Tootfinder

Explainable AI for Infection Prevention and Control: Modeling CPE Acquisition and Patient Outcomes in an Irish Hospital with Transformers
Minh-Khoi Pham, Tai Tan Mai, Martin Crane, Rob Brennan, Marie E. Ward, Una Geary, Declan Byrne, Brian O Connell, Colm Bergin, Donncha Creagh, Nick McDonald, Marija Bezbradica
https://arxiv.org/abs/2509.1…

Explainable AI for Infection Prevention and Control: Modeling CPE Acquisition and Patient Outcomes in an Irish Hospital with Transformers
Carbapenemase-Producing Enterobacteriace poses a critical concern for infection prevention and control in hospitals. However, predictive modeling of previously highlighted CPE-associated risks such as readmission, mortality, and extended length of stay (LOS) remains underexplored, particularly with modern deep learning approaches. This study introduces an eXplainable AI modeling framework to investigate CPE impact on patient outcomes from Electronic Medical Records data of an Irish hospital. We…

Australia's first national report on indoor air quality reveals urgent need for action #Australia

Australia's first national report on indoor air quality reveals urgent need for action
The "State of Indoor Air in Australia 2025" report, led by QUT's ARC Training Center for Advanced Building Systems Against Airborne Infection Transmission (THRIVE), highlights the health, well-being and economic risks posed by poor indoor air quality across homes, workplaces, schools, hospitals and public buildings.

#LazyWeb question regarding the dreaded NPM #GlassWorm or similar malware to harvest auth tokens:
To avoid a potential infection leading to harvesting the token usually stored in `~/.npmrc`, I changed that file's content to:
`//registry.npmjs.org/:_authToken=${NPM_TOKEN}`
...…

Observer-Based Source Localization in Tree Infection Networks via Laplace Transforms
Kesler O'Connor, Julia M. Jess, Devlin Costello, Manuel E. Lladser
https://arxiv.org/abs/2510.09828

Observer-Based Source Localization in Tree Infection Networks via Laplace Transforms
We address the problem of localizing the source of infection in an undirected, tree-structured network under a susceptible-infected outbreak model. The infection propagates with independent random time increments (i.e., edge-delays) between neighboring nodes, while only the infection times of a subset of nodes can be observed. We show that a reduced set of observers may be sufficient, in the statistical sense, to localize the source and characterize its identifiability via the joint Laplace tra…

"Star Trek: Infection": VR-Survival-Horror für nervenstarke Trekkies angekündigt
Als vulkanischer Offizier gegen eine unbekannte Macht: Das VR-Spiel "Star Trek: Infection" setzt auf Horror und eine Geschichte über Identitätsverlust.

Behavioral-feedback SIR epidemic model: analysis and control
Martina Alutto, Leonardo Cianfanelli, Giacomo Como, Fabio Fagnani, Francesca Parise
https://arxiv.org/abs/2509.12257

Behavioral-feedback SIR epidemic model: analysis and control
This paper investigates a behavioral-feedback SIR model in which the infection rate adapts dynamically based on the fractions of susceptible and infected individuals. We introduce an invariant of motion and we characterize the peak of infection. We further examine the system under a threshold constraint on the infection level. Based on this analysis, we formulate an optimal control problem to keep the infection curve below a healthcare capacity threshold while minimizing the economic cost. For …

Another unforeseen effect of COVID-19 vaccination has been detected.
Wait for it.
It reduces the incidence of autism (and other neurodevelopmental disorders).

COVID-19 infection during pregnancy is associated with higher rates of autism and neurodevelopmental diagnoses
A recent study found that infection with SARS-CoV-2 during pregnancy is associated with a higher risk of autism and neurodevelopment disorders. This is yet another reason why vaccination during pregna

“The spread of dangerous infections that do not respond to antibiotics has been increasing by
as much as 15 percent a year”,
says the WHO.
“The less people have access to quality care,
the more they’re likely to suffer from drug-resistant infection.”
https://kottke.org/25/10/0047706-th…

Lung Infection Severity Prediction Using Transformers with Conditional TransMix Augmentation and Cross-Attention
Bouthaina Slika, Fadi Dornaika, Fares Bougourzi, Karim Hammoudi
https://arxiv.org/abs/2510.06887

Lung Infection Severity Prediction Using Transformers with Conditional TransMix Augmentation and Cross-Attention
Lung infections, particularly pneumonia, pose serious health risks that can escalate rapidly, especially during pandemics. Accurate AI-based severity prediction from medical imaging is essential to support timely clinical decisions and optimize patient outcomes. In this work, we present a novel method applicable to both CT scans and chest X-rays for assessing lung infection severity. Our contributions are twofold: (i) QCross-Att-PVT, a Transformer-based architecture that integrates parallel enc…

