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Figures
Abstract
Background
Accurate diagnostics of dengue virus (DENV) infection are essential for patient management, outbreak control, and vaccine implementation. Serological testing plays a key role, especially when molecular assays are unavailable or viremia subsides; yet, cross-reactivity with other flaviviruses remains a challenge. This study examined the diagnostic accuracy of four Euroimmun ELISAs, including a newly developed dual-cut-off IgG ELISA.
Methods
The Dengue Virus NS1 ELISA, Anti-Dengue Virus Type 1–4 ELISA (IgM), Anti-Dengue Virus Type 1–4 ELISA (IgG; native antigen/gE-based), and the novel Anti-Dengue Virus NS1 ELISA 2.0 (IgG; recombinant NS1-based, with an alternative higher cut-off for flavivirus-endemic regions) were analyzed. Sensitivity was determined using sera from 22 Vietnamese patients with RT-PCR-confirmed DENV infection, collected during acute (t1, 1–6 dpo), early convalescent (t2, 4–9 dpo), and late convalescent (t3, 13–19 dpo) phases. Specificity was assessed with samples from 500 healthy German blood donors (HBD) and 40 patients each with West Nile virus (WNV) or Zika virus (ZIKV) infection.
Results
Sensitivities were 90.5%/70.0%/0% (t1/t2/t3) for NS1, 33.3%/85.0%/77.3% for IgM, 66.7%/100%/100% for IgG, and 33.3%/65.0%/100% vs. 19.1%/50.0%/100% for IgG 2.0 (standard vs. alternative cut-off). Combined NS1/IgM testing achieved 100% sensitivity in single acute-phase samples. Combined IgM and IgG 2.0 testing confirmed recent infection by IgM/IgG seroconversion or ≥4-fold IgG increase in 85.7% of paired samples. Overall specificity was 85.7% (HBD/WNV/ZIKV: 95.0%/50.0%/5.0%) for IgG, compared to 95.7% (98.2%/95.0%/65.0%) and 99.5% (99.8%/97.5%/97.5%) for IgG 2.0 using standard and alternative cut-offs, respectively.
Conclusions
Euroimmun ELISAs support customized, highly accurate and versatile diagnostic strategies applicable to various dengue testing contexts. Combining NS1 and IgM ELISAs may offer a practical alternative to molecular assays during acute infection. The native antigen/gE-based IgG ELISA enables early sensitive IgG detection, although with limited specificity. With minimal cross-reactivity, the NS1-based dual-cut-off ELISA 2.0 (IgG) reliably captures DENV-specific IgG dynamics and enhances differentiation from other flaviviruses, which could provide an advantage in the use for convalescent-phase diagnostics, epidemiological surveillance, and pre-vaccination screening.
Author summary
Dengue is one of the most widespread mosquito-borne viral diseases worldwide, and timely, accurate case confirmation is essential for patient care and outbreak control. However, diagnosis remains challenging because early symptoms are often non-specific. Furthermore, dynamic viral and serological markers over the course of infection and potential cross-reactivity with related flaviviruses can affect serodiagnostics. In this study, we evaluated a set of four enzyme-linked immunosorbent assays (ELISAs) targeting dengue virus antigen (NS1) and antibodies (IgM and IgG). We demonstrate that combining NS1 and IgM testing enables reliable identification of acute dengue infection from a single blood sample, which is particularly useful in settings where molecular methods are not available. We also assessed a new NS1-based IgG ELISA with an optional alternative cut-off value. Compared with an IgG ELISA based on native antigen/gE, the use of this assay reduces cross-reactivity in individuals exposed to Zika or West Nile virus. The alternative cut-off additionally allows adaptation of testing to different epidemiological settings. Overall, our findings illustrate how tailored serological strategies can improve dengue diagnosis and support more accurate determination of dengue immune status in epidemiological surveillance.
Citation: Saschenbrecker S, Muigg N, Klemens O, Klemens JM (2026) Improved and customized dengue serodiagnostics through combined NS1/IgM testing and novel dual-cut-off IgG ELISA. PLoS Negl Trop Dis 20(4): e0014295. https://doi.org/10.1371/journal.pntd.0014295
Editor: Richard A. Bowen, Colorado State University, UNITED STATES OF AMERICA
Received: January 20, 2026; Accepted: April 22, 2026; Published: April 27, 2026
Copyright: © 2026 Saschenbrecker et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All underlying raw data are included in this article and its Supporting information files. The anonymized dataset is provided as Supporting information S1 Dataset.
Funding: The authors received no specific funding for this work.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: All authors are employees of Euroimmun, a company that manufactures diagnostic tests and instruments. None of the authors benefits form any potential or actual financial or non-financial gain as a result of this publication.
Introduction
Dengue virus (DENV) belongs to the genus Flavivirus (family Flaviviridae), which also includes other arthropod-borne human pathogens such as Zika virus (ZIKV), West Nile virus (WNV), Yellow fever virus (YFV), Japanese encephalitis virus (JEV), and tick-borne encephalitis virus (TBEV) [1]. DENV is among the fastest-spreading mosquito-transmitted viruses, with about 4 billion people living in regions at risk of dengue. Each year, an estimated 400 million infections occur globally, including 96 million symptomatic cases [2–5]. Due to substantial morbidity and mortality, dengue poses a major public health challenge [6]. Its incidence has increased dramatically in recent decades, driven by climate change, expanding mosquito habitats, limited healthcare infrastructure, and rapid urbanization [5,7]. Endemic in South-East Asia, the Americas, the Western Pacific, Africa, and the Eastern Mediterranean, DENV is now emerging in previously dengue-naïve regions, including parts of Europe and South America [3,8,9].
Approximately 75% of DENV infections are asymptomatic [10]. Symptomatic cases range from mild to moderate illness and can rapidly progress to severe dengue, characterized by plasma leakage, shock, internal hemorrhage, and organ failure. Severe dengue is a medical emergency and can be fatal without prompt treatment [11–13]. Risk factors for severe disease include prior infection with a heterologous DENV serotype, viral genotype, prior flavivirus exposure, timing between infections, and host factors such as genetics, age, sex, and comorbidities [12,14].
Vaccines such as Dengvaxia (Sanofi Pasteur) and Qdenga (TAK-003, Takeda) are approved and indicated for preventing dengue; however, Dengvaxia is limited to individuals with a test-confirmed previous DENV infection and anticipated to be discontinued [15–17]. Currently, there is no specific antiviral therapy for dengue; clinical management is supportive. Timely and accurate diagnostics are essential for patient care, outbreak control, and vaccine implementation, particularly in endemic regions with co-circulating flaviviruses. Because early symptoms of dengue are non-specific, laboratory confirmation is critical to distinguish it from other febrile illnesses and guide appropriate interventions. Diagnostic strategies should consider the stage of infection, the timing of sample collection, kinetics of viremia and antibody responses, purpose of testing, regional flavivirus circulation, prior flavivirus exposure or vaccination, travel history, and available laboratory infrastructure [18–20].
During the early febrile phase (typically within the first 5–7 days after symptom onset), DENV infection can be confirmed by virus isolation, or detection of viral RNA or antigens [19,20]. Virus isolation allows serotype identification but is rarely used due to complexity and low sensitivity [21]. Reverse transcription polymerase chain reaction (RT-PCR) offers high sensitivity and specificity and enables serotyping but is limited by the short duration of viremia and possible resource constraints. Antigen detection focuses on the non-structural protein 1 (NS1), a highly immunogenic glycoprotein secreted from infected cells during viral replication. NS1 is more stable than viral RNA, extending the diagnostic window of antigen assays beyond that of molecular methods [22–25]. However, NS1 detection in secondary infections may be compromised by the early rise in anti-NS1 IgG titers due to the anamnestic immune response. The high IgG levels lead to the formation of immune complexes, which ‘mask’ the NS1 antigen, reducing its detectability and lowering assay sensitivity. This effect is particularly pronounced in secondary infections, where immune complex formation can substantially decrease the reliability of NS1-based diagnostic during the acute phase of infection [26–28].
IgM antibodies are initially detectable between 3–5 days after symptom onset and remain for several months following primary DENV infection. IgG antibodies usually appear by day 7–10 and can persist for years. In secondary flavivirus infections, the IgM response is typically altered, while IgG titers rise rapidly and reach high levels due to prior immunological priming [13,19,21]. As per WHO guidelines, a single positive IgM result indicates a probable dengue case, while IgM or IgG seroconversion, or a 4-fold rise in IgG titers in paired (acute and convalescent) samples confirms recent DENV infection [21,29,30]. In endemic areas, where molecular diagnostics are often unavailable, single-sample serology is commonly used despite its limitations, as paired samples are difficult to obtain due to short hospital stays and high outpatient loss to follow-up.
