Dr. Isaac Chun-Hai Fung is a digital health expert and an infectious disease epidemiologist. He analyses social media data for public health surveillance and health communication and uses digital technologies for public health interventions. He investigates the transmission of communicable diseases with a focus on respiratory infections and environmentally transmitted infections. He applied a variety of methods, from classical statistical methods to machine learning and mathematical modeling, to address public health problems and to provide solutions to policy-makers. He is especially interested in assisting public health agencies in their responses to public health emergencies. He is currently a guest researcher with the Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention (CDC).
Examples of his recent projects include: Surveillance of unplanned school closures through social media platforms, Analysis of social media posts pertinent to public health emergencies, such as Ebola, MERS and Zika.
Dr. Fung was a Prevention Effectiveness Fellow at the CDC (2011-13) and a postdoc at the University of Georgia Department of Epidemiology and Biostatistics (2009-11). He earned his PhD from the Department of Infectious Disease Epidemiology, Imperial College London, and his MSc in Control of Infectious Diseases from the London School of Hygiene and Tropical Medicine. He was a graduate of Trinity Hall at the University of Cambridge.
Areas of Expertise (5)
Infectious Disease Epidemiology
University of Cambridge: BA, Natural Sciences (Biological) 2003
London School of Hygiene and Tropical Medicine: MS, Control of Infectious Diseases 2005
Imperial College London: PhD, Infectious Disease Epidemiology 2009
Media Appearances (5)
How Long Will Schools Need To Stay Closed? A Pandemic Expert Weighs In
Rolling Stone online
Dr. Isaac Chun-Hai Fung is an infectious-disease epidemiologist Georgia Southern University, and he’s published science demonstrating how lengthy school shutdowns can lessen the severity of viral oubreaks. In a 2015 study modeling a potential influenza pandemic, Fung and his co-authors found that closing schools can slow the spread of disease, delay the peak of the outbreak and even reduce the total number of cases.
'Break the chain': How will Georgia halt the spread of coronavirus?
Henry Herald online
Already, epidemiologists across the world are predicting areas could see a second outbreak of coronavirus late in the year once the current wave slows down this summer, said Dr. Isaac Fung, an associate professor of epidemiology at Georgia Southern University’s Jiann-Ping Hsu College of Public Health.
YouTube advertises big brands alongside fake cancer cure videos
BBC News Services online
"We are asking corporations with people who are not experts in healthcare and public health to make those judgements on behalf of all citizens," says Isaac Chun-Hai Fung, an associate professor of epidemiology at Georgia Southern University.
Mining Of Social Media By DHS -- Another Hit To Public Health
Social media also been used to assess people’s level of understanding and reactions to specific messaging. Isaac Chun-Hai Fung expands on these uses in a review for the WHO.
That Tweet You Just Sent Could Help Predict a Flu Outbreak
NBC Mach online
“Those people who report their symptoms could have different personalities and different demographics,” says Isaac Fung, an assistant professor of epidemiology at Georgia Southern University. Fung has moved away from looking for signals in social media prior to outbreaks. Instead, he’s looking for patterns in social media reactions during outbreaks of infectious diseases.
Kamalich Muniz-Rodriguez, Sylvia K Ofori, Lauren C Bayliss, Jessica S Schwind, Kadiatou Diallo, Manyun Liu, Jingjing Yin, Gerardo Chowell, Isaac Chun-Hai Fung
Social media research during natural disasters has been presented as a tool to guide response and relief efforts in the disciplines of geography and computer sciences. This systematic review highlights the public health implications of social media use in the response phase of the emergency, assessing (1) how social media can improve the dissemination of emergency warning and response information during and after a natural disaster, and (2) how social media can help identify physical, medical, functional, and emotional needs after a natural disaster. We surveyed the literature using 3 databases and included 44 research articles. We found that analyses of social media data were performed using a wide range of spatiotemporal scales. Social media platforms were identified as broadcasting tools presenting an opportunity for public health agencies to share emergency warnings. Social media was used as a tool to identify areas in need of relief operations or medical assistance by using self-reported location, with map development as a common method to visualize data. In retrospective analyses, social media analysis showed promise as an opportunity to reduce the time of response and to identify the individuals’ location. Further research for misinformation and rumor control using social media is needed.
Andreas Handel, Joel Miller, Yang Ge, Isaac Chun-Hai Fung
If COVID-19 containment policies fail and social distancing measures cannot be sustained until vaccines becomes available, the next best approach is to use interventions that reduce mortality and prevent excess infections while allowing low-risk individuals to acquire immunity through natural infection until population level immunity is achieved. In such a situation, allowing some infections to occur in lower-risk groups might lead to an overall greater reduction in mortality than trying to protect everyone equally.
Kamalich Muniz-Rodriguez, Isaac Chun-Hai Fung, Shayesterh R. Ferdosi, Sylvia K. Ofori, Yiseul Lee, Amna Tariq, Gerardo Chowell
We computed reproduction number of COVID-19 epidemic in Iran using two different methods. We estimated R0 at 3.6 (95% CI, 3.2, 4.2) (generalized growth model) and at 3.58 (95% CI, 1.29, 8.46) (estimated epidemic doubling time of 1.20 (95% CI, 1.05, 1.44) days) respectively. Immediate social distancing measures are recommended.
Kamalich Muniz-Rodriguez, Gerardo Chowell, Chi-Hin Cheung, Dongyu Jia, Po-Ying Lai, Yiseul Lee, Manyun Liu, Sylvia K. Ofori, Kimberlyn M. Roosa, Lone Simonsen, Cecile G. Viboud, Isaac Chun-Hai Fung
COVID-19 epidemic doubling time by Chinese province was increasing from January 20 through February 9, 2020. Yet, the harmonic mean doubling time was relatively short, ranging from 1.4 (Hunan, 95% CI, 1.2-2.0) to 3.0 (Xinjiang, 95% CI, 2.0-4.9) days, with an estimate of 2.5 days (95% CI, 2.4-2.7) for Hubei.
Isaac Chun-Hai Fung, Elizabeth B Blankenship, Jennifer O Ahweyevu, Lacey K Cooper, Carmen H Duke, Stacy L Carswell, Ashley M Jackson, Jimmy C Jenkins III, Emily A Duncan, Hai Liang, King-Wa Fu, Zion Tsz Ho Tse
Image-based social media Instagram, Pinterest, Tumblr, and Flickr have become sources of health-related information and tools for health communication. No known systematic review exists that summarizes the existing research and its health implications.