Health News Weekly Links 5/14/2025
Politics-Proof Pandemic Preparedness; The Case for Simpler Aid; How Biologists Use AI; New Tools for Healthy Aging; Social Media and Mental Health
Economist Alex Tabarrok, on how we can prepare for future pandemics within existing political constraints.
“Abstract: The COVID-19 pandemic, despite its unprecedented scale, mirrored previous disasters in its predictable missteps in preparedness and response. Rather than blaming individual actors or assuming better leadership would have prevented disaster, I examine how standard political incentives—myopic voters, bureaucratic gridlock, and fear of blame—predictably produced an inadequate pandemic response. The analysis rejects romantic calls for institutional reform and instead proposes pragmatic solutions that work within existing political constraints: wastewater surveillance, prediction markets, pre-developed vaccine libraries, human challenge trials, a dedicated Pandemic Trust Fund, and temporary public–private partnerships. These mechanisms respect political realities while creating systems that can ameliorate future pandemics, potentially saving millions of lives and trillions in economic damage.”
Economist Rachel Glennerster, on the case for radically simplifying development aid:
“With less money (and in the US, very few staff), now is the time to radically simplify. By choosing a few highly cost-effective interventions and doing them at large scale in multiple countries, we would ensure
aid funds are spent on highly effective projects;
we benefit from the substantial economies of scale seen in development;
a much higher proportion of aid money goes to recipient countries, with less spent on consultants; and
politicians and the public can more easily understand what aid is being spent on, helping build support for aid.”
How are biologists actually using AI?
“Since 2010, the same tasks—classification, diagnosis, and segmentation—are consistently at the top.”
“Classification: Separating biological data into groups. AI/ML enables more rapid classification in cases where classes are known or unknown.
Diagnosis + Cancer Detection: Identifying or predicting disease status. AI-enabled diagnosis and detection can be faster and more sensitive.
Segmentation + Image Processing: Breaking down and preparing images (e.g. medical scans, microscope images) for analysis. AI can speed up and streamline this traditionally time-intensive process.”
Dr. Eric Topol on how the science of aging can extend the healthy portion of our lives:
“It’s estimated that at least 80 percent of cardiovascular disease cases, 40 percent of cancer cases and 45 percent of Alzheimer’s cases are preventable.”
“Beyond traditional tools such as medical records, routine lab results and imaging, doctors can draw from a range of biological clocks that help track how the body is aging. For example, scientists can now measure thousands of proteins from a single vial of blood to generate what are called proteomic organ clocks. These recently discovered clocks can estimate the pace of aging for the brain, heart, liver, kidneys and immune system.”
The image above was generated by Chat-GPT 4o.
“Layering all of this biological information with recent advances in artificial intelligence allows health providers to make increasingly sophisticated predictions about a person’s likelihood of developing a disease.”
“This level of insight can usher in a new way to approach such diseases: active surveillance paired with aggressive lifestyle changes.”
The effects of deactivating social media on mental wellbeing around election-time:
“We estimate the effect of social media deactivation on users’ emotional state in two large randomized experiments before the 2020 U.S. election. People who deactivated Facebook for the six weeks before the election reported a 0.060 standard deviation improvement in an index of happiness, depression, and anxiety, relative to controls who deactivated for just the first of those six weeks. People who deactivated Instagram for those six weeks reported a 0.041 standard deviation improvement relative to controls. Exploratory analysis suggests the Facebook effect is driven by people over 35, while the Instagram effect is driven by women under 25.”