Bird flu cases are spiking earlier than experts expected — and that could cause egg prices to skyrocket | The Independent
https://www.independent.co.uk/news/world/americas/bird-flu-poultry-egg-prices-infection-b2843082.html

We need the French concept.
L'infection mentale commence
avec des douleurs lancinantes
tourmente ardemment
le corps soupirant, affaiblit,
par attaques de vertiges
la faiblesse d'une dure rupture
la chair, tout au long, violée
les bubons de la mort rouge.
https://youtu.be/QEc4zQ80NFs

Check out today's Metacurity for the most crucial cybersecurity developments you should know, including
--CISA plans to fire 54 employees despite court injunction,
--Google reports new ways threat actors can use AI in their attacks,
--KT accused of concealing BPFDoor infection,
--Meta earns $7b a year in scam ads,
--Hackers stole data from Hyundai AutoEver America,
--Chinese court sentences scam operators to death,
--NV ransomware attack took plac…

CISA plans to fire 54 employees despite court injunction
Google reports new ways threat actors can use AI in their attacks, KT accused of concealing BPFDoor infection, Meta earns $7b a year in scam ads, Hackers stole data from Hyundai AutoEver America, Chinese court sentences scam operators to death, NV ransomware attack took place in May, much more

Complex dynamics and pattern formation in a diffusive epidemic model with an infection-dependent recovery rate
Wael El Khateeb, Chanaka Kottegoda, Chunhua Shan
https://arxiv.org/abs/2509.09000

Complex dynamics and pattern formation in a diffusive epidemic model with an infection-dependent recovery rate
A diffusive epidemic model with an infection-dependent recovery rate is formulated in this paper. Multiple constant steady states and spatially homogeneous periodic solutions are first proven by bifur cation analysis of the reaction kinetics. It is shown that the model exhibits diffusion-driven instability, where the infected population acts as an activator and the susceptible population functions as an in hibitor. The faster movement of the susceptible class will induce the spatial and spa…

Dynamics of Infection Spread and Hotspot Growth in Bi-Pathogen Networks
Alyssa Yu, Laura P. Schaposnik
https://arxiv.org/abs/2509.03374 https://arxiv.org/p…

Dynamics of Infection Spread and Hotspot Growth in Bi-Pathogen Networks
Understanding the spatio-temporal evolution of epidemics with multiple pathogens requires not only new theoretical models but also careful analysis of their practical consequences. Building on the Multiplex Bi-Virus Reaction-Diffusion framework (MBRD) introduced in our companion paper, we investigate how the super-infection model (MBRD-SI) and the co-infection model (MBRD-CI) behave under different epidemiological and network conditions. Through numerical experiments, we study the effects of pa…

PDE-Based Bayesian Hierarchical Modeling for Event Spread, with Application to COVID-19 Infection
Mengqi Cen, Xuejing Meng, X. Joan Hu, Juxin Liu, Jianhong Wu
https://arxiv.org/abs/2509.13174

PDE-Based Bayesian Hierarchical Modeling for Event Spread, with Application to COVID-19 Infection
We extended the Wikle's Bayesian hierarchical model based on a diffusion-reaction equation [Wikle, 2003] to investigate the COVID-19 spatio-temporal spread events across the USA from Mar 2020 to Feb 2022. Our model incorporated an advection term to account for the intra-state spread trend. We applied a Markov chain Monte Carlo (MCMC) method to obtain samples from the posterior distribution of the parameters. We implemented the approach via the collection of the COVID-19 infections across the st…

Real-time identification and control of influential pandemic regions using graph signal variation
Sudeepini Darapu, Subrata Ghosh, Dibakar Ghosh, Chittaranjan Hens, Santosh Nannuru
https://arxiv.org/abs/2509.10281

Real-time identification and control of influential pandemic regions using graph signal variation
The global spread of pandemics is facilitated by the mobility of populations, transforming localized infections into widespread phenomena. To contain it, timely identification of influential regions that accelerate this process is necessary. In this work, we model infection as a temporally evolving graph signal and propose graph signal variation-based metrics to capture spatio-temporal changes. Both graph domain and time domain locality are modeled. Based on this metric, we propose an online al…

Multicritical Infection Spreading
Leone V. Luzzatto, Juan Felipe Barrera L\'opez, Istv\'an A. Kov\'acs
https://arxiv.org/abs/2508.20895 https://

Multicritical Infection Spreading
The contact process is a simple infection spreading model showcasing an out-of-equilibrium phase transition between a macroscopically active and an inactive phase. Such absorbing state phase transitions are often sensitive to the presence of quenched disorder. Traditionally, a phase transition in the disordered contact process is either triggered by dilution or by locally varying the infection rate. However, when both factors play an important role, a multicritical point emerges that remains po…

Phew, it's been a long time since I've really been online—a nasty infection completely knocked me out for more than two weeks. But now I'm back to do Linux stuff! Let's go!
#linux #opensource

