Dengue Virus Serotypes Research Articles

Clinical Performance of MAGLUMI Diagnostic Tests for the Automated Detection of Dengue Virus

Aims: The screening and diagnosis of dengue virus infection play a crucial role in controlling the epidemic of dengue fever, highlighting the urgent need for a highly sensitive, simple, and rapid laboratory testing method. This study aims to assess the clinical performance of MAGLUMI Denv NS1 in detecting dengue virus NS1 antigen. Methods: A retrospective study was conducted to assess the sensitivity and specificity of MAGLUMI Denv NS1 using residual samples. Dengue-confirmed and excluded samples, validated by qPCR, were subjected to testing with MAGLUMI Denv NS1 in accordance with the manufacturer’s instructions. The linear range, endogenous interference, and cross-reactivity of MAGLUMI Denv NS1 were verified, and a consistency analysis with commercial comparator products was carried out. Results: The diagnostic specificity of MAGLUMI Denv NS1 is 98.41% (62/63), and the sensitivity is 98.32% (117/119). It effectively detects various serotypes of dengue virus, with no observed endogenous interference or cross-reactivity. Additionally, the consistency of NS1, IgM, and IgG tests on the MAGLUMI platform compared to commercial comparator reagents reaches 85.71%, 99.25%, and 98.97%, respectively. Conclusions: The MAGLUMI Denv NS1 represents a highly sensitive laboratory testing method capable of enhancing the diagnostic accuracy and efficiency of dengue virus infection detection.

Simultaneous detection of dengue virus serotypes in a dual-serotype-detection nucleic acid based lateral flow assay.

Dengue virus (DENV) is an important arthropod-borne viral disease, with four antigenically and genetically diverse serotypes (DENV-1, DENV-2, DENV-3, and DENV-4). Timely and accurate diagnosis of dengue virus serotypes is crucial for the management of outbreaks. This study focussed on the development of a RT-PCR based lateral flow strip assay to detect DENV serotypes in a dual detection manner without using gel electrophoresis. The assay uses anti-biotin/streptavidin colloidal gold conjugates with fluorescent/enzymatic tagged DENV serotype specific antibodies for the direct detection of DENV infected serum samples on a nitrocellulose membrane using biotin-BSA as control line. The detection limit of the assay was up to 10 copies of cDNA for DENV-1 and 100 copies for DENV-2, DENV-3, and DENV-4. In house evaluation of DENV LFIA demonstrated 100 % sensitivity in all the serotypes compared to conventional RT-PCR, 100 % specificity for DENV-1, DENV-2, DENV-3, and 95 % specificity for DENV-4 detection. DENV serotyping was assessed in a dual detection manner (DENV-1/DENV-3 and DENV-2/DENV-4 at two test lines) on the strip. The limitation of the assay is the requirement of PCR for initial amplification and confirmation of individual serotype in case of DENV-1/DENV-3 and DENV-2/DENV-4 detection, besides the field evaluation of the assay detected DENV-2 and DENV-3 serotypes, and no other serotype was detected in line with RT-PCR findings.

Early insights of dengue virus serotype 3 (DENV-3) re-emergence in São Paulo, Brazil

Early insights of dengue virus serotype 3 (DENV-3) re-emergence in São Paulo, Brazil

Evaluation of Diagnostic Performance of a Multiplex RT-qPCR Method for Detecting DENV Serotypes and CHIKV in Clinical Samples, Ouagadougou, Burkina Faso

Evaluation of Diagnostic Performance of a Multiplex RT-qPCR Method for Detecting DENV Serotypes and CHIKV in Clinical Samples, Ouagadougou, Burkina Faso

Geographic origin and evolution of dengue virus serotypes 1 and 3 circulating in Africa

