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Caitlin Rivers

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Caitlin Rivers
Rivers c. 2017
Born
United States
Other namesCaitlin Yeaton
EducationUniversity of New Hampshire (BS)
Virginia Tech (MPH, PhD)
OccupationEpidemiologist
Years active2014-present
Employer(s)Johns Hopkins Bloomberg School of Public Health, Johns Hopkins Center for Health Security (current)
U.S. Army

Caitlin M. Rivers is an American epidemiologist who as Senior Scholar at the Johns Hopkins Center for Health Security and assistant professor at the Johns Hopkins Bloomberg School of Public Health, specializing on improving epidemic preparedness. Rivers is currently working on the American response to the COVID-19 pandemic with a focus on the incorporation of infectious disease modeling and forecasting into public health decision making.[1]

Early life and education[edit]

In 2011, Rivers received a bachelor's degree in anthropology from the University of New Hampshire, where she specialized in medical anthropology.[2] She has said that she became interested in public health after reading Tracy Kidder's book, Mountains Beyond Mountains, which was about anthropologist and physician Paul Farmer's work on infectious disease eradication.[3]

In 2013, Rivers received a master's degree in public health (MPH) with a concentration in infectious disease from Virginia Tech. In 2015, she received a PhD in the Genetics, Bioinformatics & Computational Biology program, where she specialized in computational epidemiology, from Virginia Tech.[4] Her thesis was on modeling emerging infectious diseases for public health support, using non-traditional, public available sources of data, such as data collected from social media and Google search terms.[5] She specifically focused on data related to outbreaks of avian influenza A (H7N9), Middle Eastern Respiratory Syndrome Coronavirus (MERS-CoV), and Ebola virus disease (EVD).

Career[edit]

During her post-graduate studies, Rivers was a graduate research assistant at Biocomplexity Institute of Virginia Tech (formerly known as the Virginia Bioinformatics Institute) in Blacksburg, Virginia, where she built infectious disease models of emerging infectious diseases including Influenza A virus subtype H7N9, Middle East respiratory syndrome-related coronavirus, and the 2014-2015 Western African Ebola virus epidemic – the latter in coordination with the U.S. Department of Defense. Rivers maintained the only source of digital repository of data during the Ebola outbreak. As part of this work she developed Python tools, interfaces, and tutorials for epidemiologists.[3]

From 2013 to 2015, Rivers was a civilian epidemiologist for the United States Army. She worked at the U.S. Army Public Health Center as part of the Science, Mathematics, And Research For Transformation (SMART) Defense Scholarship Program during her second year of her doctoral program.[3] Rivers worked on the Army's Acute Respiratory Disease Surveillance Program, where she worked with Army data to monitor and track trends in infectious diseases and pinpoint where they occur.

In 2017, Rivers became a Senior Associate at the Johns Hopkins Center for Health Security and Assistant Professor in the Department of Environmental Health and Engineering at Johns Hopkins Bloomberg School of Public Health. Her work centers on modeling outbreaks of infectious diseases to help understand how an outbreak unfolds, its trajectory, and what approaches to take to slow—and eventually stop—the spread.[6] She and her colleagues have advocated for integrating these modeling approaches in public health decision-making into an interdisciplinary field they call "outbreak science."[7] She has argued for the creation of a National Infectious Disease Forecasting Center, which would play a role similar to that of the National Weather Service and act as a primary source of epidemiological models during times of crisis, while advancing the field.[8]

COVID-19[edit]

As it emerged in late 2019, Rivers has applied her expertise in computational epidemiology to forecast the effects of the COVID-19 pandemic in the United States, using available data from previous outbreaks since the novel coronavirus. She and her colleagues used data from intensive care unit and inpatient bed needs in two Chinese cities (Wuhan and Guangzhou) to project what health care needs would be if and when the outbreak spread to the United States.[9][10] Their analysis concluded that if an outbreak similar to the scale of the outbreak in Wuhan occurred in an American city, ICU needs of COVID-19 patients alone would exceed hospital capacity.

Rivers has used Twitter as a means of communicating her analyses as new data become available, refining the public's understanding of the trajectory of the pandemic. She has collaborated with researchers at the University of Massachusetts Amherst to analyze trends in flu-like illnesses that were not influenza and, in March, found some unusual activity that may correspond to incidence of COVID-19. The study concluded that further research was necessary to determine whether the data was indeed a signal that SARS-CoV-2 was causing widespread disease in the United States.[11] She also analyzed syndromic surveillance data from outbreaks in Taiwan, Hong Kong, and Singapore and found the containment measures they were taking were actually effective at "flattening the curve" of transmission and reducing infections.[12][13]

In March 2020, she co-authored a policy proposal through the American Enterprise Institute, along with former FDA commissioners Scott Gottlieb and Mark McClellan, former FDA chief of staff Lauren Silvis, and public health expert Crystal Watson, with a step-by-step timeline on how to safely ease restrictions in the wake of the COVID-19 pandemic.[14][15] The plan outlines four phases, with triggers to move from one phase to the next, build on an epidemiology evidence base. In an op-ed that preceded the policy proposal, Gottlieb and Rivers argued that quarantining entire cities is unnecessary; instead, government officials should focus on well-coordinated mitigation measures across the country to reduce community spread.[16] Part of these mitigation measures also include providing relief for those who will be economically impacted by closures and medical costs.