🇺🇦 #NowPlaying on KEXP's #SeekAndDestroy
Ripping Remains:
🎵 Rub My Infection on You
#RippingRemains
#newRelease 🆕 single
https://rippingremains.bandcamp.com/track/rub-my-infection-on-you
https://open.spotify.com/track/2RzmHTP1Sdfo6X9qIEvgBr
Please 🔁 BOOST to share what you like
- your followers don't see if you ⭐ favourite a post

Virus Infection Attack on LLMs: Your Poisoning Can Spread "VIA" Synthetic Data
Zi Liang, Qingqing Ye, Xuan Liu, Yanyun Wang, Jianliang Xu, Haibo Hu
https://arxiv.org/abs/2509.23041

Virus Infection Attack on LLMs: Your Poisoning Can Spread "VIA" Synthetic Data
Synthetic data refers to artificial samples generated by models. While it has been validated to significantly enhance the performance of large language models (LLMs) during training and has been widely adopted in LLM development, potential security risks it may introduce remain uninvestigated. This paper systematically evaluates the resilience of synthetic-data-integrated training paradigm for LLMs against mainstream poisoning and backdoor attacks. We reveal that such a paradigm exhibits strong…

I just found this UK report on #covid epidemiology from 2020 to Dec 2024; the graph I most noticed is below - they looked at blood donors for spike (S) and Nucleo (N) protein antibodies over time; The spike proteins are in both infection and vaccine, while N is infection only - so you can see when people got vaccinated and how now pretty much everyone (95.5% as end of January) has been infected as…

Epidemiology of COVID-19 in England: January 2020 to December 2024

Crosslisted article(s) found for math.PR. https://arxiv.org/list/math.PR/new
[1/1]:
- Observer-Based Source Localization in Tree Infection Networks via Laplace Transforms
Kesler O'Connor, Julia M. Jess, Devlin Costello, Manuel E. Lladser

I'm having a bad mental health day -- really struggling to sustain either any consistent train of thought or any degree of mood stability.
It's *probably* just a virus infection and will *probably* pass, but it's very frightening and upsetting while it's happening.
Being mad just isn't fun.

Optimal Control of an SIR Model with Noncompliance as a Social Contagion
Chloe Ngo, Christian Parkinson, Weinan Wang
https://arxiv.org/abs/2509.09075 https://

Optimal Control of an SIR Model with Noncompliance as a Social Contagion
We propose and study a compartmental model for epidemiology with human behavioral effects. Specifically, our model incorporates governmental prevention measures aimed at lowering the disease infection rate, but we split the population into those who comply with the measures and those who do not comply and therefore do not receive the reduction in infectivity. We then allow the attitude of noncompliance to spread as a social contagion parallel to the disease. We derive the reproductive ratio for…

Detecting disease progression from animal movement using hidden Markov models
Dongmin Kim, Th\'eo Michelot, Katherine Mertes, Jared A. Stabach, John Fieberg
https://arxiv.org/abs/2509.21132

Detecting disease progression from animal movement using hidden Markov models
Understanding disease dynamics is crucial for managing wildlife populations and assessing spillover risk to domestic animals and humans, but infection data on free-ranging animals are difficult to obtain. Because pathogen and parasite infections can alter host movement, infection status may be inferred from animal trajectories. We present a hidden Markov model (HMM) framework that links observed movement behaviors to unobserved infection states, consistent with epidemiological compartmental mod…

Spatial Super-Infection and Co-Infection Dynamics in Networks
Alyssa Yu, Laura P. Schaposnik
https://arxiv.org/abs/2508.15740 https://arxiv.org/pdf/2508.15…

Spatial Super-Infection and Co-Infection Dynamics in Networks
Understanding interactions between the spread of multiple pathogens during an epidemic is crucial to assessing the severity of infections in human communities. In this paper, we introduce two new Multiplex Bi-Virus Reaction-Diffusion models (MBRD) on multiplex metapopulation networks: the super-infection model (MBRD-SI) and the co-infection model (MBRD-CI). These frameworks capture two-pathogen dynamics with spatial diffusion and cross-diffusion, allowing the prediction of infection clustering …

Detection of Chagas Disease from the ECG: The George B. Moody PhysioNet Challenge 2025
Matthew A. Reyna (Department of Biomedical Informatics, Emory University, Atlanta, USA), Zuzana Koscova (Department of Biomedical Informatics, Emory University, Atlanta, USA), Jan Pavlus (Department of Biomedical Informatics, Emory University, Atlanta, USA), Soheil Saghafi (Department of Biomedical Informatics, Emory University, Atlanta, USA), James Weigle (Department of Biomedical Informatics, Emory…

