Telcos data for development
public – private partnership for sustainable development

Zbigniew SMOREDA
Orange Labs, FranceContent

 Call Detail Records (CDR) & first research trials (2006 – 2009)
 NetMob – scientific community building (2010)
 Data for Development (D4D)
─ Cote d’Ivoire (2012-2013)
─ Senegal (2014-2015)

 Open Algorithms (OPAL) project (2016)

2

CDRs telcos billing records
 Billing data collected automatically for all MPO’s customers
timestamp
party Aparty B
type
durationcell A
16/10/30 10:01:33
0689094877
0645321101
SMS
016/10/30 10:01:34
0765443321
0675448765
Voice
54
16/10/30 10:01:35

0766545566

0653344567

Voice

3

132

cell B
123
233

322
543

435

124

CDRs telcos billing records
 Billing data collected automatically for all MPO’s customers
timestamp
party Aparty B
type
durationcell Acell B
16/10/30 10:01:33
ABCXRTTAATXYRAATRRAA
SMS
0Lat, Lon
Lat, Lon
16/10/30 10:01:34
ZXXRTT554R
CC445EERSDA
Voice54
Lat, Lon
Lat, Lon
16/10/30 10:01:35

776EREREER

99TRDDAAA7

Voice

4

132

Lat, Lon

Lat, LonCDRs telcos billing records
 Billing data collected automatically for all MPO’s customers
timestamp
party Aparty B
type
durationcell Acell B
16/10/30 10:01:33
ABCXRTTAATXYRAATRRAA
SMS
0Lat, Lon
Lat, Lon
16/10/30 10:01:34
ZXXRTT554R
CC445EERSDA
Voice54
Lat, Lon
Lat, Lon
16/10/30 10:01:35

776EREREER

99TRDDAAA7

Voice

Onnela et al. 2007

132

Lat, Lon

Lat, Lon

Gonzàlez et al. 2008
5

CDRs first trials

6CDRs first trials
 Distance role in building social networks: towards the network geography

durée moyenne (s)240The probability Pd that two people living in Belgium at a
distance d are connected by a mobile phone link in a log–log
scale. The dashed line is the power-law d-2 (gravity law)

210

180

150

120
0

10

20

30

40

50

60

70

80

90 100 110 120 130 140

distance (km)R. Lambiotte et al. 2008

7

CDRs first trials

V. Blondel et al. 20118

Quickly growing research

9

NetMob – community building

10

NetMob – community building

11

How to accelerate?

An Open Innovation Projectwith Orange Cote d’Ivoire,
Orange Marketing VisionandCorporate Social Responsibility

Data for Development (D4D) Cote d’Ivoire
201212D4D: data for development Cote d’Ivoire
5 months of deidentified CDRs
OCI antennae
positions

Orange Data
Centerdata
processing at
Orange Labs

 Proposed datasets:─ (1) antenna-to-antenna traffic on an hourly basis,─ (2) individual trajectories for 50,000 randomly sampled users for two week time

windows with antenna location information,
─ (3) individual trajectories for 500,000 randomly sampled users over the entire

observation period with sub-prefecture location information,
─ and (4) a sample of communication graphs for 5,000 customers

13D4D: data for development Cote d’Ivoire

 “Scientific challenge” - halfway between a long hackathon and a scientificconference:─ Launched in June 2012 for 8 months only
─ Only research institutions admitted after signing the terms & conditions
─ Evaluation committee chaired by Vincent Blondel (UCL) with members from

Bouake University, Global Pulse (UN), GSMA, Orange Labs, WEF and MIT─ Selected projects presentation during the NetMob conference, May 2013 in

Boston (USA)─ Four prizes attributed (first prize, scientific, development, and data visualization

prizes)14

D4D: data for development
 Côte d'Ivoire CDR samples
 Open to the researchers 263 projects submitted Over 80 reports received

15

D4D: data for development Cote d’Ivoire

http://perso.uclouvain.be/vincent.blondel/netmob/2013/D4D-book.pdf

16

D4D: data for development Cote d’Ivoire
 First prize17

D4D: data for development Cote d’Ivoire
 Development prize18

D4D: data for development Cote d’Ivoire

19

D4D: data for development Cote d’Ivoire+ 50 published works!

