Tootfinder

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 …

War is an unconscionable horror. The illusions of "international law" and "rules of war" have lead us to believe that war can be clean, managed, and "civilized."
But wars are fought by humans and humans are messy. Humans are not well suited to following orderly rules. Humans respond to their environment. Humans in extraordinary situations can be extraordinarily vindictive and brutal. Sufficiently traumatized humans can act without a conscience, spreading trauma like an infection. If humans respond to their situation, then there can be no "civilized" war because war is itself an situation outside of the society. It is a place that promotes antisocial behavior and punishes pro-social behavior. War cannot be expected to follow "international law" because it is what fills the void created by the failure of "international law" (so long as we rely on nations).
To call for war is to inflict atrocities on civilians. It is to kill the parents and children who serve, and to destroy the combatants who survive. It is to infect both sides with a trauma that will spread if untreated, when soldiers come home or when they become mercenaries in other wars.
And yet... there are times when the brutality, the incompetence, the evil becomes so unbearable that no other option exists, when taking up arms is simply bringing symmetry to an existing asymmetric conflict. There are times when the worst possible thing is inescapable, though it can never be justified.
In this new era of war, in the scramble of conflict under the collapsing of the (poorly named) "Pax Americana," I hope that we, the people, can understand that war is not a tool to fulfill an objective. It is not part of a larger strategy. It is not an extension of deplomacy.
War is a failure.
While it may be the only way to deal with the irrational - the genocidal, the slaver, the dictator - it is still a failure. It is a failure to build a world in which these people can't control armies and economies, can't turn populations in to cults and bend nations to their will.
And we will continue to have such wars until we unite against those who would use as as pawns, who would control our lives and lead us to our deaths. We will have these wars until we unite, as one world, against those rulers. This is what I mean, and what a lot of other people mean, when we say, "No War, but Class War."

"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.

Epidemic Spreading with Co-infection on Long-Range Random Networks
Frank Namugera
https://arxiv.org/abs/2508.08294 https://arxiv.org/pdf/2508.08294

Epidemic Spreading with Co-infection on Long-Range Random Networks
We study a discrete-time co-infection epidemic model on spatial networks incorporating both random and long-range interactions. Using numerical analysis, we investigate how the co-infection recovery rate ($μ$), the interaction distance decay exponent ($α$), and network connectivity parameters affect epidemic persistence. Our results show that lower values of ($μ$) facilitate long-term survival, and that the presence of long-range connections ($α> 0$) robustly enhances persistence, often out…

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…

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

echoing your voice just like the ringing in my ears https://mastodon.social/@plaguepoems/114854228767889943

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…

"We can conclude that the brain has the capacity to distinguish virtual infectious patterns,
become activated,
and link this activation to a downstream response,
⭐️ resulting in systemic immunity,"
wrote Camilla Jandus, co-author of the study paper
https://www.

Human immune system reacts to the mere sight of infection
Researchers monitored brain activity when people were shown images of sick-looking avatars via VR. The brain appeared to spark an immune response.

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…

It is important to recognize how horribly *NORMAL* that is.
It's only in the past century or so that humans have had any capacity to fight infection, because we had no idea how it worked until the mid-19thC, even though we had rudimentary Smallpox vaccination (and 'variolation') earlier. We didn't have safe and effective drugs to fight *any* infection until the 20thC and didn't have useful antivirals until the 1990s.
In a sense, we're all spoiled by mode…

Clayton Cubitt (@claytoncubitt.bsky.social)
That "summer cold" you have? It's COVID. You've got COVID. It's a fact and it's still ripping through the world completely unrestrained.

