Force of infection of Middle East respiratory syndrome in dromedary camels in Kenya
Identifieur interne : 000565 ( Main/Exploration ); précédent : 000564; suivant : 000566Force of infection of Middle East respiratory syndrome in dromedary camels in Kenya
Auteurs : E. G. Gardner [Canada] ; S. Kiambi [Kenya] ; R. Sitawa [Kenya] ; D. Kelton [Canada] ; J. Kimutai [Kenya] ; Z. Poljak [Canada] ; Z. Tadesse [Kenya] ; S. Von Dobschuetz [Italie] ; L. Wiersma [Italie] ; A. L. Greer [Canada]Source :
- Epidemiology and Infection [ 0950-2688 ] ; 2019.
Descripteurs français
- KwdFr :
- MESH :
- isolement et purification : Coronavirus du syndrome respiratoire du Moyen-Orient.
- médecine vétérinaire : Infections à coronavirus.
- épidémiologie : Infections asymptomatiques, Infections à coronavirus, Kenya.
- Animaux, Chameaux, Prévalence, Études transversales.
- Wicri :
- geographic : Kenya.
English descriptors
- KwdEn :
- MESH :
- geographic , epidemiology : Kenya.
- epidemiology : Asymptomatic Infections, Coronavirus Infections.
- isolation & purification : Middle East Respiratory Syndrome Coronavirus.
- veterinary : Coronavirus Infections.
- Animals, Camelus, Cross-Sectional Studies, Prevalence.
Abstract
Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic disease transmitted from dromedary camels to people, which can result in outbreaks with human-to-human transmission. Because it is a subclinical infection in camels, epidemiological measures other than prevalence are challenging to assess. This study estimated the force of infection (FOI) of MERS-CoV in camel populations from age-stratified serological data. A cross-sectional study of MERS-CoV was conducted in Kenya from July 2016 to July 2017. Seroprevalence was stratified into four age groups: <1, 1–2, 2–3 and >3 years old. Age-independent and age-dependent linear and quadratic generalised linear models were used to estimate FOI in pastoral and ranching camel herds. Models were compared based on computed AIC values. Among pastoral herds, the age-dependent quadratic FOI was the best fit model, while the age-independent FOI was the best fit for the ranching herd data. FOI provides an indirect estimate of infection risk, which is especially valuable where direct estimates of incidence and other measures of infection are challenging to obtain. The FOIs estimated in this study provide important insight about MERS-CoV dynamics in the reservoir species, and contribute to our understanding of the zoonotic risks of this important public health threat.
Url:
DOI: 10.1017/S0950268819001663
PubMed: 31547888
PubMed Central: 6805735
Affiliations:
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G." last="Gardner">E. G. Gardner</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>University of Guelph</institution>,<addr-line>Guelph, Ontario</addr-line>,<country>Canada</country></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Kiambi, S" sort="Kiambi, S" uniqKey="Kiambi S" first="S." last="Kiambi">S. Kiambi</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Food and Agriculture Organization of the United Nations</institution>,<addr-line>Nairobi</addr-line>,<country>Kenya</country></nlm:aff><country xml:lang="fr">Kenya</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Sitawa, R" sort="Sitawa, R" uniqKey="Sitawa R" first="R." last="Sitawa">R. Sitawa</name><affiliation wicri:level="1"><nlm:aff id="aff3"><institution>Directorate of Veterinary Services</institution>,<addr-line>Nairobi</addr-line>,<country>Kenya</country></nlm:aff><country xml:lang="fr">Kenya</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Kelton, D" sort="Kelton, D" uniqKey="Kelton D" first="D." last="Kelton">D. Kelton</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>University of Guelph</institution>,<addr-line>Guelph, Ontario</addr-line>,<country>Canada</country></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Kimutai, J" sort="Kimutai, J" uniqKey="Kimutai J" first="J." last="Kimutai">J. Kimutai</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Food and Agriculture Organization of the United Nations</institution>,<addr-line>Nairobi</addr-line>,<country>Kenya</country></nlm:aff><country xml:lang="fr">Kenya</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Poljak, Z" sort="Poljak, Z" uniqKey="Poljak Z" first="Z." last="Poljak">Z. Poljak</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>University of Guelph</institution>,<addr-line>Guelph, Ontario</addr-line>,<country>Canada</country></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Tadesse, Z" sort="Tadesse, Z" uniqKey="Tadesse Z" first="Z." last="Tadesse">Z. Tadesse</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Food