Validation and Application of a Commercial Quantitative Real-Time Reverse Transcriptase-PCR Assay in Investigation of a Large Dengue Virus Outbreak in Southern Taiwan

Performance of Fujifilm Dengue NS1 Antigen Rapid Diagnosis Kit Compared to Quantitative Real-Time Polymerase Chain Reaction

Dengue is a viral infection caused by the dengue virus (DENV), transmitted to humans through the bite of infected Aedes mosquitoes. About half of the world's population is now at risk of dengue, which represents a global public health concern, especially in tropical and subtropical countries. Early detection of the viral infection is crucial to manage the disease; hence, effective rapid diagnostic tests are essential. In this study, we evaluated the performance between the new Fujifilm Dengue non-structural antigen diagnosis kit (FF NS1 kit) and the SD Bioline NS1 antigen test kit (SD NS1 kit) against the quantitative real-time polymerase chain reaction (qRT-PCR) assays. The 140 acute serum samples collected from the Yangon General Hospital and Yangon Children's Hospital, Myanmar, from 2017 to 2019 were characterised by the three assays. With the qRT-PCR as the standard, the FF NS1 kit and the SD NS1 kit exhibited sensitivity of 94.3% and 88.6%, respectively, and specificity of 100% in both kits. Moreover, the positivity rates of the FF NS1 kit and the SD NS1 kit were 97.5% and 95% in primary infection and 90% and 80% in secondary infection, respectively. Our overall results suggest that the FF NS1 kit is reliable and accurate for detecting DENV infection.

Evaluation of in-house dengue real-time PCR assays in West Java, Indonesia

Dengue is an infectious disease caused by infection of dengue virus (DENV) transmitted by Aedes aegypti and Aedes albopictus. In Indonesia, dengue commonly occurs with an increasing incidence rate annually. It is known that early detection of dengue infection is one of the keys to controlling this disease outbreak. Rapid and accurate early detection to diagnose dengue can be achieved by molecular tests, one of which is through a real-time PCR method. However, real-time PCR assay for dengue developed based on Indonesian DENV sequences has not been available. Therefore, we developed in-house dengue real-time PCR (SYBR- and TaqMan-based) assays and evaluated those assays in routine clinical testing in the community. These assays target the 3' UTR region of the four DENV serotypes and was found to be specific for DENV. The most sensitive assay was the TaqMan assay with the LOD95% of 482 copy/ml, followed by the SYBR assay with the LOD95% of 14,398 copy/ml. We recruited dengue suspected patients from three primary health care services in West Java, Indonesia to represent the community testing setting. Dengue infection was examined using the two in-house real-time PCR assays along with NS1, IgM, and IgG rapid diagnostic tests (RDT). In total, as many as 74 clinical specimens of dengue suspected patients were included in this study. Among those patients, 21 were positive for TaqMan assay, 17 were positive for SYBR assay, nine were positive for NS1 test, six were positive for both IgG and IgM tests, and 22 were positive for IgG test only. Compared with our in-house TaqMan assay, the sensitivity of NS1 test, IgM test, and IgG test were 42.86%, 14.29%, and 28.57% respectively. Among these three RDT tests, NS1 showed 100% specificity. Thus, our study confirmed that NS1 test showed high specificity, indicating that a positive result of NS1 can be confidently considered a dengue case. However, NS1, IgM, and IgG tests with RDT are not enough to diagnose a dengue case. We suggest applying the high sensitivity and specificity rRT-PCR test as the gold standard for early detection and antibody test as a follow-up test for rRT-PCR negative cases.

Dengue: A review of laboratory diagnostics in the vaccine age

Background. Dengue is an important arboviral infection of considerable public health significance. It occurs in a wide global belt within a variety of tropical regions. The timely laboratory diagnosis of Dengue infection is critical to inform both clinical management and an appropriate public health response. Vaccination against Dengue virus is being introduced in some areas.Discussion. Appropriate diagnostic strategies will vary between laboratories depending on the available resources and skills. Diagnostic methods available include viral culture, the serological detection of Dengue-specific antibodies in using enzyme immunoassays (EIAs), microsphere immunoassays, haemagglutination inhibition or in lateral flow point of care tests. The results of antibody tests may be influenced by prior vaccination and exposure to other flaviviruses. The detection of non-structural protein 1 in serum (NS1) has improved the early diagnosis of Dengue and is available in point-of-care assays in addition to EIAs. Direct detection of viral RNA from blood by PCR is more sensitive than NS1 antigen detection but requires molecular skills and resources. An increasing variety of isothermal nucleic acid detection methods are in development. Timing of specimen collection and choice of test is critical to optimize diagnostic accuracy. Metagenomics and the direct detection by sequencing of viral RNA from blood offers the ability to rapidly type isolates for epidemiologic purposes.Conclusion. The impact of vaccination on immune response must be recognized as it will impact test interpretation and diagnostic algorithms.

