In my digital health research, I have collaborated with: Prof. Lauren Bayliss (Communication arts, Georgia Southern) Prof. Jingjing Yin (Biostatistics, Georgia Southern), Prof. Zion Tse (Engineering, University of York), Prof. King-Wa Fu (Journalism and Media Studies Centre, University of Hong Kong), and Prof. Hai Liang (School of Journalism and Communication, Chinese University of Hong Kong). Previously, I also collaborated with Prof. Corey H. Basch (Department of Public Health, William Paterson University) on YouTube studies. I also worked with colleagues in CDC on a few publications. 

Researchers in the CDC have been using online systematic searches to identify unplanned closures of K-12 schools in the US. Our research has demonstrated that utilizing social media platforms, such as Twitter, can help them to identify unplanned school closure announcements that were previously unidentified.

• Jackson, Mullican, et al. (2020) Unplanned closure of public schools in Michigan, 2015-2016: Cross-sectional study on rurality and digital data harvesting. Journal of School Health. 90(7):511-519. 

• Ahweyevu, Chukwudebe, Buchanan et al. (2020) Using Twitter to Track Unplanned School Closures: Georgia Public Schools, 2015-17. Disaster Medicine and Public Health Preparedness. 

Back in 2013, Isaac Fung was part of a team of CDC epidemiologists who used Weibo to monitor online official outbreak information released by the Chinese government during the H7N9 outbreak in China. Later, as Isaac moved to Georgia Southern from CDC, he began his collaboration with Dr. Tse and Dr. Fu. 

As Dr King-Wa Fu is a leading expert in Weibo research, our consortium published three papers that studied Chinese social media users' reaction to a number of health issues:

    (a)  news about the MERS-CoV outbreak in Europe/Middle East in 2012, and the outbreak of human infections of avian influenza A(H7N9) in China in 2013. 

    (b)  information about 42 notifiable infectious diseases in China. 

    (c)  Global Handwashing Day 2012. 

In 2014, our consortium published a letter in The Lancet on  Ebola and the social media (Fung, Tse, Cheung, Miu, Fu, 2014). We suggested that the elevated Twitter and Google Trends response pertinent to Ebola in October 2014 was really due to people's reactions to the several cases in the United States and were not related to the epidemiology of Ebola in West Africa. We also studied information and misinformation about Ebola on Twitter and Weibo in August 2014 (Fung et al., 2016, Public Health Reports). Our study is the only study that compared Twitter data with Weibo data pertinent to Ebola. We have written a systematic review on Ebola and social media (Fung et al., 2016, American Journal of Infection Control). 

In collaboration with the CDC and colleagues in Hong Kong, we analyzed how Ebola information spread on Twitter and found that they spread via a broadcasting model rather than via viral spreading (Liang et al., 2019, BMC Public Health).

In summer 2015, South Korea experienced an outbreak of Middle East Respiratory Syndrome. We analyzed MERS-related Twitter data of five different languages, identify their differences in their keyword use, co-occurring hashtags, sources of information (embedded URL links), etc. (Zeng, Fung et al., Infection, Disease & Health). We argued that there are different linguo-cultural groups on Twitter, and people who used different languages on Twitter reacted to the same outbreak in different manner.

In 2016, our consortium has analyzed social media pertinent to Twitter:

• • Twitter data  (Fu et al., 2016, American Journal of Infection Control).

  • Instagram and Pinterest data (Fung, Blankenship et al., Disaster Medicine and Public Health Preparedness)

  • YouTube data (Basch, Fung et al., Journal of Preventive Medicine and Public Health).

Our consortium published 2 review papers related to natural disasters and social media research:

2016: Public Health Implications of Social Media Use During Natural Disasters, Environmental Disasters, and Other Environmental Concerns (Finch, Snook, Duke et al., 2016, Natural Hazards). 

2020: Social media use in emergency response to natural disasters: a systematic review with a public health perspective. (Muniz-Rodriguez et al., 2020, Disaster Medicine and Public Health Preparedness). 

Our consortium has worked on YouTube data pertinent to

• • cupping therapies (Yin, Basch et al., 2017 Alternative Therapies in Health and Medicine) 

  • diabetic retinopathy (Basch, Fung et al., 2016, JMIR Diabetes)

  • Eastern Equine Encephalitis (Basch, Blankenship, Goff, et al., 2018, Infection, Disease & Health)

  • lead poisoning (Basch, Jackson et al., 2017, The International Journal of Occupational and Environmental Health).

  • Lyme disease (Basch, Mullican, Boone et al., 2017, Osong Public Health and Research Perspectives)

  • temporomandibular joint disorder (Basch, Yin, Walker et al., 2018, Journal of Oral Rehabilitation)

  • tinnitus (Basch, Yin et al., 2018, Noise and Health)

  • weight loss (Basch, Fung et al., 2017 Public health)

We also commented on how we may facilitate the conversion of Big Data into public health applications (Fung, Tse & Fu, 2015, Science), why cyber-attack risk is low for medical devices (Tse, Xu, Fung & Wood, 2015, Science), and on why using social media to monitor adverse reactions to vaccine would be difficult in China (Fung, Cheung, Fu, Ip & Tse, 2016, American Journal of Infection Control).

