According to GSMA’s Digital Entrepreneurship in Kenya 2014 report, 99% of internet subscribers in Kenya access the internet through mobile devices. Kenya has been the leader in mobile banking, with apps like M-PESA, Zoona, and others. When taking TechChange’s Mobile Phones for Public Health online course with a group of 10 colleagues at PATH, I was curious to learn what mHealth looked like in Kenya and learn what lessons I can apply to my mHealth programs in Bihar, India. As part of my final project for the course, I asked Debjeet Sen, one of my colleagues at PATH based in Kisumu, Kenya, to share his views on the state of mHealth interventions in Kenya.

Like other developing countries, mHealth in Kenya primarily focuses on two core areas:

1. Data collection, where mobile devices replace and/or complement traditional paper-based tools;

2. Behaviour change, where mobile devices are used to disseminate key messages and good practices among communities.

And like any low-resource setting, there are inherent challenges in rolling out mHealth interventions, so it is important to be cognizant of them and develop appropriate counter-strategies.

mHealth training for CHWs in Kenya photo 1Community health workers (CHWs) during a mHealth training in Kenya

Here are a few challenges that Debjeet sees mHealth interventions face in Kenya:

  1. Multiple mHealth interventions have remained at the pilot stage

Many mHealth interventions in Kenya have not yet been integrated into larger health and information technology systems due to the absence of a clear scale-up strategy in the pilot project design and a lack of consensus on common software and hardware requirements. Different projects use different handsets with different operating systems for different mobile platforms. Aligning individual mHealth projects with regional and national management information systems (MIS) is necessary, but may not necessarily happen, as mHealth projects often function autonomously. Wherever possible, it is important to integrate mHealth data streams with existing MIS platforms in order to prevent duplication and mixing of data.

  1. Many mHealth projects rely on the use of smartphones

Smartphones can be expensive and beyond the purchasing power of Kenyan government institutions and individuals. Most people continue to rely on low-end phones, which are cheap and widely available.

  1. Scarcity of a reliable power source

Electricity supply in Kenya is unreliable and regular electricity is mostly available only in semi-urban and urban areas. Since graphics-enabled smartphones are highly power-intensive, any mHealth project that relies on smartphones may face challenges if users struggle to keep their phones regularly charged.

However, there are opportunities that can help tackle these mHealth challenges:

  1. Almost universal penetration of cell phones

Kenya has a very strong base for implementing mHealth projects, partly because Kenyans are familiar with the use of mobile phones for functions other than just making and receiving calls. Mobile banking app like M-PESA is used by tens of millions of Kenyans. In fact, many financial transactions in the social sector, such as paying for trainings and workshops, issuing stipends to community health workers (CHWs), and transferring conditional cash transfers are all done through M-PESA. In a way, this extensive use of M-PESA for the social sector is already (indirectly) helping improve mHealth outcomes.

  1. Incentivizing end-users such as CHWs to buy the phones

A common mistake of many mHealth projects is to provide the cell phones for the project as “giveaways.” In turn, this results in less accountability and a lack of ownership among the phone users. Asking CHWs to partially cover the cost of the phones or buy them is a good strategy to create ownership and accountability. This also has ramifications for scale-up and sustainability, as governments in low-resource countries may be unable to cover the entire cost of purchasing cell phones.

  1. Work is underway to develop a plan to coordinate mHealth activities in Kenya

There are plans to align multiple platforms, hardware, and software with a common national strategy and to ensure that data collected from these activities are facilitated to feed into national and regional MIS.

4. Simple smartphone apps.

The simpler smartphone apps have been demonstrated to assist frontline workers such as CHWs in data collection and as job aids to assist them in household visits and group and/or individual counselling.  In an environment that faces challenges in literacy rates as well as  financial and network connectivity, we cannot simply develop and run any iPhone or Android app. Sometimes, it is important to develop ways to access mHealth tools offline.

CHWs learning about mHealth in KenyaCommunity health workers explore Information for Action app during the field test

In particular, Debjeet discussed his work on the Information for Action app, an innovative app running on the Android platform designed by the Human Sciences Research Council of South Africa. The app collects information from CHW home visits and immediately turns the collected information into actionable information in the form of a key message or suggested actions that can be shared by CHWs with caregivers. It is a dynamic app because it collects information and provides contextualized key messages and suggested actions on areas of children’s development, health, nutrition, and water and sanitation. The Information for Action app also stores records of individual home visits, which can be used by CHWs to plan for future home visits, as well as uploaded into a central data server/cloud, where supervisors can monitor for quality of home visits.

