Evaluation of the WHO 2009 classification for diagnosis of acute dengue in a large cohort of adults and children in Sri Lanka during a dengue-1 epidemic

Dengue

Dengue, caused by four closely related viruses, is a growing global public health concern, with outbreaks capable of overwhelming health-care systems and disrupting economies. Dengue is endemic in more than 100 countries across tropical and subtropical regions worldwide, and the expanding range of the mosquito vector, affected in part by climate change, increases risk in new areas such as Spain, Portugal, and the southern USA, while emerging evidence points to silent epidemics in Africa. Substantial advances in our understanding of the virus, immune responses, and disease progression have been made within the past decade. Novel interventions have emerged, including partially effective vaccines and innovative mosquito control strategies, although a reliable immune correlate of protection remains a challenge for the assessment of vaccines. These developments mark the beginning of a new era in dengue prevention and control, offering promise in addressing this pressing global health issue.

Integration of population-level data sources into an individual-level clinical prediction model for dengue virus test positivity

The differentiation of dengue virus (DENV) infection, a major cause of acute febrile illness in tropical regions, from other etiologies, may help prioritize laboratory testing and limit the inappropriate use of antibiotics. While traditional clinical prediction models focus on individual patient-level parameters, we hypothesize that for infectious diseases, population-level data sources may improve predictive ability. To create a clinical prediction model that integrates patient-extrinsic data for identifying DENV among febrile patients presenting to a hospital in Thailand, we fit random forest classifiers combining clinical data with climate and population-level epidemiologic data. In cross-validation, compared to a parsimonious model with the top clinical predictors, a model with the addition of climate data, reconstructed susceptibility estimates, force of infection estimates, and a recent case clustering metric significantly improved model performance.

Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.

The Effect of Age on Dengue Presentation and the Diagnostic Accuracy of the 2015 Pan American Health Organization Case Criteria in a Puerto Rican Cohort

Background

We evaluated dengue presentation by age, the performance of the 2015 Pan American Health Organization (PAHO) case criteria in identifying dengue cases, and variables to improve specificity.

Methods

Patients with fever ≤7 days (N = 10 408) were recruited from 2 emergency departments from May 2012 through December 2015. Serum samples were tested for dengue, chikungunya, and nasopharyngeal swabs for respiratory viruses. Smoothing splines assessed differences in the frequencies of signs/symptoms by age. Least absolute shrinkage and selection operator regressions identified the variables that best predicted dengue.

Results

Among 985 dengue cases, children aged <5 years were least likely to have leukopenia, but most likely to have rash and petechiae. Adults had the highest odds of aches/pains and headaches/retro-orbital pain. The 2015 PAHO criteria had sensitivity of 93% and specificity of 25%. Specificity could be improved by requiring at least 2 of the following criteria: vomiting/nausea, petechiae, rash, or leukopenia (specificity 68%, sensitivity 71%) or by using 2015 PAHO criteria plus either (1) aspartate aminotransferase >50 IU/L or platelet count <100 000 platelets/μL (specificity 81%, sensitivity 56%) or (2) itchy skin or absence of rhinorrhea or cough (specificity 51%, sensitivity 82%).

Conclusions

The 2015 PAHO dengue case criteria had excellent sensitivity but poor specificity. This can be improved by adding signs/symptoms associated with dengue diagnosis.

An 8-gene machine learning model improves clinical prediction of severe dengue progression

BACKGROUND

Each year 3-6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed.

METHODS

We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patients and SD progressors. Using only these DEGs, we trained an XGBoost machine learning model on public data to predict progression to SD. All model parameters were "locked" prior to validation in an independent, prospectively enrolled cohort of 377 dengue patients in Colombia. We measured expression of the DEGs in whole blood samples collected upon presentation, prior to SD progression. We then compared the accuracy of the locked XGBoost model and clinical warning signs in predicting SD.

RESULTS

We identified eight SD-associated DEGs in the public datasets and built an 8-gene XGBoost model that accurately predicted SD progression in the independent validation cohort with 86.4% (95% CI 68.2-100) sensitivity and 79.7% (95% CI 75.5-83.9) specificity. Given the 5.8% proportion of SD cases in this cohort, the 8-gene model had a positive and negative predictive value (PPV and NPV) of 20.9% (95% CI 16.7-25.6) and 99.0% (95% CI 97.7-100.0), respectively. Compared to clinical warning signs at presentation, which had 77.3% (95% CI 58.3-94.1) sensitivity and 39.7% (95% CI 34.7-44.9) specificity, the 8-gene model led to an 80% reduction in the number needed to predict (NNP) from 25.4 to 5.0. Importantly, the 8-gene model accurately predicted subsequent SD in the first three days post-fever onset and up to three days prior to SD progression.