Interpretation of serological results is complicated by extensive cross-reactivity among flaviviruses, especially in populations with frequent prior infections or vaccination history [31,32]. Many assays available for the measurement of IgM or IgG antibodies are based on native whole-virus antigens or recombinant proteins, such as envelope glycoprotein E (gE). These assays detect broadly reactive antibodies, which limits their ability to differentiate between flavivirus infections [33–36]. To improve specificity, assays employing recombinant antigens have been developed, with NS1 serving as a key target for antibody detection. Containing more species-specific epitopes than structural proteins, NS1 allows better distinction among flavivirus infections, although some cross-reactivity remains [37–42]. Importantly, NS1 is absent in several inactivated flavivirus vaccines (e.g., TBEV, JEV), enabling possible distinction between vaccination responses and natural infections [37,43].
Given the limitations of individual diagnostic markers, a combined approach that integrates the determination of viral RNA, viral antigens, and host antibodies is recommended [19,20]. As molecular testing is not universally available in resource-limited settings, robust serological assays remain essential. Addressing this need, we assessed the diagnostic accuracy of a set of ELISA kits for DENV serodiagnosis provided by EUROIMMUN Medizinische Labordiagnostika AG (Lübeck, Germany; hereafter “Euroimmun”). We evaluated these assays individually and in combination, focusing on two key aspects: [i] the added diagnostic value of combining DENV NS1 antigen and anti-DENV IgM detection for confirming acute infections, and [ii] the evaluation of the Anti-DENV NS1 ELISA 2.0 (IgG), a novel assay with a dual cut-off designed to optimize serological interpretation in flavivirus-endemic and non-endemic regions.
Methods
Ethics statement
The study was conducted in accordance with the Declaration of Helsinki in its current version. The DENV samples originated from a previously published study [44], which was approved by the Institutional Review Board of Vietnam Military Medical University (VMMU), Hanoi, Vietnam (Nr. 103MCH/RES/DENV-GER_V-D1-2016) and the 108 Hospital (Nr. 108MCH/RES/DENV_D1-08-05-2018-SDL); written informed consent was obtained from all recruited dengue patients [44]. The ZIKV samples were collected under IRB Protocol No. 6874, which underwent review by the CDC IRB and was deemed exempt. For child participants in this ZIKV cohort, written informed consent was obtained from a parent or legal guardian prior to enrollment. In addition, assent was obtained from children when appropriate according to age and local regulations; verbal assent was obtained from younger children, and written assent from older minors. The CHIKV samples, provided by Cerba Xpert (Frépillon, France), were fully anonymized leftovers from clinical laboratories; therefore consent was not necessary. According to Cerba Xpert’s ethical and regulatory framework, patients may opt out of having their data and samples used for purposes other than their personal care; for child participants, a parent or legal guardian may exercise the opt‑out option. The provision of additional biospecimens from commercial suppliers was also in compliance with the relevant ethical and legal standards. All samples in this study were pseudonymized or anonymized at the participating sites following local institutional guidelines and transferred under coded or anonymized identifiers only. The pseudonymization key remained exclusively at the originating institutions and was never disclosed, ensuring that it is not possible to re-identify the samples and that all material is therefore transferred in an effectively anonymized manner.
Patients and samples
Demographic and clinical characteristics of the study cohorts are presented in Table 1. All samples were stored frozen at −20°C until serological testing.
Plasma samples were collected from 22 hospitalized Vietnamese patients with mild to moderate dengue fever during a seasonal DENV outbreak in Hanoi, Vietnam, in 2017 [44]. Clinical and laboratory diagnosis followed the revised dengue case definitions issued by the World Health Organization (WHO) in 2009 [30]. Samples were provided by SeraDiaLogistics (Munich, Germany).
Dengue panel.
Three sequential plasma samples were obtained from each patient, yielding 66 samples; 63 of which were available in sufficient quantity for serological testing. The first sample was drawn on the day of hospital admission, within 6 days after reported onset of fever (sample group t1: acute viremic phase). The second sample was collected 3 days after hospitalization (t2: early convalescent phase), and the third sample another 7–11 days later (t3: late convalescent phase; Table 1).
All t1 samples were tested by RT-PCR at SeraDiaLogistics using the LightMix Modular Dengue Virus and LightMix Modular Dengue Typing kits (TIB Molbiol, Berlin, Germany; distributed by Roche Diagnostics, Basel, Switzerland), confirming DENV infection in all patients (22/22, 100%). The infecting serotype was DENV-1 in 15/22 (68.2%), DENV-2 6/22 (27.3%), and a DENV-1/DENV-2 co-infection in 1/22 (4.5%) cases. Patients were not classified according to primary or secondary DENV infection status, as the ELISAs applied in this study are not intended to be used for this purpose and because relevant patient history was not available. Co-infections with ZIKV, CHIKV, YFV, or Plasmodium spp. were excluded by negative PCR results (Altona Diagnostics, Hamburg, Germany) at t1. Prior ZIKV infection was ruled out in 21/22 cases, based on negative Anti-ZIKV ELISA (IgG, IgM; Euroimmun) reactivity at t1.
Healthy control panel.
The study included 500 plasma samples from healthy blood donors (HBD) aged 18–69 years, residing in Northern Germany, where DENV and most other flaviviruses are not endemic [8]. Samples were collected at the University Medical Center Schleswig-Holstein (Lübeck, Germany) and were neither subjected to molecular testing for arboviral infections nor selected based on any predefined criteria.
WNV panel.
Forty plasma samples were obtained from U.S. patients with acute WNV infection (Plasma Services Group, Moorestown, NJ, USA). Acute infection was confirmed by PCR (UltraQual West Nile Virus RT-PCR; National Genetics Institute, Los Angeles, CA, USA) and by anti-WNV IgM positivity; anti-WNV IgG reactivity was additionally determined (West Nile Virus IgM Capture Dx Select ELISA, West Nile Virus IgG Dx Select ELISA; Focus Diagnostics, Cypress, CA, USA).
ZIKV panel.
Forty serum samples were collected from healthy Puerto Rican children aged 9–16 years during serosurveys after the ZIKV epidemic in 2015–2017 [45]. Samples were provided by the Centers for Disease Control and Prevention (CDC) Dengue Branch (San Juan, Puerto Rico, USA). All ZIKV cases were classified using the ZIKV EDIII IgG ELISA and FRNT50 as previously described [42]. All samples showed high ZIKV-neutralizing antibody titers (FRNT50 > 80) and no neutralizing activity against the four DENV serotypes. Sampling was performed well after ZIKV infection, as indicated by anti-ZIKV IgM negativity and IgG positivity.
CHIKV panel.
Fifty serum samples were obtained from CHIKV-infected patients, including 40 residents of the French Overseas Territories (FOTs) and 10 from mainland France. Samples were collected during the 2014–2015 CHIKV outbreak [46] and provided by Cerba Xpert (Frépillon, France). In-house ELISAs (Cerba Xpert) detected anti-CHIKV IgM and IgG in 47/50 and 50/50 samples, respectively, confirmed by a CHIKV plaque reduction neutralization test (PRNT) at the University of Padova, Italy.
ELISAs
Samples were tested using ELISA kits from Euroimmun, following the manufacturer’s instructions: [i] Dengue Virus NS1 ELISA, [ii] Anti-Dengue Virus Type 1–4 ELISA (IgM), [iii] Anti-Dengue Virus Type 1–4 ELISA (IgG), and [iv] Anti-Dengue Virus NS1 ELISA 2.0 (IgG). Assay characteristics and recommendations for result interpretation are given in S1 Table. Each test run included kit-provided calibrators and controls. ELISA testing was performed by laboratory personnel blinded to PCR results and infection status. Optical density (OD) values were automatically recorded and converted into final results.
IgM reactivity was assessed semiquantitatively by calculating the ratio of the sample OD to the calibrator OD. NS1 and IgG levels were determined quantitatively in relative units per milliliter (RU/mL) using calibration curves. Samples with results outside the measurement range were not routinely retested. Instead, results were set to the respective lower or upper limit and displayed accordingly in all analyses and plots: DENV NS1 ELISA results >100 RU/mL were set to 100 RU/mL, Anti-DENV Type 1–4 ELISA (IgG) <2 RU/mL to 2 RU/mL and >200 RU/mL to 200 RU/mL, and Anti-DENV NS1 ELISA 2.0 (IgG) <1 RU/mL to 1 RU/mL and >80 RU/mL to 80 RU/mL.