Open science[edit]

Rivers is an advocate for the open science movement, particularly as it relates to matters of public health and health security. When she began modeling the Ebola virus disease epidemic in 2014, she converted data released by ministries of health into a machine-readable format and shared it openly on GitHub, an open repository for collaborative work on software and code.[17] In the wake of the Zika virus outbreak, she co-authored a perspective piece on the importance of making data sharing the norm in order to maximize readiness for public health emergencies, outlining challenges, such as the need for data standards for sharing, and potential solutions.[18][19] She has also worked to develop an ethical framework of research standards for analyzing and reporting on publicly available data, with a specific focus on data resulting from Twitter.[20]

Awards and honors[edit]

Selected works and publications[edit]

Scholia has a profile for Caitlin Rivers (Q89071989).

References[edit]

  1. ^ Shapiro, Ari; Rivers, Caitlin (17 April 2020). "An Epidemiologist Answers What Is Needed To Reopen The Country". All Things Considered. NPR.
  2. ^ Undergraduate Research Conference: April 15–30, 2011 (PDF). Durham, NH: University of New Hampshire. 2011. p. 31. Archived from the original (PDF) on 2021-08-27. Retrieved 2020-04-19. Caitlin Rivers, Anthropology; Exploring Childhood Obesity in Rural New Hampshire
  3. ^ Jump up to: a b c d "Former student begins rewarding career at Army Public Health Center". U.S. Army. 23 September 2015.
  4. ^ Rivers, Caitlin M. (March 16, 2015). Modeling of Emerging Infectious Diseases for Public Health Decision Support (Doctor of Philosophy in Genetics, Bioinformatics and Computational Biology thesis). Blacksburg, VA: Virginia Polytechnic Institute and State University. hdl:10919/52023. Open access icon
  5. ^ Young, Sean D.; Rivers, Caitlin; Lewis, Bryan (June 2014). "Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes". Preventive Medicine. 63: 112–115. doi:10.1016/j.ypmed.2014.01.024. PMC 4031268. PMID 24513169. Wikidata ()
  6. ^ "How Computer Modeling Of COVID-19's Spread Could Help Fight The Virus". NPR.org. Retrieved 2020-03-29.
  7. ^ Rivers, Caitlin; Chretien, Jean-Paul; Riley, Steven; Pavlin, Julie A.; Woodward, Alexandra; Brett-Major, David; Maljkovic Berry, Irina; Morton, Lindsay; Jarman, Richard G.; Biggerstaff, Matthew; Johansson, Michael A. (2019-07-15). "Using "outbreak science" to strengthen the use of models during epidemics". Nature Communications. 10 (1): 3102. Bibcode:2019NatCo..10.3102R. doi:10.1038/s41467-019-11067-2. ISSN 2041-1723. PMC 6629683. PMID 31308372.
  8. ^ Enserink, Martin; Kupferschmidt, Kai (2020-03-25). "Mathematics of life and death: How disease models shape national shutdowns and other pandemic policies". Science | AAAS. Retrieved 2020-03-29.
  9. ^ Li, Ruoran; Rivers, Caitlin; Tan, Qi; Murray, Megan B.; Toner, Eric; Lipsitch, Marc (2020-03-10). "The Demand for Inpatient and ICU Beds for COVID-19 in the US: Lessons From Chinese Cities". DASH at Harvard.
  10. ^ "'Flattening the curve' may be the world's best bet to slow the coronavirus". STAT. 2020-03-11. Retrieved 2020-03-30.
  11. ^ Schnirring, Lisa (14 March 2020). "US takes more big pandemic response steps; Europe COVID-19 cases soar". Center for Infectious Disease Research and Policy. University of Minnesota.
  12. ^ Branswell, Helen (20 March 2020). "How some countries are beating back the coronavirus". The Boston Globe.
  13. ^ "When will the coronavirus pandemic and social distancing end?". Science News. 2020-03-24. Retrieved 2020-03-30.
  14. ^ McGinley, Laurie; Wan, William (29 March 2020). "Experts converge on plans for easing coronavirus restrictions safely". The Washington Post.
  15. ^ "National coronavirus response: A road map to reopening". American Enterprise Institute - AEI. Retrieved 2020-03-29.
  16. ^ Gottlieb, Scott; Rivers, Caitlin M. "Opinion | Quarantining cities isn't needed. But a fast, coordinated response to covid-19 is essential". Washington Post. Retrieved 2020-03-29.
  17. ^ Perkel, Jeffrey (2016-10-06). "Democratic databases: science on GitHub". Nature News. 538 (7623): 127–128. Bibcode:2016Natur.538..127P. doi:10.1038/538127a. PMID 27708327.
  18. ^ Chretien, Jean-Paul; Rivers, Caitlin M.; Johansson, Michael A. (2016-08-16). "Make Data Sharing Routine to Prepare for Public Health Emergencies". PLOS Medicine. 13 (8): e1002109. doi:10.1371/journal.pmed.1002109. ISSN 1549-1676. PMC 4987038. PMID 27529422.
  19. ^ "Zika, Ebola emphasize need for open, public health data sharing". FierceHealthcare. Retrieved 2020-03-30.
  20. ^ Rivers, Caitlin M.; Lewis, Bryan L. (2014-08-21). "Ethical research standards in a world of big data". F1000Research. 3: 38. doi:10.12688/f1000research.3-38.v2. ISSN 2046-1402.
  21. ^ Emerging Leaders in Biosecurity Initiative: Class of 2015 Yearbook (PDF). Center for Health Security. 2015. p. 31.

External links[edit]

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