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Close vital signs monitoring is crucial for the clinical management of patients with dengue. We investigated performance of a non-invasive wearable utilising photoplethysmography (PPG), to provide real-time risk prediction in hospitalised individuals. We performed a prospective observational clinical study in Vietnam between January 2020 and October 2022: 153 patients were included in analyses, providing 1353 h of PPG data. Using a multi-modal transformer approach, 10-min PPG waveform segments and basic clinical data (age, sex, clinical features on admission) were used as features to continuously forecast clinical state 2 h ahead. Prediction of low-risk states (17,939/80,843; 22.1%), defined by NEWS2 and mSOFA < 6, was associated with an area under the precision-recall curve of 0.67 and an area under the receiver operator curve of 0.83. Implementation of such interventions could provide cost-effective triage and clinical care in dengue, offering opportunities for safe ambulatory patient management. [ABSTRACT FROM AUTHOR]

Prophylactic drugs against dengue are currently under development. In this study, we explored how such prophylactic approaches might affect dengue cases in four communes of Nha Trang City, Vietnam. A community level dengue transmission survey indicated high levels of previous exposure to dengue (89.7%; 95% CI: 87.2,92.0). We fitted a spatially explicit model to an observed outbreak and simulated likely effectiveness of Case-Area Targeted Interventions (CATI) and One-Time Mass Distribution (OTMD) of drug and vector control strategies. Increasing the radius and effectiveness and decreasing delay of CATI was most effective, with drugs being more effective in averting dengue cases than vector control. Using an OTMD approach early in the outbreak required the least number of treatments to avert a case, suggesting that OTMD strategies should be considered as pre-emptive rather than reactive strategies. These findings show that pre-emptive interventions can substantially reduce the burden of dengue outbreaks in endemic settings. Author summary: Dengue is a mosquito-transmitted virus that is a leading cause of hospitalisation and death in Asian and Latin American countries. Protection against dengue infection mainly relies on mosquito control, but the current development of drugs against the virus opens new perspectives for prevention. To develop efficient prevention strategies, it is important to understand how prevalent and transmissible the virus is in a given population. In this study, we conducted a large serological survey in Nha Trang City, Vietnam, and developed a mathematical model to simulate the effect of preventive antiviral treatment on dengue outbreaks in that population. We compared the strength of these effects to that of other prevention startegies, such as mosquito control. We found that a large proportion of the population had been previously infected by dengue virus. In this context, our simulations showed that drugs are more effective in preventing dengue cases than mosquito control, and that these strategies are most effective when the radius of intervention increases and the delay of intervention decreases. These findings show that preventive administration of antivirals during outbreaks can substantially reduce the spread of dengue virus in part of the world where it is highly prevalent. [ABSTRACT FROM AUTHOR]

Background: Viremia is a critical factor in understanding the pathogenesis of dengue infection, but limited data exist on viremia kinetics. This study aimed to investigate the kinetics of viremia and its effects on subsequent platelet count, severe dengue, and plasma leakage. Methods: We pooled data from three studies conducted in Vietnam between 2000 and 2016, involving 2340 dengue patients with daily viremia measurements and platelet counts after symptom onset. Viremia kinetics were assessed using a random effects model that accounted for left-censored data. The effects of viremia on subsequent platelet count and clinical outcomes were examined using a landmark approach with a random effects model and logistic regression model with generalized estimating equations, respectively. The rate of viremia decline was derived from the model of viremia kinetics. Its effect on the clinical outcomes was assessed by logistic regression models. Results: Viremia levels rapidly decreased following symptom onset, with variations observed depending on the infecting serotype. DENV-1 exhibited the highest mean viremia levels during the first 5–6 days, while DENV-4 demonstrated the shortest clearance time. Higher viremia levels were associated with decreased subsequent platelet counts from day 6 onwards. Elevated viremia levels on each illness day increased the risk of developing severe dengue and plasma leakage. However, the effect size decreased with later illness days. A more rapid decline in viremia is associated with a reduced risk of the clinical outcomes. Conclusions: This study provides comprehensive insights into viremia kinetics and its effect on subsequent platelet count and clinical outcomes in dengue patients. Our findings underscore the importance of measuring viremia levels during the early febrile phase for dengue studies and support the use of viremia kinetics as outcome for phase-2 dengue therapeutic trials. Funding: Wellcome Trust and European Union Seventh Framework Programme. [ABSTRACT FROM AUTHOR]

Introduction: After the Coronavirus Disease 2019 pandemic, a high number of cases and severe dengue in children were reported in some provinces in the south of Vietnam. This study aimed to determine the distribution of dengue virus serotypes and their correlation with demographic factors, disease severity, clinical manifestations, and laboratory findings. Methodology: This study employed a cross-sectional design. Ninety-six dengue-infected children admitted to Can Tho Children's Hospital between October 2022 and March 2023 were included. Confirmation of dengue infection was achieved through the real-time polymerase chain reaction (RT-PCR). Results: Among the identified serotypes, DENV-2 accounted for the highest proportion (71.87%), followed by DENV-1 (23.96%), and DENV-4 (4.17%). DENV-3 was not detected. No significant demographic, disease severity, or laboratory differences were observed among the identified dengue serotypes. However, DENV-2 was associated with a higher occurrence of mucous membrane hemorrhages and gastrointestinal bleeding compared to other serotypes. Conclusions: Although DENV-2 was the most prevalent serotype responsible for dengue in children in southern Vietnam, it did not lead to more severe cases compared to other serotypes. This finding is crucial for evaluating the illness's prognosis. [ABSTRACT FROM AUTHOR]

Dengue shock (DS) is the most severe complication of dengue infection; endothelial hyperpermeability leads to profound plasma leakage, hypovolaemia and extravascular fluid accumulation. At present, the only treatment is supportive with intravenous fluid, but targeted endothelial stabilising therapies and host immune modulators are needed. With the aim of prioritising potential therapeutics, we conducted a prospective observational study of adults (≥16 years) with DS in Vietnam from 2019–2022, comparing the pathophysiology underlying circulatory failure with patients with septic shock (SS), and investigating the association of biomarkers with clinical severity (SOFA score, ICU admission, mortality) and pulmonary vascular leak (daily lung ultrasound for interstitial and pleural fluid). Plasma was collected at enrolment, 48 hours later and hospital discharge. We measured biomarkers of inflammation (IL-6, ferritin), endothelial activation (Ang-1, Ang-2, sTie-2, VCAM-1) and endothelial glycocalyx breakdown (hyaluronan, heparan sulfate, endocan, syndecan-1). We enrolled 135 patients with DS (median age 26, median SOFA score 7, 34 required ICU admission, 5 deaths), together with 37 patients with SS and 25 healthy controls. Within the DS group, IL-6 and ferritin were associated with admission SOFA score (IL-6: βeta0.70, p<0.001 & ferritin: βeta0.45, p<0.001), ICU admission (IL-6: OR 2.6, p<0.001 & ferritin: OR 1.55, p<0.001) and mortality (IL-6: OR 4.49, p = 0.005 & ferritin: OR 13.8, p = 0.02); both biomarkers discriminated survivors and non-survivors at 48 hours and all patients who died from DS had pre-mortem ferritin ≥100,000ng/ml. IL-6 most strongly correlated with severity of pulmonary vascular leakage (R = 0.41, p<0.001). Ang-2 correlated with pulmonary vascular leak (R = 0.33, p<0.001) and associated with SOFA score (β 0.81, p<0.001) and mortality (OR 8.06, p = 0.002). Ang-1 was associated with ICU admission (OR 1.6, p = 0.005) and mortality (OR 3.62, p = 0.006). All 4 glycocalyx biomarkers were positively associated with SOFA score, but only syndecan-1 was associated with ICU admission (OR 2.02, p<0.001) and mortality (OR 6.51, p<0.001). This study highlights the central role of hyperinflammation in determining outcomes from DS; the data suggest that anti-IL-1 and anti-IL-6 immune modulators and Tie2 agonists may be considered as candidates for therapeutic trials in severe dengue. Author summary: Dengue is the most common arboviral infection worldwide. Dengue shock is the most severe complication of dengue infection; patients develop marked plasma leakage, hypovolaemia and extravascular fluid accumulation. At present, the only treatment available is intravenous fluid, but targeted therapies are needed. With the aim of prioritizing potential therapeutics, we conducted a prospective observational study of 135 adults with dengue shock in Vietnam, investigating the association between biomarkers of inflammation, endothelial activation and endothelial glycocalyx breakdown and clinical severity, and comparing pathophysiology with patients with septic shock and healthy controls. In the dengue shock group, 5/135 patients died. The inflammatory biomarkers IL-6 and ferritin were associated with SOFA score, requirement for ICU admission and mortality. IL-6 most strongly correlated with severity of vascular leakage in the lung, measured by ultrasound. The endothelial biomarkers Angiopoietin-2 and syndecan-1 were both also associated with SOFA score and mortality. Our findings highlight the central role of hyperinflammation in determining outcomes from dengue shock; the data suggest that anti-IL-1 and anti-IL-6 immune modulators and Tie2 agonists may be considered as candidates for therapeutic trials in severe dengue. [ABSTRACT FROM AUTHOR]