CONCLUSIONS

The 8-gene XGBoost model, trained on heterogeneous public datasets, accurately predicted progression to SD in a large, independent, prospective cohort, including during the early febrile stage when SD prediction remains clinically difficult. The model has potential to be translated to a point-of-care prognostic assay to reduce dengue morbidity and mortality without overwhelming limited healthcare resources.

miR-573 rescues endothelial dysfunction during dengue infection under PPARγ regulation

Early prognosis of abnormal vasculopathy is essential for effective clinical management of severe dengue patients. An exaggerated interferon (IFN) response and release of vasoactive factors from endothelial cells cause vasculopathy. This study shows that dengue 2 (DENV2) infection of human umbilical vein endothelial cells (HUVEC) results in differentially regulated miRNAs important for endothelial function. miR-573 was significantly down-regulated in DENV2-infected HUVEC due to decreased Peroxisome Proliferator Activator Receptor Gamma (PPARγ) activity. Restoring miR-573 expression decreased endothelial permeability by suppressing the expression of vasoactive angiopoietin 2 (ANGPT2). We also found that miR-573 suppressed the proinflammatory IFN response through direct downregulation of toll like receptor 2 (TLR2) expression. Our study provides a novel insight into miR-573 mediated regulation of endothelial function during DENV2 infection which can be further translated into a potential therapeutic and prognostic agent for severe dengue patients. IMPORTANCE: We need to identify molecular factors which can predict the onset of endothelial dysfunction in dengue patients. Increase in endothelial permeability during severe dengue infections is poorly understood. In this study we focus on factors which regulate endothelial function and are dysregulated during DENV2 infection. We show that miR-573 rescues endothelial permeability and is downregulated during DENV2 infection in endothelial cells. This finding can have diagnostic as well as therapeutic applications.

Majority of pediatric dengue virus infections in Kenya do not meet 2009 WHO criteria for dengue diagnosis

From 1975-2009, the WHO guidelines classified symptomatic dengue virus infections as dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. In 2009 the case definition was changed to a clinical classification after concern the original criteria was challenging to apply in resource-limited settings and not inclusive of a substantial proportion of severe dengue cases. Our goal was to examine how well the current WHO definition identified new dengue cases at our febrile surveillance sites in Kenya. Between 2014 and 2019 as part of a child cohort study of febrile illness in our four clinical study sites (Ukunda, Kisumu, Msambweni, Chulaimbo) we identified 369 dengue PCR positive symptomatic cases and characterized whether they met the 2009 revised WHO diagnostic criteria for dengue with and without warning signs and severe dengue. We found 62% of our PCR-confirmed dengue cases did not meet criteria per the guidelines. Our findings also correlate with our experience that dengue disease in children in Kenya is less severe as reported in other parts of the world. Although the 2009 clinical classification has recently been criticized for being overly inclusive and non-specific, our findings suggest the 2009 WHO dengue case definition may miss more than 50% of symptomatic infections in Kenya and may require further modification to include the African experience.

Severe dengue in adults and children, Ouagadougou (Burkina Faso), West Africa, October 2015–January 2017

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Severe dengue was common in this sudy.

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In contrast to multiple prior studies, the risk of severe dengue was greater for patients with primary dengue compared to those with secondary infection.

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Additional risk factors for severe dengue included age, male sex, haemoglobin S, diabetes, and hypertension.  Case mapping showed that dengue cases were more concentrated  in sectors located in the centre of the city and close to the health centres.

Introduction

Although dengue is the most common arbovirus infection worldwide, studies of severe dengue in Africa are lacking, and risk factors for severe dengue have been insufficiently described. This study was conducted in the context of the 2016 dengue epidemic in Burkina Faso to determine the prevalence of severe dengue, identify factors associated with severe dengue, and perform mapping of dengue cases in the country's capital, Ouagadougou.

