Age distribution of dengue cases in southern Vietnam from 2000 to 2015

Machine Learning Nomogram for Predicting Dengue Shock Syndrome in Pediatric Patients With Dengue Fever in Vietnam

Background Early identification of pediatric patients at high risk for dengue shock syndrome (DSS) is crucial to enable timely and appropriate clinical interventions. However, the application of machine learning (ML) models for predicting DSS risk remains underexplored. Objective This study aimed to develop and validate a ML-based nomogram for predicting DSS risk in pediatric patients with dengue fever, supporting clinical decision-making. Methods A prospective study was conducted on 230 children with dengue fever admitted to Can Tho Children's Hospital, Vietnam, from January 2020 to December 2022. Clinical and laboratory data were collected and analyzed using R software (version 4.4.1). Six ML algorithms were used to develop risk prediction models for hospitalized pediatric patients with dengue, and their predictive performances were compared. The best-performing model was used to construct a nomogram for DSS prediction. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC), and the calibration of the nomogram was assessed using a calibration curve. Results Among the 230 dengue patients enrolled, 124 (53.9%) were male, with a median age of 11 years (IQR: 8-13 years). The cohort was randomly divided into a training set (n = 173) and a test set (n = 57). Five key predictors selected for the nomogram were albumin, activated partial thromboplastin time (APTT), fibrinogen, aspartate aminotransferase (AST), and platelet count. In the test set, the AUROC for the six models ranged from 0.888 to 0.945. The random forest model demonstrated the best performance, with an AUROC of 0.945 (95% CI: 0.886-1.000), an accuracy of 0.951 (95% CI: 0.865-0.989), sensitivity of 0.894, specificity of 0.976, and a Kappa score of 0.884. Conclusions ML-based models can be established and potentially help identify hospitalized pediatric patients with dengue who are at high risk of progressing to DSS. The proposed nomogram may be a valuable tool for predicting DSS in clinical practice.

Assessing the global dengue burden: Incidence, mortality, and disability trends over three decades

BACKGROUND

Dengue, the fastest-spreading vector-borne disease (VBD), significantly burdens global health systems. This study analyzed the trends in the global burden of dengue from 1990 to 2021, utilizing data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD 2021).

METHODOLOGY/PRINCIPAL FINDINGS

We retrieved data from GBD 2021 regarding dengue, including the number of incidences and age-standardized incidence rate (ASIR), the number of deaths and age-standardized death rate (ASDR), disability-adjusted life-years (DALYs) and age-standardized DALYs. The estimated annual percentage change (EAPC) of ASIR, ASDR, and standardized DALYs rate was calculated to quantify trends over time. In addition, the correlations between dengue burden and sea level rise, as well as the Socio-Demographic Index (SDI), were evaluated. In this study, it was observed that from 1990 to 2021, the global incidence of dengue escalated from 26.45 million to 58.96 million cases, accompanied by an increase in related deaths from 14,315 to 29,075, and DALYs rising from 1.25 million to 2.08 million years. These data collectively indicate that the disease burden approximately doubled, with South Asia, Southeast Asia, and tropical Latin America being the most severely affected regions. The disease burden remained substantial in middle and low-middle-SDI regions, whereas high-middle and high SDI regions experienced pronounced growth rates in ASIR, ASDR, and age-standardized DALYs rate. Adolescents and the elderly showed higher incidence, yet children under 5 had the highest DALYs. Correlation analyses revealed an inverted U-shaped relationship between the SDI and both the ASDR and age-standardized DALYs rate, and changes in sea level height strongly correlated with the overall dengue burden.

CONCLUSIONS/SIGNIFICANCE

The global dengue burden has surged due to climate change, vector transmission, and population mobility. Increased focus and tailored control strategies are essential, particularly in South Asia, Southeast Asia, and Latin America.