Background: Dengue is one of the most common diseases in the tropics and subtropics. Whilst mortality is a rare event when adequate supportive care can be provided, a large number of patients get hospitalised with dengue every year that places a heavy burden on local health systems. A better understanding of the support required at the time of hospitalisation is therefore of critical importance for healthcare planning, especially when resources are limited during major outbreaks. Methods: Here we performed a retrospective analysis of clinical data from over 1500 individuals hospitalised with dengue in Vietnam between 2017 and 2019. Using a broad panel of potential biomarkers, we sought to evaluate robust predictors of prolonged hospitalisation periods. Results: Our analyses revealed a lead-time bias, whereby early admission to hospital correlates with longer hospital stays ‐ irrespective of disease severity. Importantly, taking into account the symptom duration prior to hospitalisation significantly affects observed associations between hospitalisation length and previously reported risk markers of prolonged stays, which themselves showed marked inter-annual variations. Once corrected for symptom duration, age, temperature at admission and elevated neutrophil-to-lymphocyte ratio were found predictive of longer hospitalisation periods. Conclusion: This study demonstrates that the time since dengue symptom onset is one of the most significant predictors for the length of hospital stays, independent of the assigned severity score. Pre-hospital symptom durations need to be accounted for to evaluate clinically relevant biomarkers of dengue hospitalisation trajectories. Author summary: Dengue places a significant burden on healthcare settings. Especially in low and middle income settings and during large outbreaks, allocation of limited resources to those at high risk of morbidity and mortality can be critically important. Various risk factors of severe infection outcomes and hospitalisation, such as secondary heterologous infection, have been described, yet reliable biomarkers predictive of prolonged stays once hospitalised are still lacking. In this work we analysed dengue hospitalisation data collected over a period of three consecutive years in Northern Vietnam, which revealed an unexpected negative correlation between dengue severity and length of hospitalisation. Further analysis showed that this was primarily driven by a longer period between symptom onset and admission in those patients with a higher severity score. Moreover, we found that this delay negated other observed correlates of prolonged hospital stays, which themselves revealed significant inter-annual variations. Taken together, this work demonstrates that time to admission is one of the strongest predictors of hospitalisation length and that this needs to be taken into consideration for finding reliable biomarkers of predicted healthcare needs in patients admitted to hospital due to dengue. [ABSTRACT FROM AUTHOR]

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. The geographic distribution of dengue has been expanding in recent decades, and Vietnam is one of the most severely affected countries. In this study, the authors use Bayesian hierarchical modelling to investigate the socio-environmental and climatic drivers of dengue incidence in Vietnam and how they vary across the country. [ABSTRACT FROM AUTHOR]

In 2022, a large dengue outbreak was reported in Vietnam, where dengue was endemic. A total of 1889 acute‐phase serum samples were collected from patients with suspected dengue at Vung Tau General Hospital, the core hospital in Vung Tau Province, southern Vietnam. Among the 1889 samples analyzed for laboratory confirmation of dengue virus (DENV) infection, 339 positive cases were identified, of which 130 were primary infections and 209 were secondary infections. DENV‐2 was the dominant serotype in both primary and secondary infection groups. Phylogenetic analysis based on sequences of the envelope protein‐coding region revealed the emergence of a new DENV‐2 lineage during this outbreak. [ABSTRACT FROM AUTHOR]

Problem Direct application of digital health technologies from high-income settings to low- and middle-income countries may be inappropriate due to challenges around data availability, implementation and regulation. Hence different approaches are needed. Approach Within the Viet Nam ICU Translational Applications Laboratory project, since 2018 we have been developing a wearable device for individual patient monitoring and a clinical assessment tool to improve dengue disease management. Working closely with local staff at the Hospital for Tropical Diseases, Ho Chi Minh City, we developed and tested a prototype of the wearable device. We obtained perspectives on design and use of the sensor from patients. To develop the assessment tool, we used existing research data sets, mapped workflows and clinical priorities, interviewed stakeholders and held workshops with hospital staff. Local setting In Viet Nam, a lower middle-income country, the health-care system is in the nascent stage of implementing digital health technologies. Relevant changes Based on patient feedback, we are altering the design of the wearable sensor to increase comfort. We built the user interface of the assessment tool based on the core functionalities selected by workshop attendees. The interface was subsequently tested for usability in an iterative manner by the clinical staff members. Lessons learnt The development and implementation of digital health technologies need an interoperable and appropriate plan for data management including collection, sharing and integration. Engagements and implementation studies should be conceptualized and conducted alongside the digital health technology development. The priorities of end-users, and understanding context and regulatory landscape are crucial for success. [ABSTRACT FROM AUTHOR]

Introduction: Dengue is a major public health challenge and a growing problem due to climate change. The release of Aedes aegypti mosquitoes infected with the intracellular bacterium Wolbachia is a novel form of vector control against dengue. However, there remains a need to evaluate the benefits of such an intervention at a large scale. In this paper, we evaluate the potential economic impact and cost-effectiveness of scaled Wolbachia deployments as a form of dengue control in Vietnam–targeted at the highest burden urban areas. Methods: Ten settings within Vietnam were identified as priority locations for potential future Wolbachia deployments (using a population replacement strategy). The effectiveness of Wolbachia deployments in reducing the incidence of symptomatic dengue cases was assumed to be 75%. We assumed that the intervention would maintain this effectiveness for at least 20 years (but tested this assumption in the sensitivity analysis). A cost-utility analysis and cost-benefit analysis were conducted. Results: From the health sector perspective, the Wolbachia intervention was projected to cost US$420 per disability-adjusted life year (DALY) averted. From the societal perspective, the overall cost-effectiveness ratio was negative, i.e. the economic benefits outweighed the costs. These results are contingent on the long-term effectiveness of Wolbachia releases being sustained for 20 years. However, the intervention was still classed as cost-effective across the majority of the settings when assuming only 10 years of benefits Conclusion: Overall, we found that targeting high burden cities with Wolbachia deployments would be a cost-effective intervention in Vietnam and generate notable broader benefits besides health gains. Author summary: Dengue is a major public health challenge and a growing problem due to climate change. The release of Aedes aegypti mosquitoes infected with the intracellular bacterium Wolbachia is a novel form of vector control against dengue. However, there remains a need to evaluate the health and economic benefits of such an intervention at a large scale, as well as its value for money. In this paper, we evaluate the potential economic impact and cost-effectiveness of scaled Wolbachia deployments as a form of dengue control in Vietnam–targeted at the highest burden urban areas. Ten settings within Vietnam were identified as priority locations for potential future Wolbachia deployments (using a population replacement strategy). We assumed that the effectiveness of Wolbachia deployments in reducing the incidence of symptomatic dengue cases would be 75%. We found that targeting high burden cities with Wolbachia deployments would be a cost-effective intervention in Vietnam and generate notable broader benefits besides health gains. Overall, this work highlights the value of investment in the scaled implementation of Wolbachia deployments as an effective and cost-effective tool for dengue control in Vietnam, and more generally for addressing the global challenge of dengue control. [ABSTRACT FROM AUTHOR]

