Caroline O'Flaherty Buckee (born 1979) is an epidemiologist. She is a Professor of Epidemiology at the Harvard T.H. Chan School of Public Health. Buckee is known for her work in digital epidemiology, where mathematical models track mobile and satellite data to understand the transmission of infectious diseases through populations in an effort to understand the spatial dynamics of disease transmission. Her work examines the implications of conducting surveillance and implementing control programs as a way to understand and predict what will happen when dealing with outbreaks of infectious diseases like malaria and COVID-19.[1]
In 2010, Buckee joined the faculty at Harvard T.H. Chan School of Public Health. Her research program centers on understanding how human pathogens spread and how their spread might be controlled using a combination of genomics to understand their biology and mathematical modeling techniques to understand and forecast their spread.[5] She is particularly interested in understanding and mitigating the burden of infectious diseases among low-income populations.[6] Buckee has become known as a pioneer in digital epidemiology, taking advantage of mobile phone and satellite data to understand patterns of human travel and their impact on the spread of diseases.[7]
In 2012, Buckee's research group published a study that used mobile phone data to track the spread of malariainKenya.[7] Using data collected from text messages and cell phone calls between June 2008 and 2009, they found patterns of malaria transmission that mapped onto heavily trafficked roads. Thus, her group was able to map transmission risk, demonstrating that data derived from mobile phones were a powerful and low-cost epidemiological tool to better inform and prepare public health officials. Her group later used cell phone data from 40 million users, which was made available by the phone company Telenor, in a proof of concept study forecasting Dengue fever outbreaks in Pakistan.[2][8]
In the wake of Hurricane Maria, which devastated Puerto Rico in September 2017, Buckee worked with researchers at Carlos Albizu University to estimate the number of fatalities due to the storm.[2][9] She wanted to understand how far off the official death toll was and devised a strategy to arrive at a more accurate estimate. She and her colleagues met in Puerto Rico and surveyed over 3 thousand randomly chosen households to assess the damage and deaths caused by the storm, ultimately estimating the actual death toll was closer to 5,000 between 20 September and 31 December 2017.[9] Their calculated death toll was approximately 73 times the official fatality report.[10]
Buckee co-leads the COVID-19 Mobility Network, a coalition of infectious disease epidemiologists from over a dozen universities working to understand the coronavirus disease 2019 (COVID-19) pandemic.[11] The group is now utilising mobility data provided by Facebook's Data for Good program, which released a series of disease prevention maps for research use, both to understand the impact of social distancing measures and to utilise for contact tracing and disease forecasting.[11][12] In April 2020, she co-authored an op-edinThe Washington Post noting the various approaches to social distancing taken by different states has created a natural set of experimental conditions with which to test the efficacy of different policies.[13] She and her colleagues have since advocated for the use of aggregated and anonymised mobility data—taking into account appropriate user privacy and security measures—to understand the effectiveness of these different policies, as well as their accompanying public health messaging, in effectively executing large-scale social distancing measures.[14][15][16]
Reiner, Robert C.; Perkins, T. Alex; Barker, Christopher M.; Niu, Tianchan; Chaves, Luis Fernando; Ellis, Alicia M.; George, Dylan B.; Le Menach, Arnaud; Pulliam, Juliet R. C.; Bisanzio, Donal; Buckee, Caroline; Chiyaka, Christinah; Cummings, Derek A. T.; Garcia, Andres J.; Gatton, Michelle L.; Gething, Peter W.; Hartley, David M.; Johnston, Geoffrey; Klein, Eili Y.; Michael, Edwin; Lindsay, Steven W.; Lloyd, Alun L.; Pigott, David M.; Reisen, William K.; Ruktanonchai, Nick; Singh, Brajendra K.; Tatem, Andrew J.; Kitron, Uriel; Hay, Simon I.; Scott, Thomas W.; Smith, David L. (6 April 2013). "A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970–2010". Journal of the Royal Society Interface. 10 (81): 20120921. doi:10.1098/RSIF.2012.0921. PMC3627099. PMID23407571. Wikidata ()
Wikidata ()
