Avian influenza is one of the largest known threats to domestic poultry. Influenza outbreaks on poultry farms typically lead to the complete slaughter of the entire domestic bird population, causing severe economic losses worldwide. Moreover, there are highly pathogenic avian influenza (HPAI) strains that are able to infect the swine or human population in addition to their primary avian host and, as such, have the potential of being a global zoonotic and pandemic threat. Migratory birds, especially waterfowl, are a natural reservoir of the avian influenza virus; they carry and exchange different virus strains along their migration routes, leading to antigenic drift and antigenic shift, which results in the emergence of novel HPAI viruses. This requires monitoring over time and in different locations to allow for the upkeep of relevant knowledge on avian influenza virus evolution and the prevention of novel epizootic and epidemic outbreaks. In this review, we assess the role of migratory birds in the spread and introduction of influenza strains on a global level, based on recent data. Our analysis sheds light on the details of viral dissemination linked to avian migration, the viral exchange between migratory waterfowl and domestic poultry, virus ecology in general, and viral evolution as a process tightly linked to bird migration. We also provide insight into methods used to detect and quantify avian influenza in the wild. This review may be beneficial for the influenza research community and may pave the way to novel strategies of avian influenza and HPAI zoonosis outbreak monitoring and prevention.

Field diagnostic tools for avian influenza (AI) are indispensable for the prevention and controlled management of highly pathogenic AI-related diseases. More accurate, faster and networked on-site monitoring is demanded to detect such AI viruses with high sensitivity as well as to maintain up-to-date information about their geographical transmission. In this work, we assessed the clinical and field-level performance of a smartphone-based fluorescent diagnostic device with an efficient reflective light collection module using a coumarin-derived dendrimer-based fluorescent lateral flow immunoassay. By application of an optimized bioconjugate, a smartphone-based diagnostic device had a two-fold higher detectability as compared to that of the table-top fluorescence strip reader for three different AI subtypes (H5N3, H7N1, and H9N2). Additionally, in a clinical study of H5N1-confirmed patients, the smartphone-based diagnostic device showed a sensitivity of 96.55% (28/29) [95% confidence interval (CI): 82.24 to 99.91] and a specificity of 98.55% (68/69) (95% CI: 92.19 to 99.96). The measurement results from the distributed individual smartphones were wirelessly transmitted via short messaging service and collected by a centralized database system for further information processing and data mining. Smartphone-based diagnosis provided highly sensitive measurement results for H5N1 detection within 15 minutes. Because of its high sensitivity, portability and automatic reporting feature, the proposed device will enable agile identification of patients and efficient control of AI dissemination.

The development of a sensitive and rapid diagnostic test is needed for early detection of avian influenza (AI) H7 subtype. In this study, novel monoclonal antibodies (mAbs) against influenza A H7N9 recombinant hemagglutinin (rHA)1 were developed and applied to a Europium nanoparticle–based rapid fluorescent immunochromatographic strip test (FICT) to improve the sensitivity of the rapid diagnostic system. Two antibodies (2F4 and 6D7) exhibited H7 subtype specificity in a dot-FICT assay by optimization of the conjugate and the pH of the lysis buffer. The subtype specificity was confirmed by an immunofluorescence assay and Western blot analysis. The limit of detection of the FICT employing novel mAbs 31 ng/mL for H7N9 rHA1 and 40 hemagglutination units/mL for H7 subtype virus. Sensitivity was improved 25-fold using Europium as confirmed by comparison of colloidal gold-based rapid diagnostic kit using the 2F4 and 6D7 mAbs.

Accurate and rapid diagnosis of highly pathogenic avian influenza A H5N1 is of critical importance for the effective clinical management of patients. Here, we developed a rapid and simultaneous detection toolkit for influenza A H5 subtype viruses in human samples based on a bioconjugate of quantum dots (QDs) assembly and a smartphone-based rapid dual fluorescent diagnostic system (SRDFDS).

The widespread emergence of anti-malarial drug resistance has necessitated the discovery of novel anti-malarial drug candidates. In this study, chloroquine derivatives were evaluated for the improved anti-malarial activity. Novel two derivatives (SKM13 and SKM14) were synthesized based on the chloroquine (CQ) template containing modified side chains such as α,β-unsaturated amides and phenylmethyl group. The selective index indicated that SKM13 was 1.28-fold more effective than CQ against the CQ-resistant strain Plasmodium falciparum. An in vivo mouse study demonstrated that SKM13 (20 mg/kg) could completely inhibit Plasmodium berghei growth in blood and increased the survival rate from 40 to 100% at 12 days after infection. Haematological parameters [red blood cell (RBC) count, haemoglobin level, and haematocrit level] were observed as an indication of clinical malarial anaemia during an evaluation of the efficacy of SKM13 in a 4-day suppression test. An in vivo study showed a decrease of greater than 70% in the number of RBC in P. berghei-infected mice over 12 days, but the SKM13 (20 mg/kg)-treated group showed no loss of RBC. CQ derivatives with substituents such as α,β-unsaturated amides and phenylmethyl group have enhanced anti-malarial activity against the CQ-resistant strain P. falciparum, and SKM13 is an excellent anti-malarial drug candidate in mice model.