Investigating Forecasting Models for Pandemic Infections Using Heterogeneous Data Sources: A 2-year Study with COVID-19
Zacharias Komodromos, Kleanthis Malialis, Panayiotis Kolios
https://arxiv.org/abs/2507.12966

Investigating Forecasting Models for Pandemic Infections Using Heterogeneous Data Sources: A 2-year Study with COVID-19
Emerging in December 2019, the COVID-19 pandemic caused widespread health, economic, and social disruptions. Rapid global transmission overwhelmed healthcare systems, resulting in high infection rates, hospitalisations, and fatalities. To minimise the spread, governments implemented several non-pharmaceutical interventions like lockdowns and travel restrictions. While effective in controlling transmission, these measures also posed significant economic and societal challenges. Although the WHO …

LLM-Based Identification of Infostealer Infection Vectors from Screenshots: The Case of Aurora
Estelle Ruellan, Eric Clay, Nicholas Ascoli
https://arxiv.org/abs/2507.23611 https…

LLM-Based Identification of Infostealer Infection Vectors from Screenshots: The Case of Aurora
Infostealers exfiltrate credentials, session cookies, and sensitive data from infected systems. With over 29 million stealer logs reported in 2024, manual analysis and mitigation at scale are virtually unfeasible/unpractical. While most research focuses on proactive malware detection, a significant gap remains in leveraging reactive analysis of stealer logs and their associated artifacts. Specifically, infection artifacts such as screenshots, image captured at the point of compromise, are large…

🇺🇦 #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

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…

Empowering Nanoscale Connectivity through Molecular Communication: A Case Study of Virus Infection
Xuan Chen, Yu Huang, Miaowen Wen, Shahid Mumtaz, Fatih Gulec, Anwer Al-Dulaimi, Andrew W. Eckford
https://arxiv.org/abs/2508.04415

Empowering Nanoscale Connectivity through Molecular Communication: A Case Study of Virus Infection
The Internet of Bio-Nano Things (IoBNT), envisioned as a revolutionary healthcare paradigm, shows promise for epidemic control. This paper explores the potential of using molecular communication (MC) to address the challenges in constructing IoBNT for epidemic prevention, specifically focusing on modeling viral transmission, detecting the virus/infected individuals, and identifying virus mutations. First, the MC channels in macroscale and microscale scenarios are discussed to match viral transm…

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…

Majority bootstrap percolation on the permutahedron and other high-dimensional graphs
Maur\'icio Collares, Joshua Erde, Anna Geisler, Mihyun Kang
https://arxiv.org/abs/2507.06597

Majority bootstrap percolation on the permutahedron and other high-dimensional graphs
Majority bootstrap percolation is a model of infection spreading in networks. Starting with a set of initially infected vertices, new vertices become infected once half of their neighbours are infected. Balogh, Bollobás and Morris studied this process on the hypercube and showed that there is a phase transition as the density of the initially infected set increases. Generalising their results to a broad class of high-dimensional graphs, the authors of this work established similar bounds on th…

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

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…

Weekend #Plankton Factoid 🦠🦐
Plankton have #parasites, just like any other organism, but in some cases, this leads to improved feeding conditions. #Daphnia zooplankton must often feed on freshwater cy…

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

Get a load of these potatoes! (It's a variety, not a fungal infection.)

Investigation of a two-patch within-host model of hepatitis B viral infection
Keoni Castellano, Omar Saucedo, Stanca M. Ciupe
https://arxiv.org/abs/2507.23038 https://

Investigation of a two-patch within-host model of hepatitis B viral infection
Chronic infection with hepatitis B virus (HBV) can lead to formation of abnormal nodular structures within the liver. To address how changes in liver anatomy affect overall virus-host dynamics, we developed within-host ordinary differential equation models of two-patch hepatitis B infection, one that assumes irreversible and one that assumes reversible movement between nodular structures. We investigated the models analytically and numerically, and determined the contribution of patch susceptib…

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…

A time-adaptive optimization approach for reconstructing immune response in a mathematical model of acute HIV infection using clinical data
L. Beilina, I. Gainova, G. Bocharov
https://arxiv.org/abs/2508.13123

A time-adaptive optimization approach for reconstructing immune response in a mathematical model of acute HIV infection using clinical data
The paper proposes a time-adaptive optimization approach for determining the time-dependent immune response function in a mathematical model of acute HIV infection, using clinical data from four untreated patients. We formulate the problem as a parameter identification problem for an immune response system of ODE which includes novel component integrated into the third equation of the classical three-equation HIV model. Tikhonov's regularization method, Lagrangian approach, from which we deri…

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…

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…

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…

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

Contact process with viral load
Marco Seiler
https://arxiv.org/abs/2507.04768 https://arxiv.org/pdf/2507.04768

