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Abstract Despite the increasing burden of dengue, the regional emergence of the virus in Kenya has not been examined. This study investigates the genetic structure and regional spread of dengue virus-2 in Kenya. Viral RNA from acutely ill patients in Kenya was enriched and sequenced. Six new dengue-2 genomes were combined with 349 publicly available genomes and phylogenies used to infer gene flow between Kenya and other countries. Analyses indicate two dengue-2 Cosmopolitan genotype lineages circulating in Kenya, linked to recent outbreaks in coastal Kenya and Burkina Faso. Lineages circulating in Western, Southern, and Eastern Africa exhibiting similar evolutionary features are also reported. Phylogeography suggests importation of dengue-2 into Kenya from East and Southeast Asia and bidirectional geneflow. Additional lineages circulating in Africa are also imported from East and Southeast Asia. These findings underscore how intermittent importations from East and Southeast Asia drive dengue-2 circulation in Kenya and Africa more broadly.

Most vector control activities in urban areas are focused on household environments; however, information relating to infection risks in spaces other than households is poor, and the relative risk that these spaces represent has not yet been fully understood. We used data-driven simulations to investigate the importance of household and non-household environments for dengue entomological risk in two Kenyan cities where dengue circulation has been reported. Fieldwork was performed using four strategies that targeted different stages of mosquitoes: ovitraps, larval collections, Prokopack aspiration, and BG-sentinel traps. Data were analyzed separately between household and non-household environments to assess mosquito presence, the number of vectors collected, and the risk factors for vector presence. With these data, we simulated vector and human populations to estimate the parameter m and mosquito-to-human density in both household and non-household environments. Among the analyzed variables, the main difference was found in mosquito abundance, which was consistently higher in non-household environments in Kisumu but was similar in Ukunda. Risk factor analysis suggests that small, clean water-related containers serve as mosquito breeding places in households as opposed to the trash- and rainfall-related containers found in non-household structures. We found that the density of vectors (m) was higher in non-household than household environments in Kisumu and was also similar or slightly lower between both environments in Ukunda. These results suggest that because vectors are abundant, there is a potential risk of transmission in non-household environments; hence, vector control activities should take these spaces into account.