and Agriculture Organization of the United Nations</institution>,<addr-line>Nairobi</addr-line>,<country>Kenya</country></nlm:aff><country xml:lang="fr">Kenya</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Von Dobschuetz, S" sort="Von Dobschuetz, S" uniqKey="Von Dobschuetz S" first="S." last="Von Dobschuetz">S. Von Dobschuetz</name><affiliation wicri:level="1"><nlm:aff id="aff4"><institution>Food and Agriculture Organization of the United Nations</institution>,<addr-line>Nairobi</addr-line>,<country>Italy</country></nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Wiersma, L" sort="Wiersma, L" uniqKey="Wiersma L" first="L." last="Wiersma">L. Wiersma</name><affiliation wicri:level="1"><nlm:aff id="aff4"><institution>Food and Agriculture Organization of the United Nations</institution>,<addr-line>Nairobi</addr-line>,<country>Italy</country></nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Greer, A L" sort="Greer, A L" uniqKey="Greer A" first="A. L." last="Greer">A. L. Greer</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>University of Guelph</institution>,<addr-line>Guelph, Ontario</addr-line>,<country>Canada</country></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author></analytic><series><title level="j">Epidemiology and Infection</title><idno type="ISSN">0950-2688</idno><idno type="eISSN">1469-4409</idno><imprint><date when="2019">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Asymptomatic Infections (epidemiology)</term><term>Camelus</term><term>Coronavirus Infections (epidemiology)</term><term>Coronavirus Infections (veterinary)</term><term>Cross-Sectional Studies</term><term>Kenya (epidemiology)</term><term>Middle East Respiratory Syndrome Coronavirus (isolation & purification)</term><term>Prevalence</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Animaux</term><term>Chameaux</term><term>Coronavirus du syndrome respiratoire du Moyen-Orient (isolement et purification)</term><term>Infections asymptomatiques (épidémiologie)</term><term>Infections à coronavirus (médecine vétérinaire)</term><term>Infections à coronavirus (épidémiologie)</term><term>Kenya (épidémiologie)</term><term>Prévalence</term><term>Études transversales</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Kenya</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Asymptomatic Infections</term><term>Coronavirus Infections</term></keywords><keywords scheme="MESH" qualifier="isolation & purification" xml:lang="en"><term>Middle East Respiratory Syndrome Coronavirus</term></keywords><keywords scheme="MESH" qualifier="isolement et purification" xml:lang="fr"><term>Coronavirus du syndrome respiratoire du Moyen-Orient</term></keywords><keywords scheme="MESH" qualifier="médecine vétérinaire" xml:lang="fr"><term>Infections à coronavirus</term></keywords><keywords scheme="MESH" qualifier="veterinary" xml:lang="en"><term>Coronavirus Infections</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Infections asymptomatiques</term><term>Infections à coronavirus</term><term>Kenya</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Camelus</term><term>Cross-Sectional Studies</term><term>Prevalence</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Animaux</term><term>Chameaux</term><term>Prévalence</term><term>Études transversales</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Kenya</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic disease transmitted from dromedary camels to people, which can result in outbreaks with human-to-human transmission. Because it is a subclinical infection in camels, epidemiological measures other than prevalence are challenging to assess. This study estimated the force of infection (FOI) of MERS-CoV in camel populations from age-stratified serological data. A cross-sectional study of MERS-CoV was conducted in Kenya from July 2016 to July 2017. Seroprevalence was stratified into four age groups: <1, 1–2, 2–3 and >3 years old. Age-independent and age-dependent linear and quadratic generalised linear models were used to estimate FOI in pastoral and ranching camel herds. Models were compared based on computed AIC values. Among pastoral herds, the age-dependent quadratic FOI was the best fit model, while the age-independent FOI was the best fit for the ranching herd data. FOI provides an indirect estimate of infection risk, which is especially valuable where direct estimates of incidence and other measures of infection are challenging to obtain. The FOIs estimated in this study provide important insight about MERS-CoV dynamics in the reservoir species, and contribute to our understanding of the zoonotic risks of this important public health threat.