mundialis GmbH & Co. KG’s Post

🌍MOOD Final Meeting is almost here!🌍 After 4 years of intense collaboration among experts, the project is culminating in a major event that will shape the landscape of disease surveillance: The Final Scientific Conference, "Emerging Infectious Diseases in Europe: Challenges and Opportunities in Data Sharing and Modelling of Response for Improved One Health", hosted by Istituto Superiore di Sanità in Rome on November 26-27, 2024. 🧬 The MOOD project was designed to elevate how we monitor, detect, and assess infectious disease risks in Europe in an era marked by the global threats of pandemics. The event, jointly organized by Fondazione Edmund Mach, CIRAD and Istituto Superiore di Sanità, will gather epidemiologists, researchers, and health professionals under a common goal: better preparation and response to health crises. 💡 The Conference will feature: 🔵 Key sessions will focus on critical topics such as respiratory pathogens, antimicrobial resistance, climate-sensitive diseases, and Disease X. 🔵 MOOD Platform Reveal: A significant innovation showcased will be the MOOD platform prototype, a comprehensive tool offering data, code, and models for real-time surveillance and risk assessment. 🔵 Insights on technical topics including pandemic intelligence, respiratory virus phylodynamics, and antimicrobial resistance trends in Europe. 🦠Follow the #MOOD2020 journey in Rome for this central milestone in epidemic intelligence in Europe! 🇪🇺 https://lnkd.in/eTsXtZ9i? #InfectiousDisease #Surveillance #PublicHealth #MOODProject #OneHealth #Horizon2020 #Epidemiology #DataScience #GlobalHealth #EpidemicIntelligence #InfectiousDiseases  #PublicHealth #OpenData  #OpenScience  #DiseaseSurveillance  #WNV  #SpatialEpidemiology  #RiskMapping  #EnvironmentalScience #MOOD2020

One other important topic that the team of mundialis GmbH & Co. KG is involved in. #InfectiousDisease #Surveillance #PublicHealth #MOODProject #OneHealth #Horizon2020 #Epidemiology #DataScience #GlobalHealth #EpidemicIntelligence #InfectiousDiseases #PublicHealth #OpenData #OpenScience #DiseaseSurveillance #WNV #SpatialEpidemiology #RiskMapping #EnvironmentalScience #MOOD2020

Due to the recent surge in Mpox cases, I read this article to update my knowledge. 🌍🔍 Key Insights on Monkeypox Virus (MPXV) 🦠 Important findings from the Alakunle and colleagues review on MPXV highlight its evolving nature and impact on global health. Here are the key points: Alakunle E, Kolawole D, Diaz-Canova D, Alele F, Adegboye O, Moens U, Okeke MI. A comprehensive review of monkeypox virus and mpox characteristics. Frontiers in Cellular and Infection Microbiology. 2024 Mar 6;14:1360586. Ecology, Host Range, and Tissue Tropism 🌿🐾 - Reservoir Host: The natural reservoir of MPXV remains unidentified, complicating control efforts. - Host Range: Various animals can be infected, but monkeys are not the primary reservoir. - Tissue Tropism: Specific host-cell receptors influence MPXV's ability to infect different tissues, though the exact mechanisms are still under investigation. Infection Biology and Pathophysiology 🧬💉 - Replication Cycle: MPXV undergoes a complex replication process, leading to different forms of the virus (IMV, CEV, EEV) that facilitate transmission. - Immune Evasion: The virus employs strategies to evade the host immune response, complicating treatment and prevention efforts. Epidemiology 📈🌐 - Recent Trends: Since 2017, mpox cases have surged outside endemic regions, with significant outbreaks reported in 2022. - Global Impact: Countries like the USA and Brazil have reported the highest case numbers, indicating a shift in the disease's epidemiological profile. Diagnosis, Screening, Prevention, and Treatment 🩺🛡️ - Diagnosis: Enhanced diagnostic methods are crucial for timely identification of cases. - Screening: Increased surveillance, especially in resource-poor countries, is essential for tracking MPXV. - Prevention: A One Health approach is vital, integrating human, animal, and ecosystem health strategies. - Treatment: Ongoing research aims to develop effective drugs and vaccines against mpox. This review underscores the need for continued research and a collaborative approach to tackle the challenges posed by MPXV. Let's stay informed and proactive! 💪🌟 URL: https://lnkd.in/gPUrcy-b #Monkeypox #MPXV #GlobalHealth #InfectiousDiseases #OneHealth #Research #PublicHealth

