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. 2026 Jul 3;16:30608. doi: 10.1038/s41598-026-59068-8

Genomic investigation reveals local persistence and regional circulation of dengue virus associated with recent outbreaks in Kenya

Solomon K Langat 1,✉,#, Sheila Kageha 1,#, Victor Jeza 2, Genay Pilarowski 3, Albert Nyunja 1, Paul E Oluniyi 3, Juliana Gil 3, Nelly Ogada 2, Lewis Gande 2, Jane Thiiru 1, Seth Okeyo 1, Pascah Bulia 1, Jael Amugongo 2, Victor Ofula 1, Francis Mutuku 2, Cristina M Tato 3, Samoel Khamadi 1, Joel Lutomiah 1, Konongoi Limbaso 1
PMCID: PMC13630545  PMID: 42399298

Abstract

Dengue is an arbovirus disease caused by dengue virus. The virus has recently caused a global surge in cases, with Africa reporting over 250 million and 900 deaths since 2023. This study was conducted during the 2023 dengue outbreak in Mombasa, with the aim of understanding outbreak cases in the context of earlier cases and recent global epidemics. During the 2023 outbreak, 56 of 406 samples tested positive for DENV: including DENV-1, DENV-2, and DENV-3. The study generated 38 whole genome sequences, 24 from 2023 to 14 from cases identified between 2020 and 2025. Phylogenetic analysis showed DENV-2 exhibited patterns suggesting long-term local circulation, while DENV-1 and DENV-3 were more widespread regionally, and are linked to recent outbreaks in Eastern and Western Africa. These findings highlight the need for integrated strategies to curb dengue in Kenya, such as measures to disrupt local transmission as well as importation of new strains.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1038/s41598-026-59068-8.

Subject terms: Computational biology and bioinformatics, Diseases, Microbiology

Introduction

Dengue is an arbovirus disease caused by either one of the four serotypes of dengue virus; dengue virus 1–4 (DENV1-4)1,2. Globally, dengue cases have increased substantially over the recent past, with more than 13 million cases and 8700 deaths reported in 20243. This was a marked increase from 2023, which saw a then-record 4.6 million cases being reported globally4. Africa has also documented an unprecedented increase in dengue cases since 2023. According to the World Health Organization (WHO), several African countries reported over a quarter million cumulative cases of dengue between 2023 and 2024 and approximately 900 deaths5. This multi-country outbreak of dengue affected 13 countries in Western Africa and two countries in Eastern Africa including Ethiopia and Kenya5. However, the lack of sustained active surveillance of this disease in several African countries, especially those that border Ethiopia and Kenya could suggest an underestimation of the burden of dengue.

In Kenya, the first dengue associated outbreak was documented in the coastal town of Malindi in 198217. This was followed by a long period of relative quiescence. However, in the period between 2010 and 2014, there was a re-emergence of dengue in the country with multiple cases being reported in several counties6,7. Following this outbreak, there have been almost yearly reports of dengue outbreaks, even though each of the subsequent outbreaks was mostly linked to one serotype8–10. Genomic analysis of viruses associated with the dengue outbreak reported in 2010 and subsequent years have found evidence that the virus was possibly introduced into Kenya from India in South Asia prior to 201016. The outbreaks between 2010 and 2014 were caused by three serotypes DENV 1–3, and it occurred in both the coastal region and the north eastern region of Kenya. However, subsequent outbreaks in 2017 and 2019 were associated mostly with dengue 2 and dengue 3 respectively8,9. There was limited surveillance between 2020 and 2022, possibly due to the global SARS-CoV-2 pandemic where most of the resources were re-directed to fighting the pandemic. However, there were dengue cases reported in the country towards the end of 2022 and in 20235. This outbreaks also coincided with expanding reach of dengue which has caused increased burden globally.