Assessment of the Risk of Severe Dengue Using Intrahost Viral Population in Dengue Virus Serotype 2 Patients via Machine Learning

Dengue virus, a positive-sense single-stranded RNA virus, continuously threatens human health. Although several criteria for evaluation of severe dengue have been recently established, the ability to prognose the risk of severe outcomes for dengue patients remains limited. Mutant spectra of RNA viruses, including single nucleotide variants (SNVs) and defective virus genomes (DVGs), contribute to viral virulence and growth. Here, we determine the potency of intrahost viral population in dengue patients with primary infection that progresses into severe dengue. A total of 65 dengue virus serotype 2 infected patients in primary infection including 17 severe cases were enrolled. We utilized deep sequencing to directly define the frequency of SNVs and detection times of DVGs in sera of dengue patients and analyzed their associations with severe dengue. Among the detected SNVs and DVGs, the frequencies of 9 SNVs and the detection time of 1 DVG exhibited statistically significant differences between patients with dengue fever and those with severe dengue. By utilizing the detected frequencies/times of the selected SNVs/DVG as features, the machine learning model showed high average with a value of area under the receiver operating characteristic curve (AUROC, 0.966 ± 0.064). The elevation of the frequency of SNVs at E (nucleotide position 995 and 2216), NS2A (nucleotide position 4105), NS3 (nucleotide position 4536, 4606), and NS5 protein (nucleotide position 7643 and 10067) and the detection times of the selected DVG that had a deletion junction in the E protein region (nucleotide positions of the junction: between 969 and 1022) increased the possibility of dengue patients for severe dengue. In summary, we demonstrated the detected frequencies/times of SNVs/DVG in dengue patients associated with severe disease and successfully utilized them to discriminate severe patients using machine learning algorithm. The identified SNVs and DVGs that are associated with severe dengue will expand our understanding of intrahost viral population in dengue pathogenesis.

Assessing the risk of dengue severity using demographic information and laboratory test results with machine learning

BACKGROUND

Dengue virus causes a wide spectrum of disease, which ranges from subclinical disease to severe dengue shock syndrome. However, estimating the risk of severe outcomes using clinical presentation or laboratory test results for rapid patient triage remains a challenge. Here, we aimed to develop prognostic models for severe dengue using machine learning, according to demographic information and clinical laboratory data of patients with dengue.

METHODOLOGY/PRINCIPAL FINDINGS

Out of 1,581 patients in the National Cheng Kung University Hospital with suspected dengue infections and subjected to NS1 antigen, IgM and IgG, and qRT-PCR tests, 798 patients including 138 severe cases were enrolled in the study. The primary target outcome was severe dengue. Machine learning models were trained and tested using the patient dataset that included demographic information and qualitative laboratory test results collected on day 1 when they sought medical advice. To develop prognostic models, we applied various machine learning methods, including logistic regression, random forest, gradient boosting machine, support vector classifier, and artificial neural network, and compared the performance of the methods. The artificial neural network showed the highest average discrimination area under the receiver operating characteristic curve (0.8324 ± 0.0268) and balance accuracy (0.7523 ± 0.0273). According to the model explainer that analyzed the contributions/co-contributions of the different factors, patient age and dengue NS1 antigenemia were the two most important risk factors associated with severe dengue. Additionally, co-existence of anti-dengue IgM and IgG in patients with dengue increased the probability of severe dengue.

CONCLUSIONS/SIGNIFICANCE

We developed prognostic models for the prediction of dengue severity in patients, using machine learning. The discriminative ability of the artificial neural network exhibited good performance for severe dengue prognosis. This model could help clinicians obtain a rapid prognosis during dengue outbreaks. However, the model requires further validation using external cohorts in future studies.

Amplification chemistries in clinical virology

Molecular diagnostic methods have evolved and matured considerably over the last several decades and are constantly being evaluated and adopted by clinical laboratories for the identification of infectious pathogens. Advancement in other technologies such as fluorescence, electronics, instrumentation, automation, and sensors have made the overall diagnostic process more accurate, sensitive, and rapid. Nucleic acid based detection procedures, which rely on the fundamental principles of DNA replication have emerged as a popular and standard diagnostic method, and several commercial assays are currently available based on different nucleic acid amplification techniques. This review focuses on the major amplification chemistries that are used for developing commercial assays and discusses their application in the clinical virology laboratory.

