Mobile Warfare: The frontline of fighting infectious diseases
The UK government released the NHS test and trace app to alert members of the public to potential exposures. There is, however, potential to collect evidence on social networks and transmission. The resulting knowledge may help to prevent the spread of covid-19 and future diseases. It is worth mentioning the ZOE Covid Symptom Study app, where users voluntarily add information, collects data on symptoms and transmission. Potentially combining the functions of these two apps could be advantageous to the public and researchers.
Tracking contact by device proximity is not a new concept. A study by Smieszek and Salathé used wireless sensor technology to map the contacts of high school students. The researchers were able to identify the so-called superspreaders of disease. Superspreaders are important in disease outbreaks as they infect more people than an average person. Superspreaders have two major characteristics: large networks with many contacts and the ability to shed high numbers of virus particles. Superspreaders in previous coronavirus outbreaks have been responsible for a large number of cases. For example, Severe Acute Respiratory Syndrome (SARS) infected 8096, killed 774 and had several super spreaders. One person in Hotel Metropole spread the virus the 13 other people, one of whom was linked to an outbreak of 128 cases in Canada. Could the track and trace app be used to identify superspreaders? Arguably not. Identification of a superspreaders social network is possible with mobile phones, but measuring virus shed is not. Thus, superspreaders are retrospectively found.
Social media could also help in the battle against infectious diseases. In a recent study, Kuchler, Russel and Stroebel used anonymous Facebook profiles of residents in a New York County to assess social networks and map these against the spread of Covid-19 in America. Many wealthy people fled to areas such as the Florida coast and ski resorts in western and central Colorado. Unsurprisingly, these areas also had high numbers of coronavirus cases. There were several other factors at play in America, such as different laws across states and the late application of control measures. So, we cannot determine that it is the movement of these individuals that caused major outbreaks across America. However, using Facebook in this way has opened up doors for epidemiologists.
Previously, Twitter enabled researchers to assess the efficacy of public health campaigns. Analysis of Martinique resident’s tweets during a Chikungunya outbreak identified public awareness and interest. This information is fundamental in making public health decisions.
Digital data gathering could be useful to gauge the public reaction to Covid-19 and the control measures in place. There is a subsection of people who believe this pandemic is fake or a hoax. Even more members of the public regularly voice their concern over various lockdowns, laws and mask-wearing guidance on social media platforms. However, only certain people use Twitter. Of these, people who agree or disagree are more likely to comment, creating a bias within the data set.
The use of the digital world to gather data for epidemiology is fraught with ethical questions. Voluntary participation is linked to sample bias. Furthermore, a tweet may not be reflective of the users’ actions. For example, someone could tweet about not wearing a mask, but wear a mask in public. Using the test and trace app to gather and keep information on anything more than potential exposure could undermine people’s confidence and trust in the government. In turn, this may reduce the number of users on the app and render it less useful. Mobile phones have the potential to identify superspreaders in large social networks, but it would be ethically questionable to restrict these people before they become infected. It is possible to use Twitter and Facebook to influence and change public health strategies by analysing how receptive the public is to control measures. It does raise the question, how would the public react to their tweet data being harvested? Some would consider this a major invasion of privacy, consequently changing the way they use social media. The digital world is a novel source of information for researchers, but it must be handled carefully. It is far too great of a resource that is far too fragile to push.
Further information and sources:
Smieszek, T. and Salathé, M. (2013). A low-cost method to assess the epidemiological importance of individuals in controlling infectious disease outbreaks. BMC Medicine 11: doi: 10.1186/1741–7015–11–35.
Wong, G., Liu, W., Liu, Y., Zhou, B., Bi, Y., Gao, G.F. (2015). MERS, SARS, and Ebola: The role of super-spreaders in infectious disease. Cell Host and Microbe 18(4):398–401.
Kuchler, T., Russel, D. Stroebel, J. (2020). The geographical spread of COVID-19 correlates with structure of social networks as measured by Facebook. The National Bureau of Economic Research Doi: 10.3386/w26990.
Bengtsson, L., Lu, X., Thorson, A., Garfield, R. and von Schreeb, J. (2011). Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: A post-earthquake geospatial study in Haiti. PLoS Medicine 8(8): e1001083. doi: 10.1371/journal.pmed.1001083.
Roche, B., Gaillard, B., Léger, L., Pélagie-Moutenda, R. Sochacki, T., Cazelles, B., Ledrans, M. … and Yébakima, A. (2017). An ecological and digital epidemiology analysis on the role of human behavior on the 2014 Chikungunya outbreak in Martinique. Scientific Report 7: https://doi.org/10.1038/s41598-017-05957-y.
