Digital Epidemiology

Digital Epidemiology explores the intersection of digital technologies with public health, focusing on themes such as AI development concerns, digital contact tracing during COVID-19, the role of AI in healthcare, personalized nutrition through digital cohorts, decentralized social media platforms, and digital public health surveillance. It emphasizes the need for thoughtful regulation, privacy preservation, and the potential of AI to optimize health systems.

AI Development and Regulation Digital Contact Tracing AI in Healthcare Personalized Nutrition Decentralized Social Media Public Health Surveillance Digital Cohorts and Trials Optimizing Health Systems with AI

The hottest Substack posts of Digital Epidemiology

And their main takeaways

The dread of ChatGPT

58 implied HN points • 15 Feb 23
🕹 Technology AI Ethics Health Education
  1. Feeling dread about AI is common, even among those close to technology.
  2. Technology revolutions follow predictable patterns of early failures and eventual mass adoption.
  3. The speed of AI development is a key concern, potentially leading to irreversible damage and shifts in power dynamics.

Pausing AI development?

58 implied HN points • 01 Apr 23
🕹 Technology AI Development Ethical Concerns Regulation Future impact Debate
  1. The debate about pausing AI development focuses on concerns about next-gen AI surpassing current technology like GPT-4.
  2. Separate the message from the messenger in the discussions surrounding the call for a pause in AI development.
  3. Managing the rapid advancement of AI requires thoughtful regulation to balance progress and potential risks to society.

A Digital Cohort on Personalized Nutrition

19 implied HN points • 02 Jun 23
🔬 Science Nutrition Data Quality Recruitment
  1. The study focused on personalized nutrition with a digital cohort of 1,000+ participants tracking various data for glucose level management.
  2. Developing a digital cohort requires intricate digital infrastructure and investment in user-friendly applications for high retention rates.
  3. Data quality assessment is crucial for multi-modal data collection, and the study achieved high completion rates with a focus on improving nutrition tracking.

Why Mastodon?

19 implied HN points • 04 Apr 23
🕹 Technology Social media Open Source Decentralization User Experience Engagement
  1. Mastodon is like Twitter but open source and decentralized, making it the future of social media.
  2. Mastodon's open-source nature allows for enormous creativity with various apps and user experiences.
  3. Being decentralized, Mastodon offers users choice, control, and a niche platform with a more engaging and pleasant tone compared to mainstream social media.
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When ChatGPT is better than your doctor

19 implied HN points • 01 May 23
🏥 Health & Wellness AI Models
  1. ChatGPT can outperform doctors in providing quality and empathetic responses to patient questions.
  2. AI models interfacing directly with patients will significantly change the future of medicine.
  3. Most health-related interactions in the future may be with AI models rather than humans, requiring a focus on safety and effectiveness.

Digital Public Health Surveillance

0 implied HN points • 19 Apr 23
🏥 Health & Wellness Public Health Data Sources Challenges Future
  1. Chapter 8 of the digital epidemiology book is now released, focusing on digital public health surveillance.
  2. The chapter covers a variety of data sources like search queries, social media, and wearables.
  3. One important aspect discussed is participatory surveillance, along with future challenges and opportunities in digital public health surveillance.

The book is online

0 implied HN points • 28 Mar 23
📚 Literature Digital Epidemiology
  1. The book 'Digital Epidemiology' is now available online at www.digitalepibook.com.
  2. Seven out of ten chapters have been released, with more to come.
  3. There may be an additional chapter focusing on AI in digital epidemiology, depending on reader interest and publisher negotiations.

Digital Cohorts and Trials

0 implied HN points • 19 May 23
🔬 Science Trials Medicine Public Health
  1. Traditional cohort studies and trials are essential in modern medicine and public health for studying the relationship between exposures and outcomes.
  2. Running conventional cohorts and trials can be costly and challenging due to low participation rates, retention issues, and data collection constraints.
  3. Digital cohorts and trials are conducted digitally, collecting data electronically, which helps in remote and siteless studies, making research more accessible and cost-effective.

Digital Epidemiology Book: Table of Contents

0 implied HN points • 07 Feb 23
  1. The book on digital epidemiology aims to cater to both epidemiology experts and technical professionals interested in the field.
  2. The key philosophies of the book include prioritizing breadth over depth and emphasizing the importance of understanding traditional epidemiology in digital epidemiology.
  3. The table of contents covers a wide range of topics including epidemiology basics, infectious disease epidemiology, modeling, digital contact tracing, public health surveillance, and ethics.