Methods

This cross-sectional study was conducted from November 2015 to January 2017. Data were collected in 15 public and private health centres, and included sociodemographic, clinical and patient outcome variables. Dengue was diagnosed using SD Bioline Dengue Duo rapid diagnostic tests. Data were analysed using Epi-Info Version 7. Logistic regression was used to identify predictors of severe dengue. P<0.05 was considered significant. Dengue case mapping was performed using Geographic Information System software (ArcGIS).

Results

Of the 811 patients who tested positive for dengue, 609 (75%) had early dengue (AgNS1 positive) and 272 (33.5%) had severe dengue. Patient age ranged from 1 to 83 years (median 30.5 years) and 393 (48.3%) were female. Renal failure (13.1%) and severe bleeding (10.6%) were the most common signs of severe dengue. Risk factors for severe dengue included age, male sex, haemoglobin S, diabetes, hypertension, and primary dengue. Dengue cases were more concentrated  in sectors located in the centre of the city and close to the health centres.

Conclusion

Dengue is increasingly common in Africa and factors associated with severity should be sought systematically as soon as a patient tests positive. Additional studies are needed to determine if the factors found to be associated with severity can be used to identify patients at risk for dengue-related complications, and to provide early and specialized management to reduce morbidity and mortality related to dengue in Africa.

Successful Outpatient Management of Children at a Secondary Care Hospital in Pakistan in a Dengue Fever Epidemic and Their Clinical Outcomes

Background

There is limited published literature on the feasibility of WHO 2009 guidelines for the management of dengue fever (DF) in Pakistani children. This study aimed to assess the outcome of children with DF who received outpatient treatment according to these guidelines during a DF epidemic.

Method

This was a prospective cohort study conducted at Federal General Hospital, a secondary care hospital, Islamabad, Pakistan, from 1st August to 31st October 2019. Using WHO DF 2009 guidelines, children ≤13 years, diagnosed as confirmed DF (NS1 Ag +), were classified into the outpatient (DF) or the inpatient group (DF with warning signs or severe dengue (SD)). The inpatient group was admitted to the Pakistan Institute of Medical Sciences, a tertiary care hospital, and discharged on recovery. These children were followed for the primary outcome, i.e., recovery or hospitalization by day 14 of enrollment. Additionally, clinical and laboratory features (Hb, HCT, TLC, PLT, and ALT) of the patients in the outpatient who remained stable with those who progressed to inpatient care during follow-up were compared; also, time of recovery of blood counts was assessed.

Results

Of 93 children with DF, 87 (93.5%) received outpatient care at enrollment. Of these, 6 (7.8%) deteriorated by day 7 and were admitted to inpatient care. SD was present in 6/93 (6.4%) patients at presentation and were admitted. All children showed signs of recovery until day 14. Male gender (p=0.049), lower normal mean platelet (p=0.02), and high mean hematocrit (p=0.001) were associated with disease progression.

Conclusion

The majority of children with confirmed DF who received outpatient treatment according to WHO 2009 guidelines were successfully managed. Additionally, confirmed DF with warning signs or SD were admitted and recovered. Regular follow-ups according to the guidelines are pertinent. Thrombocytopenia and high HCT were associated with disease progression.

Plasma leakage in dengue: a systematic review of prospective observational studies

Plasma leakage is a precursor to life-threatening complications of dengue, but this group is poorly defined and not often reported in literature. Patients with Dengue haemorrhagic fever (DHF) as defined in the 1997 World Health Organization classification are often reported, and they all have plasma leakage, but some patients with plasma leakage do not meet the definition of DHF. The study aims to estimate the frequency of plasma leakage and DHF (as a surrogate of plasma leakage) in dengue and its variations based on virus serotype, geography, patient gender and pre-existing immunity to dengue. PUBMED, Scopus, EMBASE, CINAHL and Web of Science were searched for prospective observational studies reporting on plasma leakage or DHF. Quality of data was assessed using the NIH quality assessment tool for cohort studies. Forty-three studies that recruited 15,794 confirmed dengue patients were eligible. Cumulative frequency of plasma leakage was 36.8% (15 studies, 1642/4462, 95% CI 35.4-38.2%), but surprisingly the estimated cumulative frequency of DHF was higher (45.7%, 32 studies, 4758/10417, 95% CI 44.7-46.6%), indicating that current medical literature over-reports DHF or under-reports plasma leakage. Therefore, a reliable estimate for the proportion of dengue patients developing plasma leakage cannot be derived from existing medical literature even after applying rigorous inclusion criteria to select homogenous studies. Plasma leakage is an important marker of "at-risk" dengue patients and standardizing its definition, diagnosis and reporting should be a priority in research and global policy.

