EpiMap: Towards quantifying contact networks for understanding epidemiology in developing countries Eiko Yoneki ⇑ , Jon Crowcroft University of Cambridge, Computer Laboratory, Cambridge CB3 0FD, United Kingdom article info Article history: Received 10 March 2012 Received in revised form 22 May 2012 Accepted 18 June 2012 Available online xxxx Keywords: Human contact networks Epidemiology Mobile phone Proximity radio communication Delay tolerant networks Satellite communication Network modelling abstract We describe the EpiMap project, together with the FluPhone project where we developed the basic technology for EpiMap. In FluPhone, human contact data is collected using mobile phones to record information such as locality and user symptoms for flu or cold. Delay tol- erant opportunistic networks were used as a basis for communication. We are extending the technology used in FluPhone to gather information on human interactions within rural communities of developing countries. The collected information will be used to develop improved mathematical models for the spread of infectious diseases such as measles, tuberculosis and pneumococcal diseases. Survey study will aid the understanding of the living conditions in these villages. We introduce the EpiMap vision for a system of opportunistic networks combined with satellite communication, designed to face the challenges posed by weak electricity and com- munication infrastructures in rural regions of developing countries in Asia, Africa and South America. We aim to use a delay-tolerant small satellite for data transfer between developing countries and Europe ore North America. Data collected through EpiMap can be used to help design more efficient vaccination strategies and equitable control programmes. Ó 2012 Elsevier B.V. All rights reserved. 1. Introduction Many of Africa’s significant diseases such as measles, tuberculosis, meningococcal, respiratory syncytial virus, and influenza are spread directly via person to person con- tact. These diseases are vaccine preventable and there has been a significant investment in improving vaccine cover- age. Many countries face difficult decisions to refine the effective vaccination strategies within the limited budget. Modelling the spread of infectious disease mathemati- cally has been a useful tool for helping to design efficient immunisation programmes. Despite this, there is a lack of such studies. In Africa, few transmission models of vaccine preventable diseases have been developed. Thus, it is desirable to develop models for specific disease by making available social contact data, thereby encouraging others to develop their own models. For example, having a model prepared in advance based on up-to-date data on contact patterns and measles transmission data will greatly aid the efficient design of measles control. The lack of any such model with which to evaluate the polio endgame has cer- tainly hampered and delayed any progress of controlling the spread. To achieve this goal, both developing an advanced mathematical modelling and more importantly reliable and informative social contact data are essential. Thus, we focus in this paper on how to obtain such social contact data. Mathematical models are only as reliable as the assumptions and parameters upon which they are built. Social mixing patterns are central determinants of trans- mission for infections which demand close contact be- tween individuals. In reality, very little is known about contemporary social contact patterns, especially in the third-world countries. Quantifying the social network 1570-8705/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.adhoc.2012.06.003 ⇑ Corresponding author. E-mail addresses: eiko.yoneki@cl.cam.ac.uk (E. Yoneki), jon.corwcorft@ cl.cam.ac.uk (J. Crowcroft). Ad Hoc Networks xxx (2012) xxx–xxx Contents lists available at SciVerse ScienceDirect Ad Hoc Networks journal homepage: www.elsevier.com/locate/adhoc Please cite this article in press as: E. Yoneki, J. Crowcroft, EpiMap: Towards quantifying contact networks for understanding epidemiology in developing countries, Ad Hoc Netw. (2012), http://dx.doi.org/10.1016/j.adhoc.2012.06.003