dc.contributor.author |
Gikonyo, Stephen
|
|
dc.contributor.author |
Kimani, Tabitha
|
|
dc.contributor.author |
Matere, Joseph
|
|
dc.contributor.author |
Kimutai, Joshua
|
|
dc.contributor.author |
Kiambi, Stella G.
|
|
dc.contributor.author |
Bitek, Austine O.
|
|
dc.contributor.author |
Juma Ngeiywa, K.J.Z.
|
|
dc.contributor.author |
Makonnen, Yilma J.
|
|
dc.contributor.author |
Tripodi, Astrid
|
|
dc.contributor.author |
Morzaria, Subhash
|
|
dc.contributor.author |
Lubroth, Juan
|
|
dc.contributor.author |
Rugalema, Gabriel
|
|
dc.contributor.author |
Fasina, Folorunso Oludayo
|
|
dc.date.accessioned |
2018-04-17T08:10:53Z |
|
dc.date.issued |
2018-06 |
|
dc.description.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. |
en_ZA |
dc.description.department |
Veterinary Tropical Diseases |
en_ZA |
dc.description.embargo |
2019-06-01 |
|
dc.description.librarian |
hj2018 |
en_ZA |
dc.description.sponsorship |
The United States Agency for International Development through the MERS-CoV applied research activities in Middle East and North East Africa under the USAID’s Emerging Pandemic Threats Program (OSRO/GLO/505/USA). |
en_ZA |
dc.description.uri |
http://link.springer.com/journal/10393 |
en_ZA |
dc.identifier.citation |
Gikonyo, S., Kimani, T., Matere, J. et al. Mapping Potential Amplification and Transmission Hotspots for MERS-CoV, Kenya. EcoHealth (2018) 15: 372-387. https://doi.org/10.1007/s10393-018-1317-6. |
en_ZA |
dc.identifier.issn |
1612-9202 (print) |
|
dc.identifier.issn |
1612-9210 (online) |
|
dc.identifier.other |
10.1007/s10393-018-1317-6 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/64590 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
Springer |
en_ZA |
dc.rights |
© 2018 EcoHealth Alliance. The original publication is available at : http://link.springer.comjournal/10393. |
en_ZA |
dc.subject |
Middle East respiratory syndrome coronavirus (MERS-CoV) |
en_ZA |
dc.subject |
Geographic information system (GIS) |
en_ZA |
dc.subject |
Agro-ecological zone (AEZ) |
en_ZA |
dc.subject |
Camel |
en_ZA |
dc.subject |
Kenya |
en_ZA |
dc.subject |
Hotspot |
en_ZA |
dc.subject |
Transmission |
en_ZA |
dc.subject |
Risk |
en_ZA |
dc.title |
Mapping potential amplification and transmission hotspots for MERS-CoV, Kenya |
en_ZA |
dc.type |
Postprint Article |
en_ZA |