ETIDIOH - NEW

  Highlights •  Epidemiological parameters differ by pathogen and by setting. •  Unsupervised machine learning classifies pathogens into distinct epidemiological archetypes. •  Pathogens can be allocated into defined groups outlining plausible parameter ranges across epidemiologically similar pathogens. Abstract Introduction In the light of the COVID-19 pandemic many countries are trying to widen their pandemic planning from its traditional focus on influenza . However, it is impossible to draw up detailed plans for every pathogen with epidemic potential. We set out to try to simplify this process by reviewing the epidemiology of a range of pathogens with pandemic potential and seeing whether they fall into groups with shared epidemiological traits. Methods We reviewed the epidemiological characteristics of 19 different pathogens with pandemic potential (those on the WHO priority list of pathogens, different strains of influenza and Mpox). We extracted data on key pa...

  Abstract Highly pathogenic avian influenza (HPAI) represents a threat to animal and human health, with the ongoing H5N1 outbreak within the H5 2.3.4.4b clade being one of the largest on record . However, it remains unclear what factors have contributed to its intercontinental spread . We use Bayesian additive regression trees , a machine learning method designed for probabilistic modelling of complex nonlinear phenomena , to construct species distribution models (SDMs) for HPAI clade 2.3.4.4b presence. We identify factors driving geospatial patterns of infection and project risk distributions across Europe . Our models are time-stratified to capture both seasonal changes in risk and shifts in epidemiology associated with the succession of H5N6/H5N8 by H5N1 within the clade . While previous studies aimed to model HPAI presence from physical geography, we explicitly consider wild bird ecology by including estimates of bird species richness, abundance of specific taxa, and “abundanc...

  Summary Background The first chikungunya virus (CHIKV) vaccine is now licensed in Brazil, the country that reports the most cases of CHIKV globally ; however, the optimal use of the vaccine remains unclear owing to a poor understanding of CHIKV epidemiology and population immunity . We aimed to combine the distribution of cases and deaths reported since 2014 with seroprevalence studies to inform mathematical models that estimate the underlying rates of infection by state and year, and the underlying patterns of disease and death by age and sex. Methods We quantified the annual CHIKV infection and disease burden between 2014 and 2024 in each of the 27 federative units of Brazil using a mathematical model in a Bayesian framework that integrated serological surveys (n=12) and confirmed CHIKV disease cases (n=488 234) and CHIKV deaths (n=1719) reported between January, 2014, and September, 2024. Using this base, we estimated the potential impact of a vaccine over the period 2025–29 h...

  Abstract Understanding the geographic spread of emerging respiratory viruses is critical for pandemic preparedness , yet the early spatiotemporal dynamics of the 2009 H1N1 pandemic influenza and SARS-CoV-2 in the United States (US) remain unclear . While mobility and genomic data have revealed important aspects of pandemic spatial spread, several key questions remain: Did the two pandemics follow similar spatial transmission routes? How rapidly did they spread across the US? What role did stochastic processes play in early spatial transmission? To address these questions, we integrated high-resolution disease data with a robust, data-efficient inference framework combining air travel, commuting flows, and pathogen superspreading potentials to reconstruct their spatial spread across US metropolitan areas . The two pandemics exhibited distinct transmission pathways across locations; however, both pandemics established local circulation in most metropolitan areas within weeks , driv...

  Significance Annual influenza epidemics in the United States cause hundreds of thousands of hospitalizations . Quantifying vaccine impact is vital, yet many analyses overlook vaccines’ dual benefits : directly protecting recipients and indirectly protecting their contacts . Using a mathematical model that accounts for both effects, we estimate that vaccination prevented about 70,000 hospitalizations during the 2022–2023 season , with another 19,000 potentially avoidable if coverage met the 70% national target. Despite uncertainty in vaccine effectiveness against infection, our findings suggest that vaccinating younger adults offers substantial indirect protection for older adults. Tailoring annual vaccination campaigns by age group and state could further strengthen their public health impact. Abstract During the COVID-19 pandemic early years, infection prevention measures suppressed transmission of seasonal influenza and other respiratory viruses . The early onset and moderate s...