Seroepidemiology of dengue virus infection among adults during the ending phase of a severe dengue epidemic in southern Taiwan, 2015

BACKGROUND

A severe dengue epidemic occurred in 2015 which resulted in over 22,000 laboratory-confirmed cases. A cross-sectional seroprevalence study was conducted during the ending phase of this epidemic to evaluate the true incidence of dengue virus (DENV) infection and the level of herd immunity.

METHODS

Adult residents in three administrative districts with high dengue incidence were recruited; workers in two districts with intermediate dengue incidence were also recruited for comparison. DENV-specific IgM and IgG were tested using commercial enzyme-linked immunosorbent assays. DENV RNA was detected using commercial quantitative real-time reverse transcriptase polymerase chain reaction assay. Univariate and multivariate logistic regressions were performed to identify risk factors for recent and past DENV infection.

RESULTS

The overall seroprevalence of anti-DENV IgM and IgG in 1391 participants was 6.8 and 17.4%, respectively. The risk of recent DENV infection increased with age, with the elderly having the highest risk of infection. Living in areas with high incidence of reported dengue cases and having family members being diagnosed with dengue in 2015 were also independent risk factors for recent DENV infection. One sample was found to have asymptomatic viremia with viral load as high as 10⁵ PFU/ml.

CONCLUSIONS

Comparing the seroprevalence of anti-DENV IgM with the incidence of reported dengue cases in 2015, we estimated that 1 out of 3.7 dengue infections were reported to the surveillance system; widespread use of rapid diagnostic tests might contribute to this high reporting rate. The results also indicate that the overall herd immunity remains low and the current approved Dengvaxia® is not quite suitable for vaccination in Taiwan.

[Dengue fever : Symptoms, epidemiology, entomology, pathogen diagnosis and prevention]

Dengueinfektionen gehören zu den häufigsten Ursachen fieberhafter Erkrankungen im tropischen Umfeld. Die Infektion wird durch ein Flavivirus verursacht, das durch Aedes-Moskitos übertragen wird. Hauptüberträger für Dengueviren sind die weltweit in den Tropen verbreiteten Aedes-aegypti-Stechmücken. Da diese einerseits tagaktiv und andererseits sog. „container breeder“ sind, bedarf es besonderer Vorbeugungs- und Bekämpfungsmaßnahmen. Die Schwere der Symptomatik variiert und kann vom milden grippeähnlichen klinischen Bild bis hin zu schweren Hämorrhagien und Schock reichen. Zu den häufigsten Symptomen bei Reisenden gehören Fieber, Muskelschmerzen, Kopfschmerzen und Hautausschlag. Zur Diagnostik kommen, in Abhängigkeit vom Stadium der Infektion, patientennah einsetzbare Schnellteste oder – in der virämischen Phase – molekulare Erregerdirektnachweise infrage. Die serologische Diagnostik ist aufgrund von serologischen Kreuzreaktionen mit anderen Flaviviren hinsichtlich ihrer Interpretation anspruchsvoll.

Prolonged persistence of IgM against dengue virus detected by commonly used commercial assays

BACKGROUND

Initial symptoms of dengue fever are non-specific, and thus definite diagnosis requires laboratory confirmation. Detection of IgM against dengue virus (DENV) has become widely used for dengue diagnosis. Understanding the persistence of anti-DENV IgM in subjects after acute infection is essential in order to interpret test results correctly. Although the longevity of anti-DENV IgM has been vehemently investigated in symptomatic children, anti-DENV IgM persistence in adults and in asymptomatically infected people have seldom been reported.

METHODS

We prospectively investigated 44 adults with detectable anti-DENV IgM in a serosurvey conducted in the 2015 dengue epidemic in Tainan, Taiwan. Among subjects within the cohort, 17 were classified to be symptomatic and 27 were asymptomatic. The enzyme-linked immunosorbent assay (ELISA) from Standard Diagnostic (SD) and Focus Diagnostic were used to detect anti-DENV IgM for specimens collected initially, at 6 and 12 months. Regression analyses were used to estimate the duration of anti-DENV IgM fell below the detectable level. Rapid dengue tests from Standard Diagnostics had been widely adopted to detect anti-DENV IgM in Taiwan during the 2015 dengue outbreak. As such, collected specimens were also evaluated with the SD rapid dengue test in parallel.

