Hands-on Minicourse on Fundamentals of Biological Physics

Biological systems operate across multiple scales, ranging from molecular signaling inside cells to population-level dynamics in ecosystems. Despite their complexity, many of these processes can be described and understood using concepts and tools from physics. In recent years, the interface between physics and biology has emerged as a vibrant interdisciplinary research frontier, combining ideas from statistical mechanics, soft matter, information theory, and dynamical systems to tackle problems in cell biology, ecology, and collective behavior.

Building on the success of the previous edition, this year’s minicourse will first introduce key theoretical and computational approaches that have proven successful in modeling and analyzing biological systems, and then move to specific problems of biological interest. The minicourse will be based on problem-based learning. Students will work in interdisciplinary groups under the guidance of the lecturers to tackle problems carefully prepared to be both challenging and instructive, often representing real, open scientific problems. Topics will include diffusion and stochastic processes, collective behavior between moving entities, cellular signaling, active matter, movement ecology and individual-based models. The hands-on sessions will be complemented by lectures that will give an overview of the area and the theoretical fundamentals of the exercises students will be tackling.

The minicourse is aimed at advanced undergraduate and early graduate students in physics or in biology with a strong quantitative background, but other interested students are also welcome to apply. No prior expertise in biological modeling is required. Participants are welcome to submit an abstract for poster presentation. We also encourage students who participated in last year’s program to apply again, as new problems, topics and groups offer new learning opportunities.

This is an initiative promoted by the Physics of Life South American Network, PoLSAN. More details on PoLSAN can be found here: www.ictp-saifr.org/polsan

Previous edition: https://www.ictp-saifr.org/mfbp2025/ 

Announcement:

Application is now closed

Lecturers & courses

• Silvina Ponce Dawson (UBA) – Cell signaling
• Pablo de Castro (IF-USP, Brazil) – Statistical Mechanics of Self-Propelled Organisms
• Rafael Menezes (ICTP-SAIFR) – Individual Based Models in Ecology

Announcement:

Application is now closed

Schedule

 The schedule might be changed.

• 1. Aparecida Molica, Kelly (Universidade Federal de Viçosa, Brazil): Clustering in living active matter

Self-organization in living matter emerges from the collective behavior of autonomous components which replicate, die, interact, and adapt to other organisms and the clustering guided by chemotaxis is a ubiquitous pattern formation mechanism in living systems. Here, a model for cell aggregation based on stochastic cellular decision making and chemotactically environment through complex communication capabilities. In particular, cell clustering guided by chemotaxis is a ubiquitous pattern formation mechanism in living systems. Here, a model for cell aggregation based on stochastic cellular decision making and chemotactically driven motility is proposed and computationally simulated.

• 2. C. Dias, Natale (Universidade Federal do Paraná, Brazil): Sexual selection only favors cooperation if there also are survival benefits involved

The evolution of cooperation in biological systems is a widely discussed subject among evolutionary biologists, but some gaps still remain, particularly in dynamics shaped by sexual selection pressures. A particular case is cooperative display coalitions, such as those exhibited by the Swallow-Tailed Manakin (Chiroxiphia caudata, Passeriformes: Pipridae), where multiple males cooperate in a courtship display that benefits only a single individual. In this project, we have developed a mathematical model in which males may or may not cooperate and females select mates for reproduction, mimicking this biological system. Our model incorporates two elements of selection: the female preference and male mortality. Both can be neutral or favor either cooperators or non-cooperators. From this framework, we have evaluated local stability for discrete time mean-field equations. Our results indicate that a comparatively lower mortality rate for cooperators (i.e., a higher relative fitness) can render cooperation an evolutionarily stable strategy. However, female preference can shift the system’s stability towards a coexistence or even a no cooperation scenario. These findings suggest that, even when there are direct benefits to cooperation, female choice remains a critical factor in the emergence and stability of cooperative behaviors in these types of systems.