For the Anti-DENV NS1 ELISA 2.0 (IgG), an alternative cut-off of 20 RU/mL (instead of the standard cut-off 10 RU/mL) may be applied for testing in flavivirus-endemic regions.
Statistics
Statistical analyses and graph generation were performed using GraphPad Prism version 10.3.1 (GraphPad Software; Inc., San Diego, CA, USA) and SigmaPlot version 13.0 (Systat Software Inc., San Jose, CA, USA). Sensitivity was calculated as the proportion of positive results among samples from PCR-confirmed dengue patients. Specificity was calculated as the proportion of negative results among samples included in the specificity panel, which comprised specimens from German HBD and individuals with confirmed non-dengue infections. Borderline results were considered negative for diagnostic accuracy analysis to avoid overestimation of sensitivity.
Confidence intervals (95% CI) were calculated using the Clopper-Pearson method. Overall differences across time points were assessed with the Friedman test. If significant, post-hoc pairwise comparisons were performed using paired t-tests or Wilcoxon signed-rank tests, depending on the normality of paired differences (Shapiro-Wilk test). Resulting p-values were adjusted for multiple comparisons using the Bonferroni method. p-values <0.05 were considered statistically significant.
Results
Sensitivity of NS1, IgM, and IgG ELISAs in acute and convalescent stages
Sensitivities of the Euroimmun ELISAs for DENV NS1, anti-DENV IgM, and anti-DENV IgG were determined using DENV RT-PCR as the reference standard, based on qualitative results obtained at three defined sampling time points (t1-t3, Table 2).
At t1 (1–6 dpo), the DENV NS1 ELISA demonstrated the highest sensitivity (90.5%, 19/21), consistent with the presence of circulating NS1 antigen during early infection. Sensitivity decreased to 70.0% (14/20) at t2 (4–9 dpo) and dropped to 0% at t3 (13–19 dpo), reflecting the transient nature of NS1 antigenemia [47].
The Anti-DENV Type 1–4 ELISA (IgM) showed a sensitivity of 33.3% (7/21) at t1, increasing to 85.0% 17/20) at t2, before slightly declining to 77.3% (17/22) at t3. This pattern reflects typical kinetics of IgM seroconversion following acute DENV infection.
Both IgG ELISAs exhibited an upwards trend in positivity rates across all three time points. The Anti-DENV Type 1–4 ELISA (IgG), which uses a native antigen (highly purified virus particles) and recombinant envelope glycoprotein E (gE) as substrate, achieved a sensitivity of 66.7% (14/21) at t1 and reached 100% (20/20) by t2, maintaining this level at t3. The rapid attainment of full sensitivity suggests robust detection performance, likely attributable to the assay’s broad antigenic coverage.
In contrast, the Anti-DENV NS1 ELISA 2.0 (IgG) showed a slower increase in positivity rates. Using the standard (10 RU/mL) versus alternative (20 RU/mL) cut-off, sensitivity amounted to 33.3% (7/21) versus 19.1% (4/21) at t1, and 65.0% (13/20) versus 50.0% (10/20) at t2, respectively, reaching 100% (22/22) only at t3.
Kinetics of NS1, IgM and IgG
Temporal dynamics of DENV markers (NS1, IgM, and IgG) were assessed across t1, t2, and t3 based on quantitative ELISA results, revealing distinct distributions over time (Fig 1). NS1 and IgG showed an inverse kinetic pattern from acute infection to convalescence. NS1 levels were highest at t1 and declined progressively at t2 and t3. This trend was reflected by a decreasing median and a narrowing interquartile range (IQR) between t2 and t3, indicating a uniform clearance of circulating antigen during the transition from acute to convalescent stages across the cohort.
Samples were collected from 22 dengue patients at time points t1 (1-6 days post onset, dpo), t2 (4-9 dpo) and t3 (13-19 dpo). Boxes indicate interquartile ranges (outer bounds) and medians (bold red lines). Whiskers present the 90th and 10th percentiles. In each graph, the dashed line shows the assay-specific cut-off, the adjacent shaded area indicates the borderline range, and the solid horizontal line marking the upper limit of the borderline range represents the positivity threshold. For the Anti-DENV NS1 ELISA 2.0 (IgG), an alternative cut-off value (20 RU/mL, purple) may be applied for samples from flavivirus-endemic areas, instead of the standard cut-off (10 RU/mL, gray).
In contrast, IgG levels increased over time in both IgG ELISAs, with rising median values and narrowing IQRs, particularly in the Anti-DENV Type 1–4 ELISA (IgG). The Anti-DENV NS1 ELISA 2.0 (IgG) exhibited delayed detection dynamics with lower median values at t1 and t2, and a broader IQR at t2, reflecting heterogeneous IgG responses among patients. At t3, however, IgG reactivity measured with this assay was uniformly high, as indicated by a narrow IQR and a high median value at the upper detection limit (80 RU/mL). This pattern suggests that by t3, most patients had mounted a strong IgG response detectable even with the assay’s selective antigen design. The delay is likely due to the later onset of anti-NS1 IgG production compared to IgG responses against whole-virus antigens.
IgM levels peaked at t2, with a broader IQR suggesting inter-individual variability in seroconversion timing. At t3, IgM responses showed a slight decline or plateau.
These descriptive trends were further supported by statistical analysis (Fig 2). NS1 levels declined significantly over time, with pairwise comparisons showing increasing statistical strength: t1 vs. t2 (p = 0.023), t2 vs. t3 (p = 1.5 × 10 ⁻ ⁴), and t1 vs. t3 (p = 2.9 × 10 ⁻ ⁶). IgG reactivity increased significantly over time in both ELISAs. For the Anti-DENV Type 1–4 ELISA (IgG), significant differences were observed between t1 and t2 (p = 6.9 × 10 ⁻ ⁵), t2 and t3 (p = 0.047), and t1 and t3 (p = 5.7 × 10 ⁻ ⁶). The Anti-DENV NS1 ELISA 2.0 (IgG) showed similar trends: t1 vs. t2 (p = 4.6 × 10 ⁻ ⁵), t2 vs. t3 (p = 0.0015), and t1 vs. t3 (p = 1.1 × 10 ⁻ ⁵). Notably, the inverse kinetic relationship between NS1 and IgG was more evident in measurements with the anti-NS1 IgG ELISA. IgM changes were less pronounced and did not reach statistical significance (t1 vs. t2: p = 0.072; t2 vs. t3: p = 0.236; t1 vs. t3: p = 0.076).
For three patients, samples were available in sufficient quantity only from two time points. p-values were calculated for pairwise comparisons using the paired t-test if differences between paired values were normally distributed (Shapiro-Wilk test); otherwise, the Wilcoxon signed-rank test was performed. A Bonferroni correction was applied to adjust for multiple comparisons (n = 3). Statistical significance was defined as p < 0.05 after Bonferroni adjustment. Asterisks denote significance levels: ns, not significant; * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. For details on graphical elements (dashed lines, shaded areas, and thresholds), see Fig 1.
Chronological sorting of all 63 samples by dpo revealed that NS1 antigen remained detectable up to day 9. The Anti-DENV Type 1–4 ELISA (IgG) reached a positivity rate of 100% from day 7 onwards, with all subsequent samples testing positive. In contrast, the Anti-DENV NS1 ELISA 2.0 (IgG) did not achieve full sensitivity until day 13 after symptom onset (S2 Table). These results illustrate the relatively prolonged detectability of NS1 antigen, extending beyond the typical viremic period. In addition, they reflect distinct temporal windows of effective antibody detection for the two IgG ELISAs.
Seromarker kinetics across grouped dpo intervals and individual longitudinal profiles of all 22 patients are presented in S1 and S2 Figs, respectively. These data further illustrate the temporal patterns of marker levels and the variability in individual serological responses. Patient #7 showed atypical longitudinal courses (S2 Fig) with high IgG levels at t1 (3 dpo) and early IgM decline in the absence of NS1 antigen, possibly indicating a secondary infection or a longer interval between symptom onset and initial sampling than recorded.
