TL;DR:
- AI is being used to analyze past epidemics and predict future outbreaks.
- A Canadian AI algorithm detected the new virus spreading in Wuhan, inspiring researchers at UOC and UIB to investigate new predictability models.
- The EPI-DESIGUAL project will use AI and natural language processing to conduct historical data analysis.
- The project aims to analyze text from official gazettes and daily newspapers concerning cholera, the 1918 flu pandemic, and the plague that were published in Catalonia and the Balearic Islands between 1820 and 1960.
- The project aims to contribute to decision-making by authorities and reduce economic disparities through informed public health policies.
- The results of the project will contribute to the big data analysis paradigm, potentially replacing conventional inductive reasoning methods in modern science.
Main AI News:
In the pre-pandemic world, a cutting-edge AI algorithm developed by a Canadian firm astoundingly identified a new virus that was rapidly spreading in the Chinese city of Wuhan. This demonstration of AI’s potential in predicting future epidemics sparked a group of researchers at the Universitat Oberta de Catalunya (UOC) and the University of the Balearic Islands (UIB) to investigate new predictability models and assess the longevity of epidemics’ consequences.
Joana Maria Pujadas Mora, a UOC Faculty of Arts and Humanities member and principal investigator of the EPI-DESIGUAL research project, stated, “The COVID-19 health crisis has emphasized that epidemics remain a pressing concern. Although we can’t predict their form, we possess ample information from past epidemics that can aid us in preparation.” The team, under Pujadas’ leadership, plans to harness AI’s power through machine learning and natural language processing to conduct vast historical data analysis.
The collaboration between the EPI-DESIGUAL project and the Centre for Demographic Studies will encompass an analysis of text from historical gazettes and newspapers regarding cholera, the 1918 flu pandemic, and the plague in Catalonia and the Balearic Islands, spanning the years 1820 to 1960.Pujadas emphasized, “The past serves as the ideal laboratory for preventing and preparing for future health crises that will, unfortunately, persist due to globalization, increased human-animal interactions, urbanization, and climate change.”
The 14 researchers currently working on the project are meticulously gathering information from archives for further analysis. The three-year project will culminate in the publication of results in leading scientific journals, along with other dissemination initiatives.
The EPI-DESIGUAL research project is poised to make significant strides in the field of epidemic predictability and assessment of persistent effects. With a dual objective in mind, the project endeavors to not only advance the predictability models of epidemics but also evaluate the longevity of their consequences on socioeconomic inequality, including disparities in health and demographic behaviors from a gender perspective.
As Pujadas explains, “We aim to understand how pandemics impact the birth rate and other demographic behaviors.” The ultimate goal of the project is to aid decision-making by authorities and enable effective measures in the fight against epidemics while reducing economic disparities through informed public health policies.
The project’s results are expected to make a considerable contribution to the big data analysis paradigm, which seeks to comprehend reality through massive data sets. As experts predict, data science-based research projects like EPI-DESIGUAL, with its innovative results, will eventually replace the conventional inductive reasoning methods in modern science.
Conlcusion:
The utilization of AI in analyzing past epidemics and predicting future outbreaks represents a significant opportunity for the market. The demonstration of AI’s potential in identifying the virus in Wuhan has inspired researchers to investigate new predictability models and assess the longevity of epidemics’ consequences. The EPI-DESIGUAL project, which will use AI and natural language processing to conduct historical data analysis, aims to aid decision-making by authorities and reduce economic disparities through informed public health policies.
The expected results of the project will contribute to the big data analysis paradigm, potentially replacing conventional inductive reasoning methods in modern science. This development highlights the potential for AI to play a crucial role in addressing global health challenges and highlights the growing importance of data-driven solutions in the market.