20

D4D: data for development Cote d’Ivoire
 Many various topics addressed by the projects:
─ Health improvement (disease spread mapping or prevention)
─ Population statistics (urbanization, population, tourism and events analysis)

─ Communities understanding (diaspora cartography and needs, rural and urban

customers)
─ Economic Indicators (local economic development, micro finance insight)
─ City and transport planning (transport optimization, road construction, smart city

planning)
─ Emergency, Alerting & Preventing (early warning system, help distribution

localization)
─ Geo-marketing (strategic points of sales)…

 Important echo among the United Nations, NGOs, development aid

institutions
 New data challenges initiatives (Telecom Italia, Telefonica) But no project could be implemented in Ivory Cost…
21

Second D4D Senegal:
do it differently

D4D Senegal
6 January 2014: Sonatel decides to launch D4D Senegal

23

D4D Senegal
 Improvements to bring to D4D after the Cote d’Ivoire experience
1. Focus on 5 themes─

Health, Transport, Agriculture, Energy, National statistics

2. Involve local ecosystem
─Questions owners: Ministries and institutions─Contributors: Universities, entrepreneurs…

3. Reinforce governance─Regulation, Ethics,…

4. Foster Data sharing─

Find other data sources to be crossed with D4D data sets

5. Ensure an implementation of results─Prepare the « After D4D »24

A process for Ethics review, involving both Orange
staff and external experts set-up
D4D External Ethics Panel

D4D
External
EthicsPanel(DEEP)

External advisors with balanced profileProvide advise/perspective to the D4D project
team and the D4D Committee

Orange D4D Ethics workgroup (internal)
Orange D4D
EthicsworkgroupSenior managers, most of them not involved in D4D

Propose the Sonatel-Orange preliminary position

Initiate actions in case of obvious need

D4D Committee (external)

D4D project team
(D4D operations andproject responsibility)

13 external members

Advisor to D4D team and independent Prize allocation

D4D Committee(Support & Prizes)
25

D4D Senegal
12 months of deidentified CDRs
Sonatel antennae
positions

Orange Data
Centerdata
processing at
Orange Labs

 Proposed datasets:─ (1) antenna-to-antenna traffic on an hourly basis,─ (2) individual trajectories for 300,000 randomly sampled users for two week time

windows with antenna location information,
─ (3) individual trajectories for 150,000 randomly sampled users over the entire

observation period with arrondissement location information,
─ and (4) a sample of communication graphs for 5,000 customers
─ Bandicoot individual indicators with (2) & (3) http://bandicoot.mit.edu/

26

D4D Senegal
April 2014: challenge launched27

D4D Senegal
April to August: more data and resources from donors
provided socio-demographic data on HIV, Malaria andTuberculosis and the related expenditures



Data are available on the website

provides computing power to 5 teams

 Email sent to the teams that have submitted a project The opportunity is visible on the website

provided a 1 km gridded estimate of rainfall, relative
humidity and mean temperature measuresIntellectual Ventures provided us several links for the resources
Email sent to all the teams

will provide satellite images in selected regions

 That will be integrated to maps by OpenStreetMap
 OpenStreetMap will enrich the maps with data asked for by the teams
 Email sent to the teams that have submitted a project28provided its databases, publications and reportsLink on the website to these resources

provided its databases and documents bases

Link on the website to these resources

provided its databases and reportsLink on the website to these resources

OSM is detailing chosen areas with field works

Link on the website to these resources

provide vouchers to use their services

D4D Senegal - June 2014: Launch in Dakar

29

D4D Senegal
Projects proposals came from all over the world,
11 from Senegalese universities

Statistics

HealthEnergyAgriculture

Transport/Urban

30

Data Visualization Others

D4D Senegal
About 60 high quality submissions on time for the Challenge

731

D4D Senegal
All themes are represented, with a majority of Transports, Health andNational Statistics

3%
7%
Agriculture
Energy37%

20%

HealthOther
National Statistics
Transport/Urbanisation

18%
15%

32

D4D Senegal results announcement

33

The event mixed presentations, workshops, datathonsocial events and the announcement of the winners

