Year: 2025
Type: article
Abstract: The COVID-19 pandemic's lessons on the interconnectedness of human health with the natural world, social systems, and economies have been ignored with the dismantling of essential infectious-disease-monitoring programs across the world. Furthermore, over half of all infectious diseases could be made worse by climate change, complicating pandemic containment. Despite these complexities, the factors leading to pandemics are largely predictable and can be realized through a well-designed global early warning system. We have developed and deployed the first climate-informed global infectious disease platform, GeoSeeq. It integrates data from genomics, climate and environment, social dynamics, and healthcare infrastructure. It leverages community-driven modeling, modern logistics of data, and democratization of AI tools. Using the example of dengue fever in Brazil, we demonstrate how technology platforms can build global-scale precision disease detection and response systems to reduce exposure to systemic shocks, accelerate science-informed public health policies, and deliver reliable healthcare and economic opportunities.
Source: Cell Reports Sustainability
Authors: David C. Danko, John C. Papciak, James Golden, Charles Vörösmarty, Anthony Cak, Fabio Corsi, Anthony Albanese, Christopher E. Mason, Rafael Maciel-de-Freitas, Dorottya Nagy-Szakal, Xavier Rodó, Niamh B. O’Hara
Institutions: Weill Cornell Medicine, The Graduate Center, CUNY, City University of New York, Hunter College, Fundação Oswaldo Cruz, Bernhard Nocht Institute for Tropical Medicine, SUNY Downstate Health Sciences University, Institució Catalana de Recerca i Estudis Avançats, Barcelona Institute for Global Health, Cornell Tech
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $5,730
OpenAlex ID: W4413583239