• 3. Carvajal, Sara Alejandra (Universidad de Chile, Colombia): The role of topology in memory formation of fluidic Networks

Memory is the capacity of a system to store information and retrieve it at a later time. In adaptive fluidic networks, this capacity emerges from the adaptation of duct conductance, which becomes encoded in the network’s configuration and shapes its response to future flows. Recent work has shown that this memory is specifically encoded in the irreversible dynamics of the links whose conductance tends to vanish [1], and that the storage capacity of these networks is determined by the relationship between the network’s evolution time and the stimulus training time [2]. Building on the hypothesis that memory formation in network systems may be influenced by network topology, dimensionality, and the conditions of the incident flow, this work analyzes the process of memory formation in adaptive fluidic networks, evaluating how these factors affect the storage capacity developed by the system. To this end, we consider different topologies confined to two-dimensional space, subjected to varying flow conditions, with the aim of determining how the initial topology and the applied hydraulic load modify this process, and how dimensionality influences the adaptive optimization dynamics of the channels. We will present a quantitative characterization of flow-associated memory, allowing for a direct comparison of memory levels across different topologies. We will also discuss the role of weak links, that is, those whose conductance tends to vanish as a result of the irreversible breaking of connections, as a physical indicator of information storage. Finally, we will explore how the initial topology constrains the network’s evolution, delimiting the accessible final configurations and determining which structural features favor the formation and preservation of memory. This study serves as a starting point for extending these models to more complex biological systems, inspired by organisms such as Physarum polycephalum and by networks found in biological tissues, such as the liver or neural networks, whose structural organization may play an important role in information-storage mechanisms. [1] K. Bhattacharyya, D. Zwicker, and K. Alim, Phys. Rev. Lett. 129, 028101 (2022). [2] K. Bhattacharyya, D. Zwicker, and K. Alim, Phys. Rev. E 107, 034407 (2023).

• 4. Chocobar, Ezequiel Francisco (Universidad Nacional de Salta, Argentina): Stochastic dynamics of Aedes aegypti egg population under colored environmental noise

We analyze a stochastic system composed of two dynamical variables, dry eggs (E_D) and wet eggs (E_W), representing the early life stages of the Aedes aegypti mosquito. Starting from the ecological deterministic model, we incorporate precipitation variability as an external colored noise source modeled by an Ornstein–Uhlenbeck process with finite correlation time τ_c. Through a perturbative expansion around the mean rainfall, we derive effective Langevin equations and the corresponding Fokker–Planck description for population fluctuations. At first order, climatic variability does not shift the mean equilibrium but induces an effective diffusion that broadens the population distribution. At second order, the nonlinearity of the hatching function f(R) gives rise to a noise-induced drift that systematically modifies the average population. We obtain analytical expressions for the stationary variance, power spectrum, and response to periodic forcing, showing that the egg compartment acts as a low-pass filter of environmental variability. Numerical validations via Euler–Maruyama integration of the effective stochastic equations and Poisson birth–death microscopic simulations confirm the analytical predictions in the fast-noise regime (τ_c≪B^(-1)). The results highlight the role of temporal correlations in environmental forcing and provide a quantitative framework for understanding vector population dynamics under climate variability.

• 5. Da Silva, Bruno Carvalho (Pgscx/Usp/Usp, Brazil): Analysis of Complex Gene Expression Networks in Single-Cell RNA-seq

This work proposes applying the physics of complex systems to the analysis of single-cell RNA sequencing (scRNA-seq) data, focusing on the construction and characterization of complex gene expression networks. Gene relationships are established using mutual information which allows for the identification of both linear and non-linear dependencies, and Pearson correlation, used to quantify linear relationships. Comparing these networks and centrality measures, such as degree, eigenvector, closeness, and betweenness will enable the assessment of gene importance within the network organization and the investigation of their relationship with different cellular phenotypes.