34

the winners

35

D4D Senegal
Results are published on the Web:
D4D scientific contributions
http://netmob.org/assets/img/NetMob%202015_D4D%20Challenge%20Senegal_Sessions_Scientific_Papers.pdf (298 pages, 83MB)
D4D posters
http://netmob.org/assets/img/NetMob%202015_D4D%20Challenge%20Senegal_Sessions_Posters.pdf (56 pages, 53 MB)

The datasets for D4D are described here: http://arxiv.org/abs/1407.4885

36

D4D Senegal was made possible thanks to…
Core team Sonatel
Sponsor:JerômePMO:
CoumbaBI:
DaoudaLegals:Jamil, Oumar, EmilieCom:
Racky & teamCore Team Orange
Sponsor
Pascal, Brigitte
PMO:
Stephanie
Labs:
Zbigniew & Cezary
Trainees:
Vladimir then Laetitia
CSR
Ludovic
Legals:DominiqueCom:
Philippe
Web:
Serge
Anonymisation, Synthetic CDR, Weather
Anne-Sophie, Cezary, Romain, Emmanuel, Valérie,Dominique, Michel, CNRS team
D4D Committee
Vincent, Sandy, Jake, Bill, Robert, Johannes
Elizabeth, Ngalla, Toguebaye, Omar,
Zouhair, Marie-Claude, Nicolas
Ministries & Institutions
Commission des Données Personnelles
Recherche et Education supérieurePlan Sénégal Emergent
Health and Social Action
Agriculture
Energie
Transport
National Statistics - ANSD
Centre de Suivi Ecologique
Telecom regulator

Prize donors
The Bill & Melinda Gates Foundation
Orange, Sonatel
Resources donors
Tera Labs
Data donors
WHO, Digital Globe, The Global FundIDM, Centre de suivi écologique,Hackathon, Datathon
OBS: Jean-Pierre, Stephane
Valérie, Axelle, Philippe
Boston: Yves-Alexandre, Zbigniew
Paris: Ludovic, Cezary, « Le Simplon »Dakar: Ndongo & Technocentre

D4D External Ethics Panel (DEEP)
Lucy Bernholz
Philippa Foster Back
William Hoffman
Johannes Jutting
Robert Kirkpatrick
Emmanuel Lulin
Ulrich Mans
Mark Nelson
Yaye Fatou Camara Niang
Nuria Oliver
Juliana Rotich
Olivier Sagna
Jean-Philippe Vanot
Pat Walshe

NetMob
EstebanInternal Ethics Workgroup
Pierre Petillault
Fabrice André,
Bénédicte David
Annick Lelièvre
Valérie Peugeot,
Kitty Boullé
J-Y Leonnec
Ludovic Levy
Olivier Ondet
Oumar Sidibe
Catherine Fauvel
37

NetMob @ MIT
Yves-Alexandre

Orange Communication
Vanessa, Nicole, Cecile,
Sylvie, Christine, Liza, Xavier

Thanks to B&M Gates Foundation grants threeprojects were launched to explore further the useof CDRs for:Health: Disease modeling
National Statistics: Proxy for indicators
Agriculture: Food security

D4D Senegal: Grants for implementation
HealthNational Statistics

Agriculture

Uncovering the impact ofhuman mobility on
schistosomiasis...

Construction of sociodemographic indicatorswith digital breadcrumbs

Genesis of millet prices in
Senegal: the role ofproduction, markets andtheir failures

R Casagrandi et al., Politecnico
di Milano, Italy

F Bruckschen & T Zbiranski,Freïe Universität Berlin,
Germany

D Jacques, UC Louvain,
Belgium

Quantifying effect of
movement due to holidays onmalaria prevalence

A multidimensional analysisof poverty and its
determinants in Senegal

Mobility profiles andcalendars for food security
and livelihoods analysis

S Milusheva, Brown University,
USA

N Pokhriyal, State University of
New York at Buffalo, USA

PJ Zufiria et al., Universidad
Politécnica de Madrid, Spain(See: Annex)

granted access to the complete database39

D4D Senegal: 6 projects implementation
 Special event in Dakar ( Radisson Sonatel event, 6th June 2015 ) and teams

field visit to Senegal
 Collaborations with local actors:
─ ANSD (National Statistics)
─ Ministry of Health─ World Food Program Dakar
─ DAPSA Senegal (Agriculture Statistics)
─ PNLP (National Malaria Control Program)─ …

