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Detection of dengue virus serotypes 1, 2 and 3 in selected regions of Kenya: 2011–2014

Identifieur interne : 000039 ( Main/Exploration ); précédent : 000038; suivant : 000040

Detection of dengue virus serotypes 1, 2 and 3 in selected regions of Kenya: 2011–2014

Auteurs : Limbaso Konongoi [Kenya] ; Victor Ofula [Kenya] ; Albert Nyunja [Kenya] ; Samuel Owaka [Kenya] ; Hellen Koka [Kenya] ; Albina Makio [Kenya] ; Edith Koskei [Kenya] ; Fredrick Eyase [Kenya] ; Daniel Langat [Kenya] ; Randal J. Schoepp [États-Unis] ; Cynthia Ann Rossi [États-Unis] ; Ian Njeru [Kenya] ; Rodney Coldren [Kenya] ; Rosemary Sang [Kenya]

Source :

RBID : PMC:5097412

Abstract

Background

Dengue fever, a mosquito-borne disease, is associated with illness of varying severity in countries in the tropics and sub tropics. Dengue cases continue to be detected more frequently and its geographic range continues to expand. We report the largest documented laboratory confirmed circulation of dengue virus in parts of Kenya since 1982.

Methods

From September 2011 to December 2014, 868 samples from febrile patients were received from hospitals in Nairobi, northern and coastal Kenya. The immunoglobulin M enzyme linked immunosorbent assay (IgM ELISA) was used to test for the presence of IgM antibodies against dengue, yellow fever, West Nile and Zika. Reverse transcription polymerase chain reaction (RT-PCR) utilizing flavivirus family, yellow fever, West Nile, consensus and sero type dengue primers were used to detect acute arbovirus infections and determine the infecting serotypes. Representative samples of PCR positive samples for each of the three dengue serotypes detected were sequenced to confirm circulation of the various dengue serotypes.

Results

Forty percent (345/868) of the samples tested positive for dengue by either IgM ELISA (14.6 %) or by RT-PCR (25.1 %). Three dengue serotypes 1–3 (DENV1-3) were detected by serotype specific RT-PCR and sequencing with their numbers varying from year to year and by region. The overall predominant serotype detected from 2011–2014 was DENV1 accounting for 44 % (96/218) of all the serotypes detected, followed by DENV2 accounting for 38.5 % (84/218) and then DENV3 which accounted for 17.4 % (38/218). Yellow fever, West Nile and Zika was not detected in any of the samples tested.

Conclusion

From 2011–2014 serotypes 1, 2 and 3 were detected in the Northern and Coastal parts of Kenya. This confirmed the occurrence of cases and active circulation of dengue in parts of Kenya. These results have documented three circulating serotypes and highlight the need for the establishment of active dengue surveillance to continuously detect cases, circulating serotypes, and determine dengue fever disease burden in the country and region.


