National and international efforts to enhance early disease detection and to increase diagnostic capacity have stimulated the formation of laboratory networks within and between public, animal, and even plant health areas. The success of these laboratory networks can be attributed to the implementation of standardized procedures and assays, specific training programs as well as a demonstrated proficiency samples. So far, avian influenza surveillance networks have formed for performance in many countries [1, 2]. Highly pathogenic avian influenza virus (HPAIV) H5N1 continues to pose a significant threat to human health [3, 4], although it remains a zoonotic infection [5, 6]. A surveillance network with strong detection capability is required to detect any evidence that the virus has acquired the ability to transmit between humans or to emerge as the next pandemic strain.

The Chinese influenza surveillance scheme aims to reduce the burden of disease associated with influenza in China by collecting and exchanging timely information on influenza activity. It provides relevant information about influenza to health professionals and the general public, and contributes to the annual determination of the influenza vaccine content and to Chinese influenza pandemic preparedness activities. Compared with seasonal influenza surveillance in China, Chinese avian influenza surveillance networks have an independent infrastructure and information flow (Figure 1). Chinese national influenza centre (CNIC), that was established in 1957 and was designed as the 5^th WHO collaborating centre (WHO-CC) for reference and research of influenza in 2009 [7], would perform final confirmation for each suspected case in mainland China. The local laboratories of Chinese avian influenza surveillance networks could need more experiences in laboratory activities in addition to following reasons: So far, avian influenza H5N1 viruses isolated from human still are highly pathogenic [8, 9]; Documented studies suggested that the virus has potent ability of human-to-human transmission [10], and the pandemic threat from highly pathogenic avian influenza viruses (HPAIV) H5N1 has not been diminished [11, 12].

It is common knowledge that reliable detection techniques are necessary for influenza surveillance. Conventional methods for the detection of influenza viruses are virus isolation through inoculating samples into embryonated hen egg or by cell culture, and following to do HA and/or NA subtyping by serological methods (e.g., hemagglutinin inhibition (HI) assay). However, it should be a big limitation to emergency cases happened since an incubation period up to 1-2 weeks is often needed to achieve the subtype information later [13], and not all network laboratories meet the certificated requirements for HPAIV isolation. Molecular methods, specifically nucleic acid assay methods such as RT-PCR and rRT-PCR with high sensitivity and specificity have had indispensable effect on laboratory rapid diagnosis of HPAIV. So far, almost all influenza networks in China have developed and applied PCR detection system. However, PCR as a diagnostic tool requires a high degree of technological expertise including operation skill and procedure, environment support in addition to primers/probes and reagents. Therefore, quality control assessment (QCA) will be required to assess network performance. In this study, we developed a quality control panel for avian influenza A (H5N1) RT-PCR and rRT-PCR, and used the panel to implement assessment on avian influenza laboratories of local CDC from China's Provinces, Autonomous Regions & Municipalities.

QCA studies for laboratory diagnostics of avian influenza virus help to monitor the quality of service of the participating centers, to highlight problems in particular tests or specific laboratories, and to give assurance to those centers that perform well. The objective of the QCA task group are: (i) to organize QCAs; (ii) to prepare and distribute quality control panels; (iii) to analyze and report the results; and (iv)to organize follow-up help [18]. In this study, we developed a quality control panel of RT-PCR and rRT-PCR for avian influenza A (H5N1) surveillance networks in mainland China. The panel with relatively high stability and good reproducibility was used to implement assessment of avian influenza virus detection in 30 local CDC's lab from China's Provinces, Autonomous Regions & Municipalities. The results suggested that more than 90% Chinese local influenza labs have good capability to perform detection and identification of avian influenza virus H5N1 by RT-PCR and/or rRT-PCR.

The developed quality control panel included the samples for assessment of the specificity, sensitivity and reproducibility. RT-PCR or rRT-PCR have played very important role and have been extensively used in infectious diseases surveillance, especially in emergency diseases because of their good specificity, high sensitivity and quick results. However, it is not uncommon to presenting false positive or false negative results if technological operation or lab environment is not qualified [19–23]. In the present study, the developed quality control panel included samples for assessment of sensitivity, specificity and reproducibility. We designed the panel that included a series of diluted H5N1 virus lysates and in vitro transcribed H5 HA RNA for sensitivity assessment, and seasonal influenza (H1N1, H3N2 and FluB) for cross-specific detection. Known negative samples and an artificial gene RNA were also integrated into the panel for assessment of cross contamination. Additionally, the panel included duplicate samples for assessment of self-reproducibility.

The panel is relatively stability with high reproducibility. Individual, full interpreted, concise and informative reports should be the standard practice when QCA is implemented in networks [24, 25]. It is common that RNA samples easily degenerate if involving undependable processing. Therefore the stability and reproducibility of the panel is very important in implementation of panel. In present study, we performed 3 different treatments on the panel. Firstly, to simulate keeping condition and the amount of time needed in the transportation via FedEx, the panel was placed in an ice box for four days. The second treatment consisted of keeping the panel in an ice box for four days then storing at -80°C for three days. This condition was designed to evaluate the effects of samples being delivered and stored over the weekend when processing is unavailable. The final treatment was keeping the panel at 4°C for two weeks to assess unpredictable variation when the panel was implemented. In comparison to the normal storage condition of -80°C, the results suggested that no obvious affection happened on the three treatments as shown by very good CCIA. Additionally, the panel presented very high reproducibility as demonstrated by very good CCIA between different technicians, PCR machines and laboratories.

There were a relatively low number of discrepancies for both concise and reproducibility in this QCA exercise in Chinese avian influenza virus networks. In this implement of QCA, 2/29 laboratories presented fair or moderate rRT-PCR identification for the sample in the developed quality control panel. And 5/29 laboratories presented poor, fair or moderate reproducibility in excise of quality control panel. However, quality assessment is an educational exercise, not a punitive action; its aim is to assist laboratories in their continuous effort towards a higher quality services as we communicated with local labs before the implementation of assessment. Therefore, it was rather discouraging that those laboratories with inaccurate sizing results did not participate the following years. To be opposite, in this quality control exercise, these laboratories participated a specific training for the diagnosis of the avian influenza virus H5N1 after the QCA. In addition, to our knowledge, it is very difficult to develop a standard cut-off value on rRT-PCR. Professional experience should play important role on the dispose of results, especially, when the high Ct value was present. Besides, rRT-PCR should be fluctuated easier than RT-PCR as general knowledge mentioned. To get together, it should be used to explain why the RT-PCR has better CCIA in both cross concordance and self-reproducibility than rRT-PCR in the implement of QCA.

We cannot know if the QCA results reflected the true practices in diagnosis of avian influenza A (H5N1). QCA is voluntary and might be biased towards better performing laboratories as strongly recommended. Besides, QCA samples are always treated by the same way as routine referrals. However, many laboratories have never attributed the large samples or enrolled in the daily sample pool. Thus, the error rates found could still be overestimated on true laboratory performance.

We developed a quality control panel of RT-PCR and rRT-PCR for avian influenza virus H5N1 surveillance. The panel showed relatively good stability and high reproducibility which is possible for the implement of the panel. An availably statistical data, which are used to assess the detection capability of net works on avian influenza virus (H5N1), can be obtained relatively easily through implementation of the panel on networks.