  Abstract Infectious diseases are often observed to have different epidemiology in different countries , which arises due to various factors including those that are ecological, socioeconomic, and healthcare-related . Such variability can sometimes be best captured through looking at groups of countries that are similar within-group but variable between-group. In this study we use statistical learning methods to generate data-driven disease-centric groupings of countries rather than those developed for administrative or political reasons by e.g. the WHO, World Bank, and the United Nations. In particular, we apply hierarchical clustering to group countries based on shared disease-relevant characteristics for zoonotic H5N1 influenza . Using statistical methods such as classification and regression trees (CART)-based imputation and dynamic tree cutting, the analysis accounts for missing data and identifies epidemiologically (rather than politically or economically) meaningful cluster...

  Abstract Background Ebola virus disease (EVD) is a severe and often fatal illness with high transmission potential and recurring outbreaks . Traditional compartmental models often neglect biologically important delays , such as the latent period before an infected individual becomes infectious, limiting their ability to capture real-world epidemic patterns. Including such delays can provide a more accurate understanding of outbreak persistence and control strategies. Methods In this study, we develop and analyze a novel deterministic SIRR model that captures the complex transmission dynamics of Ebola by explicitly combining nonlinear incidence rates with a delay differential equation framework . Unlike traditional models, this approach integrates a biologically motivated delay to represent the latent period before infectiousness, providing a more realistic depiction of disease spread. The basic reproduction number (R0) is derived using the next-generation matrix, and local stabil...

  Abstract Highly Pathogenic Avian Influenza (HPAI) is a prominent candidate for a future human pandemic arising from a zoonotic spillover event . Its best-known subtype is H5N1 , with South- or South-East Asia a likely location for an initial outbreak. Such an outbreak would be initiated through a primary event of bird-to-human infection, followed by sustained human-to-human transmission . Early interventions require the extraction, integration and interpretation of epidemiological information from the limited and noisy case data available at outbreak onset. We studied the implications of a potential zoonotic spillover of H5N1 influenza into humans . Our simulations used BharatSim , an agent-based model framework designed primarily for the population of India , but which can be tuned easily for others. We considered a synthetic population representing primary contacts in an outbreak site with infected birds. These primary contacts transfer infections to secondary ( household) cont...

  Abstract Outbreaks of Middle East respiratory syndrome coronavirus (MERS-CoV) in humans are driven by recurring zoonotic spillover from camels , leading to demand for camel vaccination . With two vaccine candidates shown to reduce infectiousness, there is a need to better understand transmission of MERS-CoV in camels and assess the potential impact of vaccination . To help address this, we used age-stratified seroprevalence data and a combination of modelling methodologies to estimate key epidemiological quantities including MERS-CoV transmissibility in camels and to estimate vaccine impact on infection incidence. Transmissibility was higher in West Asia (R0 interquartile range 7-14) compared to Africa (3-5) and South Asia (2-3), highlighting the need for setting-specific vaccination strategies. Modelling suggested that even if the vaccine only reduced infectiousness rather than susceptibility to infection, vaccinating calves could achieve large reductions in incidence in moderat...

  Abstract The COVID-19 pandemic has accelerated the development and adoption of wastewater-based epidemiology . Wastewater samples can provide genomic information for detecting and assessing the spread of SARS-CoV-2 variants in communities and for estimating important epidemiological parameters such as the selection advantage of a viral variant . However, despite demonstrated successes, epidemiological data derived from wastewater suffers from potential biases . Of particular concern are shedding profiles , which can affect the relationship between true viral incidence and viral loads in wastewater. Changes in shedding between variants may decouple the established relationship between wastewater loads and clinical test data. Using mathematical modeling, simulations, and Swiss surveillance data , we demonstrate that estimates of the selection advantage of a variant are not biased by shedding profiles. We show that they are robust to differences in shedding between variants under a ...