Detection of Chagas Disease from the ECG: The George B. Moody PhysioNet Challenge 2025
Objective: Chagas disease is a parasitic infection that is endemic to South America, Central America, and, more recently, the U.S., primarily transmitted by insects. Chronic Chagas disease can cause cardiovascular diseases and digestive problems. Serological testing capacities for Chagas disease are limited, but Chagas cardiomyopathy often manifests in ECGs, providing an opportunity to prioritize patients for testing and treatment. Approach: The George B. Moody PhysioNet Challenge 2025 invites …

Researchers find spyware on phones belonging to Kenyan filmmakers https://therecord.media/researchers-spyware-kenya-filmmaker-phone

Scientists Reveal Biological Basis of Long COVID Brain Fog #covid
https://scitechdaily.com/scientists-finally-reveal-biological-basis-of-long-covid-brain-fog…

Scientists Finally Reveal Biological Basis of Long COVID Brain Fog
Researchers employed a specialized brain imaging technique to identify a potential biomarker and therapeutic target for Long COVID. More than four years after the onset of the COVID-19 pandemic, scientists are still working to fully understand the lingering effects of infection with SARS-CoV-2. O

Anyone want to finish this poem?
Xubuntu downloads section injection
Threatens users with crypto infection

An infection-responsive collagen-based wet-spun textile fibre for wound monitoring
Jonathon Gorman, Charles Brooker, Xinyu Li, Giuseppe Tronci
https://arxiv.org/abs/2510.00015 h…

An infection-responsive collagen-based wet-spun textile fibre for wound monitoring
Wound infections are a significant clinical and socioeconomic challenge, contributing to delayed healing and increased wound chronicity. To enable early infection detection and inform therapeutic decisions, this study investigated the design of pH-responsive collagen fibres using a scalable wet spinning process, evaluating product suitability for textile dressings and resorbable sutures. Type I collagen was chemically functionalised with 4-vinylbenzyl chloride, enabling UV-induced crosslinking …

Oh, Hacker News…FFS. Something got lost in the sad game of Popular Press Telephone between the actual study and this snotty post.
The actual study is here:
https://www.acpjournals.org/doi/10.7326/ANNALS-25-00577
It notes that:
1. Most research on air cleaning devices used air samples, not human health outcomes. (It’s far more difficult to conduct a study on the latter.)
2. Not many people are studying whether e.g. UV air purifiers create toxic byproducts.
3. The available studies sure do measure a whole bunch of different things, and wouldn’t it be nice if they had more consistent standards.
Their main recommendation is basically “scientists should do more studies where they measure infection in humans, not just germs in the air.” And that’s fair: It’s reasonable to •guess• that fewer germs in the air means less sickness, but it’s nice to actually •test• that!
However, AFAICT, nothing in the study warrants the “tinfoil hats” remark. Unlike a tinfoil hats, we have plenty good reason to think at least some of these devices actually work; the paper just wants the research to go deeper. It’s one giant “further study needed.” https://mastodon.social/@ngate/115091700894746240

A Digital Twin for Robotic Post Mortem Tissue Sampling using Virtual Reality
Maximilian Neidhardt, Ludwig Bosse, Vidas Raudonis, Kristina Allgoewer, Axel Heinemann, Benjamin Ondruschka, Alexander Schlaefer
https://arxiv.org/abs/2509.02760

A Digital Twin for Robotic Post Mortem Tissue Sampling using Virtual Reality
Studying tissue samples obtained during autopsies is the gold standard when diagnosing the cause of death and for understanding disease pathophysiology. Recently, the interest in post mortem minimally invasive biopsies has grown which is a less destructive approach in comparison to an open autopsy and reduces the risk of infection. While manual biopsies under ultrasound guidance are more widely performed, robotic post mortem biopsies have been recently proposed. This approach can further reduce…

The RFKJr. situation is generally terrible and all, but apparently CDC managed to keep enough conditions in the "high risk" qualifications to cover just about everyone.
#Covid #Vaccines

C07 - Children of Auron
DERAL: [Talks over Servalan. Then thinks better of it.] You'll get your or-
SERVALAN: Yes. With full quarantine precautions. Say we're afraid of cross infection. Under the circumstances, they shouldn't find that hard to believe.
https://blake.torpidity.net/m/307/204

Inference of epidemic networks: the effect of different data types
Oscar Fajardo-Fontiveros, Carl J. E. Suster, Eduardo G. Altmann
https://arxiv.org/abs/2509.01871 https://

Inference of epidemic networks: the effect of different data types
We investigate how the properties of epidemic networks change depending on the availability of different types of data on a disease outbreak. This is achieved by introducing mathematical and computational methods that estimate the probability of transmission trees by combining generative models that jointly determine the number of infected hosts, the probability of infection between them depending on location and genetic information, and their time of infection and sampling. We introduce a suit…