• 6. Ferreira Santos, Myrna Elis (Federal University of Alagoas, Brazil): Habitat loss drives nonlinear changes in bipartite interaction networks

Understanding the stability of ecological networks in spatially structured environments remains a challenge in theoretical ecology. Specialized interactions, such as those between host plants and herbivorous insects, may be particularly sensitive to habitat loss and spatial isolation. Here, we propose a spatially explicit Individual-Based Model (IBM) to investigate how habitat loss alters the structure of bipartite plant–herbivore networks. The model represents a two-dimensional lattice in which sessile plant agents are distributed across varying proportions of suitable habitat, while mobile herbivore agents disperse through the landscape under distance constraints. Network interactions are established when herbivores successfully encounter host plants. By simulating a gradient of habitat loss, we evaluate changes in network structure, focusing on connectance and modularity. Preliminary results suggest that network topology does not deteriorate linearly with habitat loss. Instead, the system approaches a critical threshold at which dispersal limitation reduces encounter rates, leading to a nonlinear loss of connectance and increasing network fragmentation into spatially structured modules. These results suggest that interaction networks may lose structural integrity before the extinction of the interacting species, highlighting the importance of individual movement and spatial structure in determining the resilience of ecological networks.

• 7. Gutiérrez Marrero, Adriana (Universidad de Costa Rica, Costa Rica): Sputtered chitin thin films

Chitin, the second most abundant polysaccharide, presents outstanding properties for the development of a new generation of biomaterials. The deposition of thin films via magnetron sputtering allows for the modification and optimization of material properties. Therefore, this study investigates the variation in the chemical composition of chitin thin films resulting from changes in deposition conditions. The chitin target was fabricated from dried shrimp shells, which were pulverized and compressed under high pressure to obtain a disc. During deposition, variations in the RF voltage resulted in changes in the amide groups present in the chitin thin films.

• 8. Lopez Bertazza, Luciano Carlos (Instituto Balseiro, Argentina): Models of movement behaviour based on GPS data of Patagonian tortoises

Animal behaviour shows seasonal variation throughout the year. In particular, Patagonian tortoises (Chelonoidis chilensis), which are endangered due to the advance of livestock farming, their trade as pets, and the increase of predators such as wild boar, exhibit three periods with clearly differentiated behaviours: reproduction (November–January), egg-laying (February–March), and pre-brumation (March–May). Field observations show that, as the brumation period approaches, movement trajectories become restricted to a smaller set of nighttime refuges, with a significant increase in the frequency of revisits among them. In order to understand the mechanisms underlying these movement patterns, computational simulations were developed for each of the periods mentioned. A quantitative analysis of the simulated trajectories was carried out through the study of mean squared displacement (MSD), the identification of revisitation patterns, and the spatial characterisation of the refuges used. At a smaller scale, different models were tried in order to obtain a distribution for the distance travelled during a certain amount of time. This interday analysis was compared against empirical data obtained from the animals: low-sample-rate GPS tracking data and high-sample-rate accelerometer data, in order to characterise the tortoise’s behaviour at different timescales.

• 9. Mangold, Gustavo Cavichion (UFRGS, Brazil): Persistence in games

On previous work, it was noted that persistence plays a key role in cooperating, symbiotic systems within the prisoner’s dilemma framework when mutation is present. We investigate and present results on the role of a persister and how such an individual drives collective behaviour, with an inspiration in persister cell populations.

• 10. Marques, Maurício (Instituto de Física Armando Dias Tavares – UERJ, Brazil): Use of Complex Networks for the Non-Local Mapping of Dengue Cases in the State of Rio de Janeiro