The recurring outbreaks of dengue in Kenya since its re-emergence in 2010 raises questions about whether the cases are linked to the ongoing global dengue outbreaks. Specifically, we sought to understand whether outbreak strains are periodically introduced into the country through ports of entry and subsequently drive repeated outbreaks such as the one observed in 2023, or whether strains established during previous outbreaks have continued to circulate locally, seeding subsequent outbreaks without repeated importation. Understanding which of these mechanisms is dominant has direct implications for outbreak response and control strategies. To address this, we conducted a genomic investigation of the 2023 dengue outbreak in Mombasa, contextualizing locally circulating strains against sequences from earlier Kenyan outbreaks and the global dengue emergence reported across multiple countries in recent years.

Methodology

Ethics statement

This study was conducted using anonymized human serum samples obtained through arbovirus surveillance activities and a dengue outbreak investigation study carried out in 2023. Ethical approval for the use of these samples was obtained from the relevant institutional review boards at Kenya Medical Research Institute (KEMRI) and Technical University of Mombasa (TUM). Samples collected as part of ongoing studies at TUM received ethical clearance from the TUM Ethical Review Committee (EXT/005/2022). In addition, samples collected during the active dengue outbreak investigation in 2023 received ethical approval from KEMRI’s Scientific Ethics and Review Unit (SERU) (SSC #4499). Written informed consent was obtained from all adult participants (≥ 18 years) after explanation of the study objectives and procedures by a trained staff. For adolescents aged 13–17 years, written assent was obtained prior to enrolment, while participation of children younger than 13 years required written consent from a parent or legal guardian. Participant information sheets, consent forms, and assent forms were translated into English and Swahili to ensure that study information was communicated in languages commonly understood by the study population.

The approval to use surveillance samples at KEMRI was granted by KEMRI-SERU (SSC #3035). For this set of samples, individual consent was not required, as the study utilized anonymized and coded samples collected during a public health outbreak response led by the Kenyan Ministry of Health through the Division of Disease Surveillance and Response (DDSR). Residual diagnostic samples are available for use in further characterization of the causative agent through the outbreak protocol SSC #3035. All the methods in the study were performed in accordance with the relevant guidelines and regulations.

Sample collection and detection of DENV

The primary set of samples for this study was collected during the 2023 dengue outbreak in Mombasa, Kenya (4.0435° S, 39.6682° E) (Supplementary 1 Figure S1). A total of 406 blood samples were collected between March and July 2023 from patients presenting at local health facilities with acute febrile illness clinically suspected to be due to arboviral infection. Suspected cases were evaluated and classified according to the 2009 World Health Organization (WHO) Dengue Guidelines. Patients were eligible for inclusion if they presented with an acute fever (≥ 38 °C) of ≤ 5 days duration, accompanied by at least two clinical manifestations, including headache, muscle/joint pains, nausea/vomiting, myalgia, arthralgia, rash, or hemorrhagic manifestations. These criteria were applied by attending clinicians during routine case evaluation; no laboratory-based screening was used to define enrolment. A confirmed dengue case was defined as detection of dengue virus RNA by qRT-PCR in serum collected during the acute phase of illness.

To contextualize the 2023 outbreak within the broader context of dengue virus (DENV) activity in the region, we included additional DENV-positive samples previously collected through ongoing surveillance efforts. These included samples from the KEMRI and TUM. The KEMRI samples were collected as part of routine arbovirus surveillance conducted by the Kenyan Ministry of Health through the DDSR. Through this system, local health officials identify suspected arboviral cases based on symptoms consistent with arbovirus infection, such as acute febrile illness, headache, muscle or joint pains. Blood samples are then collected and referred to KEMRI for diagnostic testing. Samples from TUM were part of ongoing surveillance studies tracking febrile illness cases in Mombasa and Kwale Counties along the Kenyan coast. The additional set of samples included 11 samples collected between 2020 and 2022, and 4 more obtained in 2024 and 2025 (Table 1). Approximately 5 mL of whole blood was collected from enrolled patients of all ages presenting to local health facilities with symptoms consistent with arboviral infection. Serum was separated by centrifugation, aliquoted into cryogenic tubes, and immediately stored in liquid nitrogen before transportation to the testing laboratories at KEMRI and TUM for further analysis.

Table 1.

