Jeff Sachs’ Post

🌍 On this International Day of Older Persons, we recognise the vital importance of understanding the experiences of older individuals living with ME/CFS and long COVID. Currently, there is little research focused on how these conditions impact older adults. Emerge Australia is committed to changing that. The AusME registry and biobank is inclusive, with no upper age limit for data and blood collections, ensuring that the voices and experiences of older persons are heard and contribute to advancing research and care. Together, we're working towards a future where everyone with ME/CFS receives the attention they deserve. Join the AusME Registry to accelerate research outcomes for older persons and improve the quality of life for those affected. Together, we can make a difference! 🌟 Sign up today and be a part of the change! https://lnkd.in/gqc6SHcF www.ausmeregistry.org #MECFS #InternationalDayOfOlderPersons #InclusiveResearch #PatientRegistry #Research #JoinUs

We are thrilled to share our #econometrics project, completed in just one day for the Warsaw Econometric Challenge on May 11th with our #DUMBLEDORS team Turgut Valiyev, Abdi and Yun . 💡 The main focus of the #challenge was the driving factors of Covid-19 vaccination in Poland, viewed through the lens of historical partitions. We set out to answer three key questions: Does the size of municipalities/cities impact vaccination rates? Is there a noticeable division in vaccination uptake between Eastern and Western Poland? Are there variations in vaccination rates among different age groups within the Polish population? 📌 Initially, we approached the analysis with a simple OLS regression model, but diagnostic tests indicated that this model was insufficient. Consequently, we utilized #Spatial #Regression, employing BP and Moran statistics for diagnostics. Our research findings revealed that the spatial lag model effectively accounts for potential neighborhood effects by considering spatial dependencies among observations. The coefficient estimates reveal factors influencing vaccination rates. A spatial analysis highlighted significant clustering of vaccination rates in neighboring regions, with Western parts of Poland exhibiting higher rates than the Eastern regions. This disparity may be attributed to cultural factors influenced by historical divisions and ties with countries from the pre-Russian era. 📌 While it might not be the best or advanced approach or model, we gave it our best shot during the one-day challenge, applying all our knowledge and techniques to address the questions. The #DUMBLEDORS TEAM—my friends Turgut Valiyev, Abdi, and Yun—had a lot of fun throughout the day and felt proud because "We tried it." Additionally, we want to thank our professor Rafal Wozniak, who inspired us to love #econometrics and encouraged us to participate ⭐ #econometrics #regression

Demographers, social scientists, and health scientists from across the world will come to the Population Association of America’s Annual Meeting 2024 to present their research and network. Exponent Data Scientist Ethan Roubenoff will present, “How Will COVID-19 Persist in the Future? Simulating Future Dynamics of COVID-19 Using an Agent-Based Network Model,” exploring how we might expect COVID-19 to circulate in the future and whether seasonal interventions like booster vaccines can help mitigate its potential severity. Register: https://hubs.li/Q02ssXYt0 Learn more about our Data Sciences expertise: https://hubs.li/Q02ssZ2B0 #Exponent #Event #PAA2024 #Demography #COVID19 #DataScience

What is disruptive and stabilizing selection? Population Genttics. Directional Selection occurs when selection favors one extreme trait value over the other extreme. This typically results in a change in the mean value of the trait under selection. Disruptive Selection occurs when selection favors the extreme trait values over the intermediate trait values. In this case the variance increases as the population is divided into two distinct groups. Disruptive selection plays an important role in speciation. Stabilizing Selection occurs when selection favors the intermediate trait value over the extreme values. Populations under this type of selection typically experience a decrease in the amount of additive genetic variation for the trait under selection. Youtube video: https://lnkd.in/d9QDSRQ5 \#nikolays_genetics_lessons