Abstract The highly pathogenic avian influenza (HPAI) subtype H5N1 is a severe viral disease which continues to pose a significant threat to public health and a rigorous understanding of its transmission dynamics across its major pathways is essential for developing effective control strategies . Phylogenetic analysis suggests that H5N1 spillover occurs primarily between wild and domestic birds . However, increasing contact between these species and humans increases the risk of zoonotic transmission . In this work, we develop a mathematical model to examine the transmission dynamics of H5N1 and evaluate the effectiveness of proposed control measures. The model employs a compartmental framework that includes human, domestic, and wild bird populations. We then use this model to estimate the basic reproduction number for each population group and perform a sensitivity analysis to assess the contribution of the parameters to the spread of the disease. Numerical simulations are also conduct...

Abstract Avian influenza is a highly contagious viral disease that affects both domestic and wild birds , with occasional spillover to mammals , including humans. As of June 2025, 117 H5N1 infections in humans have been reported worldwide since 2020. Given the ability of the virus to infect mammals, there is a growing concern about its potential for human-to-human transmission . Currently, contact tracing and self-isolation are used in the UK to manage contacts of confirmed human cases of avian influenza. In this study, we aimed to estimate potential outbreak sizes and evaluate the effectiveness of contact tracing and self-isolation in managing avian influenza spillover events. We used a novel dataset from the Avian Contact Study to analyse contact patterns within an agricultural population at high risk of avian influenza exposure through contact with birds. We modelled outbreak sizes using a stochastic branching process model with measured contact data. Most simulations resulted in sm...

Abstract We analyzed 15 cases of highly pathogenic avian influenza (HPAI) clade 2.3.4.4b virus infections detected in wild birds in South Korea during September 2023–March 2024. We isolated and sequenced 8 H5N1 and 7 H5N6 viruses . We investigated spatiotemporal transmission dynamics by using a Bayesian discrete trait phylodynamic model that incorporated geographic and host species information. Our source–sink dynamics support introductions of H5N1 viruses from northern Japan to South Korea and subsequent spread through multiple regions in South Korea. The H5N6 viruses were most likely introduced into southwestern South Korea and spread northeastward. Wild waterfowl, especially wild ducks , played a key role in transmission of both H5N1 and H5N6 viruses. Our data showed multiple introductions and extensive spread of HPAI clade 2.3.4.4b viruses and bidirectional transmission between Japan and South Korea. Our results highlight the value of enhanced active surveillance for monitoring HPA...

Abstract Collection of systemic tissues from influenza A virus (IAV)-infected ferrets at a fixed timepoint post-inoculation represents a frequent component of risk assessment activities to assess the capacity of IAV to replicate systemically. However, few studies have evaluated how the frequency and magnitude of IAV replication at discrete tissues contribute to within-host phenotypic outcomes, limiting our ability to fully contextualize results from scheduled necropsy into risk assessment settings. Employing aggregated data from ferrets inoculated with > 100 unique IAV ( both human- and avian-origin viruses, spanning H1, H2, H3, H5, H7, and H9 subtypes ), we examined relationships between infectious virus detection in four discrete tissue types ( nasal turbinate, lung, brain, and olfactory bulb [BnOB]) to clinical outcomes of IAV-inoculated ferrets, and the utility of including these discrete tissue data as features in machine learning (ML) models. We found that addition of viral ti...

