Global public health security is both a collective aspiration and a mutual responsibility that demands cooperative action at all levels. The expansion of the current H5N1 avian influenza enzootic and its incursion into human health presents a real and significant threat of an influenza pandemic. The world has for the first time an unprecedented opportunity for pandemic preparation. Current global efforts to tackle the H5N1 pandemic threat are centred around the framework of the International Health Regulations (2005) that requires countries to openly share disease intelligence including clinical samples, viruses and epidemiological information. Present international initiatives also seek to establish more equitable allocation and sharing mechanisms for developing countries, of therapeutic resources, public health interventions and other broad-based support in the event of a pandemic. To be sustainable, country preparatory efforts need to be integrated within wider national emergency preparedness frameworks and emphasise the strengthening of basic capacities in disease surveillance, outbreak response and health systems that can respond to a range of public health emergencies. Such capacity building represents permanent investments in health that will have enduring benefits beyond a pandemic. Preparations must also go beyond the health sector; greater promotion of intersectoral cooperation and an adoption of a whole-of-society approach to preparation is recommended. Broad collaboration is vital in addressing the complex challenge posed by influenza to our collective security.
Animals ; Birds ; Communicable Disease Control ; methods ; Global Health ; Health Planning ; Humans ; Influenza A Virus, H5N1 Subtype ; isolation & purification ; Influenza in Birds ; epidemiology ; virology ; Public Health

Background: The PLASMIC score is a convenient tool for predicting ADAMTS13 activity of ＜10%.Lactate dehydrogenase (LDH) is widely used as a marker of haemolysis in thrombotic thrombocytopenic purpura (TTP) monitoring, and could be used as a replacement marker for lysis. We aimed to validate the PLASMIC score in a multi-centre Asia Pacific region, and to explore whether LDH could be used as a replacement marker for lysis. Methods: Records of patients with thrombotic microangiopathy (TMA) were reviewed. Patients’ ADAMTS13 activity levels were obtained, along with clinical/laboratory findings relevant to the PLASMIC score. Both PLASMIC scores and PLASMIC-LDH scores, in which LDH replaced traditional lysis markers, were calculated. We generated a receiver operator characteristics (ROC) curve and compared the area under the curve values (AUC) to determine the predictive ability of each score. Results: 46 patients fulfilled the inclusion criteria, of which 34 had ADAMTS13 activity levels of ＜10%. When the patients were divided into intermediate-to-high risk (scores 5‒7) and low risk (scores 0‒4), the PLASMIC score showed a sensitivity of 97.1% and specificity of 58.3%, with a positive predictive value (PPV) of 86.8% and negative predictive value (NPV) of 87.5%. The PLASMIC-LDH score had a sensitivity of 97.1% and specificity of 33.3%, with a PPV of 80.5% and NPV of 80.0%. Conclusion Our study validated the utility of the PLASMIC score, and demonstrated PLASMIC-LDH as a reasonable alternative in the absence of traditional lysis markers, to help identify high-risk patients for treatment via plasma exchange.

Objective: Circulation patterns of influenza and other respiratory viruses have been globally disrupted since the emergence of coronavirus disease (COVID-19) and the introduction of public health and social measures (PHSMs) aimed at reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Methods: We reviewed respiratory virus laboratory data, Google mobility data and PHSMs in five geographically diverse regions in Australia and New Zealand. We also described respiratory virus activity from January 2017 to August 2021. Results: We observed a change in the prevalence of circulating respiratory viruses following the emergence of SARS-CoV-2 in early 2020. Influenza activity levels were very low in all regions, lower than those recorded in 2017–2019, with less than 1% of laboratory samples testing positive for influenza virus. In contrast, rates of human rhinovirus infection were increased. Respiratory syncytial virus (RSV) activity was delayed; however, once it returned, most regions experienced activity levels well above those seen in 2017–2019. The timing of the resurgence in the circulation of both rhinovirus and RSV differed within and between the two countries. Discussion: The findings of this study suggest that as domestic and international borders are opened up and other COVID-19 PHSMs are lifted, clinicians and public health professionals should be prepared for resurgences in influenza and other respiratory viruses. Recent patterns in RSV activity suggest that these resurgences in non-COVID-19 viruses have the potential to occur out of season and with increased impact.

Proteases are enzymes that cleave and hydrolyse the peptide bonds between two specific amino acid residues of target substrate proteins. Protease-controlled proteolysis plays a key role in the degradation and recycling of proteins, which is essential for various physiological processes. Thus, solving the substrate identification problem will have important implications for the precise understanding of functions and physiological roles of proteases, as well as for therapeutic target identification and pharmaceutical applicability. Consequently, there is a great demand for bioinformatics methods that can predict novel substrate cleavage events with high accuracy by utilizing both sequence and structural information. In this study, we present Procleave, a novel bioinformatics approach for predicting protease-specific substrates and specific cleavage sites by taking into account both their sequence and 3D structural information. Structural features of known cleavage sites were represented by discrete values using a LOWESS data-smoothing optimization method, which turned out to be critical for the performance of Procleave. The optimal approximations of all structural parameter values were encoded in a conditional random field (CRF) computational framework, alongside sequence and chemical group-based features. Here, we demonstrate the outstanding performance of Procleave through extensive benchmarking and independent tests. Procleave is capable of correctly identifying most cleavage sites in the case study. Importantly, when applied to the human structural proteome encompassing 17,628 protein structures, Procleave suggests a number of potential novel target substrates and their corresponding cleavage sites of different proteases. Procleave is implemented as a webserver and is freely accessible at http://procleave.erc.monash.edu/.