Correction: Influenza A H5N1 and H7N9 in China: A spatial risk analysis

Evaluation of Pre-Pandemic Trivalent COBRA HA Vaccine in Mice Pre-Immune to Historical H1N1 and H3N2 Influenza Viruses

Initial exposure to influenza virus(es) during early childhood produces protective antibodies that may be recalled following future exposure to subsequent viral infections or vaccinations. Most influenza vaccine research studies use immunologically naïve animal models to assess vaccine effectiveness. However, most people have an extensive influenza immune history, with memory cells produced by viruses or vaccines representing multiple influenza viruses. In this study, we explored the effect influenza seasonal virus-induced immunity has on pre-pandemic influenza virus vaccination. The mice that were pre-immune to historical H1N1 and H3N2 seasonal influenza viruses were vaccinated with adjuvanted pre-pandemic (H2, H5, and H7) HA-based computationally optimized broadly reactive antigen (COBRA) vaccines, and were fully protected from lethal challenge, whereas the mock-vaccinated mice, with or without pre-immunity, were not protected from morbidity or mortality. Detectable antibody titers were present in the pre-immune mice vaccinated with a single dose of vaccine, but not in the immunologically naïve mice. The mice vaccinated twice with the trivalent COBRA HA vaccine had similar antibody titers regardless of their pre-immune status. Overall, seasonal pre-immunity did not interfere with the immune responses elicited by pre-pandemic COBRA HA vaccines or the protection against pre-pandemic viruses.

A Study on a Neural Network Risk Simulation Model Construction for Avian Influenza A (H7N9) Outbreaks in Humans in China during 2013-2017

The main purposes of this study were to explore the spatial distribution characteristics of H7N9 human infections during 2013-2017, and to construct a neural network risk simulation model of H7N9 outbreaks in China and evaluate their effects. First, ArcGIS 10.6 was used for spatial autocorrelation analysis, and cluster patterns ofH7N9 outbreaks were analyzed in China during 2013-2017 to detect outbreaks' hotspots. During the study period, the incidence of H7N9 outbreaks in China was high in the eastern and southeastern coastal areas of China, with a tendency to spread to the central region. Moran's I values of global spatial autocorrelation of H7N9 outbreaks in China from 2013 to 2017 were 0.080128, 0.073792, 0.138015, 0.139221 and 0.050739, respectively (p < 0.05) indicating a statistically significant positive correlation of the epidemic. Then, SPSS 20.0 was used to analyze the correlation between H7N9 outbreaks in China and population, livestock production, the distance between the case and rivers, poultry farming, poultry market, vegetation index, etc. Statistically significant influencing factors screened out by correlation analysis were population of the city, average vegetation of the city, and the distance between the case and rivers (p < 0.05), which were included in the neural network risk simulation model of H7N9 outbreaks in China. The simulation accuracy of the neural network risk simulation model of H7N9 outbreaks in China from 2013 to 2017 were 85.71%, 91.25%, 91.54%, 90.49% and 92.74%, and the AUC were 0.903, 0.976, 0.967, 0.963 and 0.970, respectively, showing a good simulation effect of H7N9 epidemics in China. The innovation of this study lies in the epidemiological study of H7N9 outbreaks by using a variety of technical means, and the construction of a neural network risk simulation model of H7N9 outbreaks in China. This study could provide valuable references for the prevention and control of H7N9 outbreaks in China.

Effects of Receptor Specificity and Conformational Stability of Influenza A Virus Hemagglutinin on Infection and Activation of Different Cell Types in Human PBMCs

Humans can be infected by zoonotic avian, pandemic and seasonal influenza A viruses (IAVs), which differ by receptor specificity and conformational stability of their envelope glycoprotein hemagglutinin (HA). It was shown that receptor specificity of the HA determines the tropism of IAVs to human airway epithelial cells, the primary target of IAVs in humans. Less is known about potential effects of the HA properties on viral attachment, infection and activation of human immune cells. To address this question, we studied the infection of total human peripheral blood mononuclear cells (PBMCs) and subpopulations of human PBMCs with well characterized recombinant IAVs differing by the HA and the neuraminidase (NA) but sharing all other viral proteins. Monocytes and all subpopulations of lymphocytes were significantly less susceptible to infection by IAVs with avian-like receptor specificity as compared to human-like IAVs, whereas plasmacytoid dendritic cells (pDCs) and myeloid dendritic cells were equally susceptible to IAVs with avian-like and human-like receptor specificity. This tropism correlated with the surface expression of 2-3-linked sialic acids (avian-type receptors) and 2-6-linked sialic acids (human-type receptors). Despite a reduced infectivity of avian-like IAVs for PBMCs, these viruses were not less efficient than human-like IAVs in terms of cell activation as judged by the induction of cellular mRNA of IFN-α, CCL5, RIG-I, and IL-6. Elevated levels of IFN-α mRNA were accompanied by elevated IFN-α protein secretion in primary human pDC. We found that high basal expression in monocytes of antiviral interferon-induced transmembrane protein 3 (IFITM3) limited viral infection in these cells. siRNA-mediated knockdown of IFITM3 in monocytes demonstrated that viral sensitivity to inhibition by IFITM3 correlated with the conformational stability of the HA. Our study provides new insights into the role of host- and strain-specific differences of HA in the interaction of IAVs with human immune cells and advances current understanding of the mechanisms of viral cell tropism, pathogenesis and markers of virulence.

Geospatial modelling to estimate the territory at risk of establishment of influenza type A in Mexico - An ecological study

The aim of this study was to estimate the territory at risk of establishment of influenza type A (EOITA) in Mexico, using geospatial models. A spatial database of 1973 outbreaks of influenza worldwide was used to develop risk models accounting for natural (natural threat), anthropic (man-made) and environmental (combination of the above) transmission. Then, a virus establishment risk model; an introduction model of influenza A developed in another study; and the three models mentioned were utilized using multi-criteria spatial evaluation supported by geographically weighted regression (GWR), receiver operating characteristic analysis and Moran's I. The results show that environmental risk was concentrated along the Gulf and Pacific coasts, the Yucatan Peninsula and southern Baja California. The identified risk for EOITA in Mexico were: 15.6% and 4.8%, by natural and anthropic risk, respectively, while 18.5% presented simultaneous environmental, natural and anthropic risk. Overall, 28.1% of localities in Mexico presented a High/High risk for the establishment of influenza type A (area under the curve=0.923, P<0.001; GWR, r2=0.840, P<0.001; Moran's I =0.79, P<0.001). Hence, these geospatial models were able to robustly estimate those areas susceptible to EOITA, where the results obtained show the relation between the geographical area and the different effects on health. The information obtained should help devising and directing strategies leading to efficient prevention and sound administration of both human and financial resources.