Assessing the Diagnostic Value of Mean Monocyte Volume and Hematological Parameters in Predicting Dengue Fever: A Cross-Sectional Analysis

BACKGROUND AND AIM

Distinguishing dengue fever (DF) from other viral infections solely based on common presentations poses a challenge. Therefore, there is a pressing need for additional diagnostic parameters that are reliable, swift, and cost-effective. This study aims to provide novel insights into the diagnostic value of hematological parameters, particularly mean monocyte volume (MMV), in predicting DF in Kelantan, Malaysia.

METHODOLOGY

This cross-sectional study enrolled 162 patients with suspected DF symptoms. The diagnosis was confirmed through dengue immunoglobulin M (IgM) capture enzyme-linked immunosorbent assay (ELISA) or Dengue Early ELISA for nonstructural protein 1 (NS1) antigen detection. Hematological parameters were measured using the Coulter DxH 800 hematology analyzer (Beckman Coulter, Brea, CA), and the statistical analysis was performed using SPSS version 22 (IBM Corp., Armonk, NY).

RESULTS

A total of 108 patients tested positive for DF, while 54 tested negative. We observed significant differences in WBC count, platelet count, and monocyte percentage between patients with DF and non-DF, while no significant correlation was noted for MMV. Subsequent statistical analysis, including receiver operating characteristic (ROC) curve analysis, revealed that monocyte percentage exhibited the largest area under the curve (0.715), indicating its potential as moderate discriminative power in diagnosing DF.

CONCLUSIONS

Our study findings indicate that monocyte percentage and MMV outcomes are insufficient for predicting DF, suggesting potential areas for further research.

Estimating the force of infection of four dengue serotypes from serological studies in two regions of Vietnam

Dengue is endemic in Vietnam with circulation of all four serotypes (DENV1-4) all year-round. It is hard to estimate the disease's true serotype-specific transmission patterns from cases due to its high asymptomatic rate, low reporting rate and complex immunity and transmission dynamics. Seroprevalence studies have been used to great effect for understanding patterns of dengue transmission. We tested 991 population serum samples (ages 1-30 years, collected 2013 to 2017), 531 from Ho Chi Minh City and 460 from Khanh Hoa in Vietnam, using a flavivirus protein microarray assay. By applying our previously developed inference framework to the antibody profiles from this assay, we can (1) determine proportions of a population that have not been infected or infected, once, or more than once, and (2) infer the infecting serotype in those infected once. With these data, we then use mathematical models to estimate the force of infection (FOI) for all four DENV serotypes in HCMC and KH over 35 years up to 2017. Models with time-varying or serotype-specific DENV FOI assumptions fit the data better than constant FOI. Annual dengue FOI ranged from 0.005 (95%CI: 0.003-0.008) to 0.201 (95%CI: 0.174-0.228). FOI varied across serotypes, higher for DENV1 (95%CI: 0.033-0.048) and DENV2 (95%CI: 0.018-0.039) than DENV3 (95%CI: 0.007-0.010) and DENV4 (95%CI: 0.010-0.016). The use of the PMA on serial age-stratified cross-sectional samples increases the amount of information on transmission and population immunity, and should be considered for future dengue serological surveys, particularly to understand population immunity given vaccines with differential efficacy against serotypes, however, there remains limits to what can be inferred even using this assay.

Reduced protein-coding transcript diversity in severe dengue emphasises the role of alternative splicing

Dengue fever, a neglected tropical arboviral disease, has emerged as a global health concern in the past decade. Necessitating a nuanced comprehension of the intricate dynamics of host-virus interactions influencing disease severity, we analysed transcriptomic patterns using bulk RNA-seq from 112 age- and gender-matched NS1 antigen-confirmed hospital-admitted dengue patients with varying severity. Severe cases exhibited reduced platelet count, increased lymphocytosis, and neutropenia, indicating a dysregulated immune response. Using bulk RNA-seq, our analysis revealed a minimal overlap between the differentially expressed gene and transcript isoform, with a distinct expression pattern across the disease severity. Severe patients showed enrichment in retained intron and nonsense-mediated decay transcript biotypes, suggesting altered splicing efficiency. Furthermore, an up-regulated programmed cell death, a haemolytic response, and an impaired interferon and antiviral response at the transcript level were observed. We also identified the potential involvement of the RBM39 gene among others in the innate immune response during dengue viral pathogenesis, warranting further investigation. These findings provide valuable insights into potential therapeutic targets, underscoring the importance of exploring transcriptomic landscapes between different disease sub-phenotypes in infectious diseases.