More than 7 million people worldwide, mostly in Latin America, are estimated to be infected with Trypanosoma cruzi, the parasite that causes Chagas disease.
It can be transmitted by the triatomine bug (vector-borne), as well as orally (food-borne), during pregnancy or birth (congenital), through blood/blood products, organ transplantation and laboratory accidents.
Chagas disease is curable if antiparasitic treatment is initiated early, in the acute phase. In chronic infection, the…

In ant colonies infected by a tapeworm parasite, uninfected workers show signs of stress-related gene activity, in part because they're caring for infected nestmates (Photo by Matt Hamer, via AntWiki)
Parasite prevalence in a social host has colony-wide impacts on transcriptional activity and survival
https://doi.org/10.1093/ev…

@…
“This virus causes system-wide injury that accumulates with each infection: brain damage that undermines decision-making, immune dysregulation leading to infections like Kaposi sarcoma and tuberculosis in lymph nodes — the very signatures of HIV-AIDS now rising again — and cardiac injury with accelerated aging,” explains Bar-Yam.

13yo: "and at the end of art class they take our sketchbooks"
me: "that sucks"
13yo: "Yeah, it does."
13yo: "Anyway, I was trying to draw a staff but I was having problems with the feathers..." ⚚
me: "Hey, I have a Staph *infection*!"
13yo: 😐
me: "..In case you need a drawing reference or something"
13yo: 🤨
me: "...what?" 😇
13yo: "I'm afraid of what else you'…

Thought Slime posted a video on Liberals and Charlie Kirk (linked in my post). It touched on a few ideas I've been wanting to explore more.
Why is it that, even though we talk "memes" going "viral" we are still talking about "Free Market of Ideas" as though ideas were inanimate objects we could handle and observe objectively? Perhaps that idea is it's own infection.
https://hexmhell.writeas.com/memetic-effluent-and-the-wet-market-of-ideas

Identifying Asymptomatic Nodes in Network Epidemics using Graph Neural Networks
Conrado Catarcione Pinto, Amanda Camacho Novaes de Oliveira, Rodrigo Sapienza Luna, Daniel Ratton Figueiredo
https://arxiv.org/abs/2510.02568

Identifying Asymptomatic Nodes in Network Epidemics using Graph Neural Networks
Infected individuals in some epidemics can remain asymptomatic while still carrying and transmitting the infection. These individuals contribute to the spread of the epidemic and pose a significant challenge to public health policies. Identifying asymptomatic individuals is critical for measuring and controlling an epidemic, but periodic and widespread testing of healthy individuals is often too costly. This work tackles the problem of identifying asymptomatic individuals considering a classic …

It is that time of the year for us senior citizens.
Wife and I have received our influenza shots and this weekend our COVID shots are scheduled.
Approximately 23 years ago I went through hell with influenza and complications. I contracted it just before my scheduled vaccination. Major lung infection and I ended up off work for six weeks. I don't remember Christmas that year and for several weeks at the beginning we told everyone they were not allowed to visit just in case …

🫣 Rare tissue samples reveal where HIV hides in different parts of body
#medicine

Rare tissue samples reveal where HIV hides in different parts of body
Researchers at Western and the University of Calgary have discovered how HIV hides in different parts of the body by embedding itself into the DNA of cells in a tissue-specific manner, offering new insights into why the virus is so difficult to eliminate and cure—even decades after infection and treatment.

Temperature and Competition: Drivers in the Ecological Dynamics of Aedes Mosquitoes and Dengue Spread
Santiago Andr\'es Villamil Chac\'on, Mauricio Santos-Vega
https://arxiv.org/abs/2509.10785 …

Temperature and Competition: Drivers in the Ecological Dynamics of Aedes Mosquitoes and Dengue Spread
Dengue, a mosquito-borne viral disease common in tropical areas, is spread by Aedes aegypti and Aedes albopictus. Temperature changes driven by climate affect vector ecology and expand regions of species coexistence. The combined effect of temperature and larval competition on mosquito dynamics and dengue transmission is unclear. We built a deterministic model with temperature-dependent parameters to study larval-stage interactions, linked with a SEIR framework for human infection. We assessed …

Travel Bans vs. Social Distancing: A Mathematical Analysis
Christian Borgs, Karissa Huang, Geng Zhao
https://arxiv.org/abs/2510.08895 https://arxiv.org/pdf…

Travel Bans vs. Social Distancing: A Mathematical Analysis
As the world grows increasingly connected, infectious disease transmission and outbreaks become a pressing global concern for public health officials and policymakers. While policy interventions to contain and prevent the spread of disease have been proposed and implemented, there has been little rigorous quantitative analysis of the effectiveness of such interventions. In this paper, we study the susceptible-infected-recovered (SIR) infection process on a dynamic network model that models two …

On the numerical computation of $R_0$ in periodic environments
Dimitri Breda, Simone De Reggi, Jordi Ripoll
https://arxiv.org/abs/2509.00847 https://arxiv.…

