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Climate-informed surveillance-to-action models address policy gaps in Somali infectious disease managementClimate-Informed Models Could Improve Disease Tracking in Somalia

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Key Takeaway
Note that a surveillance-to-action framework can improve the integration of warning signals into district-level responses.

This narrative review evaluates the current landscape of infectious disease surveillance in Somalia, specifically focusing on conditions such as Cholera, Malaria, Dengue, Rift Valley fever, Measles, Diphtheria, and Polio. The review synthesizes existing surveillance assets, including EWARN, IDSRS/DHIS2, FEWS NET, FSNAU intelligence, WASH monitoring, livestock signals, and community-based reporting.

The authors identify a critical gap where current warning signals are not sufficiently integrated into district-level risk assessments or into pre-financed preparedness actions. To address these gaps, the review proposes a surveillance-to-action framework. This framework incorporates multisource signal detection, integrated district risk assessment, disease-specific trigger decisions, and anticipatory public health functions.

A primary limitation of this review is that it analyzes existing systems and policy gaps rather than providing primary data on clinical outcomes. The findings are intended to inform public health policy and infrastructure rather than evaluating the clinical efficacy of a specific medical intervention. The proposed framework aims to improve the transition from warning signals to actionable public health responses in high-risk regions.

How this fits prior evidence

This narrative review addresses a gap in the management of infectious diseases like Malaria and Dengue by proposing a surveillance-to-action framework. While prior coverage identified specific clinical markers for dengue severity and the efficacy of SP+AQ for malaria chemoprevention, this review focuses on the systemic infrastructure required to manage these and other diseases in the Somali population.

A narrative review examined how to improve disease tracking and response in Somalia. The study focused on how climate data can help health officials prepare for outbreaks of diseases such as cholera, malaria, dengue, and measles. It looked at how current warning signals are used to protect vulnerable groups, including nomadic communities and children.

Researchers found that while several tracking tools already exist, they are not always used effectively at the local level. Currently, warning signals are not well integrated into district-level risk assessments. This means that even when a threat is detected, it can be hard to trigger pre-financed actions to stop a disease from spreading.

Because this was a narrative review of existing systems rather than a clinical trial, it does not test a specific medicine or treatment. Instead, it proposes a new framework for health officials. This model suggests using multiple data sources to create a faster, more coordinated response to infectious diseases in the region.

What this means for you:
A proposed framework aims to better link climate data to local health actions to improve disease response.

Common questions

What diseases does this model target?

The framework focuses on several infectious diseases that are common in the region. These include cholera, malaria, dengue, Rift Valley fever, measles, diphtheria, and polio. The goal is to use better data to prepare for these specific illnesses.

What is the main problem with the current system?

The review found that warning signals are not well integrated into district-level risk assessments. This means that even when a warning is detected, it is often difficult to turn that information into immediate, pre-financed actions to stop an outbreak.

Is this a new medical treatment?

No, this is not a new medicine or clinical treatment. It is a narrative review of existing systems. It proposes a new way for health officials to organize data and coordinate their responses to disease outbreaks.

Study Details

Study typeSystematic review
EvidenceLevel 1
PublishedSep 2026
View Original Abstract ↓
Climate variability is reshaping infectious disease risk through ecological, environmental, social, and health-system pathways. However, its operational implications remain insufficiently defined in fragile and conflict-affected settings. Somalia is a critical case because recurrent droughts and floods intersect with displacement, food insecurity, weak water and sanitation infrastructure, disrupted immunisation, livestock dependence, and constrained health-system capacity. This narrative review synthesises evidence on climate-sensitive infectious disease risks in Somalia, examines existing surveillance and early warning systems, identifies policy and implementation gaps, and proposes priorities for a climate-informed surveillance-to-action model for infectious disease control. The review distinguishes directly climate-sensitive infections, including cholera, malaria, dengue, and Rift Valley fever, from indirectly climate-amplified vaccine-preventable diseases, including measles, diphtheria, and polio. While Somalia has important surveillance and early warning assets, including EWARN, IDSRS/DHIS2, FEWS NET, FSNAU intelligence, WASH monitoring, livestock signals, and community-based reporting, these streams remain insufficiently integrated into district-level risk assessment and pre-financed preparedness action. Therefore, the central challenge is not the absence of warning signals but the failure to convert them into timely, disease-specific, and accountable responses. We propose a surveillance-to-action framework based on multisource signal detection, integrated district risk assessment, disease-specific trigger decisions, early preparedness actions, and feedback, accountability, and learning. Closing Somalia's warning-to-action gap requires pre-agreed disease-specific triggers, One Health coordination, flexible anticipatory financing, strengthened district surveillance capacity, and equity-centred outreach to internally displaced persons, pastoralist and nomadic communities, zero-dose children, malnourished populations, and hard-to-reach areas. Climate-informed surveillance should be understood not merely as better data collection but as an anticipatory public health function designed to act before climate shocks become infectious disease emergencies.
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