🚀 **Unlocking Insights with Bifurcation Analysis in SEAIJR Models** 🌍 In the complex world of epidemiological modeling, the SEAIJR model (Susceptible, Exposed, Asymptomatic, Symptomatic, Isolated, Recovered) stands out as a powerful tool for understanding disease dynamics. One advanced technique that enhances the utility of this model is **bifurcation analysis**. 🔍 **What is Bifurcation Analysis?** Bifurcation analysis involves studying how the qualitative behavior of a system changes as parameters are varied. In the context of SEAIJR models, it helps us identify critical thresholds and transitions that can lead to significant shifts in disease dynamics. 💡 **Why is it Important?** 1. **Predicting Outbreaks**: Bifurcation analysis helps pinpoint conditions under which a disease outbreak can occur. By understanding these thresholds, we can implement preemptive measures to prevent epidemics.    2. **Understanding Stability**: It reveals insights into the stability of disease-free and endemic equilibria. Knowing whether a population is likely to return to a disease-free state or stabilize at an endemic level is crucial for long-term planning. 3. **Informing Policy**: By identifying critical points where small changes in parameters (like transmission rates or recovery rates) can lead to large changes in outcomes, policymakers can design more effective interventions. 4. **Optimizing Resources**: Health resources are often limited. Bifurcation analysis can help allocate resources more efficiently by highlighting which parameters are most sensitive and should be targeted for control measures. 📊 **Real-World Application** Imagine a situation where a new variant of a virus emerges. Using bifurcation analysis, we can study how changes in the transmission rate affect the overall dynamics of the disease. This allows us to adjust vaccination strategies, isolation protocols, and public health messaging to mitigate the impact effectively. 🌟 **Conclusion** Incorporating bifurcation analysis into the SEAIJR model is not just an academic exercise; it’s a practical approach to enhancing our understanding and control of infectious diseases. By leveraging this advanced analytical technique, we can better prepare for and respond to public health challenges, ensuring a safer, healthier future for all. #Epidemiology #PublicHealth #DataScience #BifurcationAnalysis #SEAIJRModel #HealthPolicy #InfectiousDiseases #Modeling #HealthcareInnovation

📢 Call for Book Chapters: "The Science and History of Emerging Infectious Diseases" 📢 We are thrilled to invite researchers, scholars, and professionals to contribute to our upcoming book titled "The Science and History of Emerging Infectious Diseases," to be published by the prestigious AAP CRC Press, Taylor and Francis Group. This book aims to explore the complex interplay between science and history in the context of emerging infectious diseases. We welcome high-quality chapters that delve into the historical perspectives, scientific advancements, epidemiology, and future challenges in this critical area of study. Editors: Shriyansh Srivastav, Sachin Kumar, Sumeal Ashique, Ashish Garg, and Dr. Ranjit Sah. 🔍 Submission Details: For more information on submission guidelines and deadlines, please refer to the attached flyer. #CallForChapters #InfectiousDiseases #AcademicPublishing #CRCPress #TaylorAndFrancis #ResearchOpportunity .

#ESWRT Outstanding Paper has been awarded to Cristina Mejías Molina, Anna Pico-Tomàs, Andrea Beltran-Rubinat, Sandra Martínez Puchol, Lluis Corominas, Marta Rusiñol and Sílvia Bofill Mas for their article titled ‘Effectiveness of passive sampling for the detection and genetic characterization of human viruses in wastewater’. Passive sampling approaches are becoming promising tools in wastewater-based epidemiology. Torpedo devices fitted with electronegative membranes are useful, affordable and practical tools to monitor viral pathogens in small scale scenarios (e.g. nursing homes). They can be used to study the presence of a diversity of viruses as well as to characterize the wastewater virome. 👀 Hear more from the authors in this video summarising their work 🔗 Check out the full article here: https://lnkd.in/eMqCAEBG #EnvSciOutstandingPapers #OpenAccess #EnvironmentalScience #RSCEnv

🚀 Exploring the Dynamics of Infectious Disease Spread: A New Spatial SIR Model! 🌍 A recent study by Armand Kanga and Étienne Pardoux presents an innovative approach to understanding the spread of infectious diseases through a Spatial SIR epidemic model. This model uniquely incorporates variable infectivity without requiring individual movement, providing a fresh perspective on epidemic dynamics. 🔍 Key Highlights: - The research defines empirical measures to track the states of individuals (susceptible, infectious, recovered) across various locations. - The study establishes a Law of Large Numbers, demonstrating how these measures converge as population size increases. - Unlike traditional models that often assume exponential infection durations, this new framework accounts for more realistic infection dynamics by allowing infectivity to vary over time. 📈 This work not only enhances our understanding of spatial heterogeneity in disease spread but also sets the stage for future models that may incorporate individual movement dynamics. 📚 For those interested in mathematical modeling and epidemiology, this research is a significant step forward in accurately simulating disease transmission patterns. 🔗 Stay tuned for more insights into how mathematical frameworks can inform public health strategies! #AI #Algorithms #ArtificialIntelligence #DL #DS #DataScience #DeepLearning #Epidemiology #InfectiousDiseases #ML #MachineLearning #MathematicalModeling #PublicHealth #ResearchInnovation #Tech #Technology Source: https://lnkd.in/eT4-Ugf3