Cholera, typhoid and sanitation 

While in CDC as a Prevention Effectiveness Fellow, Isaac completed a review of cholera mathematical models (Fung, 2014, Emerging Themes in Epidemiology) and a modeling study pertaining to cholera control in Haiti (Fung, Fitter, et al., 2013, American Journal of Tropical Medicine & Hygiene). 

Here at Georgia Southern, Isaac's team has published a review on the historical development of typhoid mathematical models (Bakach, Just, Gambhir & Fung, 2015, Transactions of Royal Society of Tropical Medicine & Hygiene) and a modeling study on the impact of shared sanitation facilities on diarrheal diseases with and without an environmental reservoir (Just, Carden, Li, Baker, Gambhir, Fung, 2018, Pathogens and Global Health)

Ebola

Isaac provides technical support to the CDC modeling team in their emergency response to the 2014-16 Ebola epidemic in West Africa (Meltzer et al., Modeling in Real Time During the Ebola Response, MMWR Supplements, 2016, 65(3):85-89) My team and collaborators published a review on transmission models of historical (pre-2014) Ebola outbreaks (Drake et al., 2015, Emerging Infectious Diseases).

Isaac offers technical support to the Health Economics & Modelling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, CDC. He has received CDC funding support for his service in the academic years of 2015-17, and 2018-2020.

According to the WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation 2010 report, 13% of the world population (884 million) do not have access to "improved" drinking water sources and 37% of humanity (2.6 billion) do not have access to "improved" sanitation. Without access to water and sanitation, it is difficult to maintain a high standard of personal hygiene. People living in such conditions are more likely to be infected with various infectious diseases.

Cholera 

While in CDC as a Prevention Effectiveness Fellow, Isaac completed 2 related papers:

• a review of cholera mathematical models (Fung, 2014, Emerging Themes in Epidemiology) 

• a modeling study pertaining to cholera control in Haiti (Fung, Fitter, et al., 2013, American Journal of Tropical Medicine & Hygiene). 

Typhoid

In collaboration with Prof. Manoj Gambhir (Monash University), Isaac and his two Mathematics graduate assistants, have published a review on the historical development of typhoid mathematical models (Bakach, Just, Gambhir & Fung, 2015, Transactions of Royal Society of Tropical Medicine & Hygiene). 

Gender, WASH and diarrheal diseases

Isaac team's published the following papers on the role of gender in WASH and diarrheal diseases

• Sevilimedu et al., Gender-based differences in water, sanitation and hygiene-related diarrheal disease and helminthic infections: a systematic review and meta-analysis, Transactions of the Royal Society of Tropical Medicine and Hygiene, 2017

• Caruso, Sevilimedu, Fung, Patkar and Baker, Gender disparities in water, sanitation and global health (The Lancet, 2015, correspondence).

Shared sanitation

Shared sanitation facilities reduce environmental contamination by some diarrhea-causing pathogens but increase person-to-person transmission by other pathogens via unhygienic latrine environment as fomites:

• Just, Carden, Li, Baker, Gambhir and Fung (2018) The impact of shared sanitation facilities on diarrheal diseases with and without an environmental reservoir: a modeling study (Pathogens and Global Health)

In 2005, under the supervision of Prof. Peter Vickerman and his colleagues, Isaac Fung used a mathematical model (created by Vickerman) to study the cost-effectiveness of an HIV interevention program among female sex workers in Ahmedabad, Gujarat, India (Fung et al., 2007), as his MSc thesis in LSHTM.

From 2005-09, under the supervision of Prof. Geoff Garnett and Prof. Frank de Wolf, Isaac Fung wrote a mathematical model of HIV within-host dynamics to study the phenomenon of superinfection of heterologous strains of HIV (Fung et al., 2010) and viral blips (transient detection of HIV in blood among patients whose viral load had been suppressed to an undetectable level by antiviral therapy) (Fung et al., 2012), as his PhD thesis (PDF) in Imperial College London.

When he was a CDC Prevention Effectiveness Fellow (2011-13), Isaac Fung studied the federal expenditure of the US vaccine campaign during the influenza pandemic, 2009-10. His paper was an internal CDC white paper. Isaac had some involvement in the CDC response to H3N2v in 2012 and MERS-CoV in 2013. He has also collaborated with colleagues in China CDC on a health economics project related to influenza vaccination (Zhou et al., 2014).

Isaac Fung has a long-standing interest in promoting the use of non-English epidemiology journals as potential sources of data. He believes that for systematic reviews of intervention effectiveness or disease burden, journal publications in all the major languages should be included to avoid language bias (if you can put together a team of multilingual speakers). He has published a few articles on this topic, including 

1. A detailed analysis of Chinese language epidemiology journals in 2008 (Fung, 2008)

   1. A paper on French, German and Italian epidemiology journals (Baussano et al., 2008) (as senior author who coordinated 3 teams of co-authors to write the paper)

   2. A paper on citation of non-English peer review publications (Fung, 2008)

   3. An editorial on encouraging translation of abstracts into other languages (Fung, 2008)

   4. An editorial on non-English epidemiological literature (Fung, 2008)

   5. An invited Viewpoint article in the European Journal of Public Health on the future public health journal in (non-English) European languages (Fung, 2010)