Abstract Despite identification of Highly Pathogenic Avian Influenza viruses nearly 75 years ago, the transmission pathways among wild animals remain incompletely described. We propose the use of social networks , to complement phylodynamic modeling , for better surveillance, prediction, and prioritization of HPAI. Source: PLoS Pathogens,  https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1013233 ____

Abstract Avian influenza A(H5N1) poses a public health risk due to its pandemic potential should the virus mutate to become human-to-human transmissible . To date, reported influenza A(H5N1) human cases have typically occurred in the lower respiratory tract with a high case fatality rate . There is prior evidence of some influenza A(H5N1) strains being a small number of amino acid mutations away from achieving droplet transmissibility , possibly allowing them to be spread between humans. We present a mechanistic within-host influenza A(H5N1) infection model , novel for its explicit consideration of the biological differences between the upper and lower respiratory tracts . We then estimate a distribution of viral lifespans and effective replication rates in human H5N1 influenza cases. By combining our within-host model with a viral mutation model, we determine the probability of an infected individual generating a droplet transmissible strain of influenza A(H5N1) through mutation. For ...

Abstract The recent resurgence of highly pathogenic avian influenza H5N1 viruses in North America and Europe has heightened global concerns regarding potential influenza pandemics. Despite significant progress in the surveillance and prevention of emerging influenza viruses, effective tools for rapid and accurate risk assessment remain limited. Here, we present FluRisk , an innovative computational framework that integrates viral genomic data with artificial intelligence (AI) to enable rapid and comprehensive risk evaluation of emerging influenza strains. FluRisk incorporates a curated database of over 1,000 experimentally validated molecular markers linked to key viral phenotypes , including mammalian adaptation, mammalian virulence, mammalian transmission, human receptor-binding preference , and antiviral drug resistance . Leveraging these markers, we developed three state-of-the-art machine learning models to predict human adaptation, mammalian virulence, and human receptor-binding ...

Abstract Since 2015, French poultry production is threatened almost every year by a reintroduction of highly pathogenic avian influenza H5 viruses . The duck sector was the most concerned by this crisis but other sectors such as broiler, layer and turkey were also affected by outbreaks. The objective of this work was to assess the risk of highly pathogenic avian influenza H5 virus transmission from one farm to another within the French broiler and layer production network. This study used the WOAH risk assessment framework . After drawing up a scenario tree of virus transmission from one farm to another, data were collected through a literature review or through experts' elicitation. Three questionnaires were developed according to the experts' field of expertise: avian influenza, broiler and layer sectors. The experts' estimates were combined using a beta distribution weighted by their confidence level. A Monte Carlo iteration process was used to combine the different prob...

Abstract Avian influenza (AI) is a highly contagious viral disease affecting poultry and wild water birds , posing significant global challenges due to its high mortality rates and economic impacts. Highly pathogenic avian influenza (HPAI) outbreaks , particularly those caused by H5N1 and its variants , have surged since their first occurrence in 1959. The HPAI H5N1 clade 2.3.4.4b viruses have notably expanded its geographical reach, affecting numerous countries, diverse avian species, and now wild and domestic mammals . Using an ecological niche modelling approach, this study aims to elucidate the environmental factors associated with the increased HPAI H5 cases since 2020, investigate potential shifts in ecological niches , and predict new areas suitable for local viral circulation. Focusing on H5N1 and H5Nx strains, we have developed ecological niche models for HPAI case in both wild and domestic birds while considering two distinct periods: 2015-2020 and 2020-2022. Key environmenta...

Abstract Accidental lab–acquired infections (LAIs) risk releasing potential pandemic pathogens (PPPs) from BSL–3/4 facilities . We constructed a stochastic network infectious disease model to simulate how the probability of an outbreak of a pathogen resembling wild–type SARS–COV–2, following an initial LAI would be influenced by test–and–isolate interventions over a 100–day horizon . We varied test frequency (0–7 tests/week), peak sensitivity (50–100%), and isolation delay (0–3 days). For each of 192 parameter combinations, we conducted 1,000 simulations and used logistic regression to quantify how each parameter influenced the likelihood of an outbreak of 50 or more infections. Results indicated that even relatively infrequent routine testing significantly reduced the risk of outbreaks under diverse plausible scenarios, with greater reductions achieved at higher test frequencies. Once-weekly testing reduced outbreak risk by 52% under optimistic assumptions (80% sensitivity, 1–day dela...