ELISA performance on single acute-phase samples: added value of combined NS1 and IgM testing
Acute-phase (t1) samples were available from 21 patients with PCR-confirmed DENV infection. The Euroimmun DENV NS1 ELISA yielded positive results in 19/21 (90.5%) samples. IgM reactivity, assessed using the Euroimmun Anti-DENV Type 1–4 ELISA (IgM), was negative or borderline in 14/21 (66.7%) samples, all of which were NS1 positive. IgM positivity was detected in 7/21 (33.3%) samples. Notably, two of these IgM-positive samples (collected at 3 and 6 dpo) were the only NS1-negative cases. Both tested positive for anti-DENV IgG using the Euroimmun Anti-DENV Type 1–4 ELISA (IgG) as well as the Anti-DENV NS1 ELISA 2.0 (IgG), regardless of whether standard or alternative cut-offs were applied. By combining NS1 and IgM ELISAs, the sensitivity gaps observed with the individual assays were fully compensated, resulting in a combined detection rate of 100% (21/21; Table 3). Although all RT-PCR-positive cases were detected in this cohort, the small sample size provides only limited statistical robustness; therefore, these results should be interpreted with caution and cannot be directly generalized to broader populations.
Paired-sample assessment of IgM/IgG seroconversion and IgG increase
To assess ELISA performance in identifying recent DENV infections using paired samples, we analyzed: [i] anti-DENV IgM/IgG seroconversion (defined as a change from an IgM-negative acute sample to an IgM-positive early or late convalescent sample and/or from an IgG-negative acute sample to an IgG-positive early or late convalescent sample); and [ii] ≥4-fold increases in IgG levels between the acute sample and at least one of the convalescent samples. These criteria are widely recognized indicators of recent infection [30] and are commonly applied in epidemiological studies and retrospective case confirmation, especially when molecular or antigen detection methods are unavailable, inconclusive, or performed outside the optimal diagnostic window.
IgM seroconversion between t1 and t2 and/or between t1 and t3 was observed in 13/21 (61.9%) dengue patients. Among the 8 patients without detectable IgM seroconversion, 7 tested IgM-positive already in the acute phase (t1), while 1 patient remained IgM-negative or -borderline throughout the sampling period as could occur in a secondary flavivirus infection (Table 4).
IgG seroconversion and/or a ≥ 4-fold increase was detected in 7/21 (33.3%) patients using the Anti-DENV Type 1–4 ELISA (IgG), including 6 cases with concomitant IgM seroconversion. For 4 patients (#1, #7, #19 and #22), IgG concentrations in the Anti-DENV NS1 ELISA 2.0 (IgG) exceeded the assay’s upper limit of quantification (80 RU/mL), which prevented assessment of ≥4-fold increases based on the initial measurements (see S2 Fig for original non-titrated IgG values). To overcome this limitation, the samples of these patients were titrated using the Anti‑DENV NS1 ELISA 2.0 (IgG), allowing accurate quantification of IgG levels. When applying the titrated measurements, IgG seroconversion and/or ≥4‑fold increases were observed in 21/21 (100%) patients, of whom 13 also had concomitant IgM seroconversion (Table 4).
Combining IgM and IgG results from paired specimens allowed confirmation of recent DENV infection in 14/21 (66.7%) of patients including the results of the Anti-DENV Type 1–4 ELISA (IgG). This rate increased to 21/21 (100%) when IgG was assessed using the Anti-DENV NS1 ELISA 2.0 (IgG).
Specificity of anti-DENV IgG ELISAs
The specificity of the IgG ELISAs was determined using samples from HBD from a flavivirus non-endemic country, and from patients with confirmed exposure to WNV and ZIKV. The ZIKV panel comprised pediatric samples in which the absence of DENV-specific neutralizing antibodies was confirmed by NT, the recognized gold standard for serological specificity in flavivirus diagnostics. The use of this ZIKV panel therefore provides a stringent approach to assessing assay cross-reactivity, which is a major challenge in flavivirus serology due to high antigenic similarity between ZIKV and DENV.
The Anti-DENV Type 1–4 ELISA (IgG) had an overall specificity of 85.7% (497/580) (Table 5). Among HBD, 95.0% (475/500) specificity was observed, indicating detectable background reactivity even in non-endemic populations. Specificity was low to moderate in the ZIKV (5.0%, 2/40) and WNV (50.0%, 20/40) panels, with positive samples frequently showing high IgG reactivity (Fig 3, Table 5).
For details on graphical elements (dashed lines, shaded areas, and thresholds), see Fig 1.
In contrast, the Anti-DENV NS1 2.0 ELISA (IgG) demonstrated higher specificity. Using the standard cut-off, overall specificity amounted to 95.7% (555/580), with 98.2% (491/500) in HBD and 95.0% (38/40) in WNV samples. Specificity in the ZIKV panel remained moderate at 65.0% (26/40), with several patients showing low or borderline IgG levels. Applying the alternative cut-off further increased overall specificity to 99.5% (577/580), with only 3 positive samples among 580 tested, reaching 99.8% (499/500) specificity in HBD and 97.5% (39/40) in both WNV and ZIKV panels (Table 5).
Compared to the Anti-DENV Type 1–4 ELISA (IgG), the Anti-DENV NS1 2.0 ELISA (IgG) showed a tighter accumulation of IgG values below the positivity threshold, particularly with the alternative cut-off. The use of this assay effectively reduced background reactivity in non-endemic samples and minimized cross-reactivity in flavivirus-exposed individuals, thereby enhancing specificity (Fig 3).
Anti-DENV IgG testing in regions with and without co-endemicity of DENV and CHIKV
To assess anti-DENV IgG positivity in settings with different flavivirus endemicities and to address the challenges in interpreting anti-DENV IgG reactivity in the absence of clinical records or flavivirus-specific reference testing, we analyzed samples from 50 patients with NT-confirmed CHIKV infection. Of these, 40 resided in the FOTs, where DENV, CHIKV, and ZIKV co-circulate [8], leading to a strong background of DENV exposure. The remaining 10 patients were from mainland France, characterized by sporadic autochthonous transmission of DENV and CHIKV [48].
Among FOT patients, 90.0% (36/40) tested positive using the Anti-DENV Type 1–4 ELISA (IgG). The Anti-DENV NS1 ELISA 2.0 (IgG) yielded positivity rates of 87.5% (35/40) and 85.0% (34/40) with standard and alternative cut-offs, respectively (Table 6). Median IgG levels among positive samples were high: 174 RU/mL (range: 38–197) for the Anti-DENV Type 1–4 ELISA (IgG), and >80 RU/mL (range: 23 to >80) for the Anti-DENV NS1 ELISA 2.0 (IgG) (Fig 4). The minimal reduction in positivity when applying the higher cut-off, along with consistently high antibody levels, suggests that most IgG signals represent true anti-DENV reactivity rather than cross-reactivity.
For details on graphical elements (dashed lines, shaded areas, and thresholds), see Fig 1.
In contrast, patients from mainland France showed lower positivity rates: 30.0% (3/10) with the Anti-DENV Type 1–4 ELISA (IgG) and 40.0% (4/10) with the Anti-DENV NS1 ELISA 2.0 (IgG) using the standard cut-off (Table 6). Median IgG reactivity was also reduced among positive samples: 93 RU/mL (range: 27–137) for the Anti-DENV Type 1–4 ELISA (IgG) and 16 RU/mL (range: 14–20) for the Anti-DENV NS1 ELISA 2.0 (IgG) (Fig 4). However, these findings should be interpreted with caution, as individual histories of prior flavivirus exposure were not available and could not be systematically assessed.
Discussion
In this study, we analyzed the accuracy of Euroimmun ELISAs for DENV serodiagnostics during acute and convalescent phases of infection, using three sequential samples from patients with mild or moderate dengue fever. Assays targeting NS1, IgM and IgG were assessed individually or combined in algorithms for single and paired samples, with RT-PCR as reference.
Overall, the Euroimmun ELISAs reflected the expected kinetics of DENV antigen clearance and antibody development [13,47,49,50]. NS1 antigen was most prominent during the early acute phase; IgM overlapped with and extended beyond the diagnostic window of NS1, peaking during early convalescence; IgG levels rose steadily, providing robust late-stage sensitivity.