Dengue virus (DENV), which has circulated in Vietnam for several decades, has multiple serotypes and genotypes. A 2019 dengue outbreak resulted in a larger number of cases than any other outbreak. We conducted a molecular characterization using samples collected in 2019–2020 from dengue patients in Hanoi and nearby cities located in northern Vietnam. The circulating serotypes were DENV-1 (25%, n = 22) and DENV-2 (73%, n = 64). Phylogenetic analyses revealed that all DENV-1 (n = 13) were genotype I and clustered to local strains circulating during the previous outbreak in the 2017, whereas DENV-2 consisted of two genotypes: Asian-I (n = 5), related to local strains from 2006–2022, and cosmopolitan (n = 18), the predominant genotype in this epidemic. The current cosmopolitan virus was identified as having an Asian-Pacific lineage. The virus was closely related to strains in other recent outbreaks in Southeast Asian countries and China. Multiple introductions occurred in 2016–2017, which were possibly from maritime Southeast Asia (Indonesia, Singapore, and Malaysia), mainland Southeast Asia (Cambodia and Thailand), or China, rather than from an expansion of localized Vietnamese cosmopolitan strains that were previously detected in the 2000s. We also analyzed the genetic relationship between Vietnam's cosmopolitan strain and recent global strains reported from Asia, Oceania, Africa, and South America. This analysis revealed that viruses of Asian-Pacific lineage are not restricted to Asia but have spread to Peru and Brazil in South America. [ABSTRACT FROM AUTHOR]

Background: Dengue is the most common vector-borne viral infection. In recent times, an increase in the age of cases with clinical dengue has been reported in the national surveillance system and published literature of Vietnam. This change not only alter the risk of transmission and disease burden in different populations but also will impact for prevention and control strategies. A retrospective study was conducted from 2000 to 2015 in 19 provinces of southern Vietnam to describe the changes in age distribution of dengue cases and circulating serotypes. Methodology/Principal findings: The study is a time trend analysis of the data aggregated from the database of dengue surveillance system. The database consisted of clinically diagnosed and laboratory-confirmed cases of dengue in southern Vietnam from 2000 to 2015. In the study period, the mean age of dengue cases increased from 12.2 ± 8.8 years old (y/o) to 16.8 ± 13.3 y/o between 2000 and 2015. Majority of severe cases were observed in the age group of 5–9 y/o and 10–14 y/o. Overall, the mortality and case fatality rates (CFR) were lowest during 2010 to 2015, and all four serotypes of dengue were observed. Conclusions/Significance: With the exception of severe form, the age distribution of clinical cases of dengue appears to be shifting towards older age groups. An increase in the mean age of clinical cases of dengue has been observed in southern Vietnam over the past decade, and the highest incidence was observed in age group of 5–14 y/o. All serotypes of dengue were in circulation. Author summary: Dengue is associated with significant health burden in southern Vietnam. A retrospective data analysis was conducted in this study to describe the age distribution of patients with dengue during 2000–2015 to inform prevention and management strategies. Data were collected from national surveillance system to describe the patterns and changes in reported cases over the time in terms of age distribution and strains in circulation. Since 2000, the age distribution of patients confirmed with dengue has increased, and the age shift occurring mainly from 5–9 y/o to 10–14 y/o. All four dengue serotypes were observed. [ABSTRACT FROM AUTHOR]

Background: Dengue is a common viral illness and severe disease results in life-threatening complications. Healthcare services in low- and middle-income countries treat the majority of dengue cases worldwide. However, the clinical decision-making processes which result in effective treatment are poorly characterised within this setting. In order to improve clinical care through interventions relating to digital clinical decision-support systems (CDSS), we set out to establish a framework for clinical decision-making in dengue management to inform implementation. Methods: We utilised process mapping and task analysis methods to characterise existing dengue management at the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam. This is a tertiary referral hospital which manages approximately 30,000 patients with dengue each year, accepting referrals from Ho Chi Minh city and the surrounding catchment area. Initial findings were expanded through semi-structured interviews with clinicians in order to understand clinical reasoning and cognitive factors in detail. A grounded theory was used for coding and emergent themes were developed through iterative discussions with clinician-researchers. Results: Key clinical decision-making points were identified: (i) at the initial patient evaluation for dengue diagnosis to decide on hospital admission and the provision of fluid/blood product therapy, (ii) in those patients who develop severe disease or other complications, (iii) at the point of recurrent shock in balancing the need for fluid therapy with complications of volume overload. From interviews the following themes were identified: prioritising clinical diagnosis and evaluation over existing diagnostics, the role of dengue guidelines published by the Ministry of Health, the impact of seasonality and caseload on decision-making strategies, and the potential role of digital decision-support and disease scoring tools. Conclusions: The study highlights the contemporary priorities in delivering clinical care to patients with dengue in an endemic setting. Key decision-making processes and the sources of information that were of the greatest utility were identified. These findings serve as a foundation for future clinical interventions and improvements in healthcare. Understanding the decision-making process in greater detail also allows for development and implementation of CDSS which are suited to the local context. [ABSTRACT FROM AUTHOR]

Dengue encephalitis is considered as a severe but unusual clinical presentation of dengue infection. Limited molecular information is available on the neurotropism of dengue virus (DENV), highlighting the need for further research. During a dengue outbreak in Vietnam in 2013, two DENV-3 strains were isolated, in which one was isolated from cerebrospinal fluid (CSF) samples from a dengue encephalitis patient and another strain was isolated from a patient with classical dengue fever in Hai Phong, Vietnam. DENV serotype-3 (DENV-3) isolated from these samples belonged to genotype III, marking the first report of this genotype in the country at that time. Genetic variation between both strains was elucidated by using a full genome sequencing by next-generation sequencing (NGS). The infectivity of the isolated DENV-3 strains was further characterized using human and mouse neuronal cell lines. Phylogenetic analysis of the isolates demonstrated high homogeneity between the CSF-derived and serum-derived DENV-3, in which the full genome sequences of the CSF-derived DENV-3 presented a Thr-1339-Ile mutation in the nonstructural 2A (NS2A) protein. The CSF-derived DENV-3 isolate grew preferentially in human neuronal cells, with a significant proportion of cells that were positive for nonstructural 1 (NS1), nonstructural 4B (NS4B), and nonstructural 5 (NS5) antigens. These results suggest that NS2A may be a crucial region in the neuropathogenesis of DENV-3 and its growth in human neuronal cells. Taken together, our results demonstrate that a CSF-derived DENV-3 has unique infectivity characteristics for human neuronal cells, which might play a crucial role in the neuropathogenesis of DENV infection. [ABSTRACT FROM AUTHOR]

We assessed predominantly pediatric patients in Vietnam with dengue and other febrile illness 3 months after acute illness. Among dengue patients, 47% reported ≥1 postacute symptom. Most resolved by 3 months, but alopecia and vision problems often persisted. Our findings provide additional evidence on postacute dengue burden and confirm children are affected. [ABSTRACT FROM AUTHOR]

Dengue virus (DENV) causes repeated outbreaks of disease in endemic areas, with patterns of local transmission strongly influenced by seasonality, importation via human movement, immunity, and vector control efforts. An understanding of how each of these interacts to enable endemic transmission (continual circulation of local virus strains) is largely unknown. There are times of the year when no cases are reported, often for extended periods of time, perhaps wrongly implying the successful eradication of a local strain from that area. Individuals who presented at a clinic or hospital in four communes in Nha Trang, Vietnam, were initially tested for DENV antigen presence. Enrolled positive individuals then had their corresponding household members invited to participate, and those who enrolled were tested for DENV. The presence of viral nucleic acid in all samples was confirmed using quantitative polymerase chain reaction, and positive samples were then whole-genome sequenced using an amplicon and target enrichment library preparation techniques and Illumina MiSeq sequencing technology. Generated consensus genome sequences were then analysed using phylogenetic tree reconstruction to categorise sequences into clades with a common ancestor, enabling investigations of both viral clade persistence and introductions. Hypothetical introduction dates were additionally assessed using a molecular clock model that calculated the time to the most recent common ancestor (TMRCA). We obtained 511 DENV whole-genome sequences covering four serotypes and more than ten distinct viral clades. For five of these clades, we had sufficient data to show that the same viral lineage persisted for at least several months. We noted that some clades persisted longer than others during the sampling time, and by comparison with other published sequences from elsewhere in Vietnam and around the world, we saw that at least two different viral lineages were introduced into the population during the study period (April 2017–2019). Next, by inferring the TMRCA from the construction of molecular clock phylogenies, we predicted that two of the viral lineages had been present in the study population for over a decade. We observed five viral lineages co-circulating in Nha Trang from three DENV serotypes, with two likely to have remained as uninterrupted transmission chains for a decade. This suggests clade cryptic persistence in the area, even during periods of low reported incidence. [ABSTRACT FROM AUTHOR]

