Complex Systems Studies

Strength and weakness of disease-induced herd immunity in networks https://www.pnas.org/doi/10.1073/pnas.2421460122 What if #herd_immunity isn’t just about how many people are immune, but how they’re 'spatially' connected? Our new PNAS paper explores this concept. We show how the topology and geometry of social networks influence the dynamics of herd immunity, whether it arises from infection or #vaccination. Here is a less technical blog post for a more general reader: abbas.sitpor.org/2025/07/10/the-spatial-puzzle-of-herd-immunity

#Postdoc Researcher on alignment of MMFM with ethical, legal, and social values. Specifically, Oxford Internet Institute https://my.corehr.com/pls/uoxrecruit/erq_jobspec_version_4.display_form?p_company=10&p_internal_external=E&p_display_in_irish=N&p_process_type=&p_applicant_no=&p_form_profile_detail=&p_display_apply_ind=Y&p_refresh_search=Y&p_recruitment_id=180757

two #PhD studentships in real-time infectious disease modelling https://www.lshtm.ac.uk/study/fees-and-funding/funding-scholarships/research-degree-funding/phd-studentships-real-time-infectious-disease-modelling

Springer Nature book on machine learning is full of made-up citations https://retractionwatch.com/2025/06/30/springer-nature-book-on-machine-learning-is-full-of-made-up-citations/

What is emergence, after all? https://arxiv.org/abs/2507.04951 We hear the word hashtag#emergence a lot—in science, philosophy, even everyday conversation—but what does it really mean? In this perspective paper, we take a clear-eyed look at emergence as it manifests in real systems, ranging from flocking birds to magnets to herd immunity in social networks. We explain how complex behaviors and patterns can emerge from simple parts interacting locally, and why these large-scale phenomena often can’t be easily understood just by looking at the pieces alone. Instead of getting lost in buzzwords, we break down the idea using concrete examples, showing that emergence isn’t magic—it’s measurable, physical, and beneficial for making sense of the multi-layered complex world we live in.

Ph.D. openings in Network Science – Minimal Subtraction https://minimalsubtraction.net/ph-d-openings-in-network-science/

#PhD Fellowship in Interdisciplinary Research on Misinformation and Pandemics https://candidate.hr-manager.net/ApplicationInit.aspx

Life ≠ alive A cat is alive, a sofa is not: that much we know. But a sofa is also part of life. Information theory tells us why https://aeon.co/essays/what-can-schrodingers-cat-say-about-3d-printers-on-mars

Micro-, meso-, macroscales: The effect of triangles on communities in networks https://journals.aps.org/pre/abstract/10.1103/PhysRevE.100.022315

What Is a Macrostate? Subjective Observations and Objective Dynamics We consider the question of whether thermodynamic macrostates are objective consequences of dynamics, or subjective reflections of our ignorance of a physical system. We argue that they are both; more specifically, that the set of macrostates forms the unique maximal partition of phase space which (1) is consistent with our observations (a subjective fact about our ability to observe the system) and (2) obeys a Markov process (an objective fact about the system’s dynamics). We review the ideas of computational mechanics, an information-theoretic method for finding optimal causal models of stochastic processes, and argue that macrostates coincide with the “causal states” of computational mechanics. Defining a set of macrostates thus consists of an inductive process where we start with a given set of observables, and then refine our partition of phase space until we reach a set of states which predict their own future, i.e. which are Markovian. Macrostates arrived at in this way are provably optimal statistical predictors of the future values of our observables.

Does Using ChatGPT Really Change Your Brain Activity? | Scientific American https://www.nature.com/articles/d41586-025-02005-y

#PhD student in Analytical Sociology - Linköping University https://liu.se/en/work-at-liu/vacancies/27064

Modelling the Dynamics of Behavioural Adaptation During Epidemics CCS Satellite 3-5 September 2025, Siena, Italy Applicants are invited to prepare a 1-page PDF (500 words max). Email your abstract to behepi.satellite@gmail.com by 20 June 2025 at 17:00 CEST time.

Today, the FDA approved a new form of PrEP, lenacapavir, a twice-a-year injectable. PrEP, or Pre-exposure prophylaxis, is 99% effective in preventing HIV. The drug could change the course of the AIDS epidemic. But the Trump administration has gutted the programs that might have paid for it in low-income countries.

The Persian plateau served as hub for Homo sapiens after the main out of Africa dispersal | Nature Communications https://www.nature.com/articles/s41467-024-46161-7

How AI chatbots are leading people into psychological crises https://www.nytimes.com/2025/06/13/technology/chatgpt-ai-chatbots-conspiracies.html?unlocked_article_code=1.O08.LDNt.2bQkdsYH8sTH&smid=url-share

Comparative evaluation of behavioral epidemic models using COVID-19 data Modeling the interplay between human behavior and infectious disease transmission remains one of the key challenges in Epidemiology. In this study, we evaluate the performance of three mechanistic behavioral epidemic models designed to address this issue. We compare data-driven and analytical approaches across the first COVID-19 wave, spanning nine diverse locations and two modeling tasks. While the optimal model may vary depending on factors such as data availability and geography, our findings show that approaches explicitly modeling behavioral feedback mechanisms often outperform data-driven approaches, even when considering data quality and the increased numbers of free parameters of these models. https://www.pnas.org/doi/10.1073/pnas.2421993122