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Figure 8-2. Mobility patterns in West-Africa according to cellphone recordsSource: Wesolowski et al. (2014).Another setting where data collection and sharing withSMS and cell phones has proved useful is in monitoringdisease outbreaks, such as the Ebola epidemics in WestAfrica. Smart phones have been deployed in Ebola affectedcountries to monitor Ebola cases – this approach is timesaving, as the information on cases can be pulled togetherin a quicker way than the traditional routes ofreporting. 816,817 Maps showing Ebola cases and the locationof Ebola Assistance Centres have been used to assistMinistries of Health in deciding where to build new centresand allocate health resources. 8188.2. Tapping into big dataBig data has been described by its volume, due to themassive data sets coming out from satellite images, socialmedia, online commercial transactions and cell phonerecords, among others. But its real power comes from thefact that these data are continuously generated andcontain information that can trace many aspects of humanlife. Big data has also been called the “data breadcrumbs”,i.e. the data people leave behind as they go about theirdaily lives (for a more detailed discussion on big data, seeChapter 7). It is thus not surprising that these data arebeing explored to fill data gaps in Africa. In a regionstruggling for resources to implement functional statisticalsystems, and with numerous data gaps, big data cancomplement other data sources. In particular, it canprovide fine granular data in space and time to uncover sofar hidden local heterogeneity, as long as privacy of theindividual is protected (see section 7.5 on big data inChapter 7 for more details on privacy).planning and billing, these records provide acomprehensive, inexpensive and continuing source ofinformation. The information is often available quickly,within minutes after a cell phone or SMS communicationoccurred. Phone companies typically have records of callpatterns among their customers extending over multipleyears. This allows not only access to real time data but alsoto historical data. CDR location information is imprecise asit is determined by the towers that captured the signal, butremains practical for many data applications (see section7.5 on big data in Chapter 7). The spatial granularity of thedata depends on the range of a cell tower which tends tobe, in sub-Saharan Africa, from 5 to 10 kilometres. 819Compared to other regions, the number of applicationsusing CDR analysis for topics related to sustainabledevelopment has been low in Africa (see Table 7-5) on bigdata in Chapter 7). The few existing applications showhowever promising results. They tend to be from countrieswhich have already achieved a relatively high mobile phoneusage, like Senegal and Côte d’Ivoire. The release of thedata by the cell phone service providers in these twocountries has also encouraged a lot of research in exploringapplications of these data (see section 8.4).Cell phone records have been used to produce estimates ofpoverty in Côte d’Ivoire, 820 literacy rates in Senegal 821 andfood expenses in a country in East Africa (Box 8-5); 822 aswell as to determine travelling patterns to better managepublic transportation in Côte d’Ivoire, 823 among others. 824CDRs are also being used for malaria prevention in Kenya 825and for estimating population flows to inform the Ebolaresponse in West Africa (Box 8-4). 826 Despite concerns onthe lack of representativeness of these data – which leavesthose without cell phones out – studies have succeeded inobtaining reliable estimates (see e.g. Box 8-4).This is not surprising as cell phone access in Africa isincreasing dramatically and thus expanding the coverage ofCDR data. In 2013, about 65% of the population in sub-Saharan Africa was in areas with sufficient signal to connectto a mobile network. In several African countries, morethan 60% of households have at least one mobile phone(Figure 8-3). In some African countries, the percentage ismore than 80%.8.2.1. Cell phone data, social media and internetsearchesCell phone service providers maintain data sets with CallDetail Records (CDRs), which contain the time of everyvoice call or SMS exchange and the duration of the callalong with the approximate location of the cell phonesinvolved. Because they are routinely recorded for resource156