Abstract Background Despite the increasing burden of dengue in Kenya and Africa, the introduction and expansion of the virus in the region remains poorly understood. The objective of this study is to examine the genetic diversity and evolutionary histories of dengue serotypes 1 and 3 in Kenya and contextualize their circulation within circulation dynamics in the broader African region. Methods Viral RNA was extracted from samples collected from a cohort of febrile patients recruited at clinical sites in Kenya from 2013 to 2022. Samples were tested by PCR for dengue virus (DENV) presence. Five DENV positive samples were serotyped, and complete viral genomes for phylogenetic inference were obtained via sequencing on Illumina platforms. Sequences generated in our study were combined with global datasets of sequences, and Bayesian and maximum likelihood methods were used to infer phylogenetic trees and geographic patterns of spread with a focus on Kenya and Africa as a whole. Results Four new DENV-1 and one new DENV-3 genome were successfully sequenced and combined with 328 DENV-1 and 395 DENV-3 genomes from elsewhere for phylogenetic analyses. The DENV-1 sequences from our study formed a monophyletic cluster with an inferred common ancestor in 2019 (MRCA 2019, 95% HPD 2018 – 2019), that was closely related to sequences from Tanzania. The single DENV-3 sequence clustered with sequences from Tanzania and Kenya collected between 2017 and 2019 and related to recent outbreaks in the region. Phylogenetic trees resolved multiple clades of DENV-1 and -3 concurrently circulating in Africa, introduced in the early to mid-2000s. Three DENV-1 and four DENV-3 clades are highlighted, introduced between 2000 and 2015. Phylogeographic models suggest frequent, independent importations of DENV lineages into Kenya and Africa from East and South-East Asia via distinct geographic pathways. Conclusions DENV-1 and -3 evolutionary dynamics in Africa are characterized by co-circulation of multiple recently introduced lineages. Circulating lineages are introduced via distinct geographic pathways that may be centered around regional nexus locations. Increased surveillance is required to identify key regional locations that drive spread, and dengue interventions should focus on interrupting spread at these locations.

Indonesian medicinal plants' therapeutic potential against dengue virus infection: A literature review

Infections caused by the dengue virus (DENV) exhibit a wide range of clinical manifestations, from asymptomatic cases to severe, and sometimes life-threatening, conditions. Therefore, identifying effective antivirals and anti-inflammatory agents is a promising strategy to reduce the impact of these infections. Indonesia, with its rich biodiversity, particularly in medicinal plants, offers potential sources for such treatments. Most research on DENV antivirals in Indonesia has been conducted in vitro and has predominantly focused on DENV serotype 2 (DENV-2). However, in vivo research on medicinal plants, as well as studies on their anti-inflammatory properties, remains limited in Indonesia.Extracts that have been investigated in both in vivo and in vitro settings are limited to Cassia alata and Curcuma longa. Plants possessing antiviral properties originate from diverse botanical families, with leaves being the most utilized plant component. Flavonoids are found in most medicinal plants that have antiviral properties. Indonesia is known to have other natural compounds, including quercetin, isobutyl gallate, curcumin, and 6-gingerol, which have antiviral properties. Curcumin and 6-gingerol are the only natural compounds that have been subjected to testing against all four serotypes of dengue. This article provides a comprehensive review of medicinal plants in Indonesia, focusing specifically on their therapeutic potential against the dengue virus.

Deciphering dengue: novel RNA barcoding segments for enhanced serotype-specific identification and global surveillance of dengue viruses

IntroductionDengue viruses (DENVs), the causative agents of dengue hemorrhagic fever and dengue shock syndrome, undergo genetic mutations that result in new strains and lead to ongoing global re-infections.ObjectivesTo address the growing complexity of identifying and tracking biological samples, this study screened RNA barcode segments for the four DENV serotypes, ensuring high specificity and recall rates for DENV identification using segments.ResultsThrough analyzing complete genome sequences of DENVs, we screened eight barcode segments for DENV, DENV-1, DENV-2, DENV-3, and DENV-4 identification. Comparing the screened barcode segments to sequences of known strains and determining the proportion of correctly or incorrectly identified nucleotides, these segments demonstrated an average recall rate at nucleotide level of 91.34% for four DENV serotypes, a specificity of 99.50% at species level within the Flaviviridae family, and a precision rate of 100% for identifying DENVs. For arboviruses, the nucleotide-level specificity was 63.58%. We designed and used the “Barcoding” software to streamline segment design, integrating automated sequence preprocessing, evaluation of barcode segments, and primer design, significantly reducing manual intervention and enhancing overall efficiency. We also established an online database called “Barcodes” for storing and preparing barcode segments.ConclusionThis work established a standard framework for DENV identification and barcode segment selection, promising significant advancements in the real-time management and control of DENVs, thereby enhancing surveillance capabilities and facilitating targeted interventions in dengue outbreak-prone regions.

Predicting the infecting dengue serotype from antibody titre data using machine learning.