This study proposes applying complex network theory to model the spatiotemporal dynamics of dengue in the State of Rio de Janeiro between 2020 and 2025, focusing on understanding non-local dispersal patterns, the impact of the unprecedented 2024 epidemic, and the influence of *Wolbachia* bacteria deployment as a biocontrol strategy. The methodology relies on constructing dynamic correlation networks based on weekly dengue incidence time series, where municipalities serve as nodes and edges represent high degrees of synchronization between their epidemic patterns. To capture propagation dynamics beyond geographic contiguity, the study employs the Motif-Synchronization technique—identifying the direction and average time lag between case peaks across municipalities—and the Time-Varying Graph (TVG) formalism to generate sequential networks, which are subsequently aggregated into a Static Aggregated Network (SAN) weighted by connection frequency over time. Analysis of the 2024 epidemic is expected to reveal increased connection density and weight, alongside the emergence of transient hubs, while the *Wolbachia* assessment will utilize interrupted time series analysis to compare the behavior of treated versus untreated municipalities. The study aims to confirm the non-local nature of dispersal—independent of geographic distance and linked to human mobility—and to identify key municipalities acting as major sources and sinks of cases, thereby serving as priority targets for surveillance and control. Ultimately, the results seek to provide evidence for redirecting containment strategies (such as “safety belts”) toward network hubs and to establish network analysis as a predictive tool for efficient resource allocation and intervention planning in the State of Rio de Janeiro.

• 11. Mosquera, Karla Nicole (Yachay Tech University, Ecuador): Bayesian Neural Networks Enhance Toxicity Prediction of Metallic Nanoparticles

Nanoparticles (NPs) have many applications, but their potential cytotoxicity poses environmental and health risks. Traditional research on their toxicity is slow and costly so it is difficult to analyze new nanomaterials. In this thesis, we develop in silico predictive models of NP cytotoxicity using machine learning and focus on predicting uncertainty. We combined physicochemical, electronic, and experimental descriptors for two in vitro cytotoxicity datasets (metal NPs and metal oxide NPs). The deterministic models are trained on 483 complete records, and the probabilistic model on 1,363. After preprocessing and feature reduction, SMOTE is applied only to the training set. The train/test split of the models was done to keep experimental replicates together so that information would not leak. We tested three classifiers (Random Forest [RF], Support Vector Machines [SVM], and Multilayer Perceptron) on 95 test cases, and all demonstrated good discrimination (ROC-AUC ~0.98). RF had the best overall performance (0.916) and linear SVM had the lowest (FNR = 0.000) (we consider no toxic NP as safe; therefore, there was the best combination of performance and sensitivity). To further evaluate the reliability of our predictive algorithm, a Bayesian Neural Network (BNN) was trained on the entire dataset, sampling the variational posterior over the weights. More than 100 NPs were evaluated, and the BNN achieved a high ROC-AUC (0.959) and ECE (0.174). Predictive confidence and data uncertainty were even higher in the toxic cases, and we found 54 doubtful NPs for future experiments. Dosage and the number of oxygen atoms were found to be the most predictive descriptors, as they are related to dose-response and oxidative stress.

• 12. Muñoz Obreque, Pamela Alejandra (Universidad de Santiago de Chile, Chile): Mathematical modeling of glycolysis in extremophiles: A study from statistical physics

This work aims to develop a kinetic and thermodynamic mathematical model of the glycolytic pathway of two extremophile microorganisms: the archaeon Pyrococcus furiosus and the bacterium Thermotoga maritima. Both microorganisms operate under extreme thermal conditions, offering an ideal scenario for studying how open dynamic systems mitigate heat dissipation and sustain their mass and energy fluxes. Using deterministic numerical simulations, a kinetic model is constructed based on in vitro measured parameters [1] to analyze the local stability and sensitivity of the network’s non-equilibrium steady states to environmental fluctuations, evaluating how macroscopic temperature constraints dictate the microscopic transition rates of each enzymatic step. This study is expected to contribute to elucidating the biophysical limits of life and provide a theoretical framework applicable to predicting metabolic behavior in scenarios that are difficult to manipulate experimentally.

