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      Heterogeneous Mobile Phone Ownership and Usage Patterns in Kenya

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          Abstract

          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.

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          The effect of mobile phone text-message reminders on Kenyan health workers' adherence to malaria treatment guidelines: a cluster randomised trial

          Dejan Zurovac, Raymond K Sudoi, Willis S Akhwale … (2011)
          Summary Background Health workers' malaria case-management practices often differ from national guidelines. We assessed whether text-message reminders sent to health workers' mobile phones could improve and maintain their adherence to treatment guidelines for outpatient paediatric malaria in Kenya. Methods From March 6, 2009, to May 31, 2010, we did a cluster-randomised controlled trial at 107 rural health facilities in 11 districts in coastal and western Kenya. With a computer-generated sequence, health facilities were randomly allocated to either the intervention group, in which all health workers received text messages on their personal mobile phones on malaria case-management for 6 months, or the control group, in which health workers did not receive any text messages. Health workers were not masked to the intervention, although patients were unaware of whether they were in an intervention or control facility. The primary outcome was correct management with artemether-lumefantrine, defined as a dichotomous composite indicator of treatment, dispensing, and counselling tasks concordant with Kenyan national guidelines. The primary analysis was by intention to treat. The trial is registered with Current Controlled Trials, ISRCTN72328636. Findings 119 health workers received the intervention. Case-management practices were assessed for 2269 children who needed treatment (1157 in the intervention group and 1112 in the control group). Intention-to-treat analysis showed that correct artemether-lumefantrine management improved by 23·7 percentage-points (95% CI 7·6–40·0; p=0·004) immediately after intervention and by 24·5 percentage-points (8·1–41·0; p=0·003) 6 months later. Interpretation In resource-limited settings, malaria control programmes should consider use of text messaging to improve health workers' case-management practices. Funding The Wellcome Trust.
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            Special delivery: an analysis of mHealth in maternal and newborn health programs and their outcomes around the world.

            Tigest Tamrat, Stan Kachnowski (2012)
            Mobile health (mHealth) encompasses the use of mobile telecommunication and multimedia into increasingly mobile and wireless health care delivery systems and has the potential to improve tens of thousands of lives each year. The ubiquity and penetration of mobile phones presents the opportunity to leverage mHealth for maternal and newborn care, particularly in under-resourced health ecosystems. Moreover, the slow progress and funding constraints in attaining the Millennium Development Goals for child and maternal health encourage harnessing innovative measures, such as mHealth, to address these public health priorities. This literature review provides a schematic overview of the outcomes, barriers, and strategies of integrating mHealth to improve prenatal and neonatal health outcomes. Six electronic databases were methodically searched using predetermined search terms. Retrieved articles were then categorized according to themes identified in previous studies. A total of 34 articles and reports contributed to the findings with information about the use and limitations of mHealth for prenatal and neonatal healthcare access and delivery. Health systems have implemented mHealth programs to facilitate emergency medical responses, point-of-care support, health promotion and data collection. However, the policy infrastructure for funding, coordinating and guiding the sustainable adoption of prenatal and neonatal mHealth services remains under-developed. The integration of mobile health for prenatal and newborn health services has demonstrated positive outcomes, but the sustainability and scalability of operations requires further feedback from and evaluation of ongoing programs.
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              The use of mobile phone data for the estimation of the travel patterns and imported Plasmodium falciparum rates among Zanzibar residents