Currently, a field test of the app is being carried out in Kenya and South Africa to determine its operational feasibility and acceptability among CHWs, their supervisors, and community members receiving home visits from CHWs. Debjeet would be happy to share the app after the field tests are completed.

Debjeet asserted that the TechChange mHealth course has provided him with a structured overview of mHealth, which is a contrast to the way he has generally learned about mHealth through on-the-job experiences. The TechChange course has exposed him to interesting resources, people, and mHealth projects and he wishes to use the learnings from the course in his current projects at PATH

Why learning about mHealth in Kenya is useful for India

Since working in Bihar is quite similar to working in other countries of low resource settings like Kenya, it is helpful to learn about the challenges and strategies of different countries as we develop mHealth programs in Bihar. The PATH team in Bihar provides knowledge management support to a behavior change community mobilization project called Parivartan, which means “transformation”. The knowledge management team is in the process of conceptualizing a mobile based data collection and analysis system for village health sanitation nutrition committee (VHSNC). The committee members would develop effective social mobilization strategies to influence people to attend village health sanitation nutrition day (VHSND) at local primary health centers for health and nutrition related services. We have already started collecting a lot quality assurance sampling (LQAS) data through tablets and Kenya’s mHealth lessons definitely help as the fuel to work at per PATH’s technology and healthcare innovation in low and middle income group setting.

The knowledge on mHealth in Kenya which Debjeet has shared will help my team develop its own mHealth strategy in a low-resource setting such as Bihar, India.

If you are interested in learning more about the current state of mHealth, enroll in our upcoming mHealth course, TC309: Mobile Phones for Public Health today.

Alumni bios 

Debjeet Sen

Debjeet Sen is a Senior Associate with PATH. He has managed and supported a range of early childhood development (ECD), infant and young child nutrition, prevention of mother-to-child transmission (PMTCT) of HIV, and maternal and child health projects — primarily in Kenya and Mozambique, but also in DRC, Ethiopia, India, Malawi, Namibia, Nigeria, Pakistan, Rwanda, and South Africa. His core skills include technical design and management of complex projects, monitoring and evaluation (M&E), behavior change communication (BCC), curriculum development, capacity building and training, organizational development, documentation, and technical research and writing. He is currently based in Kisumu, Kenya. You can connect with Debjeet on LinkedIn.

Pratyaya Mitra

Pratyaya Mitra is a communication professional with more than 12 years of experience in corporate and social sector. Currently working as communication and documentation officer in PATH Knowledge Management team in Bihar, India. Previously, worked with UNICEF as communication consultant for C4D, advocacy-partnership. Pratyaya worked in corporate communication and as copywriter with Ogilvy and Mather. He works with wide range of communication channels such as, written, audio visual, online, social media and mobile. He plays pivotal role in advocacy, PR and social and mHealth communication strategy to meet the project goal and business development. He did his masters in communication. You can connect with Pratyaya on Linkedin, Twitter, and Facebook.


This is a guest post by Dhairya Dalal. If you are interested in using crisis mapping and using technology for humanitarian relief, conflict prevention, and election monitoring, consider taking our course Technology for Conflict Management and Peacebuilding.


Recently, I had the opportunity to run an election monitoring simulation for TechChange’s TC109: Conflict Management and Peacebuilding course. Led by Charles Martin-Shields, TC109 taught over 40 international participants how mapping, social media, and mobile telephones could effectively support the work of conflict prevention and management.  Robert Baker taught participants how the Uchaguzi team leveraged crowd-sourcing and Ushahidi, a web based crisis mapping platform, to monitor the 2013 Kenyan elections.

For the simulation activity, my goal was to create a dynamic hands-on activity. I wanted to demonstrate how crisis mapping technologies are being used to promote free and fair elections, reduce electoral violence, and empower citizens. To provide students a realistic context, we leveraged live social media data from the Kenyan elections. Participants walked through the process of collecting data, verifying it, and critically analyzing it to provide a set of actionable information that could have been used by local Kenyan stakeholders to investigate reports of poll fraud, violence, and voter intimidation.

Below I’ll provide a brief history of election monitoring in the context of Kenyan elections and provide a more detailed look at the simulation activity.