Url:
DOI: 10.1186/s12985-016-0641-0
PubMed: 27814732
PubMed Central: 5097412


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<name sortKey="Koskei, Edith" sort="Koskei, Edith" uniqKey="Koskei E" first="Edith" last="Koskei">Edith Koskei</name>
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<name sortKey="Langat, Daniel" sort="Langat, Daniel" uniqKey="Langat D" first="Daniel" last="Langat">Daniel Langat</name>
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<name sortKey="Rossi, Cynthia Ann" sort="Rossi, Cynthia Ann" uniqKey="Rossi C" first="Cynthia Ann" last="Rossi">Cynthia Ann Rossi</name>
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<name sortKey="Sang, Rosemary" sort="Sang, Rosemary" uniqKey="Sang R" first="Rosemary" last="Sang">Rosemary Sang</name>
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<title level="j">Virology Journal</title>
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<title>Background</title>
<p>Dengue fever, a mosquito-borne disease, is associated with illness of varying severity in countries in the tropics and sub tropics. Dengue cases continue to be detected more frequently and its geographic range continues to expand. We report the largest documented laboratory confirmed circulation of dengue virus in parts of Kenya since 1982.</p>
</sec>
<sec>
<title>Methods</title>
<p>From September 2011 to December 2014, 868 samples from febrile patients were received from hospitals in Nairobi, northern and coastal Kenya. The immunoglobulin M enzyme linked immunosorbent assay (IgM ELISA) was used to test for the presence of IgM antibodies against dengue, yellow fever, West Nile and Zika. Reverse transcription polymerase chain reaction (RT-PCR) utilizing flavivirus family, yellow fever, West Nile, consensus and sero type dengue primers were used to detect acute arbovirus infections and determine the infecting serotypes. Representative samples of PCR positive samples for each of the three dengue serotypes detected were sequenced to confirm circulation of the various dengue serotypes.</p>
</sec>
<sec>
<title>Results</title>
<p>Forty percent (345/868) of the samples tested positive for dengue by either IgM ELISA (14.6 %) or by RT-PCR (25.1 %). Three dengue serotypes 1–3 (DENV1-3) were detected by serotype specific RT-PCR and sequencing with their numbers varying from year to year and by region. The overall predominant serotype detected from 2011–2014 was DENV1 accounting for 44 % (96/218) of all the serotypes detected, followed by DENV2 accounting for 38.5 % (84/218) and then DENV3 which accounted for 17.4 % (38/218). Yellow fever, West Nile and Zika was not detected in any of the samples tested.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>From 2011–2014 serotypes 1, 2 and 3 were detected in the Northern and Coastal parts of Kenya. This confirmed the occurrence of cases and active circulation of dengue in parts of Kenya. These results have documented three circulating serotypes and highlight the need for the establishment of active dengue surveillance to continuously detect cases, circulating serotypes, and determine dengue fever disease burden in the country and region.</p>
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</author>
<author>
<name sortKey="De Cock, Km" uniqKey="De Cock K">KM De Cock</name>
</author>
</analytic>
</biblStruct>
<biblStruct>
<analytic>
<author>
<name sortKey="Lanciotti, Rs" uniqKey="Lanciotti R">RS Lanciotti</name>
</author>
<author>
<name sortKey="Calisher, Ch" uniqKey="Calisher C">CH Calisher</name>
</author>
<author>
<name sortKey="Gubler, Dj" uniqKey="Gubler D">DJ Gubler</name>
</author>
<author>
<name sortKey="Chang, Gj" uniqKey="Chang G">GJ Chang</name>
</author>
<author>
<name sortKey="Vorndam, Av" uniqKey="Vorndam A">AV Vorndam</name>
</author>
</analytic>
</biblStruct>
</listBibl>
</div1>
</back>
</TEI>
<affiliations>
<list>
<country>
<li>Kenya</li>
<li>États-Unis</li>
</country>
<region>
<li>Maryland</li>
</region>
</list>
<tree>
<country name="Kenya">
<noRegion>
<name sortKey="Konongoi, Limbaso" sort="Konongoi, Limbaso" uniqKey="Konongoi L" first="Limbaso" last="Konongoi">Limbaso Konongoi</name>
</noRegion>
<name sortKey="Coldren, Rodney" sort="Coldren, Rodney" uniqKey="Coldren R" first="Rodney" last="Coldren">Rodney Coldren</name>
<name sortKey="Eyase, Fredrick" sort="Eyase, Fredrick" uniqKey="Eyase F" first="Fredrick" last="Eyase">Fredrick Eyase</name>
<name sortKey="Koka, Hellen" sort="Koka, Hellen" uniqKey="Koka H" first="Hellen" last="Koka">Hellen Koka</name>
<name sortKey="Konongoi, Limbaso" sort="Konongoi, Limbaso" uniqKey="Konongoi L" first="Limbaso" last="Konongoi">Limbaso Konongoi</name>
<name sortKey="Koskei, Edith" sort="Koskei, Edith" uniqKey="Koskei E" first="Edith" last="Koskei">Edith Koskei</name>
<name sortKey="Langat, Daniel" sort="Langat, Daniel" uniqKey="Langat D" first="Daniel" last="Langat">Daniel Langat</name>
<name sortKey="Makio, Albina" sort="Makio, Albina" uniqKey="Makio A" first="Albina" last="Makio">Albina Makio</name>
<name sortKey="Njeru, Ian" sort="Njeru, Ian" uniqKey="Njeru I" first="Ian" last="Njeru">Ian Njeru</name>
<name sortKey="Nyunja, Albert" sort="Nyunja, Albert" uniqKey="Nyunja A" first="Albert" last="Nyunja">Albert Nyunja</name>
<name sortKey="Ofula, Victor" sort="Ofula, Victor" uniqKey="Ofula V" first="Victor" last="Ofula">Victor Ofula</name>
<name sortKey="Owaka, Samuel" sort="Owaka, Samuel" uniqKey="Owaka S" first="Samuel" last="Owaka">Samuel Owaka</name>
<name sortKey="Sang, Rosemary" sort="Sang, Rosemary" uniqKey="Sang R" first="Rosemary" last="Sang">Rosemary Sang</name>
<name sortKey="Sang, Rosemary" sort="Sang, Rosemary" uniqKey="Sang R" first="Rosemary" last="Sang">Rosemary Sang</name>
</country>
<country name="États-Unis">
<region name="Maryland">
<name sortKey="Schoepp, Randal J" sort="Schoepp, Randal J" uniqKey="Schoepp R" first="Randal J." last="Schoepp">Randal J. Schoepp</name>
</region>
<name sortKey="Rossi, Cynthia Ann" sort="Rossi, Cynthia Ann" uniqKey="Rossi C" first="Cynthia Ann" last="Rossi">Cynthia Ann Rossi</name>
</country>
</tree>
</affiliations>
</record>

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