Background: Dengue is a neglected tropical disease, for which no therapeutic agents have shown clinical efficacy to date. Clinical trials have used strikingly variable clinical endpoints, which hampers reproducibility and comparability of findings. We investigated a delta modified Sequential Organ Failure Assessment (delta mSOFA) score as a uniform composite clinical endpoint for use in clinical trials investigating therapeutics for moderate and severe dengue.Methods: We developed a modified SOFA score for dengue, measured and evaluated its performance at baseline and 48 h after enrolment in a prospective observational cohort of 124 adults admitted to a tertiary referral hospital in Vietnam with dengue shock. The modified SOFA score included pulse pressure in the cardiovascular component. Binary logistic regression, cox proportional hazard and linear regression models were used to estimate association between mSOFA, delta mSOFA and clinical outcomes.Results: The analysis included 124 adults with dengue shock. 29 (23.4%) patients required ICU admission for organ support or due to persistent haemodynamic instability: 9/124 (7.3%) required mechanical ventilation, 8/124 (6.5%) required vasopressors, 6/124 (4.8%) required haemofiltration and 5/124 (4.0%) patients died. In univariate analyses, higher baseline and delta (48 h) mSOFA score for dengue were associated with admission to ICU, requirement for organ support and mortality, duration of ICU and hospital admission and IV fluid use.Conclusions: The baseline and delta mSOFA scores for dengue performed well to discriminate patients with dengue shock by clinical outcomes, including duration of ICU and hospital admission, requirement for organ support and death. We plan to use delta mSOFA as the primary endpoint in an upcoming host-directed therapeutic trial and investigate the performance of this score in other phenotypes of severe dengue in adults and children. [ABSTRACT FROM AUTHOR]

Dengue is a viral disease that primarily affects tropical and subtropical regions and is especially prevalent in South-East Asia. This mosquito-borne disease sometimes triggers nationwide epidemics, which results in a large number of fatalities. The development of Dengue Haemorrhagic Fever (DHF) is where most cases occur, and a large portion of them are detected among children under the age of ten, with severe conditions often progressing to a critical state known as Dengue Shock Syndrome (DSS). In this study, we analysed two separate datasets from two different countries– Vietnam and Bangladesh, which we referred as VDengu and BDengue, respectively. For the VDengu dataset, as it was structured, supervised learning models were effective for predictive analysis, among which, the decision tree classifier XGBoost in particular produced the best outcome. Furthermore, Shapley Additive Explanation (SHAP) was used over the XGBoost model to assess the significance of individual attributes of the dataset. Among the significant attributes, we applied the SHAP dependence plot to identify the range for each attribute against the number of DHF or DSS cases. In parallel, the dataset from Bangladesh was unstructured; therefore, we applied an unsupervised learning technique, i.e., hierarchical clustering, to find clusters of vital blood components of the patients according to their complete blood count reports. The clusters were further analysed to find the attributes in the dataset that led to DSS or DHF. [ABSTRACT FROM AUTHOR]

Background: Dengue virus (DENV) infection is a global health concern of increasing magnitude. To target intervention strategies, accurate estimates of the force of infection (FOI) are necessary. Catalytic models have been widely used to estimate DENV FOI and rely on a binary classification of serostatus as seropositive or seronegative, according to pre-defined antibody thresholds. Previous work has demonstrated the use of thresholds can cause serostatus misclassification and biased estimates. In contrast, mixture models do not rely on thresholds and use the full distribution of antibody titres. To date, there has been limited application of mixture models to estimate DENV FOI. Methods: We compare the application of mixture models and time-constant and time-varying catalytic models to simulated data and to serological data collected in Vietnam from 2004 to 2009 (N ≥ 2178) and Indonesia in 2014 (N = 3194). Results: The simulation study showed larger mean FOI estimate bias from the time-constant and time-varying catalytic models (-0.007 (95% Confidence Interval (CI): -0.069, 0.029) and -0.006 (95% CI -0.095, 0.043)) than from the mixture model (0.001 (95% CI -0.036, 0.065)). Coverage of the true FOI was > 95% for estimates from both the time-varying catalytic and mixture model, however the latter had reduced uncertainty. When applied to real data from Vietnam, the mixture model frequently produced higher FOI and seroprevalence estimates than the catalytic models. Conclusions: Our results suggest mixture models represent valid, potentially less biased, alternatives to catalytic models, which could be particularly useful when estimating FOI from data with largely overlapping antibody titre distributions. Author summary: Characterising the transmission intensity of dengue virus is essential to inform the implementation of interventions, such as vector control and vaccination, and to better understand the environmental drivers of transmission locally and globally. It is therefore important to understand how methodological differences and model choice may influence the accuracy of estimates of transmission intensity. Using a simulation study, we assessed the performance of catalytic and mixture models to reconstruct the force of infection (FOI) from simulated antibody titre data. Furthermore, we estimated the FOI of dengue virus from antibody titre data collected in Vietnam and Indonesia. The models produced consistent estimates of FOI when they were applied to data with clear separation between the distributions of seronegative and seropositive antibody titres. We observed greater bias in FOI estimates obtained from catalytic models than from mixture models when they were applied to data with high overlap in the bimodal distribution of antibody titres. Our results indicate that mixture models could be preferential to estimate dengue virus FOI when the antibody titre distributions of the seronegative and seropositive components largely overlap. [ABSTRACT FROM AUTHOR]

Background: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. Objective: This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change. Methods: Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997–2013 were used to train models, which were then evaluated using data from 2014–2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Results and discussion: LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features. Conclusion: This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years. Author summary: Dengue fever (DF) represents a significant health burden worldwide and in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. This study aimed to use deep learning models to develop a prediction model of DF rates in Vietnam using a wide range of climate factors as input variables to inform public health responses for outbreak prevention in the context of future climate change. The study found that LSTM-ATT outperformed competing models, scoring average places of 1.60 for RMSE-based ranking and 1.90 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 12 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreaks up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. This is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich climate features, and it demonstrates the usefulness of deep learning models for climate-based DF forecasting. [ABSTRACT FROM AUTHOR]