 Help of international development bodies (OECD, WFP, WHO, UN…)
 And finally a « twin project » on the National Statistics Senegal - Coted’Ivoire is about to start40

After D4D: the world of development needs Big Data
DATA-POP The Law, Politics and
ALLIANCE Ethics of Cell Phone
White Paper Data Analytics
April 201541

Privacy warning: impossible CDRs anonymization
 The notion of anonymity is one of thecornerstone of data protection
 But an individual spatiotemporal trace

becomes very quickly unique, even in thelargest datasets

 CDRs from an European country (1.5 M people, 15 months)
 Points: antenna tower / time step: one hour42

Privacy

The “privacy-utility” trade-off

Utility43

A paradigm-shift in data protection

Privacy

Provide accessto richer but
hidden data

• secure platform with pseudonymizeddata• bring the code to the data using APIs
• create a bank of open algorithms• set-up a governance board (local
and global)
Utility44

OPAL : a multiple privacy preserving platform
 OPAL project principles:─ Use of Robust and State of the art technologies: Hadoop, Spark…
─ Leverage Open Software and a developer community
─ Develop User interfaces that make it easy to develop and use algorithms
─ Develop Security and Auditing with Best of Breed and BlockChain

 OPAL Data Governance Board (local, multi-party: Civil Society, Academia,

Government, Data Providers…) which check and certify algorithms tosecure:─ Privacy of individuals
─ Privacy of social groups, tribes, nations
─ “Privacy” of data-provider (business risks) A central support from OPAL team with a Data Ethics Network coordination

45

OPAL Project: query private data in a safe way

46

OPAL Project: ecosystem todayCore
Capacity Building Partners

FunderServices Partner
Technical Partner
National Stat Org

Microsoft
UNGP

prototype

UNFPA

Columbia
Earth Inst.

WFP

Imperial College
LondonDeloitte

MIT

TM Forum

SDSN
Columbia

UNICEF
TEF

Data Pop Alliance(P.M.)

OrangeGroup

OPAL(ODI - PMO)

Dane

MexicoGlobe
Sun/Smart

Philippines

PSA

AndorraTelecom

Andorra

NSO

TIM

Italy

TelenorParis 21
OECD
WEF

…

Gates

GPSDD

Senegal

DIAL
World Bank

Soros

INS

Ivory Coast

Omidyar
47

AFD

ANSD

French Gov.
OGP

OPAL project The Official Launch of the OPAL Project took place on 8 December 2016

during the Open Government Partnership Global Summit in Paris OPAL contact: Natalie Shoup (Program Manager) nshoup@opalproject.org

48

Annex:B&M Gates Foundation founded
D4D Senegal projects in detail49

D4D Challenge Senegal, Grant from the B&M Gates Foundation
Uncovering the impact of human mobility on schistosomiasis
Objective of Project & key results:
 Schistosomiasis is water based parasitic worm infection affecting millions ofpeople. We build large-scale, data-driven models aimed at understanding,predicting and possibly controlling country-wide schistosomiasis transmission
in Senegal.
We show that a relatively simple model can reliably reproduce regional
patterns of schistosomiasis prevalence across the country and assist in
health care planning. The inclusion of human mobility is an important factor
for the realism of model predictions. Also, when tailored for specific regionsof Senegal, the model can help identify the focal transmission hotspots of thedisease.

Possible use for development: We use the model to study the role of human mobility on disease dynamics
and to analyze intervention strategies aimed at reducing disease burden.
 The model can also be used to map infection risk at country and regional
scales, so as to inform communication campaigns and disease control.

