Epidemic spreading on spatial higher-order network.

Higher-order interactions exist widely in mobile populations and are extremely important in spreading epidemics, such as influenza. However, research on high-order interaction modeling of mobile crowds and the propagation dynamics above is still insufficient. Therefore, this study attempts to model and simulate higher-order interactions among mobile populations and explore their impact on epidemic transmission. This study simulated the spread of the epidemic in a spatial high-order network based on agent-based model modeling. It explored its propagation dynamics and the impact of spatial characteristics on it. Meanwhile, we construct state-specific rate equations based on the uniform mixing assumption for further analysis. We found that hysteresis loops are an inherent feature of high-order networks in this space under specific scenarios. The evolution curve roughly presents three different states with the initial value change, showing different levels of the endemic balance of low, medium, and high, respectively. Similarly, network snapshots and parameter diagrams also indicate these three types of equilibrium states. Populations in space naturally form components of different sizes and isolations, and higher initial seeds generate higher-order interactions in this spatial network, leading to higher infection densities. This phenomenon emphasizes the impact of high-order interactions and high-order infection rates in propagation. In addition, crowd density and movement speed act as protective and inhibitory factors for epidemic transmission, respectively, and depending on the degree of movement weaken or enhance the effect of hysteresis loops.

Airborne Influenza Virus in Daycare Centers.

In this study, we investigated the concentration of airborne influenza virus in daycare centers and influencing factors, such as common cold prevalence, air pollutants, and meteorological factors. A total of 209 air samples were collected from daycare centers in Kaohsiung and the influenza virus was analyzed using real-time quantitative polymerase chain reaction. Air pollutants and metrological factors were measured using real-time monitoring equipment. Winter had the highest positive rates of airborne influenza virus and the highest prevalence of the common cold, followed by summer and autumn. The concentration of CO was significantly positively correlated with airborne influenza virus. Daycare center A, with natural ventilation and air condition systems, had a higher concentration of airborne influenza A virus, airborne fungi, and airborne bacteria, as well as a higher prevalence of the common cold, than daycare center B, with a mechanical ventilation system and air purifiers, while the concentrations of CO2, CO, and UFPs in daycare center A were lower than those in daycare center B. We successfully detected airborne influenza virus in daycare centers, demonstrating that aerosol sampling for influenza can provide novel epidemiological insights and inform the management of influenza in daycare centers.

Molecular Markers and Mechanisms of Influenza A Virus Cross-Species Transmission and New Host Adaptation.

Influenza A viruses continue to be a serious health risk to people and result in a large-scale socio-economic loss. Avian influenza viruses typically do not replicate efficiently in mammals, but through the accumulation of mutations or genetic reassortment, they can overcome interspecies barriers, adapt to new hosts, and spread among them. Zoonotic influenza A viruses sporadically infect humans and exhibit limited human-to-human transmission. However, further adaptation of these viruses to humans may result in airborne transmissible viruses with pandemic potential. Therefore, we are beginning to understand genetic changes and mechanisms that may influence interspecific adaptation, cross-species transmission, and the pandemic potential of influenza A viruses. We also discuss the genetic and phenotypic traits associated with the airborne transmission of influenza A viruses in order to provide theoretical guidance for the surveillance of new strains with pandemic potential and the prevention of pandemics.

Potential pandemic risk of circulating swine H1N2 influenza viruses.

Influenza A viruses in swine have considerable genetic diversity and continue to pose a pandemic threat to humans due to a potential lack of population level immunity. Here we describe a pipeline to characterize and triage influenza viruses for their pandemic risk and examine the pandemic potential of two widespread swine origin viruses. Our analysis reveals that a panel of human sera collected from healthy adults in 2020 has no cross-reactive neutralizing antibodies against a α-H1 clade strain (α-swH1N2) but do against a γ-H1 clade strain. The α-swH1N2 virus replicates efficiently in human airway cultures and exhibits phenotypic signatures similar to the human H1N1 pandemic strain from 2009 (H1N1pdm09). Furthermore, α-swH1N2 is capable of efficient airborne transmission to both naïve ferrets and ferrets with prior seasonal influenza immunity. Ferrets with H1N1pdm09 pre-existing immunity show reduced α-swH1N2 viral shedding and less severe disease signs. Despite this, H1N1pdm09-immune ferrets that became infected via the air can still onward transmit α-swH1N2 with an efficiency of 50%. These results indicate that this α-swH1N2 strain has a higher pandemic potential, but a moderate level of impact since there is reduced replication fitness and pathology in animals with prior immunity.