Background: Characterising dengue virus (DENV) infection history at the point of care is challenging as it relies on intensive laboratory techniques. We investigated how combining different rapid diagnostic tests (RDTs) can be used to accurately determine the primary and post-primary DENV immune status of reporting patients during diagnosis. Methods and findings: Serum from cross-sectional surveys of acute suspected dengue patients in Indonesia (N:200) and Vietnam (N: 1,217) were assayed using dengue laboratory assays and RDTs. Using logistic regression modelling, we determined the probability of being DENV NS1, IgM and IgG RDT positive according to corresponding laboratory viremia, IgM and IgG ELISA metrics. Laboratory test thresholds for RDT positivity/negativity were calculated using Youden's J index and were utilized to estimate the RDT outcomes in patients from the Philippines, where only data for viremia, IgM and IgG were available (N:28,326). Lastly, the probabilities of being primary or post-primary according to every outcome using all RDTs, by day of fever, were calculated. Combining NS1, IgM and IgG RDTs captured 94.6% (52/55) and 95.4% (104/109) of laboratory-confirmed primary and post-primary DENV cases, respectively, during the first 5 days of fever. Laboratory test predicted, and actual, RDT outcomes had high agreement (79.5% (159/200)). Among patients from the Philippines, different combinations of estimated RDT outcomes were indicative of post-primary and primary immune status. Overall, IgG RDT positive results were confirmatory of post-primary infections. In contrast, IgG RDT negative results were suggestive of both primary and post-primary infections on days 1–2 of fever, yet were confirmatory of primary infections on days 3–5 of fever. Conclusion: We demonstrate how the primary and post-primary DENV immune status of reporting patients can be estimated at the point of care by combining NS1, IgM and IgG RDTs and considering the days since symptoms onset. This framework has the potential to strengthen surveillance operations and dengue prognosis, particularly in low resource settings. Author summary: Combined NS1, IgM and IgG dengue rapid diagnostic tests (RDTs) have previously been shown to accurately diagnose those experiencing dengue virus (DENV) infections at the point of care and are now available as single commercial kits. Using such kits to additionally determine those experiencing primary (first) or post-primary (second, third or fourth) dengue infections however remains challenging as accurate immune status classification currently relies on laboratory analysis. We used logistic regression modelling methods to estimate RDT positive and negative outcomes according to corresponding PCR and ELISA laboratory-based methods, which showed high sensitivity and specificity. Dengue RDT outcomes were then predicted among a large sample of suspected dengue case reports, to calculate the probability of being primary or post-primary for dengue according to every possible set of dengue RDT outcomes, by day of fever. Different RDT outcomes, at certain stages of infection, were indicative of primary and post-primary immune status. Using our framework to determine dengue immune status at the point of care in low resource settings, regional surveillance systems could estimate and monitor dengue transmission intensity. Additionally, this framework could potentially support dengue prognosis and identify primary cases who would benefit from current vaccination regimes to prevent subsequent secondary infections associated with severe disease. [ABSTRACT FROM AUTHOR]

Background: Dengue fever is highly endemic in Vietnam, but scrub typhus—although recognized as an endemic disease—remains underappreciated. These diseases together are likely to account for more than half of the acute undifferentiated fever burden in Vietnam. Scrub typhus (ST) is a bacterial disease requiring antimicrobial treatment, while dengue fever (DF) is of viral etiology and does not. The access to adequate diagnostics and the current understanding of empirical treatment strategies for both illnesses remain limited. In this study we aimed to contribute to the clinical decision process in the management of these two important etiologies of febrile illness in Vietnam. Methods: Using retrospective data from 221 PCR-confirmed scrub typhus cases and 387 NS1 protein positive dengue fever patients admitted to five hospitals in Khanh Hoa province (central Vietnam), we defined predictive characteristics for both diseases that support simple clinical decision making with potential to inform decision algorithms in future. We developed models to discriminate scrub typhus from dengue fever using multivariable logistic regression (M-LR) and classification and regression trees (CART). Regression trees were developed for the entire data set initially and pruned, based on cross-validation. Regression models were developed in a training data set involving 60% of the total sample and validated in the complementary subsample. Probability cut points for the distinction between scrub typhus and dengue fever were chosen to maximise the sum of sensitivity and specificity. Results: Using M-LR, following seven predictors were identified, that reliably differentiate ST from DF; eschar, regional lymphadenopathy, an occupation in nature, increased days of fever on admission, increased neutrophil count, decreased ratio of neutrophils/lymphocytes, and age over 40. Sensitivity and specificity of predictions based on these seven factors reached 93.7% and 99.5%, respectively. When excluding the "eschar" variable, the values dropped to 76.3% and 92.3%, respectively. The CART model generated one further variable; increased days of fever on admission, when eschar was included, the sensitivity and specificity was 95% and 96.9%, respectively. The model without eschar involved the following six variables; regional lymphadenopathy, increased days of fever on admission, increased neutrophil count, increased lymphocyte count, platelet count ≥ 47 G/L and age over 28 years as predictors of ST and provided a sensitivity of 77.4% and a specificity of 90.7%. Conclusions: The generated algorithms contribute to differentiating scrub typhus from dengue fever using basic clinical and laboratory parameters, supporting clinical decision making in areas where dengue and scrub typhus are co-endemic in Vietnam. Author summary: Dengue fever is highly endemic in Vietnam, while scrub typhus is recognized as a re-emerging neglected disease. Both diseases are likely to account for more than half of the acute undifferentiated fever burden in Vietnam. However, scrub typhus is a bacterial disease requiring antimicrobial treatment, while dengue fever—of viral etiology—does not. Misdiagnosis and treatment delays cause potentially severe or fatal complications among scrub typhus patients, even though it is easily treatable. In this study, we used simple clinical and laboratory markers, which were identified upon admission of 221 PCR-confirmed scrub typhus cases and 387 NS1-positive dengue fever patients from Khanh Hoa province to identify the differences between scrub typhus and dengue. We found seven predictors that served to construct a simple clinical decision tree, holding great potential to distinguish scrub typhus from dengue using readily available clinical or laboratory findings. These predictors can strongly support medical staff in identifying scrub typhus cases from dengue, without using sophisticated diagnostic tests, and could improve the quality of diagnoses and appropriate treatment strategies at the primary health care level–especially in areas where scrub typhus and dengue fever are co-endemic in Vietnam and many parts of Asia and where diagnostic tests are not readily available. [ABSTRACT FROM AUTHOR]

Bleeding associated with endothelial damage is a key feature of severe dengue fever. In the current study, we investigated whether Notch ligands were associated with bleeding in 115 patients with confirmed dengue infection in Vietnam. Soluble Notch ligands were determined by means of enzyme-linked immunosorbent assay. Seventeen of 115 patients (14.8%) experienced bleeding manifestations. High soluble delta-like ligand 1 (sDLL1) plasma levels was associated with bleeding (median, 15 674 vs 7117 pg/mL; P < .001). Receiver operating characteristic (ROC) curve analysis demonstrated that sDLL1 had the best test performance (area under the ROC curve, 0.852), with 88% sensitivity and 84% specificity. The combination with alanine aminotransferase and aspartate aminotransferase slightly increased sDLL1 performance. sDLL1 may be useful to guide clinical management of patients with patients in endemic settings. [ABSTRACT FROM AUTHOR]

Background: In recent years, researchers have had an increased focus on multiplex microarray assays, in which antibodies are measured against multiple related antigens, for use in seroepidemiological studies to infer past transmission.Methods: We assess the performance of a flavivirus microarray assay for determining past dengue virus (DENV) infection history in a dengue-endemic setting, Vietnam. We tested the microarray on samples from 1 and 6 months postinfection from DENV-infected patients (infecting serotype was determined using reverse-transcription polymerase chain reaction during acute, past primary, and secondary infection assessed using plaque reduction neutralization tests 6 months postinfection).Results: Binomial models developed to discriminate past primary from secondary infection using the protein microarray (PMA) titers had high area under the curve (0.90-0.97) and accuracy (0.84-0.86). Multinomial models developed to identify most recent past infecting serotype using PMA titers performed well in those with past primary infection (average test set: κ = 0.85, accuracy of 0.92) but not those with past secondary infection (κ = 0.24, accuracy of 0.45).Conclusions: Our results suggest that the microarray will be useful in seroepidemiological studies aimed at classifying the past infection history of individuals (past primary vs secondary and serotype of past primary infections) and thus inferring past transmission intensity of DENV in dengue-endemic settings. Future work to validate these models should be undertaken in different transmission settings and with samples later after infection. [ABSTRACT FROM AUTHOR]

