Evidence map›Paper›PMID 42583880›Full record

ArticleHuman vaccines & immunotherapeutics2026

Somalia's lifeline: Digitalization and AI.

Abdifatah Nour Rage

Abstract readLetter
In one paragraph

Article in Human vaccines & immunotherapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Abdifatah Nour RageDepartment of Computer Science, Faculty of Computer Sciences and Information Technology, Salaam University, Mogadishu, Somalia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Somalia's fragile health system, strained by decades of conflict, climate shocks, and persistently low immunization coverage, remains dangerously vulnerable to preventable disease outbreaks. With measles resurgent and full vaccination coverage stagnating at just 55% nationally and as low as 26% in some states - the country faces recurrent epidemics it cannot withstand. Digitalization and artificial intelligence offer a critical lifeline, with potential to transform disease surveillance, optimize resource allocation, rebuild primary healthcare delivery, and empower frontline health workers through real-time data. Early initiatives demonstrate tangible benefits: an electronic immunization registry in Benadir improved vaccination tracking and reduced dropout rates, while mobile health messaging enhanced caregiver communication. AI-powered predictive models, already forecasting malnutrition trends using climate and conflict data, could be extended to anticipate measles outbreaks, enabling proactive responses. Despite significant barriers - limited connectivity, unreliable electricity, insufficient technical expertise, nascent governance frameworks, and a digital divide threatening to exclude vulnerable populations - strategic investment in context-appropriate digital health is an immediate priority, not an optional upgrade. Protecting Somali children through timely vaccination, strengthened surveillance, and data-driven decision-making must be treated as an urgent health security imperative. Digitalization and AI are practical, essential tools for a country that cannot afford another outbreak.

Indexed as

Artificial IntelligenceDigital HealthDisease OutbreaksHumansImmunization ProgramsMeaslesPublic Health InfrastructureSomaliaVaccinationVaccination Coverageartificial intelligenceDigital healthdisease surveillancefragile stateshealth system strengtheningimmunization

Identifiers

PMID42583880
PMCPMC13471107

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.