Demographic and clinical characteristics of the DENV positive cases (n = 56) that were analyzed in the study.

Age range(y)/Sex Counts %
0–5 F 2 3.64
M 4 7.27
6–12 F 1 1.82
M 1 1.82
13–19 F 4 7.27
M 5 9.09
20–44 F 20 36.36
M 16 29.09
45+ F 1 1.82
M 1 1.82
Clinical symptoms a
Headache 47 83.9
Joint/Muscle pain 46 82.1
Fever(> 38 °C) 21 37.5
Abdominal pain 18 32.1
Vomiting 15 26.8
Epigastric pain 11 19.6
Diarrhoea 6 10.7
Haemorrhage 4 7.1
Low urine output 1 1.8
Serotypes
DENV-Unknown 35 57.1
DENV-1 10 17.9
DENV-2 11 19.6
DENV-3 3 5.4
Number of samples sequenced b
2020 2 5.3
2021 2 5.3
2022 7 18.4
2023 24 63.2
2024 2 5.3
2025 1 2.6
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aThis includes information reported by participants during the visit to the clinic.

bIncludes samples from the 2023 outbreak and contextual samples selected from other years.

To detect DENV RNA and assess cycle threshold (Ct) values, viral RNA was extracted from 140ul of the serum samples using QIAmp Viral RNA Mini Kit (Qiagen, Germany) following the manufacturer’s recommended protocol. The extracted RNA was then used to screen for arboviruses using primers targeting the Flavivirus genus11. Flavivirus-positive samples were then tested with dengue specific primers, including serotype-specific primers for DENV-1 through DENV-412.

Library preparation and sequencing

The extracted RNA was first subjected to DNase digestion using the Turbo DNase kit (Ambion, US) following the manufacturer’s recommendations. Cleaned RNA was used as input for library preparation using NEBNext Ultra II RNA Library Prep Kit for Illumina (NEB, UK). We used the manufacturer’s recommended protocol which was modified to incorporate human rRNA depletion using Qiagen rRNA FastSelect kit (Qiagen, US) and addition of External RNA Controls Consortium (ERCC) controls (Thermofisher, US). The prepared libraries were sequenced on an Illumina iSeq100 and a NextSeq550 system. Raw fastq sequence reads were analyzed in CZ ID pipeline v8.3.15 (https://czid.org/) to remove host and low quality reads as well as assembly and consensus genome generation. Water controls included during library preparation were used to create a mass-normalized background model that was subsequently used to filter background signal. The CZ ID consensus genome pipeline v3.5.0 was used to create contiguous genomes based on the respective dengue serotype reference genomes obtained from the NCBI database (DENV-1: MN923102.1, DENV-2: MN577561.1, DENV-3: JN662391.1).

Phylogenetic analysis

The newly generated genome sequences were first genotyped using the DENV typing tool available in Genome Detective (https://www.genomedetective.com/app/typingtool/dengue/). Phylogenetic analysis was conducted using the Augur bioinformatics toolkit13. To generate the dataset, we downloaded all available complete and near-complete DENV genomes (9600–11700 kb) from GenBank (with collection dates up to December 31, 2021) and from GISAID (with collection dates between January 1, 2022, and March 31, 2025)36,37. Genomic sequences collected since 2022 were obtained exclusively from GISAID database, due to the predominance of recent entries, particularly those from Africa, being available through this repository. Only genomes with accompanying metadata information including the year of collection and country of origin were included in the analysis. The downloaded set of sequences were combined with the genomes obtained from the current study. Subsequently, the sequences were grouped by country and year of collection and a subset of a maximum of 12 genomes were randomly selected from each group so as to minimize geographical sampling bias. This down sampling resulted in a total of 2332, 2570 and 658 high quality genomes of DENV-1, DENV-2 and DENV-3, respectively. Multiple sequence alignments and phylogenetic inference were performed with the Augur toolkit using MAFFT14 and IQ-TREE, with the Generalized Time Reversible (GTR) model15. The resulting raw phylogenies were further processed using TreeTime22 to obtain a time-calibrated phylogeny as well as to infer the ancestral traits of the tree nodes, including amino acid changes and geographical location.

