Henry Milimo’s Post

Day 3: Modeling Epidemics – How Math Helps Control Disease Spread 🦠 Ever wonder how scientists predict the spread of diseases? Epidemic modeling is a fascinating and critical field of mathematical modeling, especially in public health. These models help us understand how diseases spread, predict infection rates, and determine effective control measures. 📊 The SIR Model: A Foundation for Epidemic Predictions One common model in epidemiology is the SIR model, which divides a population into three compartments: 1. Susceptible (S) – people who are vulnerable to the disease. 2. Infectious (I) – individuals currently infected and able to spread the disease. 3. Recovered (R) – those who have recovered or are immune. By tracking the flow between these groups, the SIR model can help predict how an epidemic might evolve and how long it will last. 💡 Applications in the Real World -Pandemic Planning: Governments use these models to forecast infection peaks and manage resources. -Vaccination Strategies: Helps in identifying when and where vaccines should be prioritized. -Public Health Policy: Predicting the effect of interventions like social distancing. These models empower healthcare systems to prepare effectively, saving lives and reducing the economic impact of outbreaks. Next time you hear about "flattening the curve," know that mathematical models make it possible! #Epidemiology #MathematicalModeling #PublicHealth #DataScience #DiseaseControl #RealWorldMath #LinkedInSeries

🔬 Excited to share our "Behind the Paper" story on our recently published article in Scientific Data! When COVID-19 hit in 2020, we saw a critical gap: detailed individual-level data needed for precise epidemiological modeling was missing. Our team developed a comprehensive dataset of Taiwan's COVID-19 cases, featuring detailed contact tracing information and course of disease data for 579 cases from January to November 2020. This dataset has already proven its value, contributing to accurate forecasting of Taiwan's third COVID-19 community outbreak. We hope this work will serve as a valuable resource for researchers and policymakers facing future public health challenges. 🔗 Read the post: https://lnkd.in/gi4n2t8s #COVID19Research #DataScience #Epidemiology #PublicHealth #OpenScience #Taiwan

🔍 Why Are People Suddenly Getting COVID-19 This Summer? Insights into the Uptick 🌞 As summer gatherings commence, Americans are noticing a rise in COVID-19 cases again. Typically, we see an increase during the winter as people spend more time indoors, but this summer, the trend continues. CDC data indicates small jumps in hospitalizations, deaths, and new cases. This persistent pattern, four years into the pandemic, suggests that COVID-19 might be becoming endemic. “When you begin to see a pattern, you then might say it’s becoming endemic,” says Dr. Jessica Justman, a professor of epidemiology and medicine at Columbia University. “When something is endemic, that does not mean it’s going away. That means it’s staying around.” #COVID19 #PublicHealth #Epidemiology https://lnkd.in/dtMyAPBG

🚀 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.

It was delightful participating in the virtual webinar series held by Centers for Disease Control and Prevention , TEPHINET Secretariat , and World Hypertension League (WHL), a new 6-part FETP NCD (Non Communicable Diseases) professional development webinar series on “Research Methodology” from January 18 through June 20, 2024. The 6-part series include: 🎨Types of Studies and Risk Estimates: The differences between a case series, a cohort study, and a case-control study, including how the interpretation of the association measure differs for various study designs, the methodology to identify potential problems in epidemiologic studies that might impact findings. 🎨 Bias in Epidemiological Studies: Concept of bias, how to assess it, the concepts and assessment of random error. 🎨Confounding: Confounding and its effects on study results, the strategies to reduce confounding. 🎨Epidemiology Abnormality, Risks, and Assessment: Ways of defining abnormal and risks, including the metrics and quantification of abnormal and risks. 🎨 ROC (Receiver Operating Characteristic )Curves: Hypothesis testing with the ROC curve approach, description of the use of the ROC curve methodology and Area under the ROC curve (AUC) methodology. 🎨 Tools for Assessing Research Study Evidence – Quality of the Studies: Various methods for assessing the quality of different studies, identification of the resources and instruments for assessing study results. Thank you the WHL Faculty, Daniel Lackland michael weber Paul Whelton. It was heartwarming receiving my certificate today after the 6-part, 6-month studies. World Health Organization #epidemiology #research #training #hypertensive #NCDs #methodology #confounding #risks

Successful TB Mass Screening Event in Chitipa: A Leap Forward in Public Health From March 18th to April 5th, 2024, we embarked on a crucial public health initiative: a mass TB screening campaign across Chitipa, encompassing Chitipa town, the District Health Office (DHO), and Chitipa prison. The results are in, and they speak volumes about the impact of such programs. 🔍 Total Screened: 1,563 individuals 🧡 Total Presumptives: 217 (13.88%) 🟣 Total TB Cases Identified: 17 (7.83%) 🟢 MTB+ (Mycobacterium Tuberculosis positive): 9 🔴 Clinically Diagnosed: 8 This mass screening was not just about numbers; it was a proactive step towards safeguarding the health of our communities. Identifying 17 TB cases may seem modest, but it is profound—each case detected is a potential chain of transmission interrupted, and numerous lives improved or even saved. The significance of TB mass screening cannot be overstated. It serves as an early warning system, catches cases that would otherwise spread, and emphasizes the need for continuous investment in public health interventions. As we analyze these outcomes, let's celebrate the lives protected and remain committed to enhancing the health of our people. Your thoughts, experiences, and insights on such public health initiatives are incredibly valuable—let's discuss below. #PublicHealth #TBScreening #HealthForAll #Epidemiology #Malawi

The World Health Organization (WHO) offers a comprehensive course on the management of tuberculosis (TB) among children and adolescents. This course equips healthcare professionals with the latest guidelines and strategies for diagnosing, treating, and preventing TB in younger populations. It covers topics like epidemiology, clinical features, diagnostic methods, and tailored therapeutic approaches. By completing this course, participants gain a deeper understanding of the unique challenges and best practices in managing TB in these vulnerable groups. #WHO #TBManagement

COVID-19 has had a profound impact on our world and understanding the global response to this pandemic is crucial. That's why Dr. James Johnson and Dr. Naomi DeShore have compiled a book that provides global perspectives on health systems and policy responses to the current pandemic. "COVID-19 Global Pandemic: The World Responds" is a one-of-a-kind book that offers timely insights, descriptions, and data to help us better comprehend the pandemic and the global response to its daunting challenges. Scholars and practitioners from around the world have contributed to this book, providing multiple country and regional level responses. The discussions cover critical topics such as social determinants, the role of leadership, crisis management and preparedness, global supply chain, One Health, and disease/social epidemiology. Additionally, the book provides a comprehensive background on the disease itself, including historical context. Order your copy today at https://lnkd.in/gGmWDEim or on sentiapublishing.com to gain a better understanding of the pandemic and the global response to it. #COVID19 #GlobalResponse #HealthSystems #PolicyResponse #PandemicResponse #OneHealth #Epidemiology #CrisisManagement #Leadership #SocialDeterminants #GlobalSupplyChain #Sentiapublishing

🎉 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