🌐 ** Exploring Epidemic Dynamics in NetLogo through Agent-Based Modeling ** I am excited to talk about my latest project in agent-based modelling: developing a simulation meant to investigate infectious diseases. In this paper, a dynamic model will be developed using the NetLogo program to test the impact of interventions involving self-isolation, social distancing, and movement restrictions on viruses transmission concerning distinct populations. This model was then used in carrying out an analysis of: Intervention efficacy in lowering infection rates. Trends of mortality and immune response by demographically heterogeneous groups. Long-term containment strategies connected with population density. These insights form the backbone of the analysis that will be done for various impacts of policy on public health outcomes and understanding real-world strategies taken up for epidemic control. The project served to enhance my technical skills in not only NetLogo and agent-based modelling but also in further reinforcing my interest in epidemiological simulations related to the development of health strategies. I am looking forward to being in contact with everyone either currently working in or interested in the modelling of complex systems, epidemiology, or AI for Social Good. #AgentBasedModeling #Epidemiology #NetLogo #Simulation #AI #PublicHealth #InfectiousDiseases #ArtificialIntelligence #MScInArtificialIntelligenceAndRobotics #UniversityOfHertfordshire --- Feel free to tailor it further based on your experience or specific findings! Let me know if you'd like to highlight additional aspects of your project.

PROJECT: TUBERCULOSIS (TB) SEGMENTATION DASHBOARD 🚀 Project Overview 🚀 ✅ I recently completed a Tuberculosis (TB) Segmentation Dashboard using Power BI to visualize chest X-ray data and track Pulmonary Tuberculosis (PTB) cases. ✅ The dashboard integrates multiple visualizations to provide insights on TB severity, trends, and geographic distribution. Key features of the project include: 1️⃣ Dynamic Visualizations: 🔹 Maps: Visualized TB prevalence across regions, identifying hotspots and areas requiring urgent attention. 🔹 Bar Graphs: Presented TB case counts segmented by age, gender, and location for easy comparison. 🔹 Stacked Bar Graphs: Showed TB severity levels in different regions, highlighting the distribution of mild, moderate, and severe cases. 🔹 Line Charts: Tracked the progression of TB cases over time, visualizing trends in new infections and recoveries. 🔹 Cards: Displayed key metrics like total PTB cases, recovery rates, and mortality rates. 🔹 Slicers: Enabled dynamic filtering by region, age group, severity, and gender, allowing users to interact with the data in real-time. 2️⃣ Color-Coding & Insights: 🔹 Used red to highlight infected areas, green for healthy regions, and yellow/orange to represent regions of concern. This colour scheme helped enhance clarity and interpretation of TB-infected regions from X-ray segmentation. 🔹 The dashboard allowed for the identification of high-risk regions, trends over time, and patterns of disease spread, making it a valuable tool for healthcare professionals and decision-makers. 🔧 Skills & Tools Used: 🔹 Power BI: Advanced data visualization, dashboard creation, and interactivity features. 🔹 Data Analysis & Transformation: Cleaning and structuring TB data for meaningful insights. 🔹 Public Health Insights: Provided actionable insights on TB trends, geographic distribution, and severity levels. 💡 Impact: This project demonstrates the power of data visualization in public health, enabling faster decision-making, better resource allocation, and more effective monitoring of TB outbreaks. #DataVisualization #PowerBI #Tuberculosis #TB #PublicHealth #MachineLearning #HealthTech #DataScience #DataAnalysis #HealthInformatics #Epidemiology #HealthcareAnalytics #DiseaseDetection #XrayAnalysis #Segmentation #PublicHealthTech #MachineLearningForHealth #DataDriven #TBPrevention #HealthcareInnovation

🎉 It is a pleasure to share my latest presentation at the Infectious Disease Modelling (IDM) Conference, Bangkok, on "Leveraging Social Contact Data to Model Viral Respiratory Infections”, a project I am doing together with Prof. dr. Niel Hens and Prof. dr. Andrea Torneri at Data Science Institute (DSI) UHasselt. Using data from POLYMOD, CoMix, and the Belgian Household Contact Survey, we explore how repeated interactions and contact clustering shape transmission dynamics. Important finding: simplifying assumptions in models can affect transmission probabilities and epidemiological measures. This research highlights the importance of considering different contact processes for effective disease control strategies. Very happy to contribute to this field and open for discussion and collaboration! #Epidemiology #DataScience #IDM2024 #MathematicalModeling #InfectiousDiseases