Evidence map›Paper›PMID 31798311›Full record

ArticleTropical medicine and health2019

A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan.

Rania Salah Eldien Bashir, Osama Ahmed Hassan

Open access · goldAbstract read
In one paragraph

Article in Tropical medicine and health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 4 pooled it
1.2field-weighted citation impact, top 22% 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

12 citing papers in PubMed, 4 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
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

2 authors at 2 institutions in 3 countries.

Rania Salah Eldien BashirAnimal Health Directorate, General Directorate of Animal Health and Epizootic Diseases Control, Ministry of Livestock, Khartoum, Sudan.
Osama Ahmed Hassan2The Centre for Global Health, Department of Community Medicine and Global Health, Faculty of Medicine, University of Oslo, Oslo, Norway.ORCID 0000-0001-7633-3782
Federal Ministry of Health · SDUniversity of Oslo · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRift Valley fever (RVF) is a zoonotic viral vector-borne disease that affects both animals and humans and leads to severe economic consequences. RVF outbreaks are triggered by a favorable environment and flooding, which enable mosquitoes to proliferate and spread the virus further. RVF is endemic to Africa and has spread to Saudi Arabia and Yemen. There is great concern that RVF may spread to previously unaffected geographic regions due to climate change. We aimed to better understand the spatiotemporal pattern of the 2007 RVF outbreak at the human-animal-environment interface and to determine environmental factors that may have effects on RVF occurrence in Gezira state, Sudan. MATERIALS AND

methodsWe compiled epidemiological, environmental, and spatiotemporal data across time and space using remote sensing and a geographical information system (GIS). The epidemiological data included 430 RVF human cases as well as human and animal population demographic data for each locality. The cases were collected from 41 locations in Gezira state. The environmental data represent classified land cover during 2007, the year of the RVF outbreak, and the average of the Normalized Difference Vegetation Index (NDVI) for 6 months of 2007 is compared with those of 2010 and 2014, when there was no RVF outbreak. To determine the effect of the environmental factors such as NDVI, soil type, and RVF case's location on the Blue Nile riverbank on RVF incidence in Gezira state, a multilevel logistic regression model was carried out.

resultsWe found that the outbreak in Gezira state occurred as a result of interaction among animals, humans, and the environment. The multilevel logistic regression model (

conclusionsPrecise remote sensing and the GIS technique, which rely on environmental indices such as NDVI and soil type that are satellite-derived, can contribute to establishing an early warning system for RVF in Sudan.Future preparedness and strengthening the capacity of regional laboratories are necessary for early notification of outbreaks in animals and humans.

Indexed as

Geographical information systemGezira stateMultilevel logistic regressionNormalized Difference Vegetation IndexOne HealthRemote sensingRift Valley feverSoil typeSudan

Identifiers

PMID31798311
PMCPMC6880409
OpenAlexW2990672357

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.