Different Profiles of Cytokines, Chemokines and Coagulation Mediators Associated with Severity in Brazilian Patients Infected with Dengue Virus

The incidence of dengue in Latin America has increased dramatically during the last decade. Understanding the pathogenic mechanisms in dengue is crucial for the identification of biomarkers for the triage of patients. We aimed to characterize the profile of cytokines (IFN-γ, TNF-α, IL-1β, IL-6, IL-18 and IL-10), chemokines (CXCL8/IL-8, CCL2/MCP-1 and CXCL10/IP-10) and coagulation mediators (Fibrinogen, D-dimer, Tissue factor-TF, Tissue factor pathway inhibitor-TFPI and Thrombomodulin) during the dengue-4 epidemic in Brazil. Laboratory-confirmed dengue cases had higher levels of TNF-α (p < 0.001), IL-6 (p = 0.005), IL-10 (p < 0.001), IL-18 (p = 0.001), CXCL8/IL-8 (p < 0.001), CCL2/MCP-1 (p < 0.001), CXCL10/IP-10 (p = 0.001), fibrinogen (p = 0.037), D-dimer (p = 0.01) and TFPI (p = 0.042) and lower levels of TF (p = 0.042) compared to healthy controls. A principal component analysis (PCA) distinguished between two profiles of mediators of inflammation and coagulation: protective (TNF-α, IL-1β and CXCL8/IL-8) and pathological (IL-6, TF and TFPI). Lastly, multivariate logistic regression analysis identified high aspartate aminotransferase-to-platelet ratio index (APRI) as independent risk factors associated with severity (adjusted OR: 1.33; 95% CI 1.03–1.71; p = 0.027), the area under the receiver operating characteristics curve (AUC) was 0.775 (95% CI 0.681–0.869) and an optimal cutoff value was 1.4 (sensitivity: 76%; specificity: 79%), so it could be a useful marker for the triage of patients attending primary care centers.

Flavivirus: From Structure to Therapeutics Development

Flaviviruses are still a hidden threat to global human safety, as we are reminded by recent reports of dengue virus infections in Singapore and African-lineage-like Zika virus infections in Brazil. Therapeutic drugs or vaccines for flavivirus infections are in urgent need but are not well developed. The Flaviviridae family comprises a large group of enveloped viruses with a single-strand RNA genome of positive polarity. The genome of flavivirus encodes ten proteins, and each of them plays a different and important role in viral infection. In this review, we briefly summarized the major information of flavivirus and further introduced some strategies for the design and development of vaccines and anti-flavivirus compound drugs based on the structure of the viral proteins. There is no doubt that in the past few years, studies of antiviral drugs have achieved solid progress based on better understanding of the flavivirus biology. However, currently, there are no fully effective antiviral drugs or vaccines for most flaviviruses. We hope that this review may provide useful information for future development of anti-flavivirus drugs and vaccines.

Assessing the serum chymase level as an early predictor of dengue severity

We conducted a prospective, observational study to assess the serum chymase level, a mast cell derived protease, as a predictor of dengue severity. NS1-positive non-severe dengue patients of age ≥14 years with duration of fever ≤4 days were included in the study. At the time of admission, the serum sample was taken for chymase estimation. Patients were followed up to four days after they became afebrile to find out the final diagnosis. Total of 338 non-severe dengue patients were recruited (mean age: 29.15 years; male: 66%). On follow-up, 26 patients (7.8%) developed severe dengue. Only chymase level (adjusted odds ratio [aOR]: 1.787; 95% confidence interval [CI]: 1.309-2.440) and platelet count at admission (aOR: 0.981; 95% CI: 0.968-0.993) were able to predict the severity after adjustment for all variables. But, for prediction of severe dengue, the area under receiver's operating curve of chymase was 0.835 (95% CI: 0.765-0.905), which was significantly higher than that of the platelet count at admission (0.760, 95% CI: 0.650-0.870) (p < .001). Patients who developed severe dengue in due course of illness had significantly higher serum chymase level at admission as compared with the rest of the patients. Similar findings were noted across all age-groups. At an optimum cut-off value of 1.35 ng/ml, chymase had a positive likelihood ratio (LR) of 3.5 and a negative LR of 0.15, for predicting severe dengue. This study demonstrated the potential ability of serum chymase levels at admission, as a biomarker for prediction of severe dengue in due course of illness.