Researchers: Renato Casagrandi, Manuela Ciddio, Marino Gatto, Lorenzo Mari – Dipartimento
di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy
Contact: renato.casagrandi@polimi.it

Further Research needs:
 CDRs for other years and/or countries to validate model predictions
 High-res schistosomiasis data for fine-tuning of the model Ecological data to describe the dynamics of intermediate snail hosts

Links to publications:

Ciddio, Mari, Sokolow, De Leo, Casagrandi, Gatto (2016). The spatial spread ofschistosomiasis: a multidimensional network model applied to Saint-Louis region, Senegal.
Advances in Water Resources, http://dx.doi.org/10.1016/j.advwatres.2016.10.012
Mari, Casagrandi, Ciddio, Dia, Sokolow, De Leo, Gatto. Big-data-driven modeling unveils
country-wide drivers of endemic schistosomiasis, submitted

Local next steps in progress:
Project MASTR-SLS (MApping Schistosomiasis Transmission Risk in Saint-Louis,
Senegal), funded by Politecnico di Milano through the PoliSocial initiative(www.polisocial.polimi.it) . The project (Jan 2017 – Dec 2018) will consist of three maintasks: i) collection of epidemiological (school surveys) and ecological data (snail
sampling) in the region; ii) elaboration of quantitative tools for transmission risk
mapping; iii) design of communication strategies to help prevent disease spread in ahighly endemic area.

Conferences where presented:








National Congress of the Italian Ecological Society, Milan (IT), Sept 2016
International Workshop DeMagma at Univ Pierre et Marie Curies, Paris (FR), 2-4 Feb 2016
5th Int Conf on Infectious Diseases, Epidemics 5, Clearwater Beach (FL-USA), 1-4 Dec 2015
9th Eu Congr on Tropical Medicine ECTMIH 2015, Basel (CH), 6-10 Sep 2015
MeetMeTonight 2015, Milano (IT), 25-26 Sep 2015, [short and long video]
Radisson Sonatel event, Dakar (SN), June 2015
Impact of Env Changes on Infectious Diseases, IECID 2015, Sitges (ES), 23-25 Mar 2015

Local Customer(s) for delivery of results:
Ministry of Health: Docteur Marie Khemesse Ngom NDIAYE, Directeur de la Lutte
Contre la Maladie

Local collaborations during the research:
Ministry of Health: Dr. Elhadji Daouda Dia
50

D4D Challenge Senegal, Grant from the B&M Gates Foundation

600

Objective of Project & key results:

400




200




Impact of Travel

0

Malaria Cases Treated or Averted

Quantifying the effect of population movement on malaria incidence using cell
phone data0

1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000

Develop model of malaria for the Ministry of Health using Mobile Meta
Data to derive patterns of mobility from and to locations where thedisease is present
Demonstrate the usefulness of CDR to improve malaria diffusion
modeling, improving the potential for targeting efforts especially in regionswith low prevalence
Used modeling to show that each infected traveler contributes to 1.20
new cases of malaria in the location they enter
Demonstrate the efficiency gain from targeting travelers most likely to be
bringing malaria infections
Presented results to PNLP policy strategy meeting Jan 2016, and being
asked to develop a service by MACEPA

Number of Travelers Targeted
Strategy 1: Random
Strategy 3: Higher malaria Aug-Dec First

Possible use for development,

Strategy 2:Random Aug-Dec First
Strategy 4:Cost EffectivenessResearchers: Sveta Milusheva, Brown University, USA
Contact: svetoslava_milusheva@brown.edu
Links to publications:(Job Market Paper, will submit for publication in the

Improve Policy making for national program (PNLP)
Develop a service/App for weekly information to health facilities in thefield
Additional mobile phone data to validate the model and test out of sample
predictions
Weekly data to test development of a weekly information app

Local next steps in progress:

Spring)https://drive.google.com/open?id=0B8oQfBs38UHGZ01fMnh2bFBmZWc

Conferences where presented:
North East Universities Development Consortium Conference (Boston, Nov 5 2016),
Population Health Sciences Research Workshop (Boston, Sept 23 2016), PopPov
Conference on Population, Reproductive Health and Development (Sept 8 2016), WorldBank ABCDE Conference (June 21 2016), Population Association of America
Conference (April 1 2016); Radisson Sonatel event, Dakar, 6 June 2015

2017 service pilot for health workers in Richard Toll for Malaria
elimination before scaling. Proposal submitted to the GPSDD innovation
fund on Sept 1st 2016.
Create SMS program for travelers when entering a new location
concerning staying healthy and potentially provide an incentive in the
SMS to visit a facility and get tested if coming from a high malaria area

Local Customer(s) for delivery of results:
Ministry of Health: Dr N’diaye, Directeur de la lutte contre la maladie

