BACKGROUND: Dengue fever (DF) has emerged as a significant public health concern in China. The spatiotemporal patterns and underlying influencing its spread, however, remain elusive. This study aims to identify the factors driving these variations and to assess the city-level risk of DF epidemics in China.
METHODS: We analyzed the frequency, intensity, and distribution of DF cases in China from 2003 to 2022 and evaluated 11 natural and socioeconomic factors as potential drivers. Using the random forest (RF) model, we assessed the contributions of these factors to local DF epidemics and predicted the corresponding city-level risk.
RESULTS: Between 2003 and 2022, there was a notable correlation between local and imported DF epidemics in case numbers (r = 0.41, P < 0.01) and affected cities (r = 0.79, P < 0.01). With the increase in the frequency and intensity of imported epidemics, local epidemics have become more severe. Their occurrence has increased from five to eight months per year, with case numbers spanning from 14 to 6641 per month. The spatial distribution of city-level DF epidemics aligns with the geographical divisions defined by the Huhuanyong Line (Hu Line) and Qin Mountain-Huai River Line (Q-H Line) and matched well with the city-level time windows for either mosquito vector activity (83.59%) or DF transmission (95.74%). The RF models achieved a high performance (AUC = 0.92) when considering the time windows. Importantly, they identified imported cases as the primary influencing factor, contributing significantly (24.82%) to local DF epidemics at the city level in the eastern region of the Hu Line (E-H region). Moreover, imported cases were found to have a linear promoting impact on local epidemics, while five climatic and six socioeconomic factors exhibited nonlinear effects (promoting or inhibiting) with varying inflection values. Additionally, this model demonstrated outstanding accuracy (hitting ratio = 95.56%) in predicting the city-level risks of local epidemics in China.
CONCLUSIONS: China is experiencing an increasing occurrence of sporadic local DF epidemics driven by an unavoidably higher frequency and intensity of imported DF epidemics. This research offers valuable insights for health authorities to strengthen their intervention capabilities against this disease.

An outbreak of dengue fever struck Tikarapada village, Rayagada district (April 2020). Among 117 fever cases, 49 tested positive for the dengue NS1 antigen. To identify mosquito-related factors in the outbreak, a survey of 101 houses found Aedes breeding sites in 11.6% of containers. Aedes aegypti (79%) and Aedes albopictus (21%) emerged from collected pupae. The village exhibited high (house index = 24.8), (container index = 11.6), (pupal index = 32.7), and (Breteau index = 40.6) indices. The findings confirmed the presence of Aedes and ample breeding sites, suggesting their role in the outbreak. A report recommending integrated vector control measures was submitted to district and state health authorities.

The pandemic due to severe respiratory syndrome coronavirus 2 (SARS-Cov-2) was one of the most damaging healthcare emergencies the world has ever seen. Co-infection with dengue virus in COVID-19-positive patients is an additional challenge especially in dengue-endemic areas. Both dengue and COVID-19 infection cause increased morbidity and adverse outcomes in pregnant women, and simultaneous infection of these two illnesses can be further detrimental and sometimes fatal in pregnant women. Here, we present a case of a pregnant woman in her early second trimester with co-infection of dengue and moderate COVID-19 disease who was managed successfully and had a favorable outcome.