Characteristics of ELISAs across infection stages and the impact of a dual cut-off strategy in NS1-based IgG detection
The Euroimmun DENV NS1 ELISA showed the highest positivity rate (90.5%) in acute-phase samples (1–6 dpo), consistent with previous reports about this assay (98.7-100%) [51,52] and meta-analyses (0–4 dpo: 90%, 1–7 dpo: 86%) [53]. IgM positivity measured with the Euroimmun Anti-DENV Type 1–4 ELISA (IgM) increased from 33.3% (1–6 dpo) to 85.0% (4–9 dpo), aligning with reported sensitivity ranges for this ELISA (38.1% to 98.8-100%) [51,54] and meta-analytic data (0–4 dpo: 17%, 1–7 dpo: 71%, 5–14 dpo: 82%) [53].
Specificity of the NS1 and IgM ELISAs was not addressed in this study but can be inferred from previous evaluations. Specificity values of 94.3-100% have been reported for the NS1 ELISA [51,52,55] with meta-analytic estimates of 90–93% [53]. For the IgM ELISA, specificity values amount to 91.4-100% [51,54,55] and meta-analytic estimates range from 82% to 91% [53].
IgG sensitivity reached 100% in early (4–9 dpo) and late convalescence (13–19 dpo) using the Euroimmun Anti-DENV Type 1–4 ELISA (IgG), matching previously reported detection rates for this assay (94.3%-100%) and other commercial ELISAs [51,56]. This assay demonstrated rapid seroconversion, reaching 100% positivity from day 7 onwards. Its native antigen/gE-based antigen enables broad epitope recognition, facilitating early detection of low-level IgG responses. This makes it a valuable tool for assessing exposure in suspected cases where direct pathogen detection is not feasible and paired samples can be obtained. Due to its high sensitivity and early IgG detectability, it may also support the diagnosis of secondary infections, especially in non-endemic regions. However, the broad antigenic coverage and the presence of conserved epitopes limits specificity in differential diagnostics, as it increases the likelihood of cross-reactivity with antibodies from prior flavivirus exposure or vaccination. The ELISA was 95.0% specific among German HBD, but showed substantial cross-reactivity in WNV-infected (50.0%), ZIKV-infected (95.0%) (this study), and TBEV-vaccinated individuals (32.0%) [57].
The Anti-DENV NS1 ELISA 2.0 (IgG) displayed delayed detection dynamics, reaching 100% IgG positivity only from day 13 onwards, reflecting the later onset of anti-NS1 IgG production compared to IgG responses against other antigens. Hence, this ELISA is not suitable for acute-phase diagnosis in individual suspected cases. However, its narrower antigenic focus enhances specificity, and the use of an alternative cut-off (20 RU/mL) additionally confines detection to robust IgG responses. This is highly relevant in flavivirus-endemic regions, helping to avoid false-positive results caused by low-level antibodies from past exposures with non-DENV flaviviruses. Overall specificity increased from 95.7% to 99.5% when applying the alternative cut-off, with gains in German HBD (1.6%), WNV-infected (2.5%), and ZIKV-infected patients (32.5%). In the HBD cohort, prior exposure to flaviviruses circulating to a small extent in Germany (e.g., WNV) or travel-associated arboviral infections cannot be ruled out and may have contributed to some positive results. By specifically confirming DENV infections in complex serological backgrounds, the NS1-based IgG ELISA improves differential diagnostics, facilitates serological surveillance, and may support epidemiological studies in regions with co-circulating flaviviruses. While the improved specificity is well demonstrated in this study, broader validation in diverse endemic settings is required.
Potential use in pre-vaccination screening
Determining dengue serostatus is required before administering the Dengvaxia vaccine to prevent antibody-dependent enhancement and severe dengue in seronegative individuals after vaccination. CDC guidelines specify that IgG tests for pre-vaccination screening must achieve ≥75% sensitivity and ≥98% specificity to reliably confirm prior DENV infection. Previously, only a two-test algorithm fulfilled these criteria [42,58]. In the present study, the Anti-DENV NS1 ELISA 2.0 (IgG) achieved 100% sensitivity and 99.5% specificity with the alternative cut-off, meeting CDC requirements as a standalone assay. However, as this study does not directly assess screening performance or predictive values in asymptomatic populations, conclusions regarding its use in pre-vaccination screening remain preliminary.
The Anti-DENV NS1 ELISA 2.0 (IgG) is not validated for this purpose, but given its high specificity in convalescent samples, it could be further investigated in studies aimed at determining the serostatus prior to dengue vaccination [59,60].
Combined NS1 and IgM serology in acute dengue: cumulative diagnostic effect
The distinct temporal profiles of NS1, IgM and IgG responses highlight the diagnostic value of combining ELISAs for accurate diagnostics throughout all stages of DENV infection. In our study, analysis of single acute-phase samples demonstrated that combining NS1 and IgM testing achieved 100% sensitivity, matching the results of RT-PCR. This supports the use of combined ELISA testing as a practical diagnostic approach, although similar detection rates in this limited cohort do not imply clinical equivalence to RT-PCR. It is also important to note, that IgM positivity in a single acute-phase sample (as observed in two cases) should be interpreted with caution. While suggestive of recent DENV exposure, it is not confirmatory and requires additional testing, such as RT-PCR or IgG serology in sample pairs [19]. Previous studies have also substantiated the diagnostic advantage of combined NS1 and IgM testing during early DENV infection (≤10 dpo) [61–65]. Incorporating IgM into the diagnostic algorithm not only extends the diagnostic window but is especially important in secondary infections, where rapid antibody responses may mask or clear circulating NS1 antigen, often already within the first few days post onset due to prompt IgG production [26,27]. The formation of immune complexes was also reflected in our measurements, showing an inverse kinetic pattern of decreasing NS1 antigen and increasing anti-NS1 IgG. NS1 was undetectable beyond t2, consistent with its reported clearance by day 14 post-onset in primary dengue [47].
Retrospective confirmation of DENV infection using paired-sample serology
Our evaluation of seroconversion and IgG dynamics in paired specimens demonstrates the ELISAs’ ability to confirm recent DENV infections, particularly when molecular or antigen detection methods are unavailable or inconclusive. IgM seroconversion was observed in 61.9% of patients. However, its diagnostic value was limited in cases with pre-existing IgM positivity in acute-phase samples (7/21), potentially due to advanced sampling days or secondary infections.
In this paired-sample approach, the Anti-DENV NS1 ELISA 2.0 (IgG) outperformed the Anti-DENV Type 1–4 ELISA (IgG), detecting IgG seroconversion and/or a ≥ 4-fold increase in 100% vs. 33.3% of patients, respectively. The lower seroconversion rate determined with the Type 1–4 ELISA can largely be attributed to the high proportion of samples already IgG-positive at the first time point (t1), which precluded documentation of seroconversion in these individuals. The Type 1–4 ELISA, based on broadly reactive native antigens/gE, may yield high IgG levels in the acute phase due to cross-reactivity, limiting its suitability for paired-sample analyses. In contrast, the Anti-DENV NS1 ELISA 2.0 (IgG) more accurately reflects IgG dynamics by specifically targeting anti-NS1 antibodies, which typically rise during the convalescent phase. Notably, the NS1-based ELISA captured more cases without IgM seroconversion than the Type 1–4 ELISA, indicating superior performance in identifying recent infections during later stages.
Overall, combining IgM and IgG results from seroconversion and 4-fold-increase analyses in paired samples confirmed recent DENV infection in 100% of cases when using the Anti-DENV NS1 ELISA 2.0 (IgG). Two patients (#7 and #19) may represent secondary infections, given their negative NS1 results and high anti-NS1 IgG levels at t1 [50]. Early detection of IgG (<6 dpo) is typically associated with prior flavivirus exposure. Moreover, NS1 antigen sensitivity is reduced in secondary infections due to rapid immune complex formation and subsequent early clearance of circulating NS1, as discussed above. These analytically true-negative NS1 results may therefore be clinically misleading if NS1 is used as the sole diagnostic marker [26]. These findings support the use of the Euroimmun ELISAs for serological follow-up, highlighting the Anti-DENV NS1 ELISA 2.0 (IgG) as a robust tool for retrospective diagnostics and surveillance. Although ELISAs are not routinely used at the point of care in resource-limited settings, they are applied in centralized laboratories to complement rapid tests, particularly when higher diagnostic accuracy is required for surveillance, confirmation, or research purposes.