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Nowotny, N" uniqKey="Nowotny N">N Nowotny</name></author><author><name sortKey="Kolodziejek, J" uniqKey="Kolodziejek J">J Kolodziejek</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kiambi, S" uniqKey="Kiambi S">S Kiambi</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wernery, U" uniqKey="Wernery U">U Wernery</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Van Doremalen, N" uniqKey="Van Doremalen N">N van Doremalen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Yusof, Mf" uniqKey="Yusof M">MF Yusof</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Adney, Dr" uniqKey="Adney D">DR Adney</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Reusken, Cb" uniqKey="Reusken C">CB Reusken</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Meyer, B" uniqKey="Meyer B">B Meyer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hemida, Mg" uniqKey="Hemida M">MG Hemida</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ali, Ma" uniqKey="Ali M">MA Ali</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Vynnycky, E" uniqKey="Vynnycky E">E Vynnycky</name></author><author><name sortKey="White, Rg" uniqKey="White R">RG White</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hens, N" uniqKey="Hens N">N Hens</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Milwid, R" uniqKey="Milwid R">R Milwid</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bollaerts, K" uniqKey="Bollaerts K">K Bollaerts</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cucunuba, Zm" uniqKey="Cucunuba Z">ZM Cucunubá</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Egger, Jr" uniqKey="Egger J">JR Egger</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Imai, N" uniqKey="Imai N">N Imai</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Abrams, S" uniqKey="Abrams S">S Abrams</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ximenes, Rada" uniqKey="Ximenes R">RADA Ximenes</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gikonyo, S" uniqKey="Gikonyo S">S Gikonyo</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Muench, H" uniqKey="Muench H">H Muench</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hemida, Mg" uniqKey="Hemida M">MG Hemida</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Miguel, E" uniqKey="Miguel E">E Miguel</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kuria, Sg" uniqKey="Kuria S">SG Kuria</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Schwartz, Hj" uniqKey="Schwartz H">HJ Schwartz</name></author><author><name sortKey="Dolan, R" uniqKey="Dolan R">R Dolan</name></author><author><name sortKey="Wilson, Aj" uniqKey="Wilson A">AJ Wilson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Deem, Sl" uniqKey="Deem S">SL Deem</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Corman, Vm" uniqKey="Corman V">VM Corman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Munyua, P" uniqKey="Munyua P">P Munyua</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hemida, Mg" uniqKey="Hemida M">MG Hemida</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Farag, Eaba" uniqKey="Farag E">EABA Farag</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>Canada</li><li>Italie</li><li>Kenya</li></country></list><tree><country name="Canada"><noRegion><name sortKey="Gardner, E G" sort="Gardner, E G" uniqKey="Gardner E" first="E. G." last="Gardner">E. G. Gardner</name></noRegion><name sortKey="Greer, A L" sort="Greer, A L" uniqKey="Greer A" first="A. L." last="Greer">A. L. Greer</name><name sortKey="Kelton, D" sort="Kelton, D" uniqKey="Kelton D" first="D." last="Kelton">D. Kelton</name><name sortKey="Poljak, Z" sort="Poljak, Z" uniqKey="Poljak Z" first="Z." last="Poljak">Z. Poljak</name></country><country name="Kenya"><noRegion><name sortKey="Kiambi, S" sort="Kiambi, S" uniqKey="Kiambi S" first="S." last="Kiambi">S. Kiambi</name></noRegion><name sortKey="Kimutai, J" sort="Kimutai, J" uniqKey="Kimutai J" first="J." last="Kimutai">J. Kimutai</name><name sortKey="Sitawa, R" sort="Sitawa, R" uniqKey="Sitawa R" first="R." last="Sitawa">R. Sitawa</name><name sortKey="Tadesse, Z" sort="Tadesse, Z" uniqKey="Tadesse Z" first="Z." last="Tadesse">Z. Tadesse</name></country><country name="Italie"><noRegion><name sortKey="Von Dobschuetz, S" sort="Von Dobschuetz, S" uniqKey="Von Dobschuetz S" first="S." last="Von Dobschuetz">S. Von Dobschuetz</name></noRegion><name sortKey="Wiersma, L" sort="Wiersma, L" uniqKey="Wiersma L" first="L." last="Wiersma">L. Wiersma</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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