BACKGROUND: Dengue is a leading cause of febrile illness among international travellers. We aimed to describe the epidemiology and clinical characteristics of imported dengue in returning travellers evaluated at GeoSentinel sites from 2007-2022.
METHODS: We retrieved GeoSentinel records of dengue among travellers residing in non-endemic countries. We considered dengue confirmed when diagnosed by a positive DENV-specific RT-PCR, positive NS-1 antigen, and/or anti-DENV IgG seroconversion, and probable when diagnosed by single anti-DENV IgM or high titre anti-DENV IgG detection. Severe dengue was defined as evidence of clinically significant plasma leakage or bleeding, organ failure, or shock, according to the 2009 WHO guidance. Complicated dengue was defined as either severe dengue or dengue with presence of any warning sign. Analyses were descriptive.
RESULTS: This analysis included 5958 travellers with confirmed (n = 4859; 81.6%) or probable (n = 1099; 18.4%) dengue. The median age was 33 years (range: < 1-91); 3007 (50.5%) travellers were female. The median travel duration was 21 days (interquartile range [IQR]: 15-32). The median time between illness onset and GeoSentinel site visit was 7 days (IQR: 4-15). The most frequent reasons for travel were tourism (67.3%), visiting friends or relatives (12.2%), and business (11.0%). The most frequent regions of acquisition were Southeast Asia (50.4%), South-Central Asia (14.9%), the Caribbean (10.9%), and South America (9.2%). Ninety-five (1.6%) travellers had complicated dengue, of whom 27 (0.5%) had severe dengue, and one died. Of 2710 travellers with data available, 724 (26.7%) were hospitalized. The largest number of cases (n = 835) was reported in 2019.
CONCLUSIONS: A broad range of international travellers should be aware of the risk of acquiring dengue and receive appropriate pretravel counselling regarding preventive measures. Prospective cohort studies are needed to further elucidate dengue risk by destination and over time, as well as severe outcomes and prolonged morbidity (long-dengue) due to travel-related dengue.

Dengue fever is a mosquito-borne viral disease caused by the dengue virus (DENV). It poses a public health threat globally and, while most people with dengue have mild symptoms or are asymptomatic, approximately 5% of affected individuals develop severe disease and need hospital care. However, knowledge of the molecular mechanisms underlying dengue infection and the interaction between the virus and its host remains limited. In the present study, we performed a quantitative proteomic and N-glycoproteomic analysis of serum from 19 patients with dengue and 11 healthy people. The results revealed distinct proteomic and N-glycoproteomic landscapes between the two groups. Notably, we report for the first time the changes in the serum N glycosylation pattern following dengue infection and provide abundant information on glycoproteins, glycosylation sites, and intact N-glycopeptides using recently developed site-specific glycoproteomic approaches. Furthermore, a series of key functional pathways in proteomic and N-glycoproteomic were identified. Collectively, our findings significantly improve understanding of host and DENV interactions and the general pathogenesis and pathology of DENV, laying a foundation for functional studies of glycosylation and glycan structures in dengue infection.

UNASSIGNED: Dengue disease severity and progression are determined by the host immune response, with both pro- and anti-inflammatory cytokines are key mediators.
UNASSIGNED: To study pro- and anti-inflammatory cytokines across dengue severity and as a biomarker for predicting severe dengue infection.
UNASSIGNED: Hospital-based cross-sectional study was conducted on 125 dengue-positive subjects across the 5-60 years age group of either gender in 2022.
UNASSIGNED: Haematological parameters and blood samples were drawn to measure cytokines IL6, IL-10 and TNF alpha using the ELISA technique.
UNASSIGNED: One-way ANOVA and the Kruskal - Wallis test were used to compare the dependent variables across categories of the dengue spectrum. Receiver operating characteristic curve was drawn to calculate the predictability of the cytokines as a predictor of severe dengue. A P < 0.05 was considered significant.
UNASSIGNED: 34.4% of cases had severe dengue infection with 53.2% of severe cases reported in >40 years of age. Only IL-6 levels significantly increased (P < 0.01) across the spectrum of dengue infection across age groups >20 years with a consistent and significant fall in platelet levels (P < 0.01). The accuracy of IL-6 to predict severe dengue was 74.4% and platelet count was 16.2%.
UNASSIGNED: Only IL-6 cytokine levels were significantly increased across the spectrum of dengue infection observed in age >20 years and can significantly predict the probability of severe dengue by 74% (sensitivity 81.4%). A significant decrease in platelet values is consistent with the severity but is not a good predictor for severe dengue infection.