The development of a safe and efficacious vaccine that provides immunity against all four dengue virus serotypes is a priority, and a significant challenge for vaccine development has been defining and measuring serotype-specific outcomes and correlates of protection. The plaque reduction neutralisation test (PRNT) is the gold standard assay for measuring serotype-specific antibodies, but this test cannot differentiate homotypic and heterotypic antibodies and characterising the infection history is challenging. To address this, we present an analysis of pre- and post-infection antibody titres measured using the PRNT, collected from a prospective cohort of Thai children. We applied four machine learning classifiers and multinomial logistic regression to the titre data to predict the infecting serotype. The models were validated against the true infecting serotype, identified using RT-PCR. Model performance was calculated using 100 bootstrap samples of the train and out-of-sample test sets. Our analysis showed that, on average, the greatest change in titre was against the infecting serotype. However, in 53.4% (109/204) of the subjects, the highest titre change did not correspond to the infecting serotype, including in 34.3% (11/35) of dengue-naïve individuals (although 8/11 of these seronegative individuals were seropositive to Japanese encephalitis virus prior to their infection). The highest post-infection titres of seropositive cases were more likely to match the serotype of the highest pre-infection titre than the infecting serotype, consistent with antigenic seniority or cross-reactive boosting of pre-infection titres. Despite these challenges, the best performing machine learning algorithm achieved 76.3% (95% CI 57.9-89.5%) accuracy on the out-of-sample test set in predicting the infecting serotype from PRNT data. Incorporating additional spatiotemporal data improved accuracy to 80.6% (95% CI 63.2-94.7%), while using only post-infection titres as predictor variables yielded an accuracy of 71.7% (95% CI 57.9-84.2%). These results show that machine learning classifiers can be used to overcome challenges in interpreting PRNT titres, making them useful tools in investigating dengue immune dynamics, infection history and identifying serotype-specific correlates of protection, which in turn can support the evaluation of clinical trial endpoints and vaccine development.

Embelin Inhibits Dengue Virus Serotype 2 Infectivity with Nonstructural Protein Helicase as a Potential Molecular Target

Embelin Inhibits Dengue Virus Serotype 2 Infectivity with Nonstructural Protein Helicase as a Potential Molecular Target

Detrimental Effects of Anti-Nucleocapsid Antibodies in SARS-CoV-2 Infection, Reinfection, and the Post-Acute Sequelae of COVID-19.

Antibody-dependent enhancement (ADE) is a phenomenon in which antibodies enhance subsequent viral infections rather than preventing them. Sub-optimal levels of neutralizing antibodies in individuals infected with dengue virus are known to be associated with severe disease upon reinfection with a different dengue virus serotype. For Severe Acute Respiratory Syndrome Coronavirus type-2 infection, three types of ADE have been proposed: (1) Fc receptor-dependent ADE of infection in cells expressing Fc receptors, such as macrophages by anti-spike antibodies, (2) Fc receptor-independent ADE of infection in epithelial cells by anti-spike antibodies, and (3) Fc receptor-dependent ADE of cytokine production in cells expressing Fc receptors, such as macrophages by anti-nucleocapsid antibodies. This review focuses on the Fc receptor-dependent ADE of cytokine production induced by anti-nucleocapsid antibodies, examining its potential role in severe COVID-19 during reinfection and its contribution to the post-acute sequelae of COVID-19, i.e., prolonged symptoms lasting at least three months after the acute phase of the disease. We also discuss the protective effects of recently identified anti-spike antibodies that neutralize Omicron variants.

Spreading of dengue virus infection cases in Malda district of West Bengal, India during COVID-19 pandemic situation (2020 to 2022): A cross-sectional study

Introduction: One of the most widespread arboviral infections is caused by the dengue virus (Family: Flaviviridae) having a positive sense single-stranded RNA genome. It causes common symptoms like fever with headache, rashes, and other associated features like thrombocytopenia. This study aims to determine the prevalence of dengue virus infection and serotype dominance in the Malda district, West Bengal, India. Methods: During January 2020 to December 2022, the fever cases visited out-patient department or admitted to in-patient department at Malda Medical College were assessed for the presence of dengue NS1 antigen (fever<5 days) along with dengue IgM (fever≥5 days) in serum by ELISA. Serotype(s) of the dengue NS1-positive patients was determined using RT-qPCR. Results: The results revealed NS1 positivity to be 2.94% in 2020, 6.50% in 2021 and an increase up to 7.36% in 2022. Dengue IgM positivity was 0.35% in 2020, 5.59% in 2021 and reached 10.89% in 2022. During this period, the male population was infected more than the female. In 2020, the age-group<15 years was mostly infected (43%), while the age-group of 15-30 years accounted for the highest rate in 2021 (38%) and 2022 (34%). The serotyping data revealed that DENV-2 was most prevalent (60%), while some mixed infections (10%) with DENV-1 and DENV-3, were also found. Conclusion: Dengue infection is a major concern in this region and the rate of infection is continuously increasing yearly. DENV-2 serotype was found most predominant. Appropriate prevention along with proper awareness among the population, is utmost necessary.

