Evidence map›Paper›PMID 39360262›Full record

ArticleFrontiers in public health2024

Diagnostics for detection and surveillance of priority epidemic-prone diseases in Africa: an assessment of testing capacity and laboratory strengthening needs.

Aytenew Ashenafi, Olajumoke Sule, Trevor Peter, Silver Mashate, Osborn Otieno, Abebaw Kebede, John Oio, Kekeletso Kao, Jane Carter, Toni Whistler and 2 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

12 authors.

Aytenew AshenafiCentre of Laboratory Systems Division, Africa Centres for Disease Control and Prevention, Addis Ababa, Ethiopia.
Olajumoke SuleInternational Health Regulations Strengthening Project, Health Protection Operations, United Kingdom Health Security Agency, London, United Kingdom.
Trevor PeterClinton Health Access Initiative, Boston, MA, United States.
Silver MashateAfrican Society for Laboratory Medicine, Addis Ababa, Ethiopia.
Osborn OtienoTechnical Advice and Partnerships Department, The Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.
Abebaw KebedeCentre of Laboratory Systems Division, Africa Centres for Disease Control and Prevention, Addis Ababa, Ethiopia.
John OioCentre of Laboratory Systems Division, Africa Centres for Disease Control and Prevention, Addis Ababa, Ethiopia.
Kekeletso KaoDiagnostic System Strengthening Unit, FIND, Geneva, Switzerland.
Jane CarterClinical and Diagnostics Programme, Amref Health Africa, Nairobi, Kenya.
Toni WhistlerTechnical Advice and Partnerships Department, The Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.
Nqobile NdlovuAfrican Society for Laboratory Medicine, Addis Ababa, Ethiopia.
Yenew KebedeCentre of Laboratory Systems Division, Africa Centres for Disease Control and Prevention, Addis Ababa, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In 2023, Africa experienced 180 public health emergencies, of which 90% were infectious diseases and 75% were related to zoonotic diseases. Testing capacity for epidemic-prone diseases is essential to enable rapid and accurate identification of causative agents, and for action to prevent disease spread. Moreover, testing is pivotal in monitoring disease transmission, evaluating public health interventions and informing targeted resource allocation during outbreaks. An online, self-assessment survey was conducted in African Union Member States to identify major challenges in testing for epidemic-prone diseases. The survey assessed current capacity for diagnosing priority epidemic-prone diseases at different laboratory levels. It explored challenges in establishing and maintaining testing capacity to improve outbreak response and mitigate public health impact. Survey data analysed diagnostic capacity for priority infectious diseases, diagnostic technologies in use, existing surveillance programmes and challenges limiting diagnostic capacity, by country. The survey result from 15 Member States who responded to the survey, showed high variability in testing capacity and technologies across countries and diverse factors limiting testing capacity for certain priority diseases like dengue and Crimean-Congo haemorrhagic fever. At the same time diagnostic capacity is better for coronavirus disease 2019 (COVID-19), polio, and measles due to previous investments. Unfortunately, many countries are not utilizing multiplex testing, despite its potential to improve diagnostic access. The challenges of limited laboratory capacity for testing future outbreaks are indeed significant. Recent disease outbreaks in Africa have underscored the urgent need to strengthen diagnostic capacity and introduce cost-effective technologies. Small sample sizes and differing disease prioritisation within each country limited the analysis. These findings suggest the benefits of evaluating laboratory testing capacity for epidemic-prone diseases and highlight the importance of effectively addressing challenges to detect diseases and prevent future pandemics.

Indexed as

EpidemicsAfricaCommunicable DiseasesCOVID-19Disease OutbreaksHumansLaboratoriesPublic HealthSurveys and Questionnairescost-effective diagnostic technologiesepidemic-prone diseaseslaboratory testing capacityoutbreak responsepublic health emergencies

Identifiers

PMID39360262
PMCPMC11445050

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.