COVID ResourcesQuickly skip to the lab's prevalence & screening calculators or COVID-19 research:
- [PDF] Model-informed COVID-19 vaccine prioritization strategies by age and serostatus
- [PDF] Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance
- [PDF] Serial population based serosurvey of antibodies to SARS-CoV-2 in a low and high transmission area of Karachi, Pakistan
- [PDF] Jointly modeling prevalence, sensitivity and specificity for optimal sample allocation
- [PDF] Reductions in commuting mobility predict geographic differences in SARS-CoV-2 prevalence in New York City
- [PDF] Implications of test characteristics and population seroprevalence on 'immune passport' strategies
- [PDF] Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys
- [PDF] Case Study: Using Facebook Data to Monitor Adherence to Stay-at-home Orders in Colorado and Utah
About the lab
Larremore Lab Collaboration Graph.
The Larremore Lab focuses on developing methods of networks, dynamical systems, and statistical inference, to solve problems in biological and social systems. We try to keep a tight loop between data and theory, and learn a lot from confronting models and algorithms with real problems.
In biological systems, we focus on the spread and evolution of infectious disease. In spite of shifted focus toward COVID modeling and seroepidemiology to meet the needs of the current moment, we focus on the malaria parasite P. falciparum which evolves rapidly to evade the human immune system. Our goal is to understand the interplay between parasite evolution and human immunity, and its implications for parasite virulence, population structure, and epidemiology.
In social systems, we focus on understanding the patterns and processes that define the ecosystem of scientific research and discovery. Our goal is to combine rigorous computation, ecological theory, and social science to understand how the scientific community can be made more equitable and more productive.The Larremore Lab is led by Dan Larremore, an assistant professor at the University of Colorado Boulder in the Department of Computer Science and the BioFrontiers Institute, with an affiliation with the Department of Applied Mathematics, and with the Center for Communicable Disease Dynamics at the Harvard T.H. Chan School of Public Health. The lab is part of CU's Complex Systems Group and many students in the lab are also officers in the Boulder/Denver chapter of the Society of Young Network Scientists.
- 2020 Sept 10 - New preprint with Kate Bubar, Model-informed COVID-19 vaccine prioritization strategies by age and serostatus.
- 2020 June 25 - New COVID preprint Serial population based serosurvey of antibodies to SARS-CoV-2 in a low and high transmission area of Karachi, Pakistan.
- 2020 June 25 - New COVID preprint Surveillance testing of SARS-CoV-2 with an online calculator.
- 2020 June 18 - Our study of antibody responses to the malaria parasite among children was published in JCI Insight.
- 2020 May 26 - New COVID preprint Jointly modeling prevalence, sensitivity and specificity for optimal sample allocation.
- 2020 May 8 - New COVID preprint Reductions in commuting mobility predict geographic differences in SARS-CoV-2 prevalence in New York City.
- 2020 May 7 - New COVID preprint Implications of test characteristics and population seroprevalence on ‘immune passport’ strategies.
- 2020 Apr 20 - Launched the COVID-19 Testing Group, a community resource for sharing the latest information on COVID-19 prevalence, seroprevalence, and burden studies, planning tools, and data.
- 2020 Apr 16 - New COVID preprint Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys with an interactive calculation tool as well as code and documentation.
- 2020 Mar 25 - Joined the COVID-19 Mobility Data Network.
- 2020 Mar 9 - Dan is giving a talk on the group's malaria work at the Computational BioScience seminar at CU Med. RC1 North 6107 10:30
- 2020 Mar 3 - New paper out with Lauren Childs: Network Models for Malaria: Antigens, Dynamics, and Evolution Over Space and Time.