Evidence map›Paper›PMID 29549589›Full record

ArticleEcoHealth2018

Mapping Potential Amplification and Transmission Hotspots for MERS-CoV, Kenya.

Stephen Gikonyo, Tabitha Kimani, Joseph Matere, Joshua Kimutai, Stella G Kiambi, Austine O Bitek, K J Z Juma Ngeiywa, Yilma J Makonnen, Astrid Tripodi, Subhash Morzaria and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in EcoHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.9field-weighted citation impact, top 7% 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

15 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
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

13 authors at 3 institutions in 3 countries.

Stephen GikonyoEmergency Centre for Transboundary Animal Diseases - (ECTAD) Kenya, Food and Agriculture Organization of the United Nations (FAO), UN Office in Nairobi, Gigiri, Kenya.
Tabitha KimaniEmergency Centre for Transboundary Animal Diseases - (ECTAD), Regional Office for East Africa Kenya, Food and Agriculture Organization of the United Nations (FAO), UN Office in Nairobi, Gigiri, Kenya.
Joseph MatereEmergency Centre for Transboundary Animal Diseases - (ECTAD) Kenya, Food and Agriculture Organization of the United Nations (FAO), UN Office in Nairobi, Gigiri, Kenya.
Joshua KimutaiEmergency Centre for Transboundary Animal Diseases - (ECTAD) Kenya, Food and Agriculture Organization of the United Nations (FAO), UN Office in Nairobi, Gigiri, Kenya.
Stella G KiambiEmergency Centre for Transboundary Animal Diseases - (ECTAD) Kenya, Food and Agriculture Organization of the United Nations (FAO), UN Office in Nairobi, Gigiri, Kenya.
Austine O BitekEmergency Centre for Transboundary Animal Diseases - (ECTAD) Kenya, Food and Agriculture Organization of the United Nations (FAO), UN Office in Nairobi, Gigiri, Kenya.
K J Z Juma NgeiywaDirectorate of Veterinary Services, State Department of Livestock, Ministry of Agriculture, Livestock and Fisheries, Nairobi, Kenya.
Yilma J MakonnenEmergency Centre for Transboundary Animal Diseases - (ECTAD), Regional Office for East Africa Kenya, Food and Agriculture Organization of the United Nations (FAO), UN Office in Nairobi, Gigiri, Kenya.
Astrid TripodiAnimal Health Service, Animal Production and Health Division, Food and Agriculture Organization of the UN (FAO), Rome, Italy.
Subhash MorzariaAnimal Health Service, Animal Production and Health Division, Food and Agriculture Organization of the UN (FAO), Rome, Italy.
Juan LubrothAnimal Health Service, Animal Production and Health Division, Food and Agriculture Organization of the UN (FAO), Rome, Italy.
Gabriel RugalemaEmergency Centre for Transboundary Animal Diseases - (ECTAD) Kenya, Food and Agriculture Organization of the United Nations (FAO), UN Office in Nairobi, Gigiri, Kenya.
Folorunso Oludayo FasinaEmergency Centre for Transboundary Animal Diseases - (ECTAD) Kenya, Food and Agriculture Organization of the United Nations (FAO), UN Office in Nairobi, Gigiri, Kenya. Folorunso.fasina@fao.org.
Food and Agriculture Organization of the United Nations · ITMinistry of Agriculture Livestock and Fisheries · KEUniversity of Pretoria · ZA

Funding

United States Agency for International Development OSRO/GLO/505/USA
6 · The paper itself

Abstract

Dromedary camels have been implicated consistently as the source of Middle East respiratory syndrome coronavirus (MERS-CoV) human infections and attention to prevent and control it has focused on camels. To understanding the epidemiological role of camels in the transmission of MERS-CoV, we utilized an iterative empirical process in Geographic Information System (GIS) to identify and qualify potential hotspots for maintenance and circulation of MERS-CoV, and produced risk-based surveillance sites in Kenya. Data on camel population and distribution were used to develop camel density map, while camel farming system was defined using multi-factorial criteria including the agro-ecological zones (AEZs), production and marketing practices. Primary and secondary MERS-CoV seroprevalence data from specific sites were analyzed, and location-based prevalence matching with camel densities was conducted. High-risk convergence points (migration zones, trade routes, camel markets, slaughter slabs) were profiled and frequent cross-border camel movement mapped. Results showed that high camel-dense areas and interaction (markets and migration zones) were potential hotspot for transmission and spread. Cross-border contacts occurred with in-migrated herds at hotspot locations. AEZ differential did not influence risk distribution and plausible risk factors for spatial MERS-CoV hotspots were camel densities, previous cases of MERS-CoV, high seroprevalence and points of camel convergences. Although Kenyan camels are predisposed to MERS-CoV, no shedding is documented to date. These potential hotspots, determined using anthropogenic, system and trade characterizations should guide selection of sampling/surveillance sites, high-risk locations, critical areas for interventions and policy development in Kenya, as well as instigate further virological examination of camels.

Indexed as

Geographic MappingAnimal DiseasesAnimalsCamelusCoronavirus InfectionsDisease ReservoirsGeographic Information SystemsKenyaMiddle East Respiratory Syndrome CoronavirusPrevalencePublic Health SurveillanceSeroepidemiologic StudiescamelhotspotKenyaMERS-CoVrisktransmission

Identifiers

PMID29549589
PMCPMC7088189
OpenAlexW2790466303

What OpenQuestion holds

Textmetadata
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.