Modeling the transmission mitigation impact of testing for infectious diseases.

A fundamental question of any program focused on the testing and timely diagnosis of a communicable disease is its effectiveness in reducing transmission. Here, we introduce testing effectiveness (TE)-the fraction by which testing and post-diagnosis isolation reduce transmission at the population scale-and a model that incorporates test specifications and usage, within-host pathogen dynamics, and human behaviors to estimate TE. Using TE to guide recommendations, we show that today's rapid diagnostics should be used immediately upon symptom onset to control influenza A and respiratory syncytial virus but delayed by up to two days to control omicron-era severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, while rapid tests are superior to reverse transcription quantitative polymerase chain reaction (RT-qPCR) to control founder-strain SARS-CoV-2, omicron-era changes in viral kinetics and rapid test sensitivity cause a reversal, with higher TE for RT-qPCR despite longer turnaround times. Last, we illustrate the model's flexibility by quantifying trade-offs in the use of post-diagnosis testing to shorten isolation times.

Editorial: Concerns as Highly Pathogenic Avian Influenza (HPAI) Virus of the H5N1 Subtype is Identified in Dairy Cows and Other Mammals.

Highly pathogenic avian influenza (HPAI) virus subtypes have been increasingly identified in poultry and wild birds since 2021. Between 2020-2023, 26 countries have reported that the H5N1 virus had infected more than 48 mammalian species. On 1 April 2024, a public health alert was issued in Texas when the first confirmed case of human infection with the H5N1 influenza virus was reported in a dairy worker. Cases of H5N1, clade 2.3.4.4b in dairy cows have been reported in several states in the US but were unexpected, even though H5N1 was previously identified in mammalian species, including cats, dogs, bears, foxes, tigers, coyotes, goats, and seals. On 29 April 2024, almost one month after the first reported cases of H5N1 infection in dairy cows, measures were to be implemented by the US Department of Agriculture (USDA) to prevent the progression of H5N1 viral transmission. This editorial summarizes what is currently known about the epidemiology, transmission, and surveillance of the HPAI virus of the H5N1 subtype in birds, mammals, and dairy cows, and why there are concerns regarding transmission to humans.

Does pasteurization inactivate bird flu virus in milk?

Recently, an outbreak of highly pathogenic avian influenza A (H5N1), which carries the clade 2.3.4.4b hemagglutinin (HA) gene and has been prevalent among North American bird populations since the winter of 2021, was reported in dairy cows in the United States. As of 24 May 2024, the virus has affected 63 dairy herds across nine states and has resulted in two human infections. The virus causes unusual symptoms in dairy cows, including an unexpected drop in milk production, and thick colostrum-like milk. Notably, The US Food and Drug Administration reported that around 20% of tested retail milk samples contained H5N1 viruses, with a higher percentage of positive results from regions with infected cattle herds. Data are scant regarding how effectively pasteurization inactivates the H5N1 virus in milk. Therefore, in this study, we evaluated the thermal stability of the H5 clade 2.3.4.4b viruses, along with one human H3N2 virus and other influenza subtype viruses, including H1, H3, H7, H9, and H10 subtype viruses. We also assessed the effectiveness of pasteurization in inactivating these viruses. We found that the avian H3 virus exhibits the highest thermal stability, whereas the H5N1 viruses that belong to clade 2.3.4.4b display moderate thermal stability. Importantly, our data provide direct evidence that the standard pasteurization methods used by dairy companies are effective in inactivating all tested subtypes of influenza viruses in raw milk. Our findings indicate that thermally pasteurized milk products do not pose a safety risk to consumers.