• 13. Resende-Lara, Pedro Túlio (Universidade Estadual de Campinas, Brazil): Investigating the dynamical changes of Nav1.1 channels in genetic epilepsies with pyAdMD: a hybrid enhanced sampling method to explore protein dynamics

Proteins exhibit a wide array of structural and dynamic properties essential for their biological roles. These behaviors occur across multiple timescales and are modulated by environmental factors, such as temperature, solvent composition, and the presence of binding partners or membranes. A comprehensive exploration of protein conformational space is crucial for elucidating functional mechanisms; however, this task is hindered by the high dimensionality of the energy landscape. To address this challenge, we recently developed Adaptive Molecular Dynamics with Excited Normal Modes (aMDeNM)1, which utilizes the kinetic excitation of normal modes (NM) during molecular dynamics simulations. The excitation of these modes was dynamically adjusted throughout the simulation, enabling extensive sampling of the energy landscape, surpassing the limitations of fixed linear displacements, and reducing structural stress and environmental resistance. In this study, we present a robust Python framework for configuring and executing aMDeNM simulations to investigate large-scale protein motions. This updated version, Adaptive Molecular Dynamics with Python (pyAdMD), generates uniformly distributed excitation vectors, ensuring that these vectors are equidistant in Cartesian space relevant to molecular dynamics. We validated the method using human calmodulin as proof of concept, and our findings indicate enhanced conformational sampling relative to standard molecular dynamics and other enhanced sampling techniques. Notably, pyAdMD can explore multidimensional collective variables, a capability that many established enhanced-sampling methods lack2. We further applied pyAdMD to study the dynamics of the wild-type Nav1.1 channel, a key protein mediating Na+ influx in GABAergic interneurons, and 28 missense variants linked to Dravet Syndrome, a severe developmental and epileptic encephalopathy. Our analysis revealed that the highest-collectivity NMs of wild-type Nav1.1 correspond to the proposed activation motion described by Deuis et al.3. These motions facilitate the dynamic coupling of the Nav1.1 voltage-sensing subdomains, a feature absent in most variants. The observed dynamic reorganization across different channel regions indicates that residue substitutions induce both localized and global structural changes in Nav1.1. These results underscore the necessity of exploring protein conformational spaces beyond local energy barriers. The pyAdMD code and usage instructions are accessible at https://github.com/pedro-tulio/pyAdMD.

• 14. Simote Ishikawa, Bianca Yumi (IFSC/USP, Brazil): FROM INDIVIDUAL THRESHOLDS TO COLLECTIVE TIPPING: FINITE-SIZE SCALING IN HETEROGENEOUS POPULATIONS

Granovetter’s threshold model is a classical paradigm for collective dynamics, where heterogeneous individuals switch from a passive to an active state once the fraction of active peers reaches or exceeds their personal threshold. Here, we study a finite population of $N$ individuals initialized with an extensive active seed density $\rho_0$ under irreversible activation rules. Individual activation thresholds $x_i \in [0, 1]$ are independently drawn from a Beta distribution $f(x) \propto x^{\alpha-1}(1-x)^{\beta-1}$ with shape parameters $\alpha$ and $\beta$. We focus on the symmetric parabolic case $\alpha = \beta = 2$, where $f(x) \propto x(1-x)$. In the deterministic limit ($N \to \infty$), the system exhibits a hybrid phase transition associated with a saddle-node bifurcation, with critical seed density $\rho_0^c = 1/9$ and bottleneck active fraction $\rho^* = 1/4$. In finite populations, however, sample-to-sample variability in threshold realizations leads to distinct macroscopic outcomes: near criticality, some realizations stall near the bottleneck, whereas others cross it to trigger a global cascade. To characterize this variability, we introduce the crossing probability $P_{\text{cross}}$ and establish the finite-size scaling form $P_{\text{cross}} \simeq \Psi[(\rho_0 – \rho_0^c)N^{1/2}]$, where $\Psi(u)$ is a sigmoidal scaling function, implying a critical-window width $\Delta \rho_0 \sim N^{-1/2}$. Furthermore, at exact criticality $\rho_0 = \rho_0^c$, the distance from the bottleneck for stalled trajectories scales as $\rho^* – \langle \rho_\infty \rangle_{\text{stall}} \sim N^{-1/4}$. These results illustrate how microscopic threshold heterogeneity and finite population size control the predictability of collective tipping phenomena.

