Dengue is the leading mosquito-borne viral cause of human illness and death. More than four billion people globally live at risk of Dengue Virus (DENV) infection and most infections are asymptomatic or present with a non-specific febrile illness (Madewell, 2020); WHO, 2024). Each year, ~ 500,000 cases progress to severe disease with appreciable mortality (Young, 2018). Four distinct serotypes (DENV-1–4) are in circulation globally and differ in epidemic potential and clinical severity (Sah et al., 2023) In Africa, confirmed outbreaks and co-circulation of multiple serotypes, including DENV-2, have been reported in Senegal, Mauritania, Cabo Verde, Burkina Faso and elsewhere, with entomological evidence of active transmission in urban settings (Fourié et al., 2021; Dieng et al., 2022), suggesting that DENV could be widespread on the continent against a backdrop of limited access to differential diagnostics and sparse pathogen-specific surveillance.
Outside malaria, often, the only routinely available point-of-care test, most non-malarial fevers are empirically managed, leaving their aetiologies largely uncharacterized and creating substantial gaps in policy response (Amoako et al., 2018). However, where differential testing has been deployed, substantial underdetection emerges: in a cohort of 515 febrile patients in southern Nigeria who were malaria- and typhoid-negative, ~ 28% had evidence of prior DENV exposure, ~ 8% showed recent/ongoing infection, and ~ 3% met criteria for acute infection (B. A. Onoja et al., 2024). This diagnostic gap obscures the burden of arboviruses such as dengue and constrains timely outbreak detection. In West and Central Africa (WCA) more broadly, dengue epidemiology remains undersampled, even as rapid urbanisation, mobility, and climate change are reshaping Aedes ecology and likely accelerating transmission potential (Mordecai et al., 2020).
Sierra Leone has no confirmed national record of dengue to date. Historical dengue reporting is sparse and fragmented, with no sustained nationwide arboviral surveillance and very limited routine testing beyond malaria(De Araújo Lobo et al., 2016; Dariano et al., 2017).Given established Aedes aegypti presence, densely populated urban city (Western Area Urban), porous regional travel networks, and ecological suitability that is likely increasing with climate variability (Jones et al., 2023; De Araújo Lobo et al., 2016), undetected endemic or recurrently imported DENV transmission is plausible. Some studies have reported the seroprevalence of DENV in Kenema and Bo (Dariano et al., 2017). However, in the absence of systematic, syndromic and laboratory-supported surveillance, the magnitude, serotype diversity, and transmission dynamics in Sierra Leone remain uncertain.
To address this gap, Sierra Leone initiated implementation of the Syndromic Sentinel Surveillance Strategies (4S) in June 2025, adapted from the Integrated Surveillance and Laboratory Network (RISLNET) model in Senegal, where 4S has repeatedly enabled early detection of respiratory and arboviral outbreaks, including Rift Valley fever virus (RVF), Crimean-Congo hemorrhagic fever (CCHF), Zika, yellow fever, chikungunya, and dengue, since 2015 (Dieng et al., 2024);(Dieng et al., 2022). 4S links frontline clinical syndromes to targeted laboratory testing and genomic confirmation, creating an operational platform for rapid risk assessment. Here, we report the first month of 4S implementation in Sierra Leone, including the country’s first laboratory-confirmed dengue case detected through this system, and we place this finding within the regional context of evolving DENV transmission. Our results underscore the need and feasibility of integrating differential diagnostics and genomic surveillance into routine febrile-illness care to understand the true burden of dengue and guide public-health action in Sierra Leone.
Clinical suspicion of Dengue Fever confirmed by RT-PCR
A 64-year-old female herbalist presented on 5 July 2025 with a five-day history of headache and arthralgia. Examination showed tachypnoea (38 breaths per minute) and mild tachycardia (104 beats per minute); blood pressure was 141/76 mmHg (widened pulse pressure) and oxygen saturation 96% on room air. No haemorrhagic signs, hypoxia or circulatory instability were observed. Based on these clinical symptoms, the doctor at the hospital suspected acute haemorrhagic fever (Likely Dengue) as these signs were most consistent with early dengue infection without evidence of plasma leakage or shock at presentation. During hospitalisation, blood samples were obtained and sent to the Central Public Health Reference Laboratory (CPHRL) for confirmation. Using RT-PCR, we confirmed that the patient was positive for the Dengue virus. However, due to the concurrent Mpox outbreak in Sierra Leone, a thorough case investigation, including detailed epidemiological follow-up, was not possible.
DENV-2 genotype II lineage F 1.1 is responsible for the febrile illness
To identify the serotype of the DENV, we generated a near-complete dengue genome from the Sierra Leone case. The consensus sequence has a genome coverage of 99.7%. BLAST analysis identified the closest matches as DENV serotype 2 (DENV-2) sequences sampled in India in 2021–2022, with 99.23–99.45% nucleotide similarity. To place our novel sequence within the context of global DENV diversity, we determined its lineage using Nextclade. The sequence was assigned to genotype II, major lineage F and minor lineage 1.1 (2II_F.1.1)(Hill et al., 2024). Also known as the Cosmopolitan genotype, DENV-2 genotype II is one of the most widely distributed and diverse DENV genotypes (Hill et al., 2024)
Next, we compiled a dataset of representative sequences for all DENV-2 from GenBank and GISAID (n = 5,475) to resolve the geographic origin of our sequence. Using this dataset, we inferred a maximum-likelihood phylogeny (Fig. 1). Consistent with previous results, our new sequence was nested within DENV-2, clustering with sequences from DENV-2 genotype II F 1.1 (2II_F.1.1) (Fig. 1). Major Lineage F is globally distributed, with minor lineage 1.1 predominantly circulating across Asia and the Caribbean(Hill et al., 2024).