Diagnostic accuracy of the WHO clinical definitions for dengue and implications for surveillance: A systematic review and meta-analysis

Background

Dengue is the world’s most common mosquito-borne virus but remains diagnostically challenging due to its nonspecific presentation. Access to laboratory confirmation is limited and thus most reported figures are based on clinical diagnosis alone, the accuracy of which is uncertain. This systematic review assesses the diagnostic accuracy of the traditional (1997) and revised (2009) WHO clinical case definitions for dengue fever, the basis for most national guidelines.

Methodology/Principal findings

PubMed, EMBASE, Scopus, OpenGrey, and the annual Dengue Bulletin were searched for studies assessing the diagnostic accuracy of the unmodified clinical criteria. Two reviewers (NR/SL) independently assessed eligibility, extracted data, and evaluated risk of bias using a modified QUADAS-2. Additional records were found by citation network analysis. A meta-analysis was done using a bivariate mixed-effects regression model. Studies that modified criteria were analysed separately. This systematic review protocol was registered on PROSPERO (CRD42020165998). We identified 11 and 12 datasets assessing the 1997 and 2009 definition, respectively, and 6 using modified criteria. Sensitivity was 93% (95% CI: 77–98) and 93% (95% CI: 86–96) for the 1997 and 2009 definitions, respectively. Specificity was 29% (95% CI: 8–65) and 31% (95% CI: 18–48) for the 1997 and 2009 definitions, respectively. Diagnostic performance suffered at the extremes of age. No modification significantly improved accuracy.

Conclusions/Significance

Diagnostic accuracy of clinical criteria is poor, with significant implications for surveillance and public health responses for dengue control. As the basis for most reported figures, this has relevance to policymakers planning resource allocation and researchers modelling transmission, particularly during COVID-19.

Dengue is the most common mosquito-borne disease worldwide, with half the world’s population living in at-risk areas, yet it remains difficult to diagnose. Existing laboratory tests have highly variable performance, and access to them remains limited in most dengue-endemic regions. Thus, most dengue cases are diagnosed on clinical criteria alone. While national guidelines vary, most are based on the WHO case definitions, produced in 1997 and revised in 2009. Here, we assess the diagnostic accuracy of both definitions and find that they have good sensitivity but poor specificity, particularly problematic given the co-circulation of multiple febrile illnesses in these regions. This makes it difficult for policymakers and researchers to model transmission, assess the introduction of new pathogens to a region, and correctly prioritise control measures and vaccination programmes in a region-specific manner. This is exacerbated by the ongoing COVID-19 pandemic, given rising cases of both diseases and the stark difference in necessary control measures. As such, improvements in dengue diagnostic and reporting practice are increasingly urgent. This could be achieved by incorporating symptom absence into clinical criteria, weighting symptoms depending on strength of association with dengue or timing within disease course, or using clinical criteria to allocate limited testing resources in borderline cases.

Causes of death among dengue patients causes of death among hospitalized adults with dengue fever in Tainan, 2015: Emphasis on cardiac events and bacterial infections

INTRODUCTION

The 2015 dengue outbreak in southern Taiwan caused substantial mortality. We analyzed the causes of death among these patients.

MATERIALS AND METHODS

This retrospective study was conducted at a medical center in Tainan from August 2015 to December 2015. Dengue was diagnosed based on the detection of serum dengue NS1 antigen, IgM, or viral RNA in the blood. Causes of death were retrieved from chart reviews by three clinicians.

RESULTS

There were 4488 cases of dengue in the study hospital, with an in-hospital fatality rate of 1.3% (60 cases). The mean age of the 60 fatal cases was 73 years, among whom 90% were aged ≥65 years. Twenty-eight (46.7%) patients died of severe dengue, and 29 (48.3%) deaths were possibly related to dengue. Of the latter, 24 (40%) died of secondary infections. Thirteen cardiac arrest events, including out-of-hospital (5 events) and in-hospital (8) cardiac arrests in the emergency department, occurred during the dengue epidemic. Seven (53.8%) patients did not receive medical aid before the event. Of the 40 deaths that occurred within one week after hospitalization, 60% died of severe dengue. In contrast, 50% of 20 deaths that occurred one week after hospitalization were related to hospital-acquired infections, mainly pneumonia.