Epidemiology of Dengue - Puerto Rico, 2010-2024.

Dengue is a mosquitoborne viral illness that can cause acute febrile illness, severe disease, or death. Worldwide, the number of dengue cases is increasing. During the last dengue outbreaks in Puerto Rico throughout 2010-2013, dengue virus (DENV) serotype 1 (DENV-1) predominated, and the largest proportion of cases occurred among adolescents and young adults aged 10-19 years. Dengue case data from January 1, 2010-November 4, 2024, were obtained from the Puerto Rico Department of Health. Bivariate analyses were conducted to evaluate the distribution of cases by patient age, DENV serotype, and hospitalization status during three periods: 2010-2019, 2020-2022, and 2023-2024. During 2023-2024, the median age of dengue cases increased to 26 years (95% CI=25-27 years) compared with that during 2020-2022 (17 years; 95% CI=17-18 years) and 2010-2019 (19 years; 95% CI=19-19 years). After >10 years of DENV-1 predominance, the proportions of DENV serotypes 2 (DENV-2) and 3 (DENV-3) increased significantly during 2023-2024, with DENV-3 replacing DENV-1 as the predominant serotype. In addition, the proportion of dengue patients who were hospitalized increased from 35.7% (2010-2019) to 53.5% (2023-2024). The current dengue outbreak in Puerto Rico marks a shift in serotype predominance to DENV-3 and increasing percentages of cases in older age groups (61.7% in adults aged ≥20 years), although a high proportion of cases still occur among adolescents aged 10-19 years (29.5%). The current dengue outbreak also has a higher rate of hospitalizations than those in previous years. Understanding the changing epidemiology of dengue is crucial to guiding public health strategies for dengue control, including clinical management, surveillance and health care system resilience, and public outreach and education.

Conserved Sequences from Dengue Virus Genomes Form Stable G-Quadruplexes.

Arthropod-borne members of the genus Orthoflavivirus cause significant human disease. Four serotypes of dengue virus are endemic globally, and approximately 50 percent of the world's population lives in a dengue-affected area. Complications from immunoenhancement occurring after a secondary infection with a different dengue serotype make vaccine development challenging. Antiviral therapies that target features conserved in all four serotypes would, therefore, be beneficial. Computational studies identified multiple potential G-quadruplex sites that are conserved in the RNA genome sequences of members of the genus Orthoflavivirus. Biophysical studies confirmed that the NS5-B quadruplex sequences obtained from viruses of each dengue serotype can form quadruplexes in vitro, and binding data showed that known quadruplex binders stabilized NS5-B quadruplexes for all four dengue serotypes.

Prevalence of Different Dengue Serotypes in Northern India, 2021-2022: A Tertiary Care Hospital-Based Study.

Dengue fever is a substantial emerging and reemerging arboviral virus in tropical and subtropical areas that seriously threatens public health worldwide. India is experiencing rising dengue epidemics in urban and rural regions linked to all four serotypes. The objective is to examine the serotypes and genotypes of the circulating dengue virus (DENV) at a tertiary care center in eastern Uttar Pradesh, India, from 2020 to 2021. This retrospective cross-sectional observational study involved dengue patients from January 2021 to December 2022. The genetic analysis of the circulating DENV was conducted by amplifying the partial CprM (511-bp) gene using nested reverse transcriptase polymerase chain reaction (RT-PCR), followed by sequencing. Only those positive for NS1 antigen (n = 581) were included in the study. A total of 204 cases (35.1%) were seropositive, with 96 cases (37.4%) out of 257 in 2021 and 108 cases (33.3%) out of 324 in 2022. With 119 cases (58.3%), men were most affected. The nested RT-PCR for dengue revealed three DENV-1 to DENV-3, except for DENV-4. DENV-2 and DENV-3 were the most predominant serotypes, with 98 (48%) and 94 (46%) cases, respectively. Conversely, DENV-1 was the least prevalent with cases 3 (1.6%). Unfortunately, 35 (17.2%) of the 204 cases died. DENV-2 had the highest mortality rate, with 23 deaths (65.7%). In cases with DENV-3, nine (25.7%) died. This study revealed regional disparities in DENV serotype prevalence in India. If regional differences in the most common serotypes and genotypes are identified early in the season, molecular surveillance may predict major dengue outbreaks and severity.