Local collaborations during the research:
PNLP: Omar Sarr
MACEPA: Philippe Guinot
51

D4D Challenge Senegal, Grant from the B&M Gates Foundation
Construction of socio-demographic indicators with digital breadcrumbs

Objective of Project & key results:
 To capture so far hidden local socio-demographic heterogeneity,such as pockets of illiteracy or poverty. We offer a uniform
approach that can be easily extended to other variables. It is basedon aggregated antenna traffic data only - data that is less prone to
privacy concerns than e.g. mobility patterns, thus facilitating
implementation.
 Models are fitted to geocoded survey data and used for prediction
on the tower level. Results are tested for spatiotemporalrobustness and visualized as heat maps.

Possible use for development: In the short-term, uncovering local socio-demographic
heterogeneity at little costs can facilitate timely & targeted relief.
 In the medium-term, variables can be modelled reliably, collectedless frequently, thereby reducing the scope and thus the costs ofsurveys.

Literacy rate in %Researchers: Fabian Bruckschen, Till Zbiranski, Freïe Universität Berlin,
Germany

Contacts: fabian.bruckschen@gmx.de, till.zbiranski@cms.hu-berlin.de
Local next steps in progress:

Links to publications:
Conferences where presented:
Radisson Sonatel event, Dakar, 6 June 2015

 2017 key socio-demographic indicators generated from CDRs forthe 17 Sustainable Development Goals

Local collaborations during the research:

Local Customer(s) for delivery of results:

PARIS21/OCDE: Johannes Jutting

ANSD: Mr. Mamadou NIANG, Informatique Statistique
INS : Mr. Be, Directeur de l’INS (Cote d’Ivoire)52

D4D Challenge Senegal, Grant from the B&M Gates Foundation
A multidimensional analysis of poverty and its determinants in Senegal
Objective of Project & key results:
 To develop highly accurate and spatially-detailed, ‘communelevel’, poverty maps using mobile phone data.
 We provide such maps ensuring full geographical coverage of
Senegal. Our model estimates of poverty have been validated
using census data provided by ANSD.
 We study the robustness of our model predictions, and its
generalization capability to data-scarce locations.
 We integrate mobile phone data with census, to build a model thatpredicts individual determinants of poverty in the dimensions ofhealth, education and standard of living.
.

Possible use for development, Spatially detailed policy-planning level poverty maps will assist in
targeted policies for inclusive growth of all the micro-regions.
 These maps are disaggregated into individual determinants ofpoverty like deprivations in health, education, assets, further
assisting in appropriate policy intervention.
 These maps can be generated at any temporal resolution, as they
are based in mobile phone data.

Clockwise from top left:
Poverty values for urban
areas of Dakar and Thies; theurban centers; and ruralcommunes. The darker colors
reflect higher poverty values.

Researchers: Neeti Pokhriyal, State University of New York at Buffalo, USA
Contacts: neetipok@buffalo.edu

Further Research needs:

Links to publications and conferences where presented:

Local next steps in progress:

1) A Computational Approach to Poverty Mapping; International Conference on
Computational Sustainability at Cornell University in July 2016.
2) Virtual Network and poverty analysis in Senegal; Radisson Sonatel event,
Dakar, 6 June 2015

 A twin project considering the synergies of the model in Ivory
Coast Newer mobile phone data for study temporal stability of the model Combining mobile data with other diverse sources of data, likesatellite imagery to better predict poverty.

Local Customer(s) for delivery of results:
ANSD – Sene Papa Ibrahima, ANSD

Local collaborations during the research:
PARIS21/OCDE: Thilo Klein, OCED53

D4D Challenge Senegal, Grant from the B&M Gates Foundation
Genesis of millet prices in Senegal: a trade flow approach
Objective of Project & key results:
Monitoring and forecasting of staple prices are capital to formulateadequate policies in favor of food security in Africa. Vegetation index
derived from Earth Observation satellite data combined with a uniquedataset of mobile phone calls between 9.000.000 users support thedevelopment of a new conceptual approach to estimate monthly millet
prices for 3 contrasted years in 57 markets in Senegal. We introduce
a mechanistic model that simulate trade flows between markets taking
into account transportation cost and information asymmetry. Prices
are accurately estimated up to 10 months after the harvest. Although
the distance between the markets is the main factor explaining pricedifferentials, the social network also appeared as a significant proxy oftrade intensity.