On the numerical computation of $R_0$ in periodic environments
We propose a novel approach to approximate the basic reproduction number $R_0$ as spectral radius of the Next-Generation Operator in time-periodic population models by characterizing the latter via evolution semigroups. Once birth/infection and transition operators are identified, we discretize them via either Fourier or Chebyshev collocation methods. Then $R_0$ is obtained by solving a generalized matrix eigenvalue problem. The order of convergence of the approximating reproduction numbers to …

"The study’s authors emphasized that, as an observational study, the findings do not prove that covid-19 causes the conditions diagnosed in children, but rather signal an association between maternal infection and these outcomes. "
Covid in pregnancy tied to autism, developmental issues, study says - The Washington Post
https://archive.ph/eSFKO

Spatial correlations in SIS processes on regular random graphs
Alexander Leibenzon, Samuel W. S. Johnson, Ruth E. Baker, Michael Assaf
https://arxiv.org/abs/2509.25386 https://

Spatial correlations in SIS processes on regular random graphs
In network-based SIS models of infectious disease transmission, infection can only occur between directly connected individuals. This constraint naturally gives rise to spatial correlations between the states of neighboring nodes, as the infection status of connected individuals becomes interdependent. Although mean-field approximations are commonly invoked to simplify disease forecasting on networks, they fail to account for these correlations by assuming that infectious individuals are well-m…

I2E2S2R Rumor Spreading Model in Homogeneous Network with Hesitating and Forgetting Mechanisms
Md. Nahid Hasan, Sujana Azmi Polin, Saiful Islam, Chandra Nath Podder
https://arxiv.org/abs/2510.10672

I2E2S2R Rumor Spreading Model in Homogeneous Network with Hesitating and Forgetting Mechanisms
The spreading and controlling of rumors have great impacts on our society. The transmission of infectious diseases and the spreading of rumors have some common scenarios. Like cross-infection propagation of diseases, two or many kinds of rumors or information may spread at the same time. In this paper, we propose a novel I2E2S2R rumor-spreading model in a homogeneous network. The rumor-free equilibrium, as well as the basic reproduction number, have been calculated from the mean-field equations…

Composite method for fast computation of individual level spatial epidemic models
Yirao Zhang, Rob Deardon, Lorna Deeth
https://arxiv.org/abs/2509.04660 https://

Composite method for fast computation of individual level spatial epidemic models
Individual-level models, also known as ILMs, are commonly used in epidemics modelling, as they can flexibly incorporate individual-level covariates that influence susceptibility and transmissibility upon infection. However, inference for ILMs is computationally intensive, especially as the total population size increases and additional covariates are incorporated. We propose a composite method, the composite ILM (C-ILM), that clusters the population into minimally-interfered subpopulations, wit…

Stabilizing by steering: Enhancing bacterial motility by non-uniform diffusiophoresis
Viet Sang Doan, Ali Nikkhah, Sangwoo Shin
https://arxiv.org/abs/2509.25770 https://

Stabilizing by steering: Enhancing bacterial motility by non-uniform diffusiophoresis
Bacteria are often required to navigate across confined spaces to reach desired destinations in biological and environmental systems, allowing critical functions in host-microbe symbiosis, infection, drug delivery, soil ecology, and soil bioremediation. While the canonical run-and-tumble motility is effective in finding targets under confinement, it may not represent the most ideal strategy due to the continuous monitoring of environmental cues and stochastic recorrection of their paths. Here, …

Estimating Global HIV Prevalence in Key Populations: A Cross-Population Hierarchical Modeling Approach
Jiahao Zhang, Keith Sabin, Le Bao
https://arxiv.org/abs/2509.10664 https:/…

Estimating Global HIV Prevalence in Key Populations: A Cross-Population Hierarchical Modeling Approach
Key populations at high risk of HIV infection are critical for understanding and monitoring HIV epidemics, but global estimation is hampered by sparse, uneven data. We analyze data from 199 countries for female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID) over 2011-2021, and introduce a cross-population hierarchical model that borrows strength across countries, years, and populations. The model combines region- and population-specific means with country…

Heterogeneous immune recovery after viral response through a dynamical model of feedback-driven persistence and clearance
Xiaoxin Wang, Kai Kang, Leyi Zhang, Changjing Zhuge
https://arxiv.org/abs/2510.05161

Heterogeneous immune recovery after viral response through a dynamical model of feedback-driven persistence and clearance
Viral infections trigger complex immune responses with heterogeneous outcomes shaped by nonlinear feedbacks. An ordinary differential equation model is developed to investigate immune response dynamics during viral infection, incorporating six modules: viral load, innate immunity, cellular immunity, humoral immunity, immune suppression, and IL-6 levels. Bifurcation analysis reveals that under continuous viral exposure, when viral clearance rate and intrinsic viral death rate satisfy specific co…