• 15. Solano Cabrera, César Osvaldo (Instituto de Física, Universidade de Sao Paulo, Mexico): Diffusion and steady-state collective properties of persistent particles on a ring

In this contribution we study the diffusion ABP’s in a ring through the mean-square displacement, the system exihibits different time regimes madiated by the persistence of the particles togheter the geometrical properties of the hosting media. We also report some steady-state properties related to clustering size and spatial distribution.

• 16. Solis, Tatiana Paulina (Yachay Tech University, Ecuador): Evaluation of the Anticancer Potential of Essential Oils from Ecuadorian Plants Using In Vitro Approaches

Natural products usually remain an important source of bioactive compounds with potential anticancer applications. Ecuador hosts a rich plant biodiversity that stay insufficiently explored for its therapeutic potential. This study aims to evaluate the anticancer potential of essential oils obtained from Ecuadorian plants. By comparing their effects on colorectal cancer cells (HCT-116) and non-tumorigenic fibroblasts (NIH/3T3). An initial screening was performed using Trypan Blue exclusion assays to see general cell viability following treatment with essential oils from Lippia dulcis, Lippia alba, Piper aduncum, and Piper tuberculatum. Based on these results that are just preliminary, Piper tuberculatum was selected for further investigation. Cell viability was then evaluated using MTT assays to establish dose-response curves and identify suitable concentrations for downstream analyses. Initial findings indicate that Piper tuberculatum extract reduces the viability of HCT-116 cells. However, cytotoxic effects were also observed in NIH/3T3 cells at certain concentrations. This highlighting the importance of determining a therapeutic window and further explore the biological activity. Ongoing work includes reactive oxygen species (ROS) measurements, statistical analyses, and in silico molecular docking studies to investigate the molecular mechanisms underlying the observed effects and identify potential biological targets.

• 17. Ternes, Caetano (Unicamp, Brazil): Hydrodynamic effects on dissipation in a breathing harmonic trap

Stochastic thermodynamics has traditionally relied on Markovian, memoryless descriptions of the environment surrounding a driven system. However, many realistic settings involve complex environments, in which memory effects and non-Markovianity play a significant role in the system’s dynamics and energetics. Here, we focus on one such case: the hydrodynamic coupling between a Brownian particle and its surrounding fluid, described by a Generalized Langevin Equation (GLE) with a Boussinesq-Basset memory kernel. To overcome the singular, fractional-power-law structure of this kernel, we employ a Markovian embedding scheme. Using this framework, we simulate a symmetric breathing protocol, in which the trap stiffness is ramped linearly between two values and back over an equal duration, and compare the resulting dissipated work per cycle against standard Markovian simulations. Working in dimensionless units, where the only remaining control parameter is the ratio between the fluid memory time and the particle’s momentum relaxation time, we find a crossover between two dissipation regimes: for fast protocols, hydrodynamic memory appears to reduce the total dissipated work relative to the memoryless case, with the crossover occurring close to the hydrodynamic timescale. This result is based on a limited set of parameters explored so far, and a broader analysis of the parameter space is still needed to confirm whether this behavior holds generally. Further studies will also explore different protocol shapes and extend the analysis to systems with multiple hydrodynamically coupled particles.

• 18. Valença Correia, Matheus (Universidade Federal de Pernambuco (UFPE), Brazil): Skyrmionic Metamachines in Synthetic Antiferromagnets