Structural Dynamics of the Dengue Virus Non-structural 5 (NS5) Interactions with Promoter Stem Loop A (SLA).

The dengue virus (DENV) NS5 protein plays a central role in dengue viral RNA synthesis which makes it an attractive target for antiviral drug development. DENV NS5 is known to interact with the stem-loop A (SLA) promoter at the 5'-untranslated region (5'-UTR) of the viral genome as a molecular recognition signature for the initiation of negative strand synthesis at the 3' end of the viral genome. However, the conformational dynamics involved in these interactions are yet to be fully elucidated. Our study explores the structural dynamics of NS5 from DENV serotype 2 (DENV2 NS5) in complex with SLA, employing surface plasmon resonance (SPR), hydrogen - deuterium exchange coupled to mass spectrometry (HDX-MS), computational modeling, and cryoEM single particle analysis to delineate the molecular details of their interaction. Our findings indicate that DENV2 NS5 binds SLA in a closed conformation with significant interdomain cooperation between the methyltransferase (MTase) and RNA-dependent RNA polymerase (RdRp) domains, a feature integral to the interaction. Our HDX-MS studies reveal SLA-induced conformational changes in both domains of DENV2 NS5, reflecting a potential mechanism for dengue NS5's multifunctional role in viral replication. Lastly, our cryoEM structure provides the first visualization of the DENV2 NS5-SLA complex, confirming a conserved SLA binding mode across DENV serotypes. These insights obtained from our study enhance our understanding of dengue NS5's complex conformational landscape, supporting the potential development of antiviral strategies targeting dengue NS5's conformational states.

A chimeric RNA consisting of siRNA and aptamer for inhibiting dengue virus replication

Abstract Silencing viruses by chimeric RNAs, wherein small interfering RNAs (siRNAs) targeting viral RNAs are conjugated with RNA aptamers specific to viral envelope proteins, is a promising treatment for viral infection diseases; however, practical evaluations are apparently lacking. Here we present a chimeric RNA comprised of siRNA and RNA aptamer, both of which target all four serotypes of dengue virus (DENV), for suppressing DENV replication. The siRNA targeting consensus sequences in the 3’UTR of all four DENV serotypes suppressed the expression of a reporter gene carrying the siRNA-targeted sequence of DENV-1 by approximately 70%. The RNA aptamer generated by VLP-SELEX using DENV-1-VLPs as baits showed an affinity for all four DENV-VLP serotypes, presumably without affecting the fusion process. After conjugation of each modality, the chimeric RNA significantly suppressed authentic DENV-1 and DENV-2 production in vitro. Our study provides evidence that chimeric RNA is a potentially effective antiviral agent.

Haematological parameters as predictors of severe dengue: a study from northern districts of West Bengal.

A hike in dengue cases was recorded in last two years, resulting from both single and multiple-serotypes of dengue virus (DENV) and secondary infections, culminating in significant hospitalizations and deaths in India. This study focuses on evaluating symptomatic and haematological parameters in acute dengue patients of the northern part of West Bengal to predict disease severity early on and also to analyze the correlation between circulating DENV serotypes with severity. Dengue patients (N=540) diagnosed as NS1 positives were categorized into 13.7% severe DHF (N=74) and 86.3% mild DF (N=466) and prediction of risk was done using logistic regression. DENV RNA was isolated from blood, converted to cDNA, and detected/serotyped via RT-qPCR by using DENV specific primers. Only 14.48% (N=11) patients showed single serotypic (DENV2 or DENV3) infection of dengue. In contrast, multi-serotypic infections (N=65) with the prevalence of DENV2 and DENV3 co-infections were found among the dengue patients, affecting severe changes in the most critical haematological parameters such as hematocrit and platelet count. The multivariate binary logistic regression model revealed that only six parameters viz., age (p=0.032), presence of joint pain (p=0.015), Haemoglobin level (p<0.001), total RBC count (p=0.024), total WBC count (p=0.003), lymphocyte% (p=0.019) were found to be significantly associated with the risk of DHF. Most prevalent DENV2 and DENV3 infections significantly impact hematocrit and platelet counts in the study region. Our prediction model, incorporating age, joint pain, hemoglobin, RBC, WBC, and lymphocyte, may effectively predict dengue severity.