Interpretation of anti-DENV IgG serology in co-endemic and non-endemic settings
Our findings highlight the necessity of interpreting anti-DENV IgG serology within the regional epidemiological context, given the differing flavivirus endemicity across settings. In the FOTs, characterized by co-circulation of DENV, CHIKV, and ZIKV [8], the high IgG positivity rates observed with both IgG ELISAs align with the known high seroprevalence of DENV in these regions [8,66]. The only slight decrease in positivity with the more stringent alternative cut-off using the Anti-DENV NS1 ELISA 2.0 (IgG), alongside consistently elevated antibody levels, suggest that the detected reactivity predominantly reflects true DENV exposure rather than non-specific cross-reactivity. Nevertheless, cross-reactivity with co-circulating flaviviruses or previous vaccination cannot be entirely excluded and remains a limitation when interpreting serological results in these regions.
Conversely, patients from mainland France, where flavivirus transmission is sporadic and rare [48], showed markedly lower IgG reactivity, with higher positivity in the Anti‑DENV NS1 ELISA 2.0 (IgG) than in the Anti-DENV Type 1–4 ELISA (IgG) (40% vs. 30%). Given the very small sample size (n = 10), and overlapping confidence intervals, this difference is likely attributable to sampling variability rather than a true performance difference.
These preliminary findings support the use of the Anti-DENV NS1 ELISA 2.0 (IgG) in diverse epidemiological contexts and the importance of cut-off adaptation where needed. Moreover, they highlight the risk of misclassification when serological findings are interpreted without clinical and epidemiological data, especially in areas with overlapping flavivirus circulation.
Limitations
This study has several limitations. First, the relatively small number of patients with DENV, WNV, or ZIKV infection limits the statistical power of diagnostic accuracy estimates and restricts the generalizability of the findings. Second, dengue patients were exclusively recruited from Vietnam, and specificity cohorts originated from a limited number of settings, thereby restricting the geographical and epidemiological diversity of the study population. As only infections with DENV-1 and DENV-2, the predominant serotypes in Vietnam, were included, the results may not fully generalize to other serotypes. Third, the absence of classification into primary and secondary DENV infections limits the interpretation of NS1 antigenemia and antibody kinetics, as known differences between these infection types could not be systematically assessed. Fourth, although the blood donor panel originated from a non-endemic region (Northern Germany), prior flavivirus exposure could not be definitely excluded as vaccination and travel histories were unavailable. Fifth, the specificity of the NS1 and IgM ELISAs were not evaluated experimentally within the scope of this study due to resource constraints; instead, relevant data from previous publications were referenced. Sixth, longitudinal analyses were restricted by capping IgG values exceeding the assay’s upper limit of quantification, as systematic dilution testing for all such samples was outside the methodological scope of the study; nevertheless, overall kinetic trends remained clearly discernible. Finally, other commercial assays (ELISAs, rapid diagnostic tests etc.) were not included, limiting direct comparison of performance data. As this was a preliminary study, comprehensive multicenter studies based on larger and more diverse cohorts from different endemic settings, including all DENV serotypes and various detection methods, are warranted to further validate and extend our findings.
Conclusion
The Euroimmun ELISAs provide a flexible and standardized framework for customized diagnostic strategies applicable to diverse clinical and epidemiological settings. By measuring serological markers with complementary diagnostic windows, these assays offer high diagnostic accuracy throughout all stages of DENV infection. In the acute phase, the combined use of NS1 antigen and IgM ELISAs detected all RT-PCR-positive dengue cases from single specimens, suggesting potential use in early diagnostics for laboratories without access to molecular diagnostics. The native antigen/gE-based IgG ELISA allows for early and sensitive IgG detection, though its specificity is limited. The new anti-DENV NS1 ELISA 2.0 (IgG), with its enhanced specificity and optional alternative cut-off, enables reliable differentiation of DENV-specific IgG from cross-reactive antibodies in regions where multiple flaviviruses co-circulate. This improved specificity is particularly relevant for epidemiological surveillance and serostatus determination. By specifically measuring the anti-NS1 IgG response, this assay captures DENV-specific IgG dynamics more accurately, which could provide an advantage in the use for convalescent-phase diagnostics. However, these findings should be regarded as preliminary and restricted to the studied settings and therefore require validation in larger multicenter studies involving more diverse cohorts from different endemic regions.
Supporting information
S1 Fig. Temporal dynamics of DENV NS1, anti-DENV IgM and anti-DENV IgG in 63 samples from dengue patients, grouped in days post onset (dpo).
Samples were grouped into dpo intervals; the number of samples per interval is given in brackets below each group. No samples were available between 10 and 12 dpo. Data points represent mean values, and shaded areas around the lines represent standard deviation. Lines connecting data points are shown for visualization purposes and represent an assumed time course, not continuous measurements. For details on graphical elements (dashed lines, shaded areas, and thresholds), see Fig 1.
https://doi.org/10.1371/journal.pntd.0014295.s001
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S2 Fig. Individual time courses of DENV NS1, anti-DENV IgM and anti-DENV IgG levels in 22 dengue patients.
Samples were collected at three distinct time points, except for patients #3, #4, and #11, for whom samples from only two time points were available in sufficient quantity for serological testing in this study. For IgG kinetics, the plots focus on the Anti-DENV NS1 ELISA 2.0 (IgG), given the study’s context within a seasonal dengue outbreak in a flavivirus-endemic region (Vietnam). Lines connecting discrete data points are shown for visualization purposes and represent an assumed time course, not continuous measurements. For details on graphical elements (dashed lines, shaded areas, and thresholds), see Fig 1.
https://doi.org/10.1371/journal.pntd.0014295.s002
(PDF)
S1 Table. Characteristics of ELISAs used in this study.
https://doi.org/10.1371/journal.pntd.0014295.s003
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S2 Table. Qualitative ELISA results across three sampling time points (t1, t2, and t3) in 22 patients with PCR-confirmed DENV infection, sorted by days post onset (dpo).
https://doi.org/10.1371/journal.pntd.0014295.s004
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S1 Dataset. Anonymized dataset used for analysis.
https://doi.org/10.1371/journal.pntd.0014295.s005
(XLSX)
Acknowledgments
The authors thank Simon Lytton (SeraDiaLogistics, Munich, Germany) for providing dengue samples collected in Vietnam. Freddy A. Medina (CDC Dengue Branch, San Juan, Puerto Rico, USA) is acknowledged for sharing the ZIKV panel dataset and for his critical review of the corresponding scientific content. Both have agreed to be named in the acknowledgements section. The authors thank Euroimmun for supporting laboratory analyses in accordance with Good Publication Practice (GPP3) guidelines [67].
References
- 1. Madere FS, Andrade da Silva AV, Okeze E, Tilley E, Grinev A, Konduru K, et al. Flavivirus infections and diagnostic challenges for dengue, West Nile and Zika Viruses. npj Viruses. 2025;3(1).
- 2. Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and burden of dengue. Nature. 2013;496(7446):504–7. pmid:23563266
- 3. Brady OJ, Gething PW, Bhatt S, Messina JP, Brownstein JS, Hoen AG, et al. Refining the global spatial limits of dengue virus transmission by evidence-based consensus. PLoS Negl Trop Dis. 2012;6(8):e1760. pmid:22880140
- 4. Messina JP, Brady OJ, Golding N, Kraemer MUG, Wint GRW, Ray SE, et al. The current and future global distribution and population at risk of dengue. Nat Microbiol. 2019;4(9):1508–15. pmid:31182801
- 5. Liang Y, Dai X. The global incidence and trends of three common flavivirus infections (Dengue, yellow fever, and Zika) from 2011 to 2021. Front Microbiol. 2024;15:1458166.
- 6. Zhang W-X, Zhao T-Y, Wang C-C, He Y, Lu H-Z, Zhang H-T, et al. Assessing the global dengue burden: Incidence, mortality, and disability trends over three decades. PLoS Negl Trop Dis. 2025;19(3):e0012932. pmid:40072961
- 7. Lim A, Shearer FM, Sewalk K, Pigott DM, Clarke J, Ghouse A, et al. The overlapping global distribution of dengue, chikungunya, Zika and yellow fever. Nat Commun. 2025;16(1):3418. pmid:40210848
- 8. Pierson TC, Diamond MS. The continued threat of emerging flaviviruses. Nat Microbiol. 2020;5(6):796–812. pmid:32367055
- 9. Kraemer MUG, Sinka ME, Duda KA, Mylne AQN, Shearer FM, Barker CM, et al. The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus. Elife. 2015;4:e08347. pmid:26126267
- 10. Kawasaki E. Anti-Islet Autoantibodies in Type 1 Diabetes. Int J Mol Sci. 2023;24(12):10012. pmid:37373160
- 11. Nakajima H, Nakamura Y, Inaba Y, Tsutsumi C, Unoda K, Hosokawa T, et al. Neurologic disorders associated with anti-glutamic acid decarboxylase antibodies: A comparison of anti-GAD antibody titers and time-dependent changes between neurologic disease and type I diabetes mellitus. J Neuroimmunol. 2018;317:84–9. pmid:29338930
- 12. Tejo AM, Hamasaki DT, Menezes LM, Ho Y-L. Severe dengue in the intensive care unit. J Intensive Med. 2023;4(1):16–33. pmid:38263966
- 13. Muller DA, Depelsenaire ACI, Young PR. Clinical and Laboratory Diagnosis of Dengue Virus Infection. J Infect Dis. 2017;215(suppl_2):S89–95. pmid:28403441
- 14. Dhole P, Zaidi A, Nariya HK, Sinha S, Jinesh S, Srivastava S. Host Immune Response to Dengue Virus Infection: Friend or Foe?. Immuno. 2024;4(4):549–77.