Researchers: Damien Jacques, Université catholique de Louvain (UCL),

Possible use for development,

Belgium

These results can be used in the assessment of the social welfare
impacts of the further development of both road and mobile phone
networks in the country. The model could be further developed as avaluable tool for the forecasting of staple prices in the country.

Contact: damienjacquesUCL@gmail.com
Links to publications:
Main publication will be submitted to PNAS week of 17th of October 2016
http://bit.ly/1QoXNpu, http://bit.ly/1TO9wDT

Local next steps in progress:
Potential support for operational monitoring still to be discussed

Conferences where presented:

Further Research needs:

Radisson Sonatel event, Dakar, 6 June 2015
AGU Fall Meeting, San Francisco, 14-18 December 2015

New findings are expected from the use of several years of mobile
phone data and the expansion of the model to other Saheliancountries.

Local collaborations during the research:

Local Customer(s) for delivery of results:

WFP Dakar: Wilfred NKWAMBI
CSE: Bamba Diop
DAPSA: Mame Nogaye Fall
CSA: Mr. Aly MAR, Directeur Général

WFP: Mr. Simon RENK, Regional Market Advisor

54

D4D Challenge Senegal, Grant from the B&M Gates Foundation
Mobility profile and calendars for food security and livelihood analysis
Objective of Project & key results:To create a mobility analysis system leading to a mobility baseline atdifferent levels (markets, cities, administrations, production areas).
To use the system for estimating and/or forecasting crops yields based on
farmers prediction capabilities and consequent movements.
To develop an food security early warning system based on the estimatedindicators.
Provide accurate estimates and forecasts of crop area and yield to policy
makers and integrate mobility information with NDVI and rainfall data.
Integration with knowledge provided by local actors..

Possible use for development,Researchers: Pedro J. Zufiria, David Pastor-Escuredo, Luis A. Úbeda-Medina,
Miguel A. Hernández-Medina, Iker Barriales-Valbuena, Alfredo Morales-Guzmán,
Universidad Politécnica de Madrid, Spain; Wilfred Nkwambi, WFP; John Quinn, Paula
Hidalgo-Sanchís, Miguel Luengo-Oroz, UN-Global Pulse

Use the mobility analysis system for estimating coping strategies and theimpact of early humanitarian actions.
Use the mobility analysis system for food security early warning. Thisapplication can be used by the WFP.
Use the system to characterize pastoralism (CSA and CIRAD).
Use the system to estimate early indicators in order to improve market
prices estimates (in collaboration with D Jacques).

Further Research needs:

Contact: pedro.zufiria@upm.es

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Links to publications:
https://www.dropbox.com/sh/x05dz5e3turyhk9/AABKJ8R2DguPi9Ox_3rRFZrxa?dl=0

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Conferences where presented:

Define a baseline of regular behavior based in CDRs corresponding to years 2014
and 2015 (new available data).
Assessment of the system with ground truth information and expertise of local
actors.
Improve space resolution of estimates.

Radisson Sonatel event, Dakar, 6 June 2015
Orange Spain, Invited lecture, Madrid, 24 June, 2015
Big Data, Good Data. Workshop. Madrid , 12-13 November 2015
Big Data and Climatic Change, Workshop FRA, 29 Feb. 2016
Data Beers, 2 Invited talks, Madrid, 25 January and 12 March, 2016

Local next steps in progress:

Local collaborations during the research:

Local Customer(s) for delivery of results:

WFP Dakar: Wilfred NKWAMBIDAPSA: Mama Nogaye Fail
CSA: Mr. Aly MAR, Directeur Général
CSE: Mr. Mouhamadou Bamba DIOPSECNSA: Mr. Cheikh Sadibou Pene

WFP: Mr. Simon RENK, Regional Market Advisor
CSE and CSA are interested in the applicability of the system

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SECNSA, CSE and CSA contacts are expected to collaborate with African Risk
Capacity.
Cheetah Accelerator (Mariéme Jamme) can provide local grassroots softwaredevelopers.