Avian Influenza outbreaks: Human infection risks for beach users - One health concern and environmental surveillance implications.

Despite its popularity for water activities, such as swimming, surfing, fishing, and rafting, inland and coastal bathing areas occasionally experience outbreaks of highly pathogenic avian influenza virus (HPAI), including A(H5N1) clade 2.3.4.4b. Asymptomatic infections and symptomatic outbreaks often impact many aquatic birds, which increase chances of spill-over events to mammals and pose concerns for public health. This review examined the existing literature to assess avian influenza virus (AIV) transmission risks to beachgoers and the general population. A comprehensive understanding of factors governing such crossing of the AIV host range is currently lacking. There is limited knowledge on key factors affecting risk, such as species-specific interactions with host cells (including binding, entry, and replication via viral proteins hemagglutinin, neuraminidase, nucleoprotein, and polymerase basic protein 2), overcoming host restrictions, and innate immune response. AIV efficiently transmits between birds and to some extent between marine scavenger mammals in aquatic environments via consumption of infected birds. However, the current literature lacks evidence of zoonotic AIV transmission via contact with the aquatic environment or consumption of contaminated water. The zoonotic transmission risk of the circulating A(H5N1) clade 2.3.4.4b virus to the general population and beachgoers is currently low. Nevertheless, it is recommended to avoid direct contact with sick or dead birds and to refrain from bathing in locations where mass bird mortalities are reported. Increasing reports of AIVs spilling over to non-human mammals have raised valid concerns about possible virus mutations that lead to crossing the species barrier and subsequent risk of human infections and outbreaks.

A simulation-based approach for estimating the time-dependent reproduction number from temporally aggregated disease incidence time series data.

Tracking pathogen transmissibility during infectious disease outbreaks is essential for assessing the effectiveness of public health measures and planning future control strategies. A key measure of transmissibility is the time-dependent reproduction number, which has been estimated in real-time during outbreaks of a range of pathogens from disease incidence time series data. While commonly used approaches for estimating the time-dependent reproduction number can be reliable when disease incidence is recorded frequently, such incidence data are often aggregated temporally (for example, numbers of cases may be reported weekly rather than daily). As we show, commonly used methods for estimating transmissibility can be unreliable when the timescale of transmission is shorter than the timescale of data recording. To address this, here we develop a simulation-based approach involving Approximate Bayesian Computation for estimating the time-dependent reproduction number from temporally aggregated disease incidence time series data. We first use a simulated dataset representative of a situation in which daily disease incidence data are unavailable and only weekly summary values are reported, demonstrating that our method provides accurate estimates of the time-dependent reproduction number under such circumstances. We then apply our method to two outbreak datasets consisting of weekly influenza case numbers in 2019-20 and 2022-23 in Wales (in the United Kingdom). Our simple-to-use approach will allow accurate estimates of time-dependent reproduction numbers to be obtained from temporally aggregated data during future infectious disease outbreaks.

Bird Flu Outbreak in Dairy Cows Is Widespread, Raising Public Health Concerns.

This Medical News article discusses the current H5N1 avian influenza outbreak in US dairy cattle and its implications for occupational and public health.

Markovian Approach for Exploring Competitive Diseases with Heterogeneity-Evidence from COVID-19 and Influenza in China.

Due to the complex interactions between multiple infectious diseases, the spreading of diseases in human bodies can vary when people are exposed to multiple sources of infection at the same time. Typically, there is heterogeneity in individuals' responses to diseases, and the transmission routes of different diseases also vary. Therefore, this paper proposes an SIS disease spreading model with individual heterogeneity and transmission route heterogeneity under the simultaneous action of two competitive infectious diseases. We derive the theoretical epidemic spreading threshold using quenched mean-field theory and perform numerical analysis under the Markovian method. Numerical results confirm the reliability of the theoretical threshold and show the inhibitory effect of the proportion of fully competitive individuals on epidemic spreading. The results also show that the diversity of disease transmission routes promotes disease spreading, and this effect gradually weakens when the epidemic spreading rate is high enough. Finally, we find a negative correlation between the theoretical spreading threshold and the average degree of the network. We demonstrate the practical application of the model by comparing simulation outputs to temporal trends of two competitive infectious diseases, COVID-19 and seasonal influenza in China.