Background One of the generally accepted constructs of dengue pathogenesis is that clinical disease severity is at least partially dependent upon plasma viremia, yet data on plasma viremia in primary versus secondary infections and in relation to clinically relevant endpoints remain limited and contradictory. Methods Using a large database comprising detailed clinical and laboratory characterization of Vietnamese participants enrolled in a series of research studies executed over a 15-year period, we explored relationships between plasma viremia measured by reverse transcription–polymerase chain reaction and 3 clinically relevant endpoints—severe dengue, plasma leakage, and hospitalization—in the dengue-confirmed cases. All 4 dengue serotypes and both primary and secondary infections were well represented. In our logistic regression models we allowed for a nonlinear effect of viremia and for associations between viremia and outcome to differ by age, serotype, host immune status, and illness day at study enrollment. Results Among 5642 dengue-confirmed cases we identified 259 (4.6%) severe dengue cases, 701 (12.4%) patients with plasma leakage, and 1441 of 4008 (40.0%) patients recruited in outpatient settings who were subsequently hospitalized. From the early febrile phase onwards, higher viremia increased the risk of developing all 3 endpoints, but effect sizes were modest (ORs ranging from 1.12–1.27 per 1-log increase) compared with the effects of a secondary immune response (ORs, 1.67–7.76). The associations were consistent across age, serotype, and immune status groups, and in the various sensitivity and subgroup analyses we undertook. Conclusions Higher plasma viremia is associated with increased dengue severity, regardless of serotype or immune status. [ABSTRACT FROM AUTHOR]

Background: With enough advanced notice, dengue outbreaks can be mitigated. As a climate-sensitive disease, environmental conditions and past patterns of dengue can be used to make predictions about future outbreak risk. These predictions improve public health planning and decision-making to ultimately reduce the burden of disease. Past approaches to dengue forecasting have used seasonal climate forecasts, but the predictive ability of a system using different lead times in a year-round prediction system has been seldom explored. Moreover, the transition from theoretical to operational systems integrated with disease control activities is rare.Methods and Findings: We introduce an operational seasonal dengue forecasting system for Vietnam where Earth observations, seasonal climate forecasts, and lagged dengue cases are used to drive a superensemble of probabilistic dengue models to predict dengue risk up to 6 months ahead. Bayesian spatiotemporal models were fit to 19 years (2002-2020) of dengue data at the province level across Vietnam. A superensemble of these models then makes probabilistic predictions of dengue incidence at various future time points aligned with key Vietnamese decision and planning deadlines. We demonstrate that the superensemble generates more accurate predictions of dengue incidence than the individual models it incorporates across a suite of time horizons and transmission settings. Using historical data, the superensemble made slightly more accurate predictions (continuous rank probability score [CRPS] = 66.8, 95% CI 60.6-148.0) than a baseline model which forecasts the same incidence rate every month (CRPS = 79.4, 95% CI 78.5-80.5) at lead times of 1 to 3 months, albeit with larger uncertainty. The outbreak detection capability of the superensemble was considerably larger (69%) than that of the baseline model (54.5%). Predictions were most accurate in southern Vietnam, an area that experiences semi-regular seasonal dengue transmission. The system also demonstrated added value across multiple areas compared to previous practice of not using a forecast. We use the system to make a prospective prediction for dengue incidence in Vietnam for the period May to October 2020. Prospective predictions made with the superensemble were slightly more accurate (CRPS = 110, 95% CI 102-575) than those made with the baseline model (CRPS = 125, 95% CI 120-168) but had larger uncertainty. Finally, we propose a framework for the evaluation of probabilistic predictions. Despite the demonstrated value of our forecasting system, the approach is limited by the consistency of the dengue case data, as well as the lack of publicly available, continuous, and long-term data sets on mosquito control efforts and serotype-specific case data.Conclusions: This study shows that by combining detailed Earth observation data, seasonal climate forecasts, and state-of-the-art models, dengue outbreaks can be predicted across a broad range of settings, with enough lead time to meaningfully inform dengue control. While our system omits some important variables not currently available at a subnational scale, the majority of past outbreaks could be predicted up to 3 months ahead. Over the next 2 years, the system will be prospectively evaluated and, if successful, potentially extended to other areas and other climate-sensitive disease systems. [ABSTRACT FROM AUTHOR]

Liver injury with marked elevation of aspartate aminotransferase enzyme (AST) is commonly observed in dengue infection. To understand the pathogenesis of this liver damage, we compared the plasma levels of hepatic specific, centrilobular predominant enzymes (glutamate dehydrogenase, GLDH; glutathione S transferase-α, αGST), periportal enriched 4-hydroxyphenylpyruvate dioxygenase (HPPD), periportal predominant arginase-1 (ARG-1), and other non-specific biomarkers (paraoxonase-1, PON-1) in patients with different outcomes of dengue infection. This hospital-based study enrolled 87 adult dengue patients, stratified into three groups based on plasma AST levels (< 80, 80-400, > 400 U/L) in a 1:1:1 ratio (n = 40, n = 40, n = 40, respectively. The new liver enzymes in the blood samples from the 4th to 6th days of their illness were measured by commercial enzyme-linked immunosorbent assay (ELISA) or colorimetric kits. Based on the diagnosis at discharge days, our patients were classified as 40 (46%) dengue without warning signs (D), 35 (40.2%) dengue with warning signs (DWS), and 11 (12.6%) severe dengue (SD) with either shock (two patients) or AST level over 1000 U/L (nine patients), using the 2009 WHO classification. The group of high AST (> 400 U/L) also had higher ALT, GLDH, ARG-1, and HPPD than the other groups, while the high (> 400 U/L) and moderate (80-400 U/L) AST groups had higher ALT, αGST, ARG-1, and HPPD than the low AST group (< 80 U/L). There was a good correlation between AST, alanine aminotransferase enzyme (ALT), and the new liver biomarkers such as GLDH, αGST, ARG-1, and HPPD. Our findings suggest that dengue-induced liver damage initiates predominantly in the centrilobular area toward the portal area during the dengue progression. Moreover, these new biomarkers should be investigated further to explain the pathogenesis of dengue and to validate their prognostic utility., (© 2024. The Author(s).)

Background: Dengue epidemics impose considerable strain on healthcare resources. Real-time continuous and non-invasive monitoring of patients admitted to the hospital could lead to improved care and outcomes. We evaluated the performance of a commercially available wearable (SmartCare) utilising photoplethysmography (PPG) to stratify clinical risk for a cohort of hospitalised patients with dengue in Vietnam., Methods: We performed a prospective observational study for adult and paediatric patients with a clinical diagnosis of dengue at the Hospital for Tropical Disease, Ho Chi Minh City, Vietnam. Patients underwent PPG monitoring early during admission alongside standard clinical care. PPG waveforms were analysed using machine learning models. Adult patients were classified between 3 severity classes: i) uncomplicated (ward-based), ii) moderate-severe (emergency department-based), and iii) severe (ICU-based). Data from paediatric patients were split into 2 classes: i) severe (during ICU stay) and ii) follow-up (14-21 days after the illness onset). Model performances were evaluated using standard classification metrics and 5-fold stratified cross-validation., Findings: We included PPG and clinical data from 132 adults and 15 paediatric patients with a median age of 28 (IQR, 21-35) and 12 (IQR, 9-13) years respectively. 1781 h of PPG data were available for analysis. The best performing convolutional neural network models (CNN) achieved a precision of 0.785 and recall of 0.771 in classifying adult patients according to severity class and a precision of 0.891 and recall of 0.891 in classifying between disease and post-disease state in paediatric patients., Interpretation: We demonstrate that the use of a low-cost wearable provided clinically actionable data to differentiate between patients with dengue of varying severity. Continuous monitoring and connectivity to early warning systems could significantly benefit clinical care in dengue, particularly within an endemic setting. Work is currently underway to implement these models for dynamic risk predictions and assist in individualised patient care., Funding: EPSRC Centre for Doctoral Training in High-Performance Embedded and Distributed Systems (HiPEDS) (Grant: EP/L016796/1) and the Wellcome Trust (Grants: 215010/Z/18/Z and 215688/Z/19/Z)., Competing Interests: Declaration of interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background Chikungunya (CHIKV), dengue (DENV), and Zika (ZIKV) viruses are of concern due to the potential of transfusion transmission in blood, especially in regions such as Southeast Asia where the viruses are endemic. The recent availability of nucleic acid testing (NAT) to screen blood donations on an automated platform provides the opportunity to detect potentially infectious units in asymptomatic donors. Study Design and Methods Three thousand blood donations from Vietnam and 6000 from Thailand were screened with a real‐time polymerase chain reaction (PCR) test (cobas CHIKV/DENV, Roche Diagnostics, Indianapolis, IN) and equal numbers on cobas Zika (Roche Diagnostics). Reactive samples were tested by alternative NAT with resolution of discordant results by heminested PCR. Throughput of simultaneous testing of the two assays on the cobas 8800 system (Roche Diagnostics) was evaluated. Results: In Vietnam, 9 of 3045 samples were reactive for DENV and all were confirmed, for a prevalence (with 95% confidence interval [CI]) of 0.296% (0.135‐0.560). In Thailand, 2 of 6000 samples were reactive for CHIKV, 4 of 6000 for DENV, and 1 of 6005 for ZIKV, and all confirmed. The prevalence of CHIKV is 0.033% (0.004‐0.120), DENV 0.067% (0.018‐0.171), and ZIKV 0.017% (0.000‐0.093). The overall specificity for the cobas CHIKV/DENV and cobas Zika tests was 100% (99.959‐100). For the simultaneous assay testing, 960 test results were available in 7 hours and 53 minutes. Conclusion: Detection of CHIKV, DENV, and ZIKV RNA in donor samples in Vietnam and Thailand indicate the presence of the virus in asymptomatic blood donors. The cobas 6800/8800 systems (Roche Molecular Systems, Pleasanton, CA) enable screening blood donations in endemic areas for these viruses together or separately. [ABSTRACT FROM AUTHOR]