CONCLUSION

Of 60 fatal cases, with a predominance of elderly patients, deaths were related to severe dengue within the first week after admission and secondary infections thereafter. The absence of medical care before cardiac arrest events highlights the importance of health education for warning signs of dengue.

A review of dengue diagnostics and implications for surveillance and control

Dengue is the world’s most common arboviral infection, with almost 4 billion people estimated to be living at risk of dengue infection. A recently introduced vaccine is currently recommended only for seropositive individuals in a restricted age range determined by transmission intensity. With no effective dengue vaccine for the general population or any antiviral therapy, dengue control continues to rely heavily on vector control measures. Early and accurate diagnosis is important for guiding appropriate management and for disease surveillance to guide prompt dengue control interventions. However, major uncertainties exist in dengue diagnosis and this has important implications for all three. Dengue can be diagnosed clinically against predefined lists of signs and symptoms and by detection of dengue-specific antibodies, non-structural 1 antigen or viral RNA by reverse transcriptase–polymerase chain reaction. All of these methods have their limitations. This review aims to describe and quantify the advantages, uncertainties and variability of the various diagnostic methods used for dengue and discuss their implications and applications for dengue surveillance and control.

Previously Derived Host Gene Expression Classifiers Identify Bacterial and Viral Etiologies of Acute Febrile Respiratory Illness in a South Asian Population

Background

Pathogen-based diagnostics for acute respiratory infection (ARI) have limited ability to detect etiology of illness. We previously showed that peripheral blood-based host gene expression classifiers accurately identify bacterial and viral ARI in cohorts of European and African descent. We determined classifier performance in a South Asian cohort.

Methods

Patients ≥15 years with fever and respiratory symptoms were enrolled in Sri Lanka. Comprehensive pathogen-based testing was performed. Peripheral blood ribonucleic acid was sequenced and previously developed signatures were applied: a pan-viral classifier (viral vs nonviral) and an ARI classifier (bacterial vs viral vs noninfectious).

Results

Ribonucleic acid sequencing was performed in 79 subjects: 58 viral infections (36 influenza, 22 dengue) and 21 bacterial infections (10 leptospirosis, 11 scrub typhus). The pan-viral classifier had an overall classification accuracy of 95%. The ARI classifier had an overall classification accuracy of 94%, with sensitivity and specificity of 91% and 95%, respectively, for bacterial infection. The sensitivity and specificity of C-reactive protein (>10 mg/L) and procalcitonin (>0.25 ng/mL) for bacterial infection were 100% and 34%, and 100% and 41%, respectively.

Conclusions

Previously derived gene expression classifiers had high predictive accuracy at distinguishing viral and bacterial infection in South Asian patients with ARI caused by typical and atypical pathogens.

Towards Predicting Progression to Severe Dengue

There is an urgent need for prognostic assays to predict progression to severe dengue infection, which is a major global threat. While the majority of symptomatic dengue patients experience an acute febrile illness, 5-20% progress to severe infection associated with significant morbidity and mortality. Early monitoring and administration of supportive care reduce mortality and clinically usable biomarkers to predict severe dengue are needed. Here, we review recent discoveries of gene sets, anti-dengue antibody properties, and inflammatory markers with potential utility as predictors of disease progression. Upon larger scale validation and development of affordable sample-to-answer technologies, some of these biomarkers may be utilized to develop the first prognostic assay for improving patient care and allocating healthcare resources more effectively in dengue endemic countries.

