Novel reassortant H5N5 viruses bind to a human-type receptor as a factor in pandemic risk

A Stochastic SEIRS Epidemic Model with Infection Forces and Intervention Strategies

The spread of epidemics has been extensively investigated using susceptible-exposed infectious-recovered-susceptible (SEIRS) models. In this work, we propose a SEIRS pandemic model with infection forces and intervention strategies. The proposed model is characterized by a stochastic differential equation (SDE) framework with arbitrary parameter settings. Based on a Markov semigroup hypothesis, we demonstrate the effect of the proliferation number R 0 S on the SDE solution. On the one hand, when R 0 S < 1, the SDE has an illness-free solution set under gentle additional conditions. This implies that the epidemic can be eliminated with a likelihood of 1. On the other hand, when R 0 S > 1, the SDE has an endemic stationary circulation under mild additional conditions. This prompts the stochastic regeneration of the epidemic. Also, we show that arbitrary fluctuations can reduce the infection outbreak. Hence, valuable procedures can be created to manage and control epidemics.

The Emergence and Decennary Distribution of Clade 2.3.4.4 HPAI H5Nx

Reassortment events among influenza viruses occur naturally and may lead to the development of new and different subtypes which often ignite the possibility of an influenza outbreak. Between 2008 and 2010, highly pathogenic avian influenza (HPAI) H5 of the N1 subtype from the A/goose/Guangdong/1/96-like (Gs/GD) lineage generated novel reassortants by introducing other neuraminidase (NA) subtypes reported to cause most outbreaks in poultry. With the extensive divergence of the H5 hemagglutinin (HA) sequences of documented viruses, the WHO/FAO/OIE H5 Evolutionary Working Group clustered these viruses into a systematic and unified nomenclature of clade 2.3.4.4 currently known as “H5Nx” viruses. The rapid emergence and circulation of these viruses, namely, H5N2, H5N3, H5N5, H5N6, H5N8, and the regenerated H5N1, are of great concern based on their pandemic potential. Knowing the evolution and emergence of these novel reassortants helps to better understand their complex nature. The eruption of reports of each H5Nx reassortant through time demonstrates that it could persist beyond its usual seasonal activity, intensifying the possibility of these emerging viruses’ pandemic potential. This review paper provides an overview of the emergence of each novel HPAI H5Nx virus as well as its current epidemiological distribution.

The T160A hemagglutinin substitution affects not only receptor binding property but also transmissibility of H5N1 clade 2.3.4 avian influenza virus in guinea pigs

We generated and characterized site-directed HA mutants on the genetic backbone of H5N1 clade 2.3.4 virus preferentially binding to α-2,3 receptors in order to identify the key determinants in hemagglutinin rendering the dual affinity to both α-2,3 (avian-type) and α-2,6 (human-type) linked sialic acid receptors of the current clade 2.3.4.4 H5NX subtype avian influenza reassortants. The results show that the T160A substitution resulted in the loss of a glycosylation site at 158N and led not only to enhanced binding specificity for human-type receptors but also transmissibility among guinea pigs, which could be considered as an important molecular marker for assessing pandemic potential of H5 subtype avian influenza isolates.

Viral factors in influenza pandemic risk assessment

The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk.

Artificial infectious disease optimization: A SEIQR epidemic dynamic model-based function optimization algorithm

To solve some complicated function optimization problems, an artificial infectious disease optimization algorithm based on the SEIQR epidemic model is constructed, it is called as the SEIQR algorithm, or SEIQRA in short. The algorithm supposes that some human individuals exist in an ecosystem; each individual is characterized by a number of features; an infectious disease (SARS) exists in the ecosystem and spreads among individuals, the disease attacks only a part of features of an individual. Each infected individual may pass through such states as susceptibility (S), exposure (E), infection (I), quarantine (Q) and recovery (R). State S, E, I, Q and R can automatically and dynamically divide all people in the ecosystem into five classes, it provides the diversity for SEIQRA; that people can be attacked by the infectious disease and then transfer it to other people can cause information exchange among people, information exchange can make a person to transit from one state to another; state transitions can be transformed into operators of SEIQRA; the algorithm has 13 legal state transitions, which corresponds to 13 operators; the transmission rules of the infectious disease among people is just the logic to control state transitions of individuals among S, E, I, Q and R, it is just the synergy of SEIQRA, the synergy can be transformed into the logic structure of the algorithm. The 13 operators in the algorithm provide a native opportunity to integrate many operations with different purposes; these operations include average, differential, expansion, chevy, reflection and crossover. The 13 operators are executed equi-probably; a stable heart rhythm of the algorithm is realized. Because the infectious disease can only attack a small part of organs of a person when it spreads among people, the part variables iteration strategy (PVI) can be ingeniously applied, thus enabling the algorithm to possess of high performance of computation, high suitability for solving some kinds of complicated optimization problems, especially high dimensional optimization problems. Results show that SEIQRA has characteristics of strong search capability and global convergence, and has a high convergence speed for some complicated functions optimization problems.

Development of Disease-specific, Context-specific Surveillance Models: Avian Influenza (H5N1)-Related Risks and Behaviours in African Countries

Avian influenza virus (H5N1) is a rapidly disseminating infection that affects poultry and, potentially, humans. Because the avian virus has already adapted to several mammalian species, decreasing the rate of avian-mammalian contacts is critical to diminish the chances of a total adaptation of H5N1 to humans. To prevent the pandemic such adaptation could facilitate, a biology-specific disease surveillance model is needed, which should also consider geographical and socio-cultural factors. Here, we conceptualized a surveillance model meant to capture H5N1-related biological and cultural aspects, which included food processing, trade and cooking-related practices, as well as incentives (or disincentives) for desirable behaviours. This proof of concept was tested with data collected from 378 Egyptian and Nigerian sites (local [backyard] producers/live bird markets/village abattoirs/commercial abattoirs and veterinary agencies). Findings revealed numerous opportunities for pathogens to disseminate, as well as lack of incentives to adopt preventive measures, and factors that promoted epidemic dissemination. Supporting such observations, the estimated risk for H5N1-related human mortality was higher than previously reported. The need for multidimensional disease surveillance models, which may detect risks at higher levels than models that only measure one factor or outcome, was supported. To develop efficient surveillance systems, interactions should be captured, which include but exceed biological factors. This low-cost and easily implementable model, if conducted over time, may identify focal instances where tailored policies may diminish both endemicity and the total adaptation of H5N1 to the human species.