Background: Dengue has spread rapidly in all regions during recent years and the epidemiological features of the disease have changed considerably despite many advances in epidemic prevention. Children and young adults have been the populations most at risk of dengue fever and severe complications. Objectives: Evaluate epidemiological characteristics and the severity of dengue among children in the 2017 dengue outbreak. Results: A review of 1446 paediatric cases with dengue in 2017 showed that male occupied predominantly for 56.9% of the total patients. Patients ≤ 1 year old, 2-5 years old, 6-12 years old and 13-18 years old accounted for 5.2%, 13.8%, 36.6% and 44.4% of the study sample, respectively. The major age group at the Children's Hospital 1 was from 6-12 years old (44.4%) while at the National Hospital for Tropical Diseases, it was from 13-18 years old (61.6%). Dengue outbreak happens widely across Vietnam. In the Southern region, dengue occurs all year round and peaks in the rainy season from June to October, after that, the infection decreases at the end of the year but still maintaining until the beginning of next year. In comparison, dengue transmission in the Northern region had suddenly increased since June 2017, then hit a peak in August 2017 and declined in the remaining months until the end of the year. Speciality, the infection is highly endemic in the Southwest region. It also expanded to the Southeast provinces such as Dong Nai and Binh Duong where emerging industrial zones located. The number of patients with dengue fever in Hanoi in 2017 was not only the greatest in the Northern region but also in the whole country. Comorbidities reported in children were rare with the most frequent diseases being respiratory diseases, gastroenteritis or infections. The incidence of dengue fever, dengue haemorrhagic fever and dengue shock syndrome made up 42%, 35.5% and 22.4%, respectively. Conclusions: Our findings potentially develop a strategy for early detection, prognosis and proactive prevention of dengue in order to reduce the number of cases as well as the fatality rates. [ABSTRACT FROM AUTHOR]

Introduction: Dengue hemorrhagic fever is caused by four serotypes of dengue viruses transmitted by mosquitoes. In Vietnam, dengue outbreaks occur every year, and all four serotypes have been found circulating with the dominant one varying over time. However, in 2017 an unusual dengue fever outbreak occurred in the North of Vietnam, predominantly caused by DENV1 (92%) and DENV2 (7.3%). The objective of the present study was to obtain and characterize the full-length genome sequence of seven DENV2 strains in 2017 epidemic. Materials and Methods: Whole-genome sequencing of seven DENV2 isolates from the 2017 outbreak were obtained using the Illumina MiSeq next generation sequencer system. Complete genome sequences were then analyzed to find out genetic variants and genetic relationships between these DENV2 with other strains that circulated in Vietnam previously and other regions of the world. Results: The complete genome sequence of seven DENV2 isolates in the 2017 dengue outbreak comprised 10,696 nucleotides with an open reading frame coding for 3392 amino acids. The genome analysis showed only a small number of amino acid changes which were obtained in all genes, in which a few amino acids substitutions were distributed over the positions such as G156 (NS1), V106 (NS2A), and L258/T260 (NS5). The phylogenetic analysis revealed that the DENV2 isolates in the 2017 outbreak were most closely related to the dengue virus from India in 2006, suggesting that the causative virus originated from the DENV2 that caused dengue hemorrhagic fever in 2006 in India. Conclusion: The first complete genome sequences of seven DENV2 isolates in the 2017 dengue outbreak in Northern Vietnam were successfully obtained. The genetic and phylogenetic data indicated that these DENV2 isolates were not causative virus circulating in Vietnam previously but originated from India in 2006. These data are emerging and providing valuable information for the management and surveillance of dengue in Vietnam. [ABSTRACT FROM AUTHOR]

Background: Dengue is arthropod-borne disease and one of major causes of morbidity and fatality in the Western Pacific Region. Climate is considered one of the main factors for dengue transmission. Objective of the study is to determine correlations between climatic factors and dengue, using reported cases in Southern Lam Dong Province, Vietnam, 2007-2017 and to validate the predictive model for number of dengue cases in 2017 using data from 2007 to 2016. Materials and Methods: This was a retrospective quantitative study. Spearman's Rank test was used to examine the correlation between each climatic factor and dengue reported cases. Seasonal Autoregressive Integrated Moving Average (SARIMA) models using the training data set from 2007 to 2016, correlative factors of dengue cases, the Bayes Information Criterion (BIC) and improved Box-Jenkins models, were applied to predict dengue cases during 2017. There is a wide range of potential confounders for annual dengue epidemics such as mosquito ecology, population density, population immunity and dengue cycle. Amongst these factors, population density was forced into the predictive model. Data analysis was done using Excel and SPSS version 16. Result: There were significant correlations between dengue cases and climatic factors, consisting of minimum temperature (r = 0.384, p < 0.01) and relative humidity (r = 0.372, p < 0.01). The SARIMA (1,2,1) x (1,1,1)12 model at lag one month was the best fitted model for predicting dengue cases. Conclusion: Predicted cases from time series model would be imperative for controlling and preventing the occurrence of dengue epidemics in the community. This study used secondary data, so it was difficult to control the occurrence of missing data point. Climatic and nonclimate factors should be considered in predictive models for dengue epidemiology in the future. [ABSTRACT FROM AUTHOR]

Background: Dengue hemorrhagic fever is an acute viral infection transmitted by mosquitoes. In the 2017, a dengue epidemic occurred in Hanoi in a short time interval and many cases were serious with associated mortality. This was the largest and unusual dengue fever outbreak in the North of Vietnam over the past 20 years. The objective of the present study was to understand the genetic characteristics of the DENV-1 strain in the 2017 epidemic and its relationship with previous viruses in Vietnam and the rest of the world. Methods: Complete genomes of 72 DENV-1 from patients in the 2017 epidemic were sequenced using NGS. The full genome sequences were then analyzed to find out the genetic variants in the groups of 72 strains, followed by their comparison with other strains that caused disease in Vietnam previously and several other regions of the world, revealing a genetic relationship between them. Results: The complete genome sequence of 72 DENV-1 strains comprised 10,697 nucleotides with an open reading frame coding for 3392 amino acids. The genomic analysis revealed different amino acid substitutions in all genes, especially varying at position S75 (Capsid), M125 (PrM), D54 (E), T147, V180 (NS1), G45, Y126, I154 (NS2A), A94 (NS2B), M298 (NS3), K47, V68 (NS4A), I29 (NS4B), and R166, E536, G614, T821 (NS5). The genetic analysis suggested that the viruses were most closely related to the causative virus of the dengue outbreak in Vietnam and Cambodia from 2006 to 2008. These results indicated that DENV-1 from the dengue epidemic 2017 in Northern Vietnam originated from the virus that caused the dengue outbreak during the 2007 to 2008 period in Vietnam. Conclusion: The present study is the first of its kind to describe complete genome sequence as well as genetic variants and phylogenetic analysis of DENV-1 associated with the unusual dengue epidemic of 2017 in northern Vietnam. These results provide detailed evidence to elucidate the origin, circulation, and genetic evolution of DENV in Vietnam. [ABSTRACT FROM AUTHOR]

