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. 2019 Aug 23;13(8):e0007686.
doi: 10.1371/journal.pntd.0007686. eCollection 2019 Aug.

Entomological assessment of dengue virus transmission risk in three urban areas of Kenya

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Entomological assessment of dengue virus transmission risk in three urban areas of Kenya

Sheila B Agha et al. PLoS Negl Trop Dis. .

Abstract

Urbanization is one of the major drivers of dengue epidemics globally. In Kenya, an intriguing pattern of urban dengue virus epidemics has been documented in which recurrent epidemics are reported from the coastal city of Mombasa, whereas no outbreaks occur in the two major inland cities of Kisumu and Nairobi. In an attempt to understand the entomological risk factors underlying the observed urban dengue epidemic pattern in Kenya, we evaluated vector density, human feeding patterns, vector genetics, and prevailing environmental temperature to establish how these may interact with one another to shape the disease transmission pattern. We determined that (i) Nairobi and Kisumu had lower vector density and human blood indices, respectively, than Mombasa, (ii) vector competence for dengue-2 virus was comparable among Ae. aegypti populations from the three cities, with no discernible association between susceptibility and vector cytochrome c oxidase subunit 1 gene variation, and (iii) vector competence was temperature-dependent. Our study suggests that lower temperature and Ae. aegypti vector density in Nairobi may be responsible for the absence of dengue outbreaks in the capital city, whereas differences in feeding behavior, but not vector competence, temperature, or vector density, contribute in part to the observed recurrent dengue epidemics in coastal Mombasa compared to Kisumu.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Map showing the study sites within the urban areas of Kisumu, Mombasa, and Nairobi in Kenya [10].
Fig 2
Fig 2. Host blood meal sources for Aedes aegypti mosquitoes collected from Mombasa, Kisumu and Nairobi from October 2014 to June 2016.
Fig 3
Fig 3. Maximum likelihood tree inferred using the (GTR+G) model of sequence evolution for COI barcode region (860 bp) of dengue virus susceptible (SS) and non-susceptible (NS) Aedes aegypti mosquitoes from Mombasa (MSA), Kisumu (KSM), and Nairobi (NRB), Kenya.
The number of individuals sharing a haplotype is indicated in parentheses. Bayesian posterior probabilities ≥0.90 and bootstrap support values from 5,000 replications ≥65 are indicated above and below the three major lineages, respectively, with terminal nodes reflecting bootstrap support values alone. Aedes albopictus was included for outgroup purposes.

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