Our SLE sequence clustered together with a 2024 USA genome with a bootstrap support of 99, and they are both nested in but diverged from sequences sampled in India. Our SLE sequence is separated from the closest USA sequences with 64 substitutions and Indian relatives (2021–2022) by a total of 127 substitutions, with 45 substitutions along the branch from the common ancestor (Fig. 1). This degree of divergence is inconsistent with a recent import from South Asia; instead, it suggests a prolonged period of diversification from the shared ancestor likely circulating in India or somewhere in South Asia or an unsampled location outside of the South Asia network. Our SLE sequence formed a sister lineage to sequences sampled from Réunion Island (2023–2024) (Bootstrap support = 100). Our SLE sequence is separated from the closest sequence from Réunion by 66 substitutions. There have been recurrent DENV epidemics in Réunion since 2017, resulting from repeated introductions from the Indian Ocean region (Frumence et al., 2024;Vincent et al., 2020). Together with the degree of divergence, points to independent exports from an unsampled 2II_F.1.1 reservoir in the Indian-Ocean/South Asia network, rather than direct transmission from India or the USA or Réunion to Sierra Leone.
Tree of representative DENV-2 viruses coloured by minor lineages, the Sierra Leone genome 064_S23|SLE|2025 is highlighted in blue. The solid box expands the relevant DENV-2 lineage 2II_F.1.1 clade. Within this clade, two Indian genomes from 2021–2022 are basal to the Sierra Leone genome, followed by a sister clade of a tight Réunion Island cluster sampled in 2023–2024. Tip labels show accession | location | host | date. Branch lengths are substitutions per site (100 bootstrap support). The topology places the Sierra Leone virus within DENV-2 2II_F.1.1, nearest to Indian Ocean/South Asia lineages and adjacent to the Réunion outbreak cluster.
2II_F.1.1 reported is part of the South Asia lineages
We performed Bayesian phylogenetic reconstructions to understand the timing of divergence between our SLE sequence relative to the 2II_F.1.1 Diversity in India and Réunion. We performed Bayesian phylogenetic reconstruction under a log-normal uncorrelated relaxed clock and a constant demographic model. The SLE genome’s median divergence time from its closest sampled South-Asia relative was December 2021, with wide uncertainty [95% HPD: November 2020 to October 2022] (Fig. 2). Given the phylogenetic placement of our SLE sequence nested within India diversity (Fig. 1), this suggests that our sequence likely descended from diversity circulating in India or the wider Asian lineages or an unsampled location outside of the South Asia network more than three years before this case report. This is inconsistent with a recent import from South Asia. However, we cannot infer the source of the introduction with any confidence owing to sparse sampling in the African region and beyond (Fig. 2B). We cannot infer that it was a direct introduction from South Asia, with the lineages diverging locally in India in the reservoir population before a more recent introduction. We also cannot exclude the possibility that the introduction from South Asia was facilitated via an unsampled location. As only one SLE genome was available, we could not resolve the extent of cryptic transmission locally. Additional sampling from Sierra Leone and neighbouring regions will be critical to distinguish between unsampled persistence and repeated introductions.
No drug resistance-associated mutations
No drug resistance-associated mutations
Substitutions at specific NS4B residues (notably V91A, L94F, T108I, and, context-dependently, T216N/P) have been shown to reduce susceptibility to NS4B-targeting dengue antivirals (e.g., JNJ-A07, JNJ-1802) by restoring the NS3–NS4B interaction disrupted by these compounds (Goethals et al., 2023); (Bouzidi et al., 2024)
We screened our Sierra Leone genome against this resistance panel using output from the Nextclade lineage assignment tool (Aksamentov et al., 2021a). The SLE genome has the NS4B:A19T, V48I, F112L, and T244A substitutions, but none of the canonical resistance substitutions (V91A, L94F, T108I, T216N/P) were present (Supplementary table). To contextualise these findings, we downloaded all publicly available 2II_F.1.1 high-quality genomes from GISAID and NCBI (n = 5,110). We found that our sequence exhibits a background NS4B profile typical of 2II_F.1.1. We found that the mutations observed at the NS4B region of our Sierra Leonean sequence are common, clade-typical polymorphisms. A19T occurred in 3,180 of the 5,110 sequences (62.2%), V48I in 3,117/5,110 (61.0%), F112L in 3,183/5,110 (62.3%), and T244A in 3,145/5,110 (61.6%). We found that canonical resistance signatures are exceptionally infrequent across this lineage: V91A occurs in 5 of the 5,110 sequences (0.10%), T108I in 3/5,110 (0.06%), and L94F or T216N/P was not detected. No genomes carried any combination of resistance substitutions (e.g., V91A + T108I or larger constellations).