Results

The circulating DENV cases

The 2023 Mombasa outbreak investigation identified 56 dengue virus–positive cases by qRT-PCR among 406 suspected samples tested. This corresponds to a positivity rate of 13.8% among suspected acute febrile illness cases. Three dengue virus serotypes were detected: DENV-1 (10 cases, 17.9%), DENV-2 (11 cases, 19.6%), and DENV-3 (3 cases, 5.4%) (Table 1). The majority of RT-PCR–confirmed cases (> 65%) occurred among adults aged 20–44 years (Table 1). However, this distribution reflects only laboratory-confirmed cases within the enrolled study population. Clinical presentation among confirmed cases was predominantly characterized by fever, headache, myalgia, and arthralgia. Hemorrhagic manifestations were observed in four RT-PCR–confirmed cases (7.1%), including two DENV-1 infections (Table 1).

mNGS sequencing and phylogenetic characterization

We sequenced 24 samples associated with DENV cases from the 2023 outbreak in Mombasa (Appendix Table 1). To provide broader context for the outbreak, we also included 14 previously confirmed DENV-positive samples collected between 2020 and 2025. In total, 38 DENV samples with Ct (< 30) values were sequenced using a metagenomics next-generation sequencing (mNGS) approach (Appendix Table 1). The dataset comprised samples from multiple locations within the country including Mombasa, Kwale, Lamu, Garissa and Wajir. Among the sequenced genomes, we identified 21 DENV-1 genomes, 14 DENV-2 and 3 DENV-3. Genotyping analysis classified all sequences into single genotypes for each serotype: Genotype III for DENV-1, genotype II for DENV-2 and genotype III for DENV-3. Phylogenetic analysis showed that the circulating DENV-1 strains formed a single cluster within lineage A.2 in genotype III (Fig. 1A). This strain has been detected in Kenya since 2020, and it shares a common ancestor with strains from other countries in Africa (Fig. 1A). Similar strains were previously identified in several Eastern African countries prior to 2020 and in Western Africa since 2017. The Western African clade has a distinct clustering pattern that differentiates it from the Eastern African clade. However, they both share a common ancestor which is estimated to have existed in the continent around September, 2014 (Fig. 1A). Phylogenetic analysis of DENV-2 revealed that the circulating strains belong to lineage A.2 of genotype II. The current strain formed a ladder-like cluster with the earlier strains that were linked to dengue outbreaks that occurred between 2010 and 2017 in different parts of Kenya (Fig. 2A). In addition, our analysis showed that the 2023 outbreak strain evolved from these earlier strains. Interestingly, the current circulating strain shares a common ancestor with a strain detected in China and Thailand in 2023 (Fig. 2A). Temporal phylogenetic analysis estimated the divergence of this lineage to aroundOctober 2023 (Confidence interval: 2020-05-16 to 2021-04-27), coinciding with the detection of this lineage in Kenya (Fig. 2A). For DENV-3, three sequences were recovered from the 2023 outbreak and our analysis showed that they form a similar cluster within lineage B in genotype III (Fig. 3A). Although distinct, the 2023 outbreak strain clustered closely with strains that were responsible for the 2023 dengue outbreak in Ethiopia, a neighboring country to the north. In addition, a related isolate detected in Italy in August 2023 was reported to have been imported from Eastern Africa, consistent with the regional clustering pattern observed in our analysis19.

Fig. 1.

Fig. 1

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A) Time-resolved maximum likelihood phylogeny of DENV-1 including strains obtained from the study and reference sequences sampled worldwide. The tree branches have been colored according to the geographic origin of the sequences. The inset on the right represents an expansion of the branch containing strains from the study as well as closely related strains from other countries. B) Genome map showing amino acid mutations common among the DENV-1 strains generated in the study. The position in the phylogeny where the mutations occur are indicated in the inset in A, with the color of the dots in the tree branches corresponding to the color of the lollipop depicting the mutation.

Fig. 2.