Despite being the fastest-growing population in the U.S., Asian American (AA) communities are the least studied group in peer-reviewed literature. An American Journal of Public Health (AJPH) editorial, co-authored by Dr. Xinzhi Zhang, underscores the importance of addressing this historical underrepresentation of Asian Americans, Native Hawaiians, and Pacific Islanders (AA NHPI) in research data and advocates for equitable and collaborative approaches to public health efforts and research. Through the AA NHPI Interest Group and the American Indian, Alaska Native, Native Hawaiian, and Pacific Islander (AI/AN NHPI) Enrichment Initiative, CEAL has adopted an integrated health equity strategy, addressing critical needs in community engagement and outreach for clinical research and public health and supporting population-specific research initiatives for AI/AN NHPI communities. Find out more: https://bit.ly/3U8oM1R #AANHPIMonth #NIHCEAL

📋 Human biomonitoring studies that are part of the #PARC Aligned Studies have already started implementing their surveys. Since 2023 and during the first quarter of 2024, the following partners started the recruitment of participants: - National Institute of Public Health (SZU) (CZ): Children (6-11 years) - Nacionalni inštitut za javno zdravje NIJZ (Sl): Children (6-11 years) and Teenagers (12-17 years) - Umweltbundesamt - German Environment Agency (DE): Adults (18-39 years) - National Public Health Centre (HU): Children (6-11 years) - Norwegian Institute of Public Health (NIPH) (NO): Teenagers (12-17 years) and Adults (18-39 years) - Universidad del País Vasco/Euskal Herriko Unibertsitatea (ES): Adults (18-39 years) “Recruiting in the post-Covid era, especially for a population-representative random sample, posed its own challenges from which we gained plenty of experience. We are delighted to see that the newly set-up components of sampling for GerES have been successfully implemented, including blood sampling and processing in the field. Established ambient sampling and monitoring were continued and also expanded, thus yielding a highly comprehensive assessment of exposure to potentially harmful substances in the general population in Germany once again.” explains Aline Murawski, deputy study lead of GerES VI at Umweltbundesamt - German Environment Agency. ℹ️ More info 👉 https://shorturl.at/oIMsA #HBM #HBM4EU #humanhealth #biomonitoring #alignedstudies

How to find population mean? The Hardy-Weinberg equation is a mathematical equation that can be used to calculate the genetic variation of a population at equilibrium. In 1908, G. H. Hardy and Wilhelm Weinberg independently described a basic principle of population genetics, which is now named the Hardy-Weinberg equation. The equation is an expression of the principle known as Hardy-Weinberg equilibrium, which states that the amount of genetic variation in a population will remain constant from one generation to the next in the absence of disturbing factors. To explore the Hardy-Weinberg equation, we can examine a simple genetic locus at which there are two alleles, A and a. The Hardy-Weinberg equation is expressed as: p2 + 2pq + q2 = 1 where p is the frequency of the "A" allele and q is the frequency of the "a" allele in the population. In the equation, p2 represents the frequency of the homozygous genotype AA, q2 represents the frequency of the homozygous genotype aa, and 2pq represents the frequency of the heterozygous genotype Aa. In addition, the sum of the allele frequencies for all the alleles at the locus must be 1, so p + q = 1. If the p and q allele frequencies are known, then the frequencies of the three genotypes may be calculated using the Hardy-Weinberg equation. In population genetics studies, the Hardy-Weinberg equation can be used to measure whether the observed genotype frequencies in a population differ from the frequencies predicted by the equation. Youtube video: https://lnkd.in/drNUqwm5 \#nikolays_genetics_lessons

So important for population health and health inequalities to convene systems leadership around practical action. Looking forward to the conversations we're going to have and the change that we are going to generate.

🌟 Exciting International Collaboration Announcement! 🌟   We're thrilled to announce a collaboration within FaCe! Together, we're exploring health interventions and care for long-term adult cancer survivors and their families. 🌿   👩🔬 Lead by the Dr. Elisabeth Coyne, the project team includes PhD Barbara Voltelen, Senior Associate Professor Cristina García-Vivar, and Professor Karin Dieperink.   🎯 OBJECTIVE: What is the current knowledge of research on health interventions/care for long-term adult survivors of cancer and their families?   🔍 Project Design: Systematic review of literature Method: Integrative literature review across English, Danish, Spanish, French languages.  Analysis: Thematic analysis of the included articles, Descriptive demographics of included articles   #Health #Interventions #CancerSurvivors #FamilyCare #Family Health #ResearchProject #SystematicReview #HealthcareAnalysis #Care