Akihiro Nishi
University of California-Los Angeles, CA·Public Health & Epidemiology·Early-career
During the COVID-19 pandemic, infections and human behavior fed back on each other. Rising cases made people anxious and prompted mask mandates or stay-at-home orders.
- Fields
Public Health & Epidemiology
Mathematics & Statistics
Social Science
- Topics
infectious disease modeling
SARS-CoV-2
epidemiology
- Grants
- 2 known grants, through Jan 2027
What they work on
- Build psychological and behavioral processes into COVID-19 epidemic models and estimate how links among emotions, behavior, policies and infections changed over time, using data from 20 U.S. metro areas, including Reddit conversations.
- Identify social, behavioral and political factors that shape people's contact patterns and policy responses, using social mixing surveys and simulations to test their effect on model predictions.
- Design new non-pharmaceutical interventions, like the dividing + balancing groups strategy, that need no actual network data, and test them with network simulations of a 10,000-person city.
- Develop network-based vaccine allocation strategies that work without real contact network data, evaluated through network simulations and mathematical modeling.
- Test whether early warning signals from nonlinear dynamical systems can anticipate COVID-19 trends, using data from 76 California counties.
More about the research
These measures slowed spread until people relaxed and infections rebounded. Understanding this loop, and how people's social contacts shape disease spread, is key to forecasting epidemics and designing policies. The research in these grants builds mathematical and simulation models that put human behavior, emotions, policies and social networks into infectious disease models.
Why it matters
COVID-19 was the third leading cause of death in the U.S. in 2020. This work could help health officials anticipate future epidemic waves and choose better policies. Before vaccines exist, it could guide interventions that slow spread while keeping schools and businesses running. Once vaccines exist, it could guide how to allocate them, strengthening preparedness for COVID-19 and emerging infectious diseases.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Lauren Gardner
Johns Hopkins University, MD·Public Health & Epidemiology
Develop an integrated mathematical framework that couples mechanistic models of infectious disease transmission with economic models of individual decision-making, so that behavior responds to the epidemic state and to policies.
Fuqing Wu
University of Texas Health Science Center at Houston, TX·Public Health & Epidemiology
Build models that connect how virus levels change inside one infected person with how the virus passes between people, so that SARS-CoV-2 levels in wastewater can be read as measures of community transmission.
Alun Lloyd
North Carolina State University, NC·Mathematics & Statistics
Measure how residents of Ibagué, Colombia differ in adopting mosquito-prevention behaviors around the home, such as water container management, and identify the cues that drive them, using observational and experimental social science methods.
The school
University of California-Los Angeles: 84 labs on PI Pages, $1.9B a year on research, 803 research doctorates a year.
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