Brief History of Election Monitoring and Uchaguzi

uchaguziIn 1969, the Republic of Kenya became a one-party state whose electoral system was based on districts that aligned with tribal areas. This fragile partitioning often generated internal friction during the electoral cycle. The post-election violence of 2007-2008 was characterized by crimes of murder, rape, forcible transfer of the population and other inhumane acts. During the 30 days of violence more than 1,220 people were killed, 3,500 injured and 350,000 displaced, as well as hundreds of rapes and the destruction of over 100,000 properties. 2

Ushahidi was developed in the wake of the 2008 post-election violence. Ushahidi, is a website that was designed to map reports of violence in Kenya after the post-election fallout. However, Usahidi has since evolved into a platform used for crisis mapping, crowd-sourced data gathering, and many other things. Since then, the name Ushahidi has come to represent the people behind the Ushahidi platform. 2

Uchaguzi was an Ushahidi deployment, formed to monitor the 2013 Kenyan general elections held this past March. The Uchaguzi project aimed to contribute to stability efforts in Kenya, by increasing transparency and accountability through active civic participation in the electoral cycles. The project leveraged existing (traditional) activities around electoral observation, such as those carried out by the Elections Observer Group (ELOG) in Kenya.3

Election Monitoring with CrowdMaps

TC109 Simulation Figure 1: TC109 Simulation map (view official Uchaguzi map here:

For the simulation activity, we used Ushahidi’s CrowdMap web application. CrowdMap is a cloud-based implementation of the Ushahidi platform that allows users to quickly generate a crisis map. Crowdmap has the ability to collect and aggregate data from various sources likes SMS text messages, Twitter, and online report submissions.

To provide the participants a more realistic context, our simulation collected real tweets from the Kenyan elections that had just occured the prior week. Our simulation aggregated tweets from Uchaguzi’s official hashtag, #Uchaguzi, as well several other hashtags like #KenyanElections and #KenyaDecides. In addition students were tasked with creating reports from Uchaguzi’s facebook page and local Kenyan news sites.

The aggregated information was then geo-tagged, classified and processed by the participants. The participants created reports, which described incidents licrowdmapke instances of voter intimidation, suspected poll fraud, and reports of violence. The CrowdMap platform plotted these reports on a map of Kenya based on coordinates the participants provided during the geo-tagging phase.  The resulting map showed aggregation patterns, which would have allowed local actors to see where certain types of incidents were taking place and respond accordingly.

Conclusion: Going beyond the Technology and Cultivating Information Ecosystems

workflow   Figure 2: Uchaguzi Workflow

While technological innovations have made it easier to collect vast amounts of data in real-time during a crisis or an live event, a lot of process and human capital is still required to ensure that the data can processed and acted upon. Prior to the Kenyan elections, the Uchaguzi team established a well-planned information workflow and local relationships to ensure that information was ultimately delivered to the local police, elections monitors, and other stakeholders who could take action on the reports received. This workflow also delineated volunteer workgroups (based on Standby TaskForce’s information processing workflow) which were responsible for different parts of information collection process from Media Monitoring and Translation to Verification and Analysis.

To provide the participants an understanding of the full picture, we had them assume the role of various workgroups. They were challenged to identify how the information would be gathered, verified, classified, and distributed to local stakeholders. Participants followed the official Uchaguzi workflow and learned more about the challenges faced by the various workgroups. For example how would you translate a report submitted in Swahili? How would you determine if a report is true or falsely submitted to instigate provocation? How would you escalate reports of violence or imminent danger like a bomb threat?

Overall, the participants were able to learn about both the technology that enables the crowd-sourcing of election monitoring and the strategic and deliberate structures put in place to ensure an information feedback loop. Participants were able to gain an understanding of the complexity involved in monitoring an election using real data from the Kenyan elections. They were also given an opportunity to recommend creative suggestions and innovations that were sent to the Ushahidi team for future deployments.

About the Author:
Dhairya Dalal is a business systems analyst at Harvard University, where he is also pursuing his master’s degree in Software Engineering. Dhairya serves a curriculum consultant for TechChange and is responsible for teaching hands-on technical workshops centered around crisis mapping and open gov APIs, as well as strategic lessons on social media strategy and digital organizing.

1:Background on the Kenyan Electoral Violence 
2: Uchaguzi Deployment
3: Uchaguzi Overview