Biological microswimmers, molecular motors, and cilia excel at converting time-periodic, non-directional energy into directed motion and mechanical work in low Reynolds numbers, overdamped regimes. In condensed matter and spintronics, realizing autonomous, trackless micro- and nanomachines with programmable degrees of freedom remains an outstanding frontier – already explored in other areas such as active colloids. In this work, we present the design and non-equilibrium dynamics of skyrmionic metamachines based on coupled magnetic skyrmions in synthetic antiferromagnetic (SAF) multilayers. Building upon our recent demonstrations of topological stability in asymmetric multilayers [Phys. Rev. B 110, 094430 (2024)] and emergent self-propulsion in synthetic antiferromagnets [Phys. Rev. Lett. 135, 086701 (2025)], we explore how structural symmetry breaking and eigenmode resonance enable rich locomotive behaviors under uniform, time-dependent excitation fields without physical tracks or spatial potential gradients. We investigate how symmetric and asymmetric linear chains, with balanced or imbalanced number of skyrmions, and more complex 2D architectures are formed and how they can move. Our findings establish SAF skyrmion clusters as a versatile, reconfigurable platform for magnetic active matter,offering direct physical analogies to biological microscale propulsion and opening promising avenues for nanoscale cargo transport and biomimetic nanorobotics. Keywords: Magnetic Skyrmions, Synthetic Antiferromagnets, Active Matter, Low Reynolds number, Non-Equilibrium Dynamics, Collective Motion. Refs: [1] M. V. Correia, J. C. Piña Velásquez, C. C. S. Silva, Phys. Rev. B 110, 094430 (2024). [2] C. C. S. Silva, M. V. Correia, J. P. Velásquez, Phys. Rev. Lett. 135, 086701 (2025).

• 19. Vian, Gabriel (IFT – UNESP, Brazil): Does Poverty Drive the Epidemic? A Bayesian Hierarchical Spatiotemporal Model of Dengue in São Paulo, Brazil

Understanding climatic, sociodemographic, and spatial drivers is crucial for dengue prevention. We analyzed monthly dengue cases across 645 municipalities in São Paulo, Brazil (2010–2024), using a Bayesian hierarchical spatiotemporal model (INLA). The model integrated sociodemographic data, non-linear climatic effects (minimum temperature and precipitation via DLNM), epidemic autoregression, and spatial-seasonal effects. Results show socioeconomic vulnerabilities persistently amplify dengue risk: lack of garbage collection (RR=1.131), low education (RR=1.108), irregular water supply (RR=1.120), inadequate sewage (RR=1.101), and low income (RR=1.107). Short-term epidemic inertia (1-month autoregression, RR=1.961) and climatic variables also presented positive risks. By quantifying contributions from environmental, social, and autoregressive drivers, this study offers insights into São Paulo’s dengue epidemic, providing a scalable approach for other endemic regions.

Attention! Some participants in ICTP-SAIFR activities have received email from fake travel agencies asking for credit card information. All communication with participants will be made by ICTP-SAIFR staff using an e-mail “@ictp-saifr.org”. We will not send any mailings about accommodation that require a credit card number or any sort of deposit. Also, if you are staying at Hotel Intercity the Universe Paulista, please confirm with the Uber/Taxi driver that the hotel is located at Rua Pamplona 83 in Bela Vista (and not in Jardim Etelvina).

BOARDING PASS: All participants, whose travel has been provided or will be reimbursed by ICTP-SAIFR, should bring the boarding pass  upon registration. The return boarding pass (PDF, if online check-in, scan or picture, if physical) should be sent to secretary@ictp-saifr.org by e-mail.

Visa information: Nationals from several countries in Latin America and Europe are exempt from tourist visa. Nationals from Australia, Canada and USA are required to apply for a tourist visa.

Accommodation: Participants, whose accommodation will be provided by the institute, will stay at Hotel Intercity the Universe Paulista. Hotel recommendations are available here.

Power outlets: The standard power outlet in Brazil is type N (two round pins + grounding pin). Some European devices are compatible with the Brazilian power outlets. US devices will require an adapter.

Poster presentation: Participants who are presenting a poster MUST BRING A PRINTED BANNER . The banner size should be at most 1 m (width) x 1,5 m (length). We do not accept A4 or A3 paper.

Badge: You will receive an identification badge upon registration, which must be used during the entire event. Without the badge, it may not be possible to enter the venue.

Security issues: Although São Paulo is a relatively safe city, be careful when using cellphones on the street, avoid isolated areas at night, and be aware when crossing the street that cars may not stop for pedestrians. Also, please do not leave valuable items like laptops unattended even for short breaks. At the IFT-UNESP, there are storage lockers available and keys can be obtained with our secretaries.