Sara Del Valle

Sara Yemimah Del Valle is a senior scientist and mathematical epidemiologist at Los Alamos National Laboratory (LANL). Named as a 2024 Laboratory Fellow, Del Valle leads the Los Alamos Laboratory Fusion Team, where she combines internet data with satellite imagery to forecast disease outbreaks. During the COVID-19 pandemic Del Valle created a computational model that could predict the spread of COVID-19 around the United States.

Education Del Valle attended the New Jersey Institute of Technology, where she studied applied mathematics. Here she was awarded the Excellence in Mathematics Award in 1996. She earned her bachelor's degree in 2001. For her graduate studies she moved to the University of Iowa, where she developed mathematical models to describe outbreaks of smallpox. She showed that the spread of smallpox is particularly sensitive to how rapidly people self-isolate. Her early worked involved modelling the spread of severe acute respiratory syndrome (SARS) in Toronto, and accurately predicted the peak and number of people who would be infected.

Research and career Del Valle was appointed a permanent staff member at LANL after completing her postdoctoral research. Alongside the computational models, Del Valle has developed algorithms that can quantify their uncertainty.

In 2012 Del Valle studied the economic benefits of wearing face masks during the 2009 swine flu pandemic. She predicted that an unmitigated pandemic could cause over $800 billion of damage to the United States economy. She used natural language processing to capture critical information and case counts from Wikipedia articles. Del Valle believes that the history sections of Wikipedia pages not only gauge public interest, but also provide chronological information on disease incidence. Del Valle has combined internet data from Wikipedia and social media with satellite imagery and climate information to improve disease forecasting. For mosquito-borne diseases, satellite data can provide information on vegetation and surface water.

In 2019, Del Valle and co-workers won a Centers for Disease Control competition to improve flu forecasting software. As there is no historical data for SARS-CoV-2, the computational models developed by Del Valle were very different to those she had previously used understand the spread of influenza. Her models were used to inform states on social distancing guidelines and quarantine restrictions. By locking down early, New Mexico, the state that is home to the LANL, avoided a steep SARS-CoV-2 death toll. Del Valle has called for a global centre to be established that can monitor information about the spread of COVID-19.

Selected works and publications

Selected works

Selected publications