Fig. 2

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A) Time-resolved maximum likelihood phylogeny of DENV-2 which includes strains obtained from the study and reference sequences sampled worldwide. The tree branches are colored according to the geographic origin of the sequences and the inset on the right represents an expansion of the branch containing strains from the study as well as closely related strains from other countries. B) Genome map showing amino acid mutations common among the DENV-1 strains generated in the study. The position in the phylogeny where the mutations occur are indicated in the inset in A, with the color of the dots in the tree branches corresponding to the color of the lollipop depicting the mutation.

Fig. 3.

Fig. 3

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A) Time-resolved maximum likelihood phylogeny of DENV-3 including strains obtained from the study and reference sequences sampled worldwide. The tree branches are colored according to the geographic origin of the sequences and the inset on the right represents an expansion of the branch containing strains from the study as well as closely related strains from other countries. B) Genome map showing amino acid mutations common among the DENV-1 strains generated in the study. The position in the phylogeny where the mutations occur are indicated in the inset in A, with the color of the dots in the tree branches corresponding to the color of the lollipop depicting the mutation.

Mutation analysis

Analysis of the mutational pattern associated with the Kenyan outbreak revealed that DENV-1 had three signature mutations on NS1: V89I, NS4A: L19Q and NS5: S810T (Fig. 1B). On the other hand, DENV-2 had 8 unique mutations, 3 in the NS5 gene (NS5: E169D, NS5: I267V, NS5: A648V), two in the NS2A (I116M, NS1: I120M) and one mutation each in the NS3 (NS3: M333I), NS1(NS1: T146A), and NS4B (NS4B: I18T) genes (Fig. 2B). DENV-3 strains had two mutations in the E gene (E: V158A, E: Q341E) and one in the NS4B gene (NS4B: I159T) (Fig. 3B).

Discussion

In this study, we conducted a genomic investigation of the 2023 dengue outbreak that occurred in Mombasa County, with the aim of exploring the relationship between locally circulating DENV strains and the strains responsible for the global dengue emergence. Our investigation confirmed the co-circulation of three dengue virus serotypes (DENV-1, DENV-2, and DENV-3) during the 2023 outbreak. The majority of RT-PCR–confirmed cases occurred among adults aged 20–44 years. This age distribution reflects the pattern observed among laboratory-confirmed cases within the study population. However, given that no direct exposure or behavioural data were collected in this study, differences in risk across age groups cannot be conclusively explained.Our findings also show that most of the cases were associated with headaches, joint and muscle pains as well as high fever. Notably, hemorrhagic manifestations were observed in four cases, likely due to secondary heterotypic DENV infection which is a phenomenon commonly observed in regions with multiple co-circulating serotypes21. These findings underscore the risk of severe dengue, including Dengue Hemorrhagic Fever (DHF) and Dengue Shock Syndrome (DSS), which are associated with elevated case fatality rates20,21.

Phylogenetic analysis of DENV-1 revealed that the circulating strains in 2023 belonged to A.2 lineage. The same strain was previously linked to dengue outbreak in Mandera and Wajir in 2022 as well as Lamu and Mombasa in 2020. This suggests multi-year circulation of this strain across the coastal and north-eastern regions since at least 2020, when the earliest case existed in Kenya. This Kenyan strain shares a common ancestor with strains circulating in other Eastern African countries including Tanzania as well as Mayotte and Reunion Islands27. Similarly, this strain also shares a common ancestor with Western African strains circulating in Nigeria, Benin, Burkina-Faso and Togo28,29. This strain appears to be unique to the African continent and has been detected locally since 2017, having diverged from the South Asian strains detected mostly in India at around 2006 (Fig. 1A). The findings in this study, therefore, suggest sustained local and regional circulation of this strain, with confirmed outbreaks in several African countries including Kenya27–29.

