Digital surveillance in health emergencies

Digital surveillance in health emergencies


Like many of her African counterparts, Kenya faces unique challenges and opportunities in battling the Coronavirus. Due to high unemployment, many people survive on income from casual and informal employment. Such income is unpredictable, and many people in this situation have no significant savings or other buffers against periods when work is scarce. It may therefore not be practical to put major cities and towns on complete lockdown without inviting potentially unmanageable social problems. Indeed, it has so far proven difficult to close open air markets or stop (the privately owned) public service vehicles from operating. To highlight these challenges, Journalist James Smart used social media to show the difficult balance that is the life of informal traders who now have to stretch their meagre earnings to cover their daily needs, after the middle class to whom they supply their labour retreated to social distancing.

The reality of rural urban migration is that many who come to Nairobi and other town centres in search of work never really settle in the towns. Their souls are rooted in their upcountry homes, as Joe Mopero’s classic hit Naona heri nirudi nyumbani, kwa baba na mama nikawasaidie (“I’ve decided to go back to my father’s and mother’s house, to help”)reminds us. At the slightest sight of insecurity, such as the lack of income brought about by Kenya’s partial lockdown, many city dwellers will travel back home to wait it out. This, of course, presents the greatest means of spreading the Coronavirus throughout the country, and government officials have been begging people to resist from taking that trip to the countryside.

Data enthusiasts are mooting the idea of analysing movement data to track and trace the Coronavirus. Such data includes mobile phone operator data, internet location data as well as data from apps that people can voluntarily share. The Israeli firm NSO, infamous for selling surveillance software to governments, has developed a civilian software that is capable of analysing SIM card data. As explained here, the software works by tracing the Coronavirus patient’s SIM card to other SIM cards that were in close proximity. This is done through analysing mobile network operator data. It is possible for smart phone operating systems such as Android or Apple to do similar data analysis with location data of the smartphones. In countries such as Singapore, the Ministry of Health is requesting citizens to download a bluetooth-powered app that it has developed to facilitate tracing of persons who may have come into contact with Coronavirus patients if need arises.

Locally, the Ministry of Health has been sending SMS to every phone subscriber in Kenya to update them on the virus. But technology can play a much bigger role in tracing victims of the epidemic through sharing of data on the movement of persons of interest. It can also be used to draw maps of instances of the disease, and this would greatly help in directing public resources where they are most needed. However, it is not lost to many that we are in a data economy, and even in an emergency, data can still be misused, or mined for unlawful processing. How then should data collected in emergencies be processed, stored, and used once the emergency is resolved? Fortunately, Kenya (along with many countries in Africa) has a legal framework that should guide data processing in this emergency.

Article 31 of the Constitution protects everyone from unnecessary intrusion into their private affairs including their communications. In addition, the Data Protection Act that was enacted last year envisages that all data processing activities in Kenya shall be done in a lawful and fair manner with the highest regard for people’s privacy. The Act also provides specific provisions that would be useful in this situation, such as requiring that data is kept no longer than is needed for the specific purpose of collection.  Unfortunately, the Act has not been operationalised and there is, as yet, no office to oversee data protection activities in the country. As this is the first public interest and emergency situation we are facing since enactment of the law, it would be of great service for the Cabinet Secretary ICT to issue guidance on data sharing for public interest. Some of the issues the guidance should cover include:

Data protection principles: It should be noted that an emergency does not exempt any player from data protection principles such as lawful processing, being very specific on data to be accessed, not collecting more data than is necessary, taking care to collect accurate data, not identifying people unless there is need to do so, and not transferring the data outside Kenya.

Sensitivity: Location data is quite sensitive, as is health data. Processing of such data should be done not only in accordance with the data protection principles but also with regard and consultation with affected persons where possible.

Transparency: That any person or organization, including government and the private sector, is accessing mobile network data or any other movement data should be known to the public. This will be important in post epidemic evaluation of how data was used as well as monitoring issues such as whether actors who accessed the data retained it without a legitimate reason.

Assessment: Even during the crisis, data sharing should be assessed for necessity and proportionality. For example, as there is a centralised tracing mechanism, it would be necessary to access whether and to what extent decentralised actors such as county health committees should access movement data. If there are other means for actors to achieve the same objective without being intrusive, then those means should be applied.

Reassessment: Access to movement data should be for limited periods. Need for further access can be reassessed periodically. 

There is every reason to remain hopeful that we shall overcome the epidemic, and we should use this public emergency to set good data sharing practices that are centred around the wellness of people. We should also protect ourselves against data harvesting that may put us at risk later on. In addition, as much as we may leverage on technology, we should also not forget that we live in communities that have working mechanisms for dealing with tragedies. For example, many middleclass people who still have income are sustaining their extended families and other relations through mobile money transfers and packages that are couriered by public service vehicles. Plot and estate leaders are sending prayers, humour, words of encouragement and government communication through Whatsapp groups. Many others are obeying government directives on social distancing to the extent they are able to. These social actions and interactions are strengths to be relied upon for tracing of persons, should that need arise.

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