iiRT‐PCR reagents yielded comparable levels of analytical sensitivity and specificity with real‐time RT‐PCR for the detection of H7N9 virus. Diagnostic sensitivity and specificity of H7 iiRT‐PCR were 98% and 100%, respectively. Conclusion: The observed high sensitivity and specificity of iiRT‐PCR for H7N9 detection show its potential for early detection of H7N9 in risk‐based surveillance. [ABSTRACT FROM AUTHOR]

Aims: To present a new approach for estimating the "true prevalence" of malaria and apply it to datasets from Peru, Vietnam, and Cambodia., Methods: Bayesian models were developed for estimating both the malaria prevalence using different diagnostic tests (microscopy, PCR & ELISA), without the need of a gold standard, and the tests' characteristics. Several sources of information, i.e. data, expert opinions and other sources of knowledge can be integrated into the model. This approach resulting in an optimal and harmonized estimate of malaria infection prevalence, with no conflict between the different sources of information, was tested on data from Peru, Vietnam and Cambodia., Results: Malaria sero-prevalence was relatively low in all sites, with ELISA showing the highest estimates. The sensitivity of microscopy and ELISA were statistically lower in Vietnam than in the other sites. Similarly, the specificities of microscopy, ELISA and PCR were significantly lower in Vietnam than in the other sites. In Vietnam and Peru, microscopy was closer to the "true" estimate than the other 2 tests while as expected ELISA, with its lower specificity, usually overestimated the prevalence., Conclusions: Bayesian methods are useful for analyzing prevalence results when no gold standard diagnostic test is available. Though some results are expected, e.g. PCR more sensitive than microscopy, a standardized and context-independent quantification of the diagnostic tests' characteristics (sensitivity and specificity) and the underlying malaria prevalence may be useful for comparing different sites. Indeed, the use of a single diagnostic technique could strongly bias the prevalence estimation. This limitation can be circumvented by using a Bayesian framework taking into account the imperfect characteristics of the currently available diagnostic tests. As discussed in the paper, this approach may further support global malaria burden estimation initiatives.