The DENV-2 phylogenetic analysis revealed the circulation of one lineage A.2 of genotype II. This particular strain was first introduced into coastal Kenya around 200816 and our analysis suggests it has been circulating within the country ever since. This strain had not been detected outside Kenya until April 2023, when a closely related lineage was identified during an outbreak in Guangzhou, China23. The outbreak in China was linked to several imported cases that subsequently led to an epidemic24,25. Phylogenetic clustering indicates that the China 2023 and 2023 Kenyan outbreak strains share a common ancestor, consistent with a possible connectivity between the two outbreak lineages (Fig. 2A). Further, the clustering pattern suggests these 2023 strains evolved from earlier Kenyan outbreak strains, 2010–2017, but the long branch leading to the 2023 strains suggests potential circulation in unsampled outbreaks between 2017 and 2023. Analysis of the mutational pattern of the 2023 outbreak strain found the majority of the changes in NS5 gene. The NS5 gene in DENV plays a crucial role in viral replication and inhibition of the host interferon (IFN) signaling25. Therefore, given its potential role in virus-host interaction, it would be crucial to determine the effect of these mutations on the long-term local circulation of this lineage.

The phylogenetic analysis of DENV-3 revealed that the circulating 2023 outbreak strain belonged to lineage B.2 of Genotype III, which was also associated with outbreaks in 2011 and in 201930,31. However, the strains detected during each of the outbreaks were genetically distinct. The 2019 outbreak strain circulated mostly in South Asian countries, specifically Pakistan, around 2006 to 200935. However, phylogenetic analysis suggests that this strain may have circulated in unsampled outbreaks prior to causing the outbreak in Kenya in 201930. On the other hand, the 2011 strain shares a common ancestor with strains responsible for the Kenyan 2023 outbreak. Further, the Kenyan strain is in a cluster that is dominated by strains detected across the African continent; specifically in countries that include Ethiopia, Senegal, Burkina-Faso, Benin and Gabon. The clustering pattern of this African clade is characterized by long branches, suggesting unsampled diversity of this lineage over a long period. Nonetheless, our analysis points to ongoing regional circulation in sub-Saharan Africa, which is supported by recently confirmed outbreak cases in Senegal, Ethiopia, Benin and Burkina-Faso18,31–34 as well as the contemporaneous detection of a related isolate in Italy which was linked to Eastern Africa19. However, as these inferences are based on clustering patterns rather than formal phylogeographic modeling, the directionality of any such movement cannot be established with certainty, and additional genomic surveillance from the region would be required to resolve the transmission history more precisely.

Analysis of mutational patterns across the three circulating serotypes revealed distinct evolutionary signatures, with the most extensive amino acid variation observed in DENV-2, potentially due to the prolonged local circulation of this serotype over approximately 15 years. The Kenyan DENV-2 outbreak strain carries eight unique amino acid substitutions, including three in NS5, two in NS2A and one each in the NS1, NS3 and NS4B proteins (Fig. 2B). The clustering of mutations within NS5 is particularly notable given the multifunctional role of this protein in viral replication and host immune evasion25. NS5 is the largest nonstructural protein in DENV and encodes two critical enzymatic activities: an N-terminal methyltransferase (MTase) domain responsible for 5′ RNA capping and a C-terminal RNA-dependent RNA polymerase (RdRp) domain that mediates genome replication25. Beyond its enzymatic functions, DENV NS5 antagonizes the host type I interferon (IFN) response by binding human STAT2 and recruiting the host ubiquitin ligase UBR4, resulting in proteasomal degradation of STAT2 and consequent suppression of interferon-stimulated genes (ISGs)26,38,39. Structural studies reveal that the MTase and RdRp domains adopt an extended conformation required for STAT2 engagement, suggesting that mutations in either domain could influence both replication efficiency and immune antagonism simultaneously40. The replication and immune evasion functions of NS5 are therefore tightly interconnected, and mutations that enhance one function may impose trade-offs on the other41. In this context, the NS5 substitutions identified in the Kenyan DENV-2 lineage may reflect evolutionary diversification during prolonged local circulation. Whether these substitutions alter STAT2 binding affinity, RdRp catalytic efficiency, or replication kinetics remains to be determined; however, their presence in a lineage with persistent local circulation warrants functional characterization, particularly given implications for viral fitness and immune evasion in a partially immune population.