The envelope protein of dengue virus (DENV) is a primary target of the humoral immune response. The domain III of the DENV envelope protein (EDIII) is known to be the target of multiple potently neutralizing antibodies. One such antibody is 3H5, a mouse antibody that binds strongly to EDIII and potently neutralizes DENV serotype 2 (DENV-2) with unusually minimal antibody-dependent enhancement (ADE). To selectively display the binding epitope of 3H5, we strategically modified DENV-2 EDIII by shielding other known epitopes with engineered N-glycosylation sites. The modifications resulted in a glycosylated EDIII antigen termed \"EDIII mutant N\". This antigen was successfully used to sift through a dengue-immune scFv-phage library to select for scFv antibodies that bind to or closely surround the 3H5 epitope. The selected scFv antibodies were expressed as full-length human antibodies and showed potent neutralization activity to DENV-2 with low or negligible ADE resembling 3H5. These findings not only demonstrate the capability of the N-glycosylated EDIII mutant N as a tool to drive an epitope-directed antibody selection campaign but also highlight its potential as a dengue immunogen. This glycosylated antigen shows promise in focusing the antibody response toward a potently neutralizing epitope while reducing the risk of antibody-dependent enhancement.

System Dynamics (SD) models have been used to understand complex, multi-faceted dengue transmission dynamics, but a gap persists between research and actionable public health tools for decision-making. Spain is an at-risk country of imported dengue outbreaks, but only qualitative assessments are available to guide public health action and control. We propose a modular SD model combining temperature-dependent vector population, transmission parameters, and epidemiological interactions to simulate outbreaks from imported cases accounting for heterogeneous local climate-related transmission patterns. Under our assumptions, 15 provinces sustain vector populations capable of generating outbreaks from imported cases, with heterogeneous risk profiles regarding seasonality, magnitude and risk window shifting from late Spring to early Autum. Results being relative to given vector-to-human populations allow flexibility when translating outcomes between geographic scales. The model and the framework are meant to serve public health by incorporating transmission dynamics and quantitative-qualitative input to the evidence-based decision-making chain. It is a flexible tool that can easily adapt to changing contexts, parametrizations and epidemiological settings thanks to the modular approach.

BACKGROUND: Obesity and diabetes are known risk factors for severe dengue. Therefore, we sought to investigate the association of obesity with increased risk of hospitalization, as there is limited information.
RESULTS: Children aged 10 to 18 years (n = 4782), were recruited from 9 districts in Sri Lanka using a stratified multi-stage cluster sampling method. Details of previous admissions to hospital due to dengue and anthropometric measurements were recorded and seropositivity rates for dengue were assessed. The body mass index (BMI) centile in children aged 10 to 18, was derived by plotting the values on the WHO BMI-for-age growth charts, to acquire the percentile ranking.
RESULTS: Although the dengue seropositivity rates were similar in children of the different BMI centiles, 12/66 (18.2%) seropositive children with a BMI centile >97th, had been hospitalized for dengue, compared to 103/1086 (9.48%) of children with a BMI centile of <97th. The logistic regression model suggested that BMI centiles 50th to 85th (OR = 1.06, 95% CI, 1.00 to 1.11, p = 0.048) and BMI centile of >97th (OR 2.33, 95% CI, 1.47 to 3.67, p = 0.0003) was significantly associated with hospitalization when compared to children in other BMI categories.
CONCLUSIONS: Obesity appears to be associated with an increased risk of hospitalization in dengue, which should be further investigated in longitudinal prospective studies. With the increase in obesity in many countries, it would be important to create awareness regarding obesity and risk of severe disease and hospitalization in dengue.

UNASSIGNED: Dengue is one of the neglected tropical diseases, with a wide spectrum of diseases, ranging from acute febrile illness dengue fever to life-threatening dengue hemorrhagic fever or dengue shock syndrome. In recent years, it has become a major public health concern in many nonendemic areas as well.
UNASSIGNED: A secondary data analysis of records available with district Integrated Disease Surveillance Programme cell was conducted to study distribution (time, place, and person) of dengue from 2017 to 2022 in Kangra, a sub-Himalayan district of Himachal Pradesh (HP).
UNASSIGNED: In the evaluated period (2017-2022), a total of 6008 cases suspected of dengue were tested and test positivity of 7% (441) with male gender predominance was found. Mean age of the diagnosed cases was 37.7 ± 16.8 years. A seasonal trend was observed starting from late August to November in all study years.
UNASSIGNED: Dengue is still a neglected disease, but it has shown its presence especially in this part of HP, indicating the need for better preparation and sensitization of vector-borne disease control program activities, especially in post-monsoon, to prevent future epidemics.