RESULTS

Anti-DENV IgM was detectable in 70.5 and 46.2% of the 44 subjects at 6 months and 12 months by the SD ELISA, respectively, while 13.6 and 7.7%, respectively, by the Focus ELISA. There was no significant difference in anti-DENV IgM detection for the follow-up specimens between subjects with symptomatic and asymptomatic infections. The regression analysis estimated that anti-DENV IgM persistence fell to the undetectable level at 338.3 days (95% CI 279.7-446.9) by SD ELISA, while at 175.7 days (95% CI 121.9-221.1) by Focus ELISA. The detectable frequency of anti-DENV IgM by rapid tests was 86.4%, 68.2 and 35.9% at initial, 6 and 12 months, respectively.

CONCLUSION

Anti-DENV IgM was found to persist much longer than previously thought, suggesting a necessity of re-evaluation of the use of anti-DENV IgM for both the diagnosis of dengue and serological surveillance, especially when large outbreaks have occurred in the preceding year.

Macrophage migration inhibitory factor is critical for dengue NS1-induced endothelial glycocalyx degradation and hyperpermeability

Vascular leakage is one of the salient characteristics of severe dengue. Nonstructural protein 1 (NS1) of dengue virus (DENV) can stimulate endothelial cells to secrete endothelial hyperpermeability factor, macrophage migration inhibitory factor (MIF), and the glycocalyx degradation factor heparanase 1 (HPA-1). However, it is unclear whether MIF is directly involved in NS1-induced glycocalyx degradation. In this study, we observed that among NS1, MIF and glycocalyx degradation-related molecules, the HPA-1, metalloproteinase 9 (MMP-9) and syndecan 1 (CD138) serum levels were all increased in dengue patients, and only NS1 and MIF showed a positive correlation with the CD138 level in severe patients. To further characterize and clarify the relationship between MIF and CD138, we used recombinant NS1 to stimulate human cells in vitro and challenge mice in vivo. Our tabulated results suggested that NS1 stimulation could induce human endothelial cells to secrete HPA-1 and immune cells to secrete MMP-9, resulting in endothelial glycocalyx degradation and hyperpermeability. Moreover, HPA-1, MMP-9, and CD138 secretion after NS1 stimulation was blocked by MIF inhibitors or antibodies both in vitro and in mice. Taken together, these results suggest that MIF directly engages in dengue NS1-induced glycocalyx degradation and that targeting MIF may represent a possible therapeutic approach for preventing dengue-induced vascular leakage.

Trend and geographic analysis of the prevalence of dengue in Taiwan, 2010-2015

BACKGROUND

Dengue is the most rapidly spreading disease caused by a mosquito-borne virus in the world. The incidence of dengue globally has increased 30-fold in the last 50 years. Understanding the prevalence of dengue and its longitudinal trends can improve prevention and control strategies. This study assessed the trends in prevalence of dengue in Taiwan by population characteristics and geographical region.

METHODS

Dengue and population data for the years 2010-2015 were obtained from the public statistics databases of the Taiwan Centers for Disease Control and Department of Statistics, Taiwan Ministry of Interior. Yearly prevalence rates of dengue were calculated by age group, sex, and administrative area within five geographic regions (northern, mid-western, southern, and eastern regions, and outer islands).

RESULTS

The national prevalence rate of dengue decreased gradually from 8 to 4 per 100000 population between 2010 and 2013, but it increased substantially in 2014 and 2015 to 67 and 187 per 100000 population, respectively. There was no significant difference in prevalence rate between males and females. People aged 60-69 years had a significantly higher prevalence rate than those in the other age groups during 2010-2014, and people aged over 70 years had the highest rate in 2015 (309 per 100000 population). The southern region had the highest yearly dengue prevalence rate (the rate decreased from 23 to 9 per 100000 population between 2010 and 2013, but increased to 220 and 616 per 100000 population in 2014 and 2015, respectively). Three unexpected outbreaks of dengue were observed during the study period: the first outbreak occurred in Penghu County in 2011 (prevalence rate 101 per 100000 population), the second in Kaohsiung City in 2014 (prevalence rate 540 per 100000 population), and the third in Tainan City in 2015 (prevalence rate 1208 per 100000 population).

CONCLUSIONS

More efforts are still needed to prevent and control dengue in Taiwan. The government should direct resources and interventions to southern Taiwan, which has a tropical climate and a high population density, and should target older people who are more likely to be infected. Strategies are also needed to respond quickly to unexpected incidents to prevent dengue outbreaks.