Comparative Effectiveness of Baloxavir Marboxil and Oseltamivir Treatment in Reducing Household Transmission of Influenza: A Post Hoc Analysis of the BLOCKSTONE Trial.

BACKGROUND: The transmission of influenza virus in households, especially by children, is a major route of infection. Prior studies suggest that timely antiviral treatment of ill cases may reduce infection in household contacts. The aim of the study was to compare the effects of oseltamivir (OTV) and baloxavir marboxil (BXM) treatment of index cases on the secondary attack rate (SAR) of influenza within household. METHODS: A post hoc analysis was done in BLOCKSTONE trial-a placebo-controlled, double-blinded post-exposure prophylaxis of BXM. Data were derived from the laboratory-confirmed index cases' household contacts who received placebo in the trial and also from household members who did not participate in the trial but completed illness questionnaires. To assess the SAR of household members, multivariate analyses adjusted for factors including age, vaccination status, and household size were performed and compared between contacts of index cases treated with BXM or OTV. RESULTS: In total, 185 index cases (116 treated with BXM and 69 treated with OTV) and 410 household contacts (201 from trial, 209 by questionnaire) were included. The Poisson regression modeling showed that the SAR in household contacts of index cases treated with BXM and OTV was 10.8% and 18.5%, respectively; the adjusted relative reduction in SAR was 41.8% (95% confidence interval: 1.0%-65.7%, p = 0.0456) greater with BXM than OTV. Similar reductions were found in contacts from the trial and those included by questionnaire. CONCLUSION: BXM treatment of index cases appeared to result in a greater reduction in secondary household transmission than OTV treatment.

Ozone as an environmental driver of influenza.

Under long-standing threat of seasonal influenza outbreaks, it remains imperative to understand the drivers of influenza dynamics which can guide mitigation measures. While the role of absolute humidity and temperature is extensively studied, the possibility of ambient ozone (O3) as an environmental driver of influenza has received scant attention. Here, using state-level data in the USA during 2010-2015, we examined such research hypothesis. For rigorous causal inference by evidence triangulation, we applied 3 distinct methods for data analysis: Convergent Cross Mapping from state-space reconstruction theory, Peter-Clark-momentary-conditional-independence plus as graphical modeling algorithms, and regression-based Generalised Linear Model. The negative impact of ambient O3 on influenza activity at 1-week lag is consistently demonstrated by those 3 methods. With O3 commonly known as air pollutant, the novel findings here on the inhibition effect of O3 on influenza activity warrant further investigations to inform environmental management and public health protection.

Risk assessment of a highly pathogenic H5N1 influenza virus from mink.

Outbreaks of highly pathogenic H5N1 clade 2.3.4.4b viruses in farmed mink and seals combined with isolated human infections suggest these viruses pose a pandemic threat. To assess this threat, using the ferret model, we show an H5N1 isolate derived from mink transmits by direct contact to 75% of exposed ferrets and, in airborne transmission studies, the virus transmits to 37.5% of contacts. Sequence analyses show no mutations were associated with transmission. The H5N1 virus also has a low infectious dose and remains virulent at low doses. This isolate carries the adaptive mutation, PB2 T271A, and reversing this mutation reduces mortality and airborne transmission. This is the first report of a H5N1 clade 2.3.4.4b virus exhibiting direct contact and airborne transmissibility in ferrets. These data indicate heightened pandemic potential of the panzootic H5N1 viruses and emphasize the need for continued efforts to control outbreaks and monitor viral evolution.

Evaluating Seasonal Variations in Human Contact Patterns and Their Impact on the Transmission of Respiratory Infectious Diseases.