- 15. Kulmala P, Savola K, Petersen JS, Vahasalo P, Karjalainen J, Lopponen T. Prediction of insulin-dependent diabetes mellitus in siblings of children with diabetes. A population-based study. J Clin Invest. 1998;101(2):327–36.
- 16. Bingley PJ, Bonifacio E, Williams AJ, Genovese S, Bottazzo GF, Gale EA. Prediction of IDDM in the general population: strategies based on combinations of autoantibody markers. Diabetes. 1997;46(11):1701–10. pmid:9356015
- 17. Maclaren N, Lan M, Coutant R, Schatz D, Silverstein J, Muir A, et al. Only multiple autoantibodies to islet cells (ICA), insulin, GAD65, IA-2 and IA-2beta predict immune-mediated (Type 1) diabetes in relatives. J Autoimmun. 1999;12(4):279–87. pmid:10330299
- 18. Mardekian SK, Roberts AL. Diagnostic Options and Challenges for Dengue and Chikungunya Viruses. Biomed Res Int. 2015;2015:834371. pmid:26509163
- 19. Saiz A, Blanco Y, Sabater L, González F, Bataller L, Casamitjana R, et al. Spectrum of neurological syndromes associated with glutamic acid decarboxylase antibodies: diagnostic clues for this association. Brain. 2008;131(Pt 10):2553–63. pmid:18687732
- 20. Snaith JR, Frampton R, Samocha-Bonet D, Greenfield JR. Tirzepatide in Adults With Type 1 Diabetes: A Phase 2 Randomized Placebo-Controlled Clinical Trial. Diabetes Care. 2026;49(1):161–70. pmid:41264593
- 21. Peeling RW, Artsob H, Pelegrino JL, Buchy P, Cardosa MJ, Devi S, et al. Evaluation of diagnostic tests: dengue. Nat Rev Microbiol. 2010;8(12 Suppl):S30-8. pmid:21548185
- 22. Huhtamo E, Hasu E, Uzcátegui NY, Erra E, Nikkari S, Kantele A, et al. Early diagnosis of dengue in travelers: comparison of a novel real-time RT-PCR, NS1 antigen detection and serology. J Clin Virol. 2010;47(1):49–53. pmid:19963435
- 23. Singh MP, Majumdar M, Singh G, Goyal K, Preet K, Sarwal A, et al. NS1 antigen as an early diagnostic marker in dengue: report from India. Diagn Microbiol Infect Dis. 2010;68(1):50–4. pmid:20727470
- 24. Alcon S, Talarmin A, Debruyne M, Falconar A, Deubel V, Flamand M. Enzyme-linked immunosorbent assay specific to Dengue virus type 1 nonstructural protein NS1 reveals circulation of the antigen in the blood during the acute phase of disease in patients experiencing primary or secondary infections. J Clin Microbiol. 2002;40(2):376–81. pmid:11825945
- 25. Zhang H, Li W, Wang J, Peng H, Che X, Chen X, et al. NS1-based tests with diagnostic utility for confirming dengue infection: a meta-analysis. Int J Infect Dis. 2014;26:57–66. pmid:24984164
- 26. Muller DA, Choo JJY, McElnea C, Duyen HTL, Wills B, Young PR. Kinetics of NS1 and anti-NS1 IgG following dengue infection reveals likely early formation of immune complexes in secondary infected patients. Sci Rep. 2025;15(1):6684. pmid:39994315
- 27. Premazzi Papa M, Mendoza-Torres E, Sun P, Encinales L, Goulet J, Defang G, et al. Dengue NS1 Antibodies Are Associated With Clearance of Viral Nonstructural Protein-1. J Infect Dis. 2024;230(6):e1226–34. pmid:38842497
- 28. Hermann LL, Thaisomboonsuk B, Poolpanichupatam Y, Jarman RG, Kalayanarooj S, Nisalak A, et al. Evaluation of a dengue NS1 antigen detection assay sensitivity and specificity for the diagnosis of acute dengue virus infection. PLoS Negl Trop Dis. 2014;8(10):e3193. pmid:25275493
- 29. Goncalves A, Peeling RW, Chu MC, Gubler DJ, de Silva AM, Harris E, et al. Innovative and New Approaches to Laboratory Diagnosis of Zika and Dengue: A Meeting Report. J Infect Dis. 2018;217(7):1060–8. pmid:29294035
- 30. Orban T, Sosenko JM, Cuthbertson D, Krischer JP, Skyler JS, Jackson R, et al. Pancreatic islet autoantibodies as predictors of type 1 diabetes in the Diabetes Prevention Trial-Type 1. Diabetes Care. 2009;32(12):2269–74. pmid:19741189
- 31. Gaspar-Castillo C, Rodríguez MH, Ortiz-Navarrete V, Alpuche-Aranda CM, Martinez-Barnetche J. Structural and immunological basis of cross-reactivity between dengue and Zika infections: Implications in serosurveillance in endemic regions. Front Microbiol. 2023;14:1107496. pmid:37007463
- 32. Endale A, Medhin G, Darfiro K, Kebede N, Legesse M. Magnitude of Antibody Cross-Reactivity in Medically Important Mosquito-Borne Flaviviruses: A Systematic Review. Infect Drug Resist. 2021;14:4291–9. pmid:34703255
- 33. Priyamvada L, Quicke KM, Hudson WH, Onlamoon N, Sewatanon J, Edupuganti S, et al. Human antibody responses after dengue virus infection are highly cross-reactive to Zika virus. Proc Natl Acad Sci U S A. 2016;113(28):7852–7. pmid:27354515
- 34. Wen J, Shresta S. Antigenic cross-reactivity between Zika and dengue viruses: is it time to develop a universal vaccine?. Curr Opin Immunol. 2019;59:1–8. pmid:30884384
- 35. Koraka P, Zeller H, Niedrig M, Osterhaus ADME, Groen J. Reactivity of serum samples from patients with a flavivirus infection measured by immunofluorescence assay and ELISA. Microbes Infect. 2002;4(12):1209–15. pmid:12467761
- 36. Allwin R, Doerr H, Emmerich P, Schmitz H, Preiser W. Cross-reactivity in flavivirus serology: new implications of an old finding?. Med Microbiol Immunol. 2002;190:199–202.
