Evidence map›Paper›PMID 26664978›Full record

ArticleFrontiers in veterinary science2015

African Swine Fever in Uganda: Qualitative Evaluation of Three Surveillance Methods with Implications for Other Resource-Poor Settings.

Erika Chenais, Susanna Sternberg-Lewerin, Sofia Boqvist, Ulf Emanuelson, Tonny Aliro, Emma Tejler, Giampaolo Cocca, Charles Masembe, Karl Ståhl

Open access · goldAbstract read
In one paragraph

Article in Frontiers in veterinary science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.8field-weighted citation impact, top 5% of its field
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, 38 citations in OpenAlex.

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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

9 authors at 3 institutions in 2 countries.

Erika ChenaisNational Veterinary Institute , Uppsala , Sweden ; Swedish University of Agricultural Sciences , Uppsala , Sweden.
Susanna Sternberg-LewerinSwedish University of Agricultural Sciences , Uppsala , Sweden.
Sofia BoqvistSwedish University of Agricultural Sciences , Uppsala , Sweden.
Ulf EmanuelsonSwedish University of Agricultural Sciences , Uppsala , Sweden.
Tonny AliroGulu District Local Government , Gulu , Uganda.
Emma TejlerTorslanda Djurklinik , Torslanda , Sweden.
Giampaolo CoccaNational Veterinary Institute , Uppsala , Sweden.
Charles MasembeMakerere University , Kampala , Uganda.
Karl StåhlNational Veterinary Institute , Uppsala , Sweden ; Swedish University of Agricultural Sciences , Uppsala , Sweden.
Swedish University of Agricultural Sciences · SESwedish Veterinary Agency · SEMakerere University · UG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Animal diseases impact negatively on households and on national economies. In low-income countries, this pertains especially to socio-economic effects on household level. To control animal diseases and mitigate their impact, it is necessary to understand the epidemiology of the disease in its local context. Such understanding, gained through disease surveillance, is often lacking in resource-poor settings. Alternative surveillance methods have been developed to overcome some of the hurdles obstructing surveillance. The objective of this study was to evaluate and qualitatively compare three methods for surveillance of acute infectious diseases using African swine fever in northern Uganda as an example. Report-driven outbreak investigations, participatory rural appraisals (PRAs), and a household survey using a smartphone application were evaluated. All three methods had good disease-detecting capacity, and each of them detected many more outbreaks compared to those reported to the World Organization for Animal Health during the same time period. Apparent mortality rates were similar for the three methods although highest for the report-driven outbreak investigations, followed by the PRAs, and then the household survey. The three methods have different characteristics and the method of choice will depend on the surveillance objective. The optimal situation might be achieved by a combination of the methods: outbreak detection via smartphone-based real-time surveillance, outbreak investigation for collection of biological samples, and a PRA for a better understanding of the epidemiology of the specific outbreak. All three methods require initial investments and continuous efforts. The sustainability of the surveillance system should, therefore, be carefully evaluated before making such investments.

Indexed as

disease detectioninfectious animal diseaseslow-income countriesoutbreak investigationparticipatory epidemiologysmartphone

Identifiers

PMID26664978
PMCPMC4673915
OpenAlexW2203122348

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.