Flooding through the lens of mobile phone activity

Natural disasters affect hundreds of millions of people worldwide every year. Emergency response efforts depend upon the availability of timely information, such as information concerning the movements of affected populations. The analysis of aggregated and anonymized Call Detail Records (CDR) captured from the mobile phone infrastructure provides new possibilities to characterize human behavior during critical events. In this work, we investigate the viability of using CDR data combined with other sources of information to characterize the floods that occurred in Tabasco, Mexico in 2009. An impact map has been reconstructed using Landsat-7 images to identify the floods. Within this frame, the underlying communication activity signals in the CDR data have been analyzed and compared against rainfall levels extracted from data of the NASA-TRMM project. The variations in the number of active phones connected to each cell tower reveal abnormal activity patterns in the most affected locations during and after the floods that could be used as signatures of the floods - both in terms of infrastructure impact assessment and population information awareness. The representativeness of the analysis has been assessed using census data and civil protection records. While a more extensive validation is required, these early results suggest high potential in using cell tower activity information to improve early warning and emergency management mechanisms.Comment: Submitted to IEEE Global Humanitarian Technologies Conference (GHTC) 201

Strategic Planning Practices Among Churches in Kibera Slum

Graduate Applie

Modeling the Influence of Environment and Intervention on Cholera in Haiti

We propose a simple model with two infective classes in order to model the cholera epidemic in Haiti. We include the impact of environmental events (rainfall, temperature and tidal range) on the epidemic in the Artibonite and Ouest regions by introducing terms in the transmission rate that vary with environmental conditions. We fit the model on weekly data from the beginning of the epidemic until December 2013, including the vaccination programs that were recently undertaken in the Ouest and Artibonite regions. We then modified these projections excluding vaccination to assess the programs' effectiveness. Using real-time daily rainfall, we found lag times between precipitation events and new cases that range from 3.4 to 8.4 weeks in Artibonite and 5.1 to 7.4 in Ouest. In addition, it appears that, in the Ouest region, tidal influences play a significant role in the dynamics of the disease. Intervention efforts of all types have reduced case numbers in both regions; however, persistent outbreaks continue. In Ouest, where the population at risk seems particularly besieged and the overall population is larger, vaccination efforts seem to be taking hold more slowly than in Artibonite, where a smaller core population was vaccinated. The models including the vaccination programs predicted that a year and six months later, the mean number of cases in Artibonite would be reduced by about two thousand cases, and in Ouest by twenty four hundred cases below that predicted by the models without vaccination. We also found that vaccination is best when done in the early spring, and as early as possible in the epidemic. Comparing vaccination between the first spring and the second, there is a drop of about 40% in the case reduction due to the vaccine and about 10% per year after that

Making Slums Governable: Integration and Resistance in a Nairobi Slum

"This study first reviews existing literature on the impact of mobile phones on governance and participation, highlighting limitations of the current literature. It then details the methodology used in field research. The recent political history of Kenya, and ICT developments, are explored, and the Kibera slum is introduced in greater detail. The study then discusses the dynamics of mobile phone usage in Kibera in relation to policies and projects of the formal governance network and introduces arguments by James Scott concerning state optics and state-society relations, which provide valuable tools in understanding ICT usage in Kibera. Finally, the paper presents implications for the formal governance network resulting from the politics of ICT adoption in marginalized communities."--from page 22

Heterogeneous Mobile Phone Ownership and Usage Patterns in Kenya

The rapid adoption of mobile phone technologies in Africa is offering exciting opportunities for engaging with high-risk populations through mHealth programs, and the vast volumes of behavioral data being generated as people use their phones provide valuable data about human behavioral dynamics in these regions. Taking advantage of these opportunities requires an understanding of the penetration of mobile phones and phone usage patterns across the continent, but very little is known about the social and geographical heterogeneities in mobile phone ownership among African populations. Here, we analyze a survey of mobile phone ownership and usage across Kenya in 2009 and show that distinct regional, gender-related, and socioeconomic variations exist, with particularly low ownership among rural communities and poor people. We also examine patterns of phone sharing and highlight the contrasting relationships between ownership and sharing in different parts of the country. This heterogeneous penetration of mobile phones has important implications for the use of mobile technologies as a source of population data and as a public health tool in sub-Saharan Africa

Road Planning for Slums via Deep Reinforcement Learning

Millions of slum dwellers suffer from poor accessibility to urban services due to inadequate road infrastructure within slums, and road planning for slums is critical to the sustainable development of cities. Existing re-blocking or heuristic methods are either time-consuming which cannot generalize to different slums, or yield sub-optimal road plans in terms of accessibility and construction costs. In this paper, we present a deep reinforcement learning based approach to automatically layout roads for slums. We propose a generic graph model to capture the topological structure of a slum, and devise a novel graph neural network to select locations for the planned roads. Through masked policy optimization, our model can generate road plans that connect places in a slum at minimal construction costs. Extensive experiments on real-world slums in different countries verify the effectiveness of our model, which can significantly improve accessibility by 14.3% against existing baseline methods. Further investigations on transferring across different tasks demonstrate that our model can master road planning skills in simple scenarios and adapt them to much more complicated ones, indicating the potential of applying our model in real-world slum upgrading. The code and data are available at https://github.com/tsinghua-fib-lab/road-planning-for-slums.Comment: KDD'2

Implications of Mandatory Registration of Mobile Phone Users in Africa

Sub-Saharan Africa ranks among the top regions in terms of growth in the number of mobile phone users. The success of mobile telephony is attributed to the opening of markets for private players and lenient regulatory policy. However, markets may be increasingly saturated and new regulations introduced across Africa could also have a negative impact on future growth. Since 2006, the majority of countries in the region have introduced mandatory registration of users of prepaid SIM cards with their personal identity details. This potentially increases the costs of using mobile telephony. I present a fixed effects model for the estimation of the impact of mandatory registration on mobile penetration growth, which is based upon a panel dataset of 32 countries in Sub-Saharan Africa for the years 2000 to 2010. The results show that the introduction of mandatory registration depresses growth in mobile penetration.Telecommunication, government policy, consumer protection, privacy

Protection conferred by typhoid fever against recurrent typhoid fever in urban Kolkata.

We evaluated the protection conferred by a first documented visit for clinical care of typhoid fever against recurrent typhoid fever prompting a visit. This study takes advantage of multi-year follow-up of a population with endemic typhoid participating in a cluster-randomized control trial of Vi capsular polysaccharide typhoid vaccine in Kolkata, India. A population of 70,566 individuals, of whom 37,673 were vaccinated with one dose of either Vi vaccine or a control (Hepatitis A) vaccine, were observed for four years. Surveillance detected 315 first typhoid visits, among whom 4 developed subsequent typhoid, 3 due to reinfection, defined using genomic criteria and corresponding to -124% (95% CI: -599, 28) protection by the initial illness. Point estimates of protection conferred by an initial illness were negative or negligible in both vaccinated and non-vaccinated subjects, though confidence intervals around the point estimates were wide. These data provide little support for a protective immunizing effect of clinically treated typhoid illness, though modest levels of protection cannot be excluded