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

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About: Mapping Potential Amplification and Transmission Hotspots for MERS-CoV, Kenya Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Mapping Potential Amplification and Transmission Hotspots for MERS-CoV, Kenya
Creator	Tripodi, Astrid Kiambi, Stella Kimutai, Joshua Lubroth, Juan Makonnen, Yilma Morzaria, Subhash Rugalema, Gabriel Bitek, Austine Kimani, Tabitha Gikonyo, Stephen Matere, Joseph Juma Ngeiywa, K Oludayo Fasina, Folorunso
topic	covid:019d06da261e61aaf09079bc2ebed8e1a13fbea2#this
Source	Medline; PMC
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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10393-018-1317-6) contains supplementary material, which is available to authorized users.
has issue date	2018-03-16(xsd:dateTime)
bibo:doi	10.1007/s10393-018-1317-6
bibo:pmid	29549589
has license	no-cc
sha1sum (hex)	019d06da261e61aaf09079bc2ebed8e1a13fbea2
schema:url	https://doi.org/10.1007/s10393-018-1317-6
resource representing a document's title	Mapping Potential Amplification and Transmission Hotspots for MERS-CoV, Kenya
has PubMed Central identifier	PMC7088189
has PubMed identifier	29549589
schema:publication	Ecohealth
resource representing a document's body	covid:019d06da261e61aaf09079bc2ebed8e1a13fbea2#body_text
is http://vocab.deri.ie/void#inDataset of	proxy:http/ns.inria.fr/covid19/019d06da261e61aaf09079bc2ebed8e1a13fbea2
is schema:about of	named entity 'hotspots' named entity 'MERS-CoV' named entity 'surveillance' named entity 'Diseases' named entity 'Office' named entity 'FARMING' named entity 'TO PREVENT' named entity 'FREQUENT' named entity 'EPIDEMIOLOGICAL' named entity 'MATCHING' named entity 'MIDDLE EAST RESPIRATORY SYNDROME CORONAVIRUS' named entity 'RESULTS' named entity 'FACTORIAL' named entity 'EMPIRICAL' named entity 'ROLE' named entity 'UNDERSTANDING' named entity 'HIGH-RISK' named entity 'PREVALENCE' named entity 'ROUTES' named entity 'CAMELS' named entity 'NAIROBI' named entity 'KENYA' named entity 'CENTRE' named entity 'SOURCE' named entity 'RISK' named entity 'SYSTEM' named entity 'KENYA' named entity 'TO IDENTIFY' named entity 'SPREAD' named entity 'GEOGRAPHIC INFORMATION SYSTEM' named entity 'REGIONAL OFFICE' named entity 'ANIMAL DISEASES' named entity 'CRITERIA' named entity 'TRADE' named entity 'HAVE' named entity 'FOCUSED' named entity 'MARKETS' named entity 'DENSITY' named entity 'MARKETING' named entity 'PRACTICES' named entity 'CAMEL' named entity 'HIGH' named entity 'SPECIFIC' named entity 'CONTROL' named entity 'SURVEILLANCE' named entity 'SLABS' named entity 'INFECTIONS' named entity 'CONVERGENCE' named entity 'PROCESS' named entity 'HUMAN' named entity 'USING' named entity 'TRANSMISSION' named entity 'PRODUCTION' named entity 'MIGRATION' named entity 'POPULATION' named entity 'INTERACTION' named entity 'USED' named entity 'DROMEDARY' named entity 'SEROPREVALENCE' named entity 'POTENTIAL' named entity 'MAPPED' named entity 'AGRO' named entity 'POINTS' named entity 'CIRCULATION' named entity 'PRIMARY' named entity 'DEFINED' named entity 'MULTI'

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