Contact process with viral load
In this article, we introduce two new variants of the contact process. In the first variant, instead of just being infected, individuals carry a viral load, indicating how severe the infection is. If the viral load reaches zero, an individual is considered to be healthy and if an individual becomes infected, a viral load of 1 is assigned that evolves according to a Birth-Death process. Thus, in this model, individuals with a higher viral load are more infectious, and the recovery times, are in …

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 …

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…

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 …

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…

This approach (crippling the species with a Wallbachia infection) is an excellent one. I wish we adopted it for our problem species. https://flipboard.com/@npr/all-things-considered-ji18657oz/-/a-hfTp74UFR4yvd9JvEdSd6Q:a:3195441-/0

Brazil aims to reduce dengue with modified mosquitoes
For years, researchers have been trying to shut down a mosquito's ability to transmit certain diseases. Brazil is making a massive investment in the effort, aimed at throttling dengue levels.

Epidemic threshold and localization of the SIS model on directed complex networks
Vin\'icius B. M\"uller, Fernando L. Metz
https://arxiv.org/abs/2508.06332 https://

Epidemic threshold and localization of the SIS model on directed complex networks
We study the susceptible-infected-susceptible (SIS) model on directed complex networks within the quenched mean-field approximation. Combining results from random matrix theory with an analytic approach to the distribution of fixed-point infection probabilities, we derive the phase diagram and show that the model exhibits a nonequilibrium phase transition between the absorbing and endemic phases for $c \geq λ^{-1}$, where $c$ is the mean degree and $λ$ the average infection rate. Interestingl…

Infectious Dallas Cowboys coaching staff will have opponents' Spidey senses tingling https://www.si.com/nfl/cowboys/news/infectious-dallas-cowboys-coaching-staff-will-have-opponents-spidey-senses-tingling

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.…

Self-Supervised Joint Reconstruction and Denoising of T2-Weighted PROPELLER MRI of the Lungs at 0.55T
Jingjia Chen, Haoyang Pei, Christoph Maier, Mary Bruno, Qiuting Wen, Seon-Hi Shin, William Moore, Hersh Chandarana, Li Feng
https://arxiv.org/abs/2507.14308

Self-Supervised Joint Reconstruction and Denoising of T2-Weighted PROPELLER MRI of the Lungs at 0.55T
Purpose: This study aims to improve 0.55T T2-weighted PROPELLER lung MRI through a self-supervised joint reconstruction and denoising model. Methods: T2-weighted 0.55T lung MRI dataset including 44 patients with previous covid infection were used. A self-supervised learning framework was developed, where each blade of the PROPELLER acquisition was split along the readout direction into two partitions. One subset trains the unrolled reconstruction network, while the other subset is used for lo…

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…

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…

Under the Hood of BlotchyQuasar: DLL-Based RAT Campaigns Against Latin America
Alessio Di Santo
https://arxiv.org/abs/2506.22323 https://

Under the Hood of BlotchyQuasar: DLL-Based RAT Campaigns Against Latin America
A sophisticated malspam campaign was recently uncovered targeting Latin American countries, with a particular focus on Brazil. This operation utilizes a highly deceptive phishing email to trick users into executing a malicious MSI file, initiating a multi-stage infection. The core of the attack leverages DLL side-loading, where a legitimate executable from Valve Corporation is used to load a trojanized DLL, thereby bypassing standard security defenses. Once active, the malware, a variant of Q…

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

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…

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 …

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…

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

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…

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

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…

Distributed Kaplan-Meier Analysis via the Influence Function with Application to COVID-19 and COVID-19 Vaccine Adverse Events
Malcolm Risk, Xu Shi, Lili Zhao
https://arxiv.org/abs/2507.14351

Distributed Kaplan-Meier Analysis via the Influence Function with Application to COVID-19 and COVID-19 Vaccine Adverse Events
During the COVID-19 pandemic, regulatory decision-making was hampered by a lack of timely and high-quality data on rare outcomes. Studying rare outcomes following infection and vaccination requires conducting multi-center observational studies, where sharing individual-level data is a privacy concern. In this paper, we conduct a multi-center observational study of thromboembolic events following COVID-19 and COVID-19 vaccination without sharing individual-level data. We accomplish this by devel…