Assessing the impact of emergency measures in varied population density areas during a large dengue outbreak

Background

The patterns of dengue are affected by many factors, including population density and climate factors. Densely populated areas could play a role in dengue transmission due to increased human-mosquito contacts, the presence of more diverse and suitable vector habitats and breeding sites, and changes in land use. In addition to population densities, climatic factors such as temperature, relative humidity, and precipitation have been demonstrated to predict dengue patterns. To control dengue, emergency measures should focus on vector management. Most approaches to assessing emergency responses to dengue risks involve applying simulation models or describing emergency activities and the results of implementing those responses. Research using real-world data with analytical methods to evaluate emergency responses to dengue has been limited. This study investigated emergency control measures associated with dengue risks in areas with high and low population densities, considering their different control capacities.

Methodology

Data from the 2015 dengue outbreak in Kaohsiung City, Taiwan, were utilized. The government database provided information on confirmed dengue cases, emergency control measures, and climatic data. The study employed a distributed lag non-linear model (DLNM) to assess the effect of emergency control measures and their time lags on dengue risk.

Principal findings

The findings revealed that in areas with high population density, the absence of emergency measures significantly elevated the risks of dengue. However, implementing emergency measures, especially a higher number, was associated with lower risks. In contrast, in areas with low population density, the risks of dengue were only significantly elevated at the 1st week lag if no emergency control measures were implemented. When emergency activities were carried out, the risks of dengue significantly decreased only for the 1st week lag.

Conclusions

Our findings reveal distinct exposure-lag-response patterns in the associations between emergency control measures and dengue in areas with high and low population density. In regions with a high population density, implementing emergency activities during a significant dengue outbreak is crucial for reducing the risk. Conversely, in areas of low population density, the necessity of applying emergency activities may be less pronounced. The implications of this study on dengue management could provide valuable insights for health authorities dealing with limited resources.

Proceedings of the 6th Asia Dengue Summit, June 2023

The 6th Asia Dengue Summit (ADS) themed "Road Map to Zero Dengue Death" was held in Thailand from 15th-16th June 2023. The summit was hosted by Tropical Medicine Cluster, Chulalongkorn University, Bangkok, Thailand in conjunction with Queen Saovabha Memorial Institute, The Thai Red Cross Society; Faculty of Tropical Medicine, Mahidol University; and the Ministry of Public Health. The 6th ADS was convened by Asia Dengue Voice and Action (ADVA); Global Dengue and Aedes Transmitted Diseases Consortium (GDAC); Southeast Asian Ministers of Education Tropical Medicine and Public Health Network (SEAMEO TROPMED); Fondation Mérieux (FMx) and the International Society for Neglected Tropical Diseases (ISNTD). Dengue experts from academia and research, and representatives from the Ministries of Health, Regional and Global World Health Organization (WHO) and International Vaccine Institute (IVI) participated in the three-day summit. With more than 51 speakers and 451 delegates from over 24 countries, 10 symposiums, and 2 full days, the 6th ADS highlighted the growing threat of dengue and its antigenic evolution, flagged the urgent need to overcome vaccine hesitancy and misinformation crisis, and focused on dengue control policies, newer diagnostics, therapeutics and vaccines, travel-associated dengue, and strategies to improve community involvement.