Ransomware Negotiation: Dynamics and Privacy-Preserving Mechanism Design
Haohui Zhang, Sirui Shen, Xinyu Hu, Chenglu Jin
https://arxiv.org/abs/2508.15844 https://

Ransomware Negotiation: Dynamics and Privacy-Preserving Mechanism Design
Ransomware attacks have become a pervasive and costly form of cybercrime, causing tens of millions of dollars in losses as organizations increasingly pay ransoms to mitigate operational disruptions and financial risks. While prior research has largely focused on proactive defenses, the post-infection negotiation dynamics between attackers and victims remains underexplored. This paper presents a formal analysis of attacker-victim interactions in modern ransomware incidents using a finite-horizon…

Crosslisted article(s) found for physics.app-ph. https://arxiv.org/list/physics.app-ph/new
[1/1]:
- An infection-responsive collagen-based wet-spun textile fibre for wound monitoring
Jonathon Gorman, Charles Brooker, Xinyu Li, Giuseppe Tronci

Crosslisted article(s) found for nlin.AO. https://arxiv.org/list/nlin.AO/new
[1/1]:
- Spatial Super-Infection and Co-Infection Dynamics in Networks
Alyssa Yu, Laura P. Schaposnik

MicroDetect-Net (MDN): Leveraging Deep Learning to Detect Microplastics in Clam Blood, a Step Towards Human Blood Analysis
Riju Marwah, Riya Arora, Navneet Yadav, Himank Arora
https://arxiv.org/abs/2508.19021

MicroDetect-Net (MDN): Leveraging Deep Learning to Detect Microplastics in Clam Blood, a Step Towards Human Blood Analysis
With the prevalence of plastics exceeding 368 million tons yearly, microplastic pollution has grown to an extent where air, water, soil, and living organisms have all tested positive for microplastic presence. These particles, which are smaller than 5 millimeters in size, are no less harmful to humans than to the environment. Toxicity research on microplastics has shown that exposure may cause liver infection, intestinal injuries, and gut flora imbalance, leading to numerous potential health ha…

Stochastic Compartment Model of Epidemic Spreading in Complex Networks with Mortality and Resetting
Thomas M. Michelitsch, Bernard Collet, Michael Bestehorn, Alejandro P. Riascos, Andrzej F. Nowakowski
https://arxiv.org/abs/2509.06039

Stochastic Compartment Model of Epidemic Spreading in Complex Networks with Mortality and Resetting
We propose an epidemic compartment model, which includes mortality caused by the disease, but excludes demographic birth and death processes. Individuals are represented by random walkers, which are in one of the following states (compartments) S (susceptible to infection), E (exposed: infected but not infectious corresponding to the latency period), I (infected and infectious), R (recovered, immune), D (dead). The disease is transmitted with a certain probability at contacts of I to S walkers.…

The Trump administration is dismantling the last of the public commons.
It’s cutting billions to state programs tracking disease,
repealing emissions and drinking water regulations,
revoking hundreds of millions in funding for life-saving research,
canceling local food programs for schools and food banks,
rolling back vaccinations,
and shutting down the Centers for Disease Control and Prevention’s (CDC’s) Healthcare Infection Control Practices Advisory Commi…

“Make America Healthy Again” Aims to Make Public Health Your Private Responsibility
The message coming from the Trump administration is: “Take care of yourselves — because we won’t.”…

Large deviations in non-Markovian stochastic epidemics
Matan Shmunik, Michael Assaf
https://arxiv.org/abs/2509.09480 https://arxiv.org/pdf/2509.09480

Large deviations in non-Markovian stochastic epidemics
We develop a framework for non-Markovian SIR and SIS models beyond mean field, utilizing the continuous-time random walk formalism. Using a gamma distribution for the infection and recovery inter-event times as a test case, we derive asymptotical late-time master equations with effective memory kernels and obtain analytical predictions for the final outbreak size distribution in the SIR model, and quasistationary distribution and disease lifetime in the SIS model. We show that increasing memory…

Temporal Exposure Dependence Bias in Vaccine Efficacy Trials
Hiroyasu Ando, A. James O'Malley, Akihiro Nishi
https://arxiv.org/abs/2509.03476 https://a…

Temporal Exposure Dependence Bias in Vaccine Efficacy Trials
Using time-to-event methods such as Cox proportional hazards models, it is well established that unmeasured heterogeneity in exposure or infection risk can lead to downward bias in point estimates of the per-contact vaccine efficacy (VE) in infectious disease trials. In this study, we explore an unreported source of bias-arising from temporally correlated exposure status-that is typically unmeasured and overlooked in standard analyses. Although this form of bias can plausibly affect a wide rang…

Contact process on interchange process
M. Hil\'ario, D. Ungaretti, D. Valesin, M. E. Vares
https://arxiv.org/abs/2509.02747 https://arxiv.org/pdf/2509.…