- 37. Cleton NB, Godeke G-J, Reimerink J, Beersma MF, Doorn HR van, Franco L, et al. Spot the difference-development of a syndrome based protein microarray for specific serological detection of multiple flavivirus infections in travelers. PLoS Negl Trop Dis. 2015;9(3):e0003580. pmid:25767876
- 38. Nascimento EJM, George JK, Velasco M, Bonaparte MI, Zheng L, DiazGranados CA, et al. Development of an anti-dengue NS1 IgG ELISA to evaluate exposure to dengue virus. J Virol Methods. 2018;257:48–57. pmid:29567514
- 39. Steinhagen K, Probst C, Radzimski C, Schmidt-Chanasit J, Emmerich P, van Esbroeck M, et al. Serodiagnosis of Zika virus (ZIKV) infections by a novel NS1-based ELISA devoid of cross-reactivity with dengue virus antibodies: a multicohort study of assay performance, 2015 to 2016. Euro Surveill. 2016;21(50):30426. pmid:28006649
- 40. L’Huillier AG, Hamid-Allie A, Kristjanson E, Papageorgiou L, Hung S, Wong CF, et al. Evaluation of Euroimmun Anti-Zika Virus IgM and IgG Enzyme-Linked Immunosorbent Assays for Zika Virus Serologic Testing. J Clin Microbiol. 2017;55(8):2462–71. pmid:28566316
- 41. Tyson J, Tsai W-Y, Tsai J-J, Mässgård L, Stramer SL, Lehrer AT, et al. A high-throughput and multiplex microsphere immunoassay based on non-structural protein 1 can discriminate three flavivirus infections. PLoS Negl Trop Dis. 2019;13(8):e0007649. pmid:31442225
- 42. Medina FA, Vila F, Adams LE, Cardona J, Carrion J, Lamirande E, et al. Comparison of the sensitivity and specificity of commercial anti-dengue virus IgG tests to identify persons eligible for dengue vaccination. J Clin Microbiol. 2024;62(10):e0059324. pmid:39194193
- 43. Mora-Cárdenas E, Aloise C, Faoro V, Knap Gašper N, Korva M, Caracciolo I, et al. Comparative specificity and sensitivity of NS1-based serological assays for the detection of flavivirus immune response. PLoS Negl Trop Dis. 2020;14(1):e0008039. pmid:31995566
- 44. Lytton SD, Nematollahi G, van Tong H, Xuan Anh C, Hung HV, Hoan NX, et al. Predominant secondary dengue infection among Vietnamese adults mostly without warning signs and severe disease. Int J Infect Dis. 2020;100:316–23. pmid:32896661
- 45. Adams L, Bello-Pagan M, Lozier M, Ryff KR, Espinet C, Torres J. Update: Ongoing Zika virus transmission — Puerto Rico, November 1, 2015 – July 7, 2016. MMWR Morb Mortal Wkly Rep. 2016;65(30):774–9.
- 46. Vasquez V, Haddad E, Perignon A, Jaureguiberry S, Brichler S, Leparc-Goffart I, et al. Dengue, chikungunya, and Zika virus infections imported to Paris between 2009 and 2016: Characteristics and correlation with outbreaks in the French overseas territories of Guadeloupe and Martinique. Int J Infect Dis. 2018;72:34–9. pmid:29782922
- 47. Hu D, Di B, Ding X, Wang Y, Chen Y, Pan Y, et al. Kinetics of non-structural protein 1, IgM and IgG antibodies in dengue type 1 primary infection. Virol J. 2011;8:47. pmid:21284891
- 48. Franke F, Giron S, Cochet A, Jeannin C, Leparc-Goffart I, de Valk H. Autochthonous chikungunya and dengue fever outbreak in mainland France, 2010-2018. Eur J Public Health. 2019;29(Suppl. 4):316–7.
- 49. Blacksell SD. Commercial dengue rapid diagnostic tests for point-of-care application: recent evaluations and future needs?. J Biomed Biotechnol. 2012;2012:151967.
- 50. Shu P-Y, Chen L-K, Chang S-F, Yueh Y-Y, Chow L, Chien L-J, et al. Comparison of capture immunoglobulin M (IgM) and IgG enzyme-linked immunosorbent assay (ELISA) and nonstructural protein NS1 serotype-specific IgG ELISA for differentiation of primary and secondary dengue virus infections. Clin Diagn Lab Immunol. 2003;10(4):622–30. pmid:12853395
- 51. Lee H, Ryu JH, Park HS, Park KH, Bae H, Yun S, et al. Comparison of Six Commercial Diagnostic Tests for the Detection of Dengue Virus Non-Structural-1 Antigen and IgM/IgG Antibodies. Ann Lab Med. 2019;39(6):566–71. pmid:31240885
- 52.
Euroimmun. Dengue Virus NS1 ELISA [instructions for use, order no. EQ 266a-9601-1]. Lübeck: EUROIMMUN Medizinische Labordiagnostika AG; 2019.
- 53. Pillay K, Keddie SH, Fitchett E, Akinde C, Bärenbold O, Bradley J, et al. Evaluating the performance of common reference laboratory tests for acute dengue diagnosis: a systematic review and meta-analysis of RT-PCR, NS1 ELISA, and IgM ELISA. Lancet Microbe. 2025;6(7):101088. pmid:40209729
- 54.
Euroimmun. Anti-Dengue Virus Type 1-4 ELISA (IgM) [instructions for use, order no. EI 266a-9601-1 M]. Lübeck: EUROIMMUN Medizinische Labordiagnostika AG; 2019.
- 55. Luvira V, Thawornkuno C, Lawpoolsri S, Thippornchai N, Duangdee C, Ngamprasertchai T, et al. Diagnostic Performance of Dengue NS1 and Antibodies by Serum Concentration Technique. Trop Med Infect Dis. 2023;8(2):117. pmid:36828533
- 56.
Euroimmun. Anti-Dengue Virus Type 1-4 ELISA (IgG) [instructions for use, order no. EI 266a-9601-1 G]. Lübeck: EUROIMMUN Medizinische Labordiagnostika AG; 2022.
- 57.
Euroimmun. Anti-Dengue Virus NS1 ELISA 2.0 (IgG) [instructions for use, order no. EI 266a-9601-3 G]. Lübeck: EUROIMMUN Medizinische Labordiagnostika AG; 2025.
- 58. Bonifacio E, Winkler C, Achenbach P, Ziegler A-G. Effect of population-wide screening for presymptomatic early-stage type 1 diabetes on paediatric clinical care. Lancet Diabetes Endocrinol. 2024;12(6):376–8. pmid:38723647
- 59.
Committee to Advise on Tropical Medicine and Travel (CATMAT). Recommendations on use of QDENGA (dengue vaccine) in jurisdictions where it is authorized for travellers [Internet]. Ottawa: Public Health Agency of Canada; 2025 [Cited 2025 October 22}. Available from: https://www.canada.ca/en/public-health/services/catmat/recommendations-qdenga-dengue-vaccine-jurisdictions-authorized-travellers.html
- 60. Kling K, Külper-Schiek W, Schmidt-Chanasit J, Stratil J, Bogdan C, Ramharter M, et al. STIKO-Empfehlung und wissenschaftliche Begründung der STIKO zur Impfung gegen Dengue mit dem Impfstoff Qdenga. Epidemiol Bul. 2023;48:3–43.
- 61. Ramirez RMG, Consuegra MP, Estupinan MI, Rangel AT, Herrera VM, de Lamballerie X. Experience in the validation of a rapid test for NS1 and IgM for early diagnosis during a dengue epidemic in Colombia. Clin Res Infect Dis. 2024;8(1):1064.
- 62. Blacksell SD, Jarman RG, Bailey MS, Tanganuchitcharnchai A, Jenjaroen K, Gibbons RV, et al. Evaluation of six commercial point-of-care tests for diagnosis of acute dengue infections: the need for combining NS1 antigen and IgM/IgG antibody detection to achieve acceptable levels of accuracy. Clin Vaccine Immunol. 2011;18(12):2095–101. pmid:22012979
- 63. Guzman MG, Jaenisch T, Gaczkowski R, Ty Hang VT, Sekaran SD, Kroeger A, et al. Multi-country evaluation of the sensitivity and specificity of two commercially-available NS1 ELISA assays for dengue diagnosis. PLoS Negl Trop Dis. 2010;4(8):e811. pmid:20824173
- 64. Fry SR, Meyer M, Semple MG, Simmons CP, Sekaran SD, Huang JX, et al. The diagnostic sensitivity of dengue rapid test assays is significantly enhanced by using a combined antigen and antibody testing approach. PLoS Negl Trop Dis. 2011;5(6):e1199. pmid:21713023
- 65. Hunsperger EA, Muñoz-Jordán J, Beltran M, Colón C, Carrión J, Vazquez J, et al. Performance of Dengue Diagnostic Tests in a Single-Specimen Diagnostic Algorithm. J Infect Dis. 2016;214(6):836–44. pmid:26984143
- 66. Garcia-Van Smévoorde M, Piorkowski G, Emboulé L, Dos Santos G, Loraux C, Guyomard-Rabenirina S, et al. Phylogenetic Investigations of Dengue 2019-2021 Outbreak in Guadeloupe and Martinique Caribbean Islands. Pathogens. 2023;12(9):1182. pmid:37764990
- 67. DeTora LM, Toroser D, Sykes A, Vanderlinden C, Plunkett FJ, Lane T, et al. Good Publication Practice (GPP) Guidelines for Company-Sponsored Biomedical Research: 2022 Update. Ann Intern Med. 2022;175(9):1298–304. pmid:36037471