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At the height of the West African Ebola epidemic, West African governments and Mobile Network Operators (MNOs) were barraged with requests from international humanitarian and Western data analytics agencies to provide Call Detail Record data. This data could furnish the large-scale ambitions of data modelling to track and predict contagion. Despite its utility in tracking mobility and, as such, disease, CDR’s use raises many privacy concerns. In addition, embedded within a turn towards datafication, CDR technologies for surveillance embed specific ontologies of the data-focused society they emerge from. There is a false equivalence embedded in the relationship between humans and technology. The predominantly Western idea that one phone equals one person underlines the claim that CDR data accurately tracks distinct user movements, encoding a Western “phone self-subjectivity” (Erikson 2018). However, the refusal by some African actors to hand over sensitive mobile data to international agencies was met with forceful rhetoric of Africa’s moral obligation to comply—to forgo privacy rights in the name of ‘safety.’ The Ebola context reflects an emergent digitization of emergencies in the Global South, which is reshaping the way societies understand and manage emergencies, risk, data, and technology. The big data frenzy has seen a rising demand to test novel methods of epidemic/pandemic surveillance, prediction, and containment in some of the most vulnerable communities. These communities lack the regulatory and infrastructural capacity to mitigate harmful ramifications. With this emergence is a pivot towards 'humanitarian innovation,' where technological advancements and corporate industry collaboration are foregrounded as means to enhance aid delivery. In many ways, these narratives of innovation and scale replicate the language of Silicon Valley’s start-up culture. Surveillance of the poor and disempowered is carried out under the guise and rhetoric of care. In this scenario, market ideals and data technologies (re)construe social good as dependent on the “imposition of certain unfreedoms” as the cost of protection (Magalhaes and Couldry 2021). As big data technologies, they foreground a convergence of market logistics and global networks with existing and already problematic international humanitarian infrastructures (Madianou 2019). These convergences create new power arrangements that further perpetuate an unequal and complex dependency of developing countries on foreign organizations and corporations. Pushback against these data demands showcases competing notions of where risk truly lies. While resistance to data demands was at the state level, community responses to imposed epidemic regulations ranged from non-compliance to riots. These resistances demonstrated how the questions of ‘who and what is a threat?’ or ‘who and what is risky?’ and ‘to whom?’ experience shifting definitions in relation to these technologies as global, national, and community imaginaries are reinforced and reproduced as cultural, political, as well as biological units. 

Source

Akinwumi, Adjua. 2023. "Technological care vs Fugitive care: Exploring Power, Risk, and Resistance in AI and Big Data During the Ebola Epidemic." In 4S Paraconference X EiJ: Building a Global Record, curated by Misria Shaik Ali, Kim Fortun, Phillip Baum and Prerna Srigyan. Annual Meeting of the Society of Social Studies of Science.

(MNOs) were barraged with requests from international humanitarian and Western data analytics agencies to provide Call Detail Record data. This data could furnish the large-scale ambitions of data modelling to track and predict contagion. Despite its utility in tracking mobility and, as such, disease, CDR’s use raises many privacy concerns. In addition, embedded within a turn towards datafication, CDR technologies for surveillance embed specific ontologies of the data-focused society they emerge from. There is a false equivalence embedded in the relationship between humans and technology. The predominantly Western idea that one phone equals one person underlines the claim that CDR data accurately tracks distinct user movements, encoding a Western “phone self-subjectivity” (Erikson 2018). However, the refusal by some African actors to hand over sensitive mobile data to international agencies was met with forceful rhetoric of Africa’s moral obligation to comply—to forgo privacy rights in the name of ‘safety.’ The Ebola context reflects an emergent digitization of emergencies in the Global South, which is reshaping the way societies understand and manage emergencies, risk, data, and technology. The big data frenzy has seen a rising demand to test novel methods of epidemic/pandemic surveillance, prediction, and containment in some of the most vulnerable communities. These communities lack the regulatory and infrastructural capacity to mitigate harmful ramifications. With this emergence is a pivot towards 'humanitarian innovation,' where technological advancements and corporate industry collaboration are foregrounded as means to enhance aid delivery. In many ways, these narratives of innovation and scale replicate the language of Silicon Valley’s start-up culture. Surveillance of the poor and disempowered is carried out under the guise and rhetoric of care. In this scenario, market ideals and data technologies (re)construe social good as dependent on the “imposition of certain unfreedoms” as the cost of protection (Magalhaes and Couldry 2021). As big data technologies, they foreground a convergence of market logistics and global networks with existing and already problematic international humanitarian infrastructures (Madianou 2019). These convergences create new power arrangements that further perpetuate an unequal and complex dependency of developing countries on foreign organizations and corporations. Pushback against these data demands showcases competing notions of where risk truly lies. While resistance to data demands was at the state level, community responses to imposed epidemic regulations ranged from non-compliance to riots. These resistances demonstrated how the questions of ‘who and what is a threat?’ or ‘who and what is risky?’ and ‘to whom?’ experience shifting definitions in relation to these technologies as global, national, and community imaginaries are reinforced and reproduced as cultural, political, as well as biological units. 