Limitations

A key limitation of this study is the sampling bias inherent in both the genomic and epidemiological datasets. The number of sequences generated from Kenya was relatively low compared with the larger global sequence dataset used for phylogenetic analyses. Although a down-sampling strategy was applied to intensively sampled regions, this imbalance may still have limited the detection of unsampled local diversity and reduced phylogenetic resolution within Kenyan lineages. In addition, study inclusion was restricted to patients presenting with clinically suspected acute febrile illness, and case confirmation relied solely on qRT-PCR performed on acute samples. The absence of serological testing and paired acute–convalescent samples likely resulted in under-detection of infections occurring outside the viraemic window and precluded assessment of recent versus past infections. Furthermore, the observed age distribution among confirmed cases may reflect healthcare-seeking behaviour or sampling bias rather than true differences in infection risk across age groups. Nevertheless, the genomic data generated in this study provide important insights into the long-term circulation and evolutionary dynamics of dengue virus in Kenya.

Conclusion

This study provides a comprehensive genomic characterization of the 2023 DENV outbreak in Coastal Kenya. Our analysis confirmed the co-circulation of three DENV serotypes; DENV-1, DENV-2 and DENV-3. Majority of the confirmed cases were are attributed to DENV-1 and DENV-2, but concurrent circulation of all three serotypes raises significant public health concerns, especially the increased risk of secondary infections by the different serotypes and the potential for severe disease manifestations such as dengue hemorrhagic fever (DSS) and dengue shock syndrome (DHF). Phylogenetic analysis revealed the long-term local circulation of DENV-2 in Kenya, and the clustering of Kenyan 2023 strain with contemporaneous strains from China is consistent with possible epidemiological connectivity, although formal migration modeling would be required to confirm the direction and timing of any such movement. On the other hand, DENV-1 and DENV-3 strains detected during this outbreak are genetically related to strains involved in the 2023-24 multi-country dengue outbreaks reported across Eastern and Western Africa, pointing to regional viral movement and possible travel-associated introductions. Our findings, therefore, call for more integrated strategies to contain the dengue outbreak in Kenya, including measures to curtail the long-term local circulation as well as measures to control travel-related importation of new dengue strains from countries within the region.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (335KB, pdf)
Supplementary Material 2 (20.9KB, pdf)

Acknowledgements

We gratefully acknowledge all data contributors including the authors and their laboratories for obtaining the specimens, generating the genetic sequence data and associated metadata and sharing them via the GISAID Initiative as well as GenBank. We also thank Samuel Owaka for his contribution to generating the map of sampling sites used in Supplementary 1 Figure S1. The study was made possible through the support of Kenya Medical Research Institutes Internal Research Grants (KEMRI-IRG) under award number KEMRI/IRG/EC0010 as well as Bill and Melinda Gates Foundation/Chan Zuckerberg Initiative (CZI) grant INV-050635 and INV-046964. The findings and conclusions in the study are those of the author(s) and do not necessarily represent the official position of the funders.

Author contributions

S.K.L and SK collected the primary set of samples used in the study and wrote the original draft. S.K.L, S.K, V.J, A.N, N.O, L.G, J.T, P.B, J.S, K.L and V.O performed the laboratory analysis of the samples reported in the study. S.K.L, G.P, P.O, J.G, and O.S performed data analysis and report generation. F.M., C.T., Samoel K., J.L., and K.L. were responsible for overall project planning and ensuring its successful execution. All authors read and revised the final manuscript.

Data availability

The genome sequences generated in the study are available in GenBank under accession numbers; PV717358-PV717395. Publicly available sequence data used in the study are available in the appendix section.

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Solomon K. Langat and Sheila Kageha contributed equally to this work.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (335KB, pdf)
Supplementary Material 2 (20.9KB, pdf)

Data Availability Statement

The genome sequences generated in the study are available in GenBank under accession numbers; PV717358-PV717395. Publicly available sequence data used in the study are available in the appendix section.

Articles from Scientific Reports are provided here courtesy of Nature Publishing Group

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