Primary Dengue Infection in Patients Requiring Hospitalization During an Outbreak in a Low Incidence Mexican Region

Background: Dengue manifestations can range from subclinical to fatal. The study of factors that influence dengue's clinical severity can provide information to potentially limit or predict severe cases. Secondary infection (SI) with a different dengue serotype has been recognized as an important determinant of severity. However, severe dengue (SD) manifestations, including shock, can happen during primary infection (PI) too and the mechanisms involved are less understood. To characterize the severe manifestations associated to PI, we distinguished between primary and secondary dengue cases in hospitalized patients from a region of low and recent dengue incidence in central Mexico. This region can serve as a model for dengue's behavior as it spreads to new areas worldwide. Methods: Dengue-specific immunoglobulin M (IgM) and IgG concentrations were measured in the serum of 78 hospitalized patients with dengue hemorrhagic fever, and their ratios were used to discriminate between PI and SI, as recommended by World Health Organization. Clinical and laboratory manifestations were compared between PI and SI. Results and Conclusions: PI was detected in 23% of hospitalized dengue cases, a proportion similar to that reported in high-incidence regions in Mexico. PI was more frequent in 16- to 40-year-olds, and was absent in patients older than 60 years. Only dengue with warning signs and SD were present in the studied population of hospitalized patients, and case frequency decreased with clinical severity both in PI and SI groups. No significant differences in demographics, laboratory tests, or symptoms were found between PI and SI, which illustrates that cases requiring hospitalization during outbreaks can be severe, even if they are PI. This information can help plan for sanitary contingencies in places where dengue is recently emergent and numerous PI cases are expected. The mechanisms involved in PI clinical severity need to be studied further.

Diversity of infectious aetiologies of acute undifferentiated febrile illnesses in south and Southeast Asia: a systematic review

BACKGROUND

Acute undifferentiated febrile illness (AUFI) is caused by a multitude of diverse pathogens, with significant morbidity and mortality in the developing world. The objective of this review was to characterise the diversity and relative importance of common infectious aetiologies of AUFI in South and Southeast Asia.

METHODS

We conducted a comprehensive literature review to identify common aetiologies of AUFI in Asian countries. Four medical and life sciences databases including PubMed, Medline, Embase and Cochrane Central, and Google Scholar were searched for articles published from January 1998 to March 2019.

RESULTS

Forty-three studies met the inclusion criteria. Among AUFI cases, viral aetiologies at 18.5% (14888) were more common than bacterial aetiologies (12.9% [10384]). From 80,554 cases, dengue fever was the most common aetiology (11.8%, 9511), followed by leptospirosis (4.4%, 3549), typhoid (4.0%, 3258), scrub typhus (4.0%, 3243) and influenza other than H1N1 (3.1%, 2514). In both adults and children: dengue fever was the leading cause of AUFI with 16.6% (1928) and 18.7% (1281) of the total cases. In admitted patients, dengue fever was the main cause of AUFI at 16.4% (2377), however leptospirosis at 13.9% (2090) was the main cause of AUFI for outpatients. In South Asia, dengue fever was the main cause of AUFI, causing 12.0% (6821) of cases, whereas in Southeast Asia, leptospirosis was the main diagnosis, causing 12.1% (2861) of cases.

CONCLUSIONS

In this study the most common causes of AUFI were viral, followed by bacterial and protozoal (malaria) infections. Dengue was the commonest virus that caused AUFI while leptospirosis and typhoid were important bacterial infectious causes. Therefore, it is imperative to maintain a sound epidemiological knowledge of AUFI so that evidence-based diagnostic criteria and treatment guidelines can be developed.

Classification of dengue cases in Southwest India based on the WHO systems-a retrospective analysis

Background

The WHO dengue classification 1997 was revised in 2009 and the revised classification system has now been in use for the past decade. This study was carried out to compare the 1997 and revised classifications in assessing the severity of dengue infection among all age groups during a dengue outbreak in southwest India.

Methodology

This retrospective cross-sectional study was carried out including serologically confirmed dengue cases. A total of 1033 dengue cases were classified on the basis of the 1997 WHO classification and 2009 revised classification. The statistical analysis was carried out using SPSS 15.0 for Windows (SPSSTM Inc, Chicago, IL, USA).

Results

Both the 1997 and revised WHO classifications were applied to 1033 confirmed dengue cases, including 692 males (67%) and 341 females (33%). The median age of the study participants was 23 years (IQR 10-33), including 112 (10.8%) children at and below the age of 5 years. The level of agreement between the two systems of classification was poor (kappa=0.143, 0.055-0.198, p-value <0.001).

Conclusion

A greater sensitivity and specificity of the revised classification was observed in comparison with the 1997 WHO classification. In the context of changing dengue epidemiology and geographical expansion, the revised classification is helpful in the identification of severe cases, facilitating timely management.