Contact process on interchange process
We introduce a model of epidemics among moving particles on any locally finite graph. At any time, each vertex is empty, occupied by a healthy particle, or occupied by an infected particle. Infected particles recover at rate $1$ and transmit the infection to healthy particles at neighboring vertices at rate $λ$. In addition, particles perform an interchange process with rate $\mathsf{v}$, that is, the states of adjacent vertices are swapped independently at rate $\mathsf{v}$, allowing the infe…

Changes in Liver Fibrosis in Patients with Chronic Hepatitis B Treated with Pegylated Interferon Combined with Oral Antiviral Agents: A 48-Week Observation from a Prospective Cohort Study
Zhao Jinhua
https://arxiv.org/abs/2509.15854

Changes in Liver Fibrosis in Patients with Chronic Hepatitis B Treated with Pegylated Interferon Combined with Oral Antiviral Agents: A 48-Week Observation from a Prospective Cohort Study
Background and Aims: Pegylated interferon (PEG-IFN) combined with oral antiviral agents is currently the most widely used and highly effective treatment regimen for chronic hepatitis B virus (HBV) infection. While effectively suppressing HBV replication, its impact on liver histopathological fibrosis and inflammation remains a critical concern for clinicians and patients. Methods : A total of 625 patients who completed 48 weeks of PEG-IFN combined with oral antiviral therapy were enrolled in th…

HIP: Model-Agnostic Hypergraph Influence Prediction via Distance-Centrality Fusion and Neural ODEs
Su-Su Zhang, JinFeng Xie, Yang Chen, Min Gao, Cong Li, Chuang Liu, Xiu-Xiu Zhan
https://arxiv.org/abs/2508.15312

HIP: Model-Agnostic Hypergraph Influence Prediction via Distance-Centrality Fusion and Neural ODEs
Predicting user influence in social networks is a critical problem, and hypergraphs, as a prevalent higher-order modeling approach, provide new perspectives for this task. However, the absence of explicit cascade or infection probability data makes it particularly challenging to infer influence in hypergraphs. To address this, we introduce HIP, a unified and model-independent framework for influence prediction without knowing the underlying spreading model. HIP fuses multi-dimensional centralit…

Finding the Best Route During the Pandemic Disease
Amirsadegh Mirgalooyebayat, Farzad Didehvar
https://arxiv.org/abs/2510.02396 https://arxiv.org/pdf/2510.…

Finding the Best Route During the Pandemic Disease
This article presents a mathematical model for identifying the safest travel routes during a pandemic by minimizing disease contraction risks, such as COVID-19. We formulate this as the LEAST INFECTION PROBABILITY PATH (LIPP) problem, which optimizes routes between two nodes in a transportation network based on minimal disease transmission probability. Our model evaluates risk factors including environmental density, likelihood of encountering carriers, and exposure duration across multiple tra…

Crosslisted article(s) found for nlin.AO. https://arxiv.org/list/nlin.AO/new
[1/1]:
- Dynamics of Infection Spread and Hotspot Growth in Bi-Pathogen Networks
Alyssa Yu, Laura P. Schaposnik

Crosslisted article(s) found for physics.bio-ph. https://arxiv.org/list/physics.bio-ph/new
[1/1]:
- Multicritical Infection Spreading
Leone V. Luzzatto, Juan Felipe Barrera L\'opez, Istv\'an A. Kov\'acs

Activity propagation with Hebbian learning
Will T. Engedal, R\'obert Juh\'asz, Istv\'an A. Kov\'acs
https://arxiv.org/abs/2508.21053 https://

Activity propagation with Hebbian learning
We investigate the impact of Hebbian learning on the contact process, a paradigmatic model for infection spreading, which has been also proposed as a simple model to capture the dynamics of inter-regional brain activity propagation as well as population spreading. Each of these contexts calls for an extension of the contact process with local learning. We introduce Hebbian learning as a positive or negative reinforcement of the activation rate between a pair of sites after each successful activ…

Daily Profile of COVID-19 Infections in Germany, throughout the Pandemic
Derek Marsh
https://arxiv.org/abs/2510.05721 https://arxiv.org/pdf/2510.05721

Daily Profile of COVID-19 Infections in Germany, throughout the Pandemic
Progress of the COVID-19 pandemic was quantified, in the first instance, using the daily number of positive cases recorded by the national public health authorities. Averaged over a seven-day window, the daily incidence of COVID-19 in Germany reveals clear sections of exponential growth or decay in propagation of infection. Comparing with incidence profiles according to onset-of-symptoms shows that reporting of cases involves variable delays. Observed changes in exponential rates come from grow…

Crosslisted article(s) found for q-bio.PE. https://arxiv.org/list/q-bio.PE/new
[1/1]:
- Spatial Super-Infection and Co-Infection Dynamics in Networks
Alyssa Yu, Laura P. Schaposnik