Rapid spread of the emerging cosmopolitan genotype of dengue virus serotype 2, and expansion of dengue virus serotype 1 genotype V in Peru

Objectives. This study aimed to evaluate the prevalence and distribution of dengue virus genotype V serotype 1 (DENV-1) and cosmopolitan genotype serotype 2 (DENV-2) in Peru between 2019 and 2022. Materials and methods. The envelope (E) gene region was amplified from 79 serum samples by polymerase chain reaction (PCR) and sequenced by next-generation sequencing (NGS) technology. The obtained sequences were subsequently analyzed with bioinformatics tools. Results. The study generated envelope gene sequences of DENV-1 and DENV-2 serotypes. Our study revealed a rapid dispersal and wide distribution of the cosmopolitan DENV-2 genotype in several regions of Peru in 2022, as well as the spread of DENV-1 genotype V to new Peruvian regions, along with the cosmopolitan DENV-2 genotype. Conclusions. Our findings suggest the urgent need to strengthen epidemiological and genomic surveillance systems to understand and control the spread of circulating DENV genotypes in Peru. This will allow a more rapid response, as well as the monitoring of its potential dissemination to other countries in the Americas.

Optimized high-yield expression of envelope glycoprotein domain III from dengue virus serotypes 1 to 4.

Dengue virus (DENV) envelope glycoprotein Domain III (EDIII) is critical for viral entry, highly immunogenic, and induces robust neutralizing antibody response. It is a prominent candidate for designing subunit-based vaccines and can also be harnessed as an antigenic bait for isolation of neutralizing human mAbs. Here, we describe an optimized method for high-yield expression of recombinant domain EDIII protein from DENV serotypes 1 to 4 in different Escherichia coli (E. coli) expression strains. The DENV EDIII proteins show differential expression patterns in tested E. coli expression strains. The structural integrity of the purified and refolded proteins is further validated using the Circular Dichroism (CD) spectroscopy and Fourier Transform Infrared (FTIR) spectroscopic analysis. The functional validation of the purified refolded DENV EDIII proteins through Enzyme-linked Immunosorbent Assay (ELISA) and co-immunoprecipitation (Co-IP) exhibits efficient binding with a well-characterized humanized neutralizing mAb 513. Further, we compared the potency of purified EDIII in blocking viral through competitive inhibition assay. Our study highlights that a universal expression system may not be an ideal approach for all DENV EDIII protein expression.

Diagnostic Challenges of Arboviral Infections and Dengue Virus Serotype Distribution in Febrile Patients in East Java, Indonesia

ObjectivesArboviruses pose significant public health threats globally, with Southeast Asia being a hotspot for these infections. This study aimed to reassess the incidence of dengue, Zika, and chikungunya viruses in patients clinically diagnosed with dengue in East Java, Indonesia in 2023. MethodsThe study included 108 patients admitted to hospitals in Jember, with blood samples collected on admission. Multiplex RT-PCR was used to detect viral RNA for dengue, Zika, and chikungunya, while dengue serotypes were identified using real-time PCR. ResultsA total of n=67/108 patients (62%) tested positive for dengue virus (DENV), one patient tested positive for chikungunya and no cases of Zika were detected. Differences in laboratory parameters between DENV RNA-negative patients and confirmed dengue cases suggest possible misdiagnosis of dengue. Serotyping of DENV-positive samples revealed DENV-3 as predominant serotype in Jember, accounting for 34% of cases (n=23/67), followed by DENV-1 and DENV-2 at 19% each (n=13/67), and 6% for DENV-4 (n=4/67), while 21% (n=14/67) remained untyped. ConclusionsThis study highlights the nature of the dengue outbreak in Jember in 2023, where all four DENV serotypes were in circulation, and underlines the need for serological or nucleic acid-based methods to improve arbovirus diagnosis in the region.