Barriers and Entry Points for Community Participation in Early Warning Systems

Abstract

Early Warning Systems (EWS) are crucial for safeguarding communities, but are vulnerable to failure due to a technocratic focus that excludes local communities. This thesis closes the gap between normative participatory principles and practical implementation by exploring the entry points or challenges that affect community participation. Adopting a complexity theory lens, the study conducts a qualitative, instrumental case study to analyze participation in EWS in Homa Bay and Kilifi counties, in Kenya. Data were collected through 15 semi-structured individual and joint interviews and 7 focus group discussions (FGDs). A broad spectrum of stakeholders was consulted, including government officials, Kenya Red Cross Society (KRCS) staff, and community members. The results reveal that participation is primarily geared toward dissemination (Pillar III) and is mostly ad hoc and instrumental. Critical challenges include the lack of DRM planning and institutionalized procedures to include communities. These challenges reinforce unequal power dynamics and frequently regard communities as passive recipients of information. On the other hand, the study identifies important entry points, such as ensuring inclusive and decentralized communication, and leveraging existing community structures. The research highlights the importance of advancing knowledge co-creation processes and the systematic inclusion of vulnerable groups across all four pillars of EWS to establish context-sensitive and transformative EWS.

Popular Abstract

How can we strengthen community participation in Early Warning Systems?

Early warning systems (EWS) save lives, but only if the right people are involved from the start, reached by alerts, understand the message, and know what to do. In Kenya, some communities are still left out of the loop.

Every year, floods, droughts, and storms destroy livelihoods across East Africa. EWS are designed to alert people before disaster hits, giving them time to act. But a warning that never reaches you, or that you don't understand, is no warning at all. So who actually gets warned, and who gets to help shape the system?

To find out, this study travelled to two counties in Kenya: Homa Bay on the shores of Lake Victoria, and Kilifi on the Indian Ocean coast. Both counties are regularly struck by extreme weather. Through interviews and focus group discussions with community members, government officials, and staff from the Kenya Red Cross Society, a clear pattern emerged:communities are mostly treated as passive recipients of information, not as active contributors.

In practice, this means local people often receive alerts, but they are rarely involved in identifying risks, monitoring hazards, or planning how to respond. Participation is sporadic and top-down. Crucially, the most vulnerable people—women, persons with disabilities, and low-income households—are often left out entirely.

Why does this matter? Because communities hold irreplaceable knowledge. A farmer knows which fields flood first. A local elder knows which routes become impassable. When that knowledge is ignored, warnings become generic, responses become slower, and lives are lost that didn't need to be.

The study found concrete ways forward. Using trusted community figures to relay messages, building two-way communication so people can report what they're seeing on the ground, and strengthening local response capacities can all dramatically improve how warning systems work. The key is shifting from a megaphone model—where authorities broadcast and communities listen—to a genuine partnership, where local knowledge shapes decisions from the start.

The findings are grounded in real conversations with real people living with real risk. While the study focuses on Kenya, the lessons speak to everywhere: the technology itself matters far less than whether the people it's meant to protect are part of building it.

• author: Guidotti, Ismea and Cestino Lopez, Gabriela Ana
• supervisor: Mo Hamza
• organization: Division of Risk Management and Societal Safety
• course: VBRM15 20261
• year: 2026
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering
• keywords: Disaster Risk Management, Climate Change Adaptation, Early Warning Systems, Community Participation, Localization, Inclusivity
• language: English
• id: 9234799
• date added to LUP: 2026-06-12 09:38:59
• date last changed: 2026-06-12 09:38:59