Akinwumi, Adjua. 2023. "Technological care vs Fugitive care: Exploring Power, Risk, and Resistance in AI and Big Data During the Ebola Epidemic." In 4S Paraconference X EiJ: Building a Global Record, curated by Misria Shaik Ali, Kim Fortun, Phillip Baum and Prerna Srigyan. Annual Meeting of the Society of Social Studies of Science. Honolulu, Hawai'i, Nov 8-11.

This study examined the risk of acquiring Ebola Virus Disease (EVD) by healthcare workers in the setting of general hospitals and isolation units. By looking retrospectively at the Ebola Outbreak in Sierra Leone, the relative levels of risk to healthcare workers were computed and compared. The reasoning for these levels was also examined through interviews of surviving workers and the families/associates/colleagues of the deceased workers. The interviews reviewed common actions (and lack there of) for affected workers. This revealed certain themes that should be visited when reveising/creating hospital infection prevention and control policies.

In the case of this study, the vulnerable population examined was healthcare workers in Sierra Leone during the outbreak. These workers were found to be at a significant level of risk for transmission for a number of reasons. These include proximity to the virus (due to the occupation), lack of training in the area of infection control, and cultural factors (such as prevalence of self-medication and home management of illness). Nurses as a whole were most affected, with over half of the infected members. 

The data acquired in this study can be used not only for improvement in policies and training for healthcare workers, but also to examine the risk factors for the disease. One example is the age and gender disparities in those nfected. These could be explained by the typical age and gender of healthcare workers, but could also show a trend in risk when coupled with patient data. The data on the districts and their infection rates can be used to help pinpoint the origin of infection. 

The study was published in BMC Infectious Diseases, a peer-reviewed journal on the prevention, diagnoisis, and management of infectious disease. The journal seems to be genrally well respected.

This was a retrospective study. While not the most accurate and well supported way to conduct a study, due to the effects of recall bias, it was really the only way to gain the data that was presented in the report. There isn't really anything new about the style of research. 

At least one further study has been conducted using this data. A more focussed paper on the Kenema District in Sierra Leone was written, addressing the staggering number of cases with infected healthcare workers. The paper is titled "Facors Underlying Ebola Virus Infection Among healthcare Workers, Kenema, Sierra Leone, 2014-2015."  The paper reached similar conlusions as the original one, with a need for better practices in infection control and prevention. 

The study was funded by the WHO Country Office for Sierra leone.

The main point of this article is to look at the shortcomings of the response to the World Trade Center on 9/11/01 by the NYPD, PAPD, and FDNY. The article shows that the response was plauged by communication breakdowns between fire companies and commanders, a complete lack of communication between fire and law enforcement agencies with heavy roots in the history of the two departments, and an uncoordinated response by off duty firefighters, who swarmed the area after the attacks. The article discusses various improvements that could have been made after the 1993 bombing and would have significantly effected response on 9/11 such as the improvement and standardization of radio hardware and channels between departments, joint training drills, more rigid command durring response, and the adoption of the FEMA incident command system.