BACKGROUND: Human contact patterns are a key determinant driving the spread of respiratory infectious diseases. However, the relationship between contact patterns and seasonality as well as their possible association with the seasonality of respiratory diseases is yet to be clarified. METHODS: We investigated the association between temperature and human contact patterns using data collected through a cross-sectional diary-based contact survey in Shanghai, China, between December 24, 2017, and May 30, 2018. We then developed a compartmental model of influenza transmission informed by the derived seasonal trends in the number of contacts and validated it against A(H1N1)pdm09 influenza data collected in Shanghai during the same period. RESULTS: We identified a significant inverse relationship between the number of contacts and the seasonal temperature trend defined as a spline interpolation of temperature data (p = 0.003). We estimated an average of 16.4 (95% PrI: 15.1-17.5) contacts per day in December 2017 that increased to an average of 17.6 contacts (95% PrI: 16.5-19.3) in January 2018 and then declined to an average of 10.3 (95% PrI: 9.4-10.8) in May 2018. Estimates of influenza incidence obtained by the compartmental model comply with the observed epidemiological data. The reproduction number was estimated to increase from 1.24 (95% CI: 1.21-1.27) in December to a peak of 1.34 (95% CI: 1.31-1.37) in January. The estimated median infection attack rate at the end of the season was 27.4% (95% CI: 23.7-30.5%). CONCLUSIONS: Our findings support a relationship between temperature and contact patterns, which can contribute to deepen the understanding of the relationship between social interactions and the epidemiology of respiratory infectious diseases.

Diet-induced obesity affects influenza disease severity and transmission dynamics in ferrets.

Obesity, and the associated metabolic syndrome, is a risk factor for increased disease severity with a variety of infectious agents, including influenza virus. Yet, the mechanisms are only partially understood. As the number of people, particularly children, living with obesity continues to rise, it is critical to understand the role of host status on disease pathogenesis. In these studies, we use a diet-induced obese ferret model and tools to demonstrate that, like humans, obesity resulted in notable changes to the lung microenvironment, leading to increased clinical disease and viral spread to the lower respiratory tract. The decreased antiviral responses also resulted in obese animals shedding higher infectious virus for a longer period, making them more likely to transmit to contacts. These data suggest that the obese ferret model may be crucial to understanding obesity's impact on influenza disease severity and community transmission and a key tool for therapeutic and intervention development for this high-risk population.

Bat-borne H9N2 influenza virus evades MxA restriction and exhibits efficient replication and transmission in ferrets.

Influenza A viruses (IAVs) of subtype H9N2 have reached an endemic stage in poultry farms in the Middle East and Asia. As a result, human infections with avian H9N2 viruses have been increasingly reported. In 2017, an H9N2 virus was isolated for the first time from Egyptian fruit bats (Rousettus aegyptiacus). Phylogenetic analyses revealed that bat H9N2 is descended from a common ancestor dating back centuries ago. However, the H9 and N2 sequences appear to be genetically similar to current avian IAVs, suggesting recent reassortment events. These observations raise the question of the zoonotic potential of the mammal-adapted bat H9N2. Here, we investigate the infection and transmission potential of bat H9N2 in vitro and in vivo, the ability to overcome the antiviral activity of the human MxA protein, and the presence of N2-specific cross-reactive antibodies in human sera. We show that bat H9N2 has high replication and transmission potential in ferrets, efficiently infects human lung explant cultures, and is able to evade antiviral inhibition by MxA in transgenic B6 mice. Together with its low antigenic similarity to the N2 of seasonal human strains, bat H9N2 fulfils key criteria for pre-pandemic IAVs.

The airborne transmission of viruses causes tight transmission bottlenecks.

The transmission bottleneck describes the number of viral particles that initiate an infection in a new host. Previous studies have used genome sequence data to suggest that transmission bottlenecks for influenza and SARS-CoV-2 involve few viral particles, but the general principles of virus transmission are not fully understood. Here we show that, across a broad range of circumstances, tight transmission bottlenecks are a simple consequence of the physical process of airborne viral transmission. We use mathematical modelling to describe the physical process of the emission and inhalation of infectious particles, deriving the result that that the great majority of transmission bottlenecks involve few viral particles. While exceptions to this rule exist, the circumstances needed to create these exceptions are likely very rare. We thus provide a physical explanation for previous inferences of bottleneck size, while predicting that tight transmission bottlenecks prevail more generally in respiratory virus transmission.