Trends in emerging vector-borne viral infections and their outcome in children over two decades

This review utilizes quatitative methods and bibliometric data to analyse the trends of emerging and re-emerging vector-borne diseases, with a focus on their impact on pediatric population. To conduct this analysis, a systematic search of PubMed articles from the past two decades was performed, specifically looking at 26 different vector-borne viruses listed in WHO and CDC list of vector-borne viruses. The review found that diseases like Dengue, Zika, West Nile, and Chikungunya were frequently discussed in the literature. On the other hand, diseases such as Tick-borne encephalitis, Rift Valley fever, Venezuelan equine encephalitis, Sindbis fever, Venezuelan equine encephalitis, Ross River virus, and Eastern equine encephalitis showed an upward trend in publications, indicating potential resurgence. In addition to discussing trends and patterns, the review delves into the clinical manifestations and long-term effects of the top 10 viruses in children. It highlights various factors including deforestation, urbanization, global travel, and immunosuppression that contribute to disease emergence and resurgence. To effectively combat these vector-borne diseases, continuous surveillance is crucial. The review also emphasizes the importance of increased vaccination efforts and targeted research to address the health challenges they pose. IMPACT: This review employs quantitative analysis of publications to elucidate trends in emerging pediatric vector-borne viral diseases over two decades. Dengue, the most prevalent of these diseases, has spread to new regions. New strains of Japanese Encephalitis have caused outbreaks. Resurgence of Tick-borne Encephalitis, West Nile, and Yellow Fever due to vaccine hesitancy has also transpired. Continuous global surveillance, increased vaccination, and research into novel therapeutics are imperative to combat the substantial morbidity and mortality burden these diseases pose for children worldwide.

Interactions between climate change, urban infrastructure and mobility are driving dengue emergence in Vietnam

Dengue is expanding globally, but how dengue emergence is shaped locally by interactions between climatic and socio-environmental factors is not well understood. Here, we investigate the drivers of dengue incidence and emergence in Vietnam, through analysing 23 years of district-level case data spanning a period of significant socioeconomic change (1998-2020). We show that urban infrastructure factors (sanitation, water supply, long-term urban growth) predict local spatial patterns of dengue incidence, while human mobility is a more influential driver in subtropical northern regions than the endemic south. Temperature is the dominant factor shaping dengue's distribution and dynamics, and using long-term reanalysis temperature data we show that warming since 1950 has expanded transmission risk throughout Vietnam, and most strongly in current dengue emergence hotspots (e.g., southern central regions, Ha Noi). In contrast, effects of hydrometeorology are complex, multi-scalar and dependent on local context: risk increases under either short-term precipitation excess or long-term drought, but improvements in water supply mitigate drought-associated risks except under extreme conditions. Our findings challenge the assumption that dengue is an urban disease, instead suggesting that incidence peaks in transitional landscapes with intermediate infrastructure provision, and provide evidence that interactions between recent climate change and mobility are contributing to dengue's expansion throughout Vietnam.

Serological and Molecular Epidemiology of Chikungunya Virus Infection in Vietnam, 2017-2019

Chikungunya fever is an acute febrile illness caused by the chikungunya virus (CHIKV), which is transmitted by Aedes mosquitoes. Since 1965, only a few studies with limited scope have been conducted on CHIKV in Vietnam. Thus, this study aimed to determine the seroprevalence and molecular epidemiology of CHIKV infection among febrile patients in Vietnam from 2017 to 2019. A total of 1063 serum samples from 31 provinces were collected and tested for anti-CHIKV IgM and IgG ELISA. The 50% focus reduction neutralization test (FRNT50) was used to confirm CHIKV-neutralizing antibodies. Quantitative real-time RT-PCR (RT-qPCR) was performed to confirm the presence of the CHIKV genome. The results showed that 15.9% (169/1063) of the patients had anti-CHIKV IgM antibodies, 20.1% (214/1063) had anti-CHIKV IgG antibodies, 10.4% (111/1063) had CHIKV-neutralizing antibodies, and 27.7% (130/469) of the samples were positive in RT-qPCR analysis. The E1 CHIKV genome sequences were detected among the positive RT-qPCR samples. Our identified sequences belonged to the East/Central/South/African (ECSA) genotype, which has been prevalent in Vietnam previously, suggesting CHIKV has been maintained and is endemic in Vietnam. This study demonstrates a high prevalence of CHIKV infection in Vietnam and calls for an annual surveillance program to understand its impact.