              Andrew Tatem, Youliang Qiu, David Smith … (2009)
              Background Malaria endemicity in Zanzibar has reached historically low levels, and the epidemiology of malaria transmission is in transition. To capitalize on these gains, Zanzibar has commissioned a feasibility assessment to help inform on whether to move to an elimination campaign. Declining local transmission has refocused attention on imported malaria. Recent studies have shown that anonimized mobile phone records provide a valuable data source for characterizing human movements without compromizing the privacy of phone users. Such movement data in combination with spatial data on P. falciparum endemicity provide a way of characterizing the patterns of parasite carrier movements and the rates of malaria importation, which have been used as part of the malaria elimination feasibility assessment for the islands of Zanzibar. Data and Methods Records encompassing three months of complete mobile phone usage for the period October-December 2008 were obtained from the Zanzibar Telecom (Zantel) mobile phone network company, the principal provider on the islands of Zanzibar. The data included the dates of all phone usage by 770,369 individual anonymous users. Each individual call and message was spatially referenced to one of six areas: Zanzibar and five mainland Tanzania regions. Information on the numbers of Zanzibar residents travelling to the mainland, locations visited and lengths of stay were extracted. Spatial and temporal data on P. falciparum transmission intensity and seasonality enabled linkage of this information to endemicity exposure and, motivated by malaria transmission models, estimates of the expected patterns of parasite importation to be made. Results Over the three month period studied, 88% of users made calls that were routed only through masts on Zanzibar, suggesting that no long distance travel was undertaken by this group. Of those who made calls routed through mainland masts the vast majority of trips were estimated to be of less than five days in length, and to the Dar Es Salaam Zantel-defined region. Though this region covered a wide range of transmission intensities, data on total infection numbers in Zanzibar combined with mathematical models enabled informed estimation of transmission exposure and imported infection numbers. These showed that the majority of trips made posed a relatively low risk for parasite importation, but risk groups visiting higher transmission regions for extended periods of time could be identified. Conclusion Anonymous mobile phone records provide valuable information on human movement patterns in areas that are typically data-sparse. Estimates of human movement patterns from Zanzibar to mainland Tanzania suggest that imported malaria risk from this group is heterogeneously distributed; a few people account for most of the risk for imported malaria. In combination with spatial data on malaria endemicity and transmission models, movement patterns derived from phone records can inform on the likely sources and rates of malaria importation. Such information is important for assessing the feasibility of malaria elimination and planning an elimination campaign.
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                Author and article information

                Contributors
                : Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, USA )
                ISSN (Electronic): 1932-6203
                Publication date Collection: 2012
                Publication date (Electronic): 25 April 2012
                Volume: 7
                Issue: 4
                Electronic Location Identifier: e35319
                Affiliations
                [1 ]Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
                [2 ]Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
                [3 ]Malaria Public Health and Epidemiology Group, Centre of Geographic Medicine, KEMRI-Wellcome Trust-University of Oxford Collaborative Programme, Nairobi, Kenya
                [4 ]Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
                [5 ]Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, Massachusetts, United States of America
                Universitat Rovira i Virgili, Spain
                Author notes

                Conceived and designed the experiments: AW NE AMN RWS COB. Analyzed the data: AW COB. Wrote the paper: AW RWS COB.

                Article
                Publisher ID: PONE-D-11-19306
                DOI: 10.1371/journal.pone.0035319
                PMC ID: 3338828
                PubMed ID: 22558140
                SO-VID: c88e942f-873e-40bd-9e27-63fe2dbb2061
                Copyright © Wesolowski et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                Date received : 28 September 2011
                Date accepted : 15 March 2012
                Page count
                Pages: 6
                Categories
                Subject: Research Article
                Subject: Biology
                Subject: Population Biology
                Subject: Epidemiology
                Subject: Economic Epidemiology
                Subject: Social Epidemiology
                Subject: Computer Science
                Subject: Information Technology
                Subject: Earth Sciences
                Subject: Geography
                Subject: Human Geography
                Subject: Social Geography
                Subject: Engineering
                Subject: Electrical Engineering
                Subject: Communications
                Subject: Medicine
                Subject: Global Health
                Subject: Non-Clinical Medicine
                Subject: Health Care Policy
                Subject: Geographic and National Differences
                Subject: Public Health
                Subject: Socioeconomic Aspects of Health
                Subject: Science Policy
                Subject: Technology Development
                Subject: Social and Behavioral Sciences
                Subject: Communications
                Subject: Economics
                Subject: Economic Models
                Subject: Behavioral Matrix
                Subject: Health Economics
                Subject: Information Economics
                Subject: Sociology
                Subject: Social Networks
                Subject: Social Research

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