Source Detection in Hypergraph Epidemic Dynamics using a Higher-Order Dynamic Message Passing Algorithm
Qiao Ke, Naoki Masuda, Zhen Jin, Chuang Liu, Xiu-Xiu Zhan
https://arxiv.org/abs/2507.02523

Source Detection in Hypergraph Epidemic Dynamics using a Higher-Order Dynamic Message Passing Algorithm
Source detection is crucial for capturing the dynamics of real-world infectious diseases and informing effective containment strategies. Most existing approaches to source detection focus on conventional pairwise networks, whereas recent efforts on both mathematical modeling and analysis of contact data suggest that higher-order (e.g., group) interactions among individuals may both account for a large fraction of infection events and change our understanding of how epidemic spreading proceeds i…

Determining disease attributes from epidemic trajectories
Mark P. Rast, Luke I. Rast
https://arxiv.org/abs/2507.22087 https://arxiv.org/pdf/2507.22087

Determining disease attributes from epidemic trajectories
Effective public health decisions require early reliable inference of the infectious disease properties. In this paper we assess the ability to infer infectious disease attributes from population-level stochastic epidemic trajectories. In particular, we construct stochastic Kermack-McKendrick model trajectories, sample them with and without measurement error, and evaluate inversions for the population mean infectiousness as a function of time since infection, the infection duration distribution…

Replaced article(s) found for math.PR. https://arxiv.org/list/math.PR/new
[1/1]:
- Spatially dense stochastic epidemic models with infection-age dependent infectivity
Guodong Pang, Etienne Pardoux

Herd Immunity with Spatial Adaptation Based on Global Prevalence Information
Akhil Panicker, Sasidevan V
https://arxiv.org/abs/2507.20747 https://arxiv.org…

Herd Immunity with Spatial Adaptation Based on Global Prevalence Information
During an epidemic outbreak, individuals often modify their behavior in response to global prevalence cues, using spatially mediated adaptations such as reduced mobility or transmission range. In this work, we investigate the impact of distance-based adaptive behaviors on epidemic dynamics, where a fraction of the population adjusts its transmission range and susceptibility to infection based on global prevalence. We consider three adaptation scenarios: a constant adaptive fraction, a power-law…

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

Household scale Wolbachia release strategies for effective dengue control
Abby Barlow, Ben Adams
https://arxiv.org/abs/2507.23636 https://arxiv.org/pdf/250…

Household scale Wolbachia release strategies for effective dengue control
The release of Wolbachia-infected mosquitoes into Aedes aegypti infested areas is a promising strategy for localised eradication of dengue infection. Ae aegypti mosquitoes favour urban environments as breeding habitats, so are often found in and around houses. Therefore, it is likely that they will infect members of the households that they reside around. Since population groupings within households are small, stochastic effects become important. Despite this, little work has been carried out t…

Pre-exposure prophylaxis and syphilis in men who have sex with men: a network analysis
Esteban Vargas Bernal, Morgan Spahnie, William Miller, Abigail Turner, Joseph Tien
https://arxiv.org/abs/2507.19711

Pre-exposure prophylaxis and syphilis in men who have sex with men: a network analysis
Pre-exposure prophylaxis (PrEP) has been established as an effective tool for preventing HIV infection among men who have sex with men (MSM). However, there is the possibility of PrEP usage leading to increased sexual partners and increased transmission of non-HIV sexually transmitted infections such as syphilis. We take here a network perspective to examine this possibility using data on sexual partnerships, demographic data, PrEP usage, and syphilis among MSM in Columbus, Ohio. We use a recen…

Time-varying confounding in epidemic intervention evaluations
Yichi Zhang, Forrest W. Crawford
https://arxiv.org/abs/2508.13427 https://arxiv.org/pdf/2508.…

Time-varying confounding in epidemic intervention evaluations
Estimating the causal effect of a time-varying public health intervention on the course of an infectious disease epidemic is an important methodological challenge. During the COVID-19 pandemic, researchers attempted to estimate the effects of social distancing policies, stay-at-home orders, school closures, mask mandates, vaccination programs, and many other interventions on population-level infection outcomes. However, measuring the effect of these interventions is complicated by time-varying …