Objective: This study aims to enhance the capacity of dengue prediction by investigating the relationship of dengue incidence with climate and environmental factors in the Mekong Delta region (MDR) of Viet Nam by using remote sensing data. Methods: To produce monthly data sets for each province, we extracted and aggregated precipitation data from the Global Satellite Mapping of Precipitation project and land surface temperatures and normalized difference vegetation indexes from the Moderate Resolution Imaging Spectroradiometer satellite observations. Monthly data sets from 2000 to 2016 were used to construct autoregressive integrated moving average (ARIMA) models to predict dengue incidence for 12 provinces across the study region. Results: The final models were able to predict dengue incidence from January to December 2016 that concurred with the observation that dengue epidemics occur mostly in rainy seasons. As a result, the obtained model presents a good fit at a regional level with the correlation value of 0.65 between predicted and reported dengue cases; nevertheless, its performance declines at the subregional scale. Conclusion: We demonstrated the use of remote sensing data in time-series to develop a model of dengue incidence in the MDR of Viet Nam. Results indicated that this approach could be an effective method to predict regional dengue incidence and its trends. [ABSTRACT FROM AUTHOR]

Objectives: To estimate the number and risk of imported infections resulting from people visiting Asian and Latin American countries. Methods: The dataset of visitors to 5 Asian countries with dengue were analyzed for 2016 and 2017, and in the Philippines, Thailand and Vietnam, imported cases of zika virus infection were also reported. For zika virus, a single imported case was reported from Brazil in 2016, and 2 imported cases reported from the Maldives in 2017. To understand the transmissibility in 5 Southeast Asian countries, the estimate of the force of infection, i.e., the hazard of infection per year and the average duration of travel has been extracted. Outbound travel numbers were retrieved from the World Tourism Organization, including business travelers. Results: The incidence of imported dengue in 2016 was estimated at 7.46, 15.00, 2.14, 4.73 and 2.40 per 100,000 travelers visiting Philippines, Indonesia, Thailand, Malaysia and Vietnam, respectively. Similarly, 2.55, 1.65, 1.53, 1.86 and 1.70 per 100,000 travelers in 2017, respectively. It was estimated that there were 60.1 infections (range: from 16.8 to 150.7 infections) with zika virus in Brazil, 2016, and 345.6 infections (range: from 85.4 to 425.5 infections) with zika virus in the Maldives, 2017. Conclusion: This study emphasizes that dengue and zika virus infections are mild in their nature, and a substantial number of infections may go undetected. An appropriate risk assessment of zika virus infection must use the estimated total size of infections. [ABSTRACT FROM AUTHOR]

Background: Dengue fever is the most widespread infectious disease of humans transmitted by Aedes mosquitoes. It is the leading cause of hospitalization and death in children in the Southeast Asia and western Pacific regions. We analyzed surveillance records from health centers in Vietnam collected between 2001–2012 to determine seasonal trends, develop risk maps and an incidence forecasting model. Methods: The data were analyzed using a hierarchical spatial Bayesian model that approximates its posterior parameter distributions using the integrated Laplace approximation algorithm (INLA). Meteorological, altitude and land cover (LC) data were used as predictors. The data were grouped by province (n = 63) and month (n = 144) and divided into training (2001–2009) and validation (2010–2012) sets. Thirteen meteorological variables, 7 land cover data and altitude were considered as predictors. Only significant predictors were kept in the final multivariable model. Eleven dummy variables representing month were also fitted to account for seasonal effects. Spatial and temporal effects were accounted for using Besag-York-Mollie (BYM) and autoregressive (1) models. Their levels of significance were analyzed using deviance information criterion (DIC). The model was validated based on the Theil's coefficient which compared predicted and observed incidence estimated using the validation data. Dengue incidence predictions for 2010–2012 were also used to generate risk maps. Results: The mean monthly dengue incidence during the period was 6.94 cases (SD 14.49) per 100,000 people. Analyses on the temporal trends of the disease showed regular seasonal epidemics that were interrupted every 3 years (specifically in July 2004, July 2007 and September 2010) by major fluctuations in incidence. Monthly mean minimum temperature, rainfall, area under urban settlement/build-up areas and altitude were significant in the final model. Minimum temperature and rainfall had non-linear effects and lagging them by two months provided a better fitting model compared to using unlagged variables. Forecasts for the validation period closely mirrored the observed data and accurately captured the troughs and peaks of dengue incidence trajectories. A favorable Theil's coefficient of inequality of 0.22 was generated. Conclusions: The study identified temperature, rainfall, altitude and area under urban settlement as being significant predictors of dengue incidence. The statistical model fitted the data well based on Theil's coefficient of inequality, and risk maps generated from its predictions identified most of the high-risk provinces throughout the country. [ABSTRACT FROM AUTHOR]

Purpose. The clinical features and laboratory results of dengue-infected adult patients admitted to the hospital during the 2017 outbreak were analyzed in this study. Method. This is a cross-sectional study. 2922 patients aged 18 years or more with dengue fever in National Hospital for Tropical Diseases (NHTD) in the North and Hospital for Tropical Disease (HTD) in the South of Vietnam were recruited in this study. Result. Patients were admitted in the hospital around the year and concentrated from August to December, in 53/63 (84.0%) provinces in Vietnam, and patients in all ages were affected. The number of patients with dengue fever was 1675 (57.3%), dengue with warning signs 914 (31.3%), and severe dengue 333 (11.4%), respectively. Among patients with severe dengue, severe plasma leakage and dengue shock account for 238 (8.1%), severe organ impairment 73 (2.5%), and severe bleeding 22 (0.75%). The rate of mortality was 0.8%, and the outcome of dengue patients is worse in the elderly and people with underlying diseases. Conclusion. The 2017 dengue outbreak occurred in a larger scale than in the previous years in terms of time, location, and number of patients. More elderly patients were infected by dengue in this outbreak, and this may contribute to the mortality rate. Clinical manifestations of dengue patients in Southern Vietnam are more typical than the northern, but the rate of severe dengue is not different. The mortality risk and underlying conditions associated with dengue-infected elderly patients are worthy of further investigations in the future. [ABSTRACT FROM AUTHOR]

Aedes aegypti and Ae. albopictus are key vectors in the spread of arboviruses such as dengue, chikungunya, yellow fever, and Zika. Triatoma rubrofasciata is an "assassin bug" whose populations and association with humans have dramatically increased and may represent a serious health concern. Control of insect vectors is a logical course of action to prevent the spread of these insect-borne infections. This work presents the leaf essential oil composition, mosquito larvicidal activities, and insect-repellent activity of Severinia monophylla. The essential oil of S. monophylla from Vietnam was obtained by hydrodistillation and analyzed by gas chromatography and mass spectrometry. The major components were sabinene, β-caryophyllene, bicyclogermacrene, germacrene D, (E)-nerolidol, globulol, and linalool. The leaf essential oil showed remarkable larvicidal activity against Ae. aegypti with LC50 (48 h) of 7.1 μg/mL and Ae. albopictus with LC50 (48 h) of 36 μg/mL. The essential oil also showed repellent activity on T. rubrofasciata at a concentration of 0.5%. [ABSTRACT FROM AUTHOR]

Dengue epidemics can rapidly increase demand in healthcare services across many endemic settings. However, there remains a lack of tools which can rapidly inform patient management and can be used at the point of care. Digital clinical decision-support systems (CDSSs) allow for efficient organisation of care as well as improve the quality of patient management. It is important that these tools are designed for the end-user and with the healthcare setting in mind to increase adoption and usability. We adopted a ground-up human-centred design approach to design a digital CDSS system for dengue management in Vietnam (D-CASS). A multidisciplinary team of data scientists, clinicians and social scientists were involved in a series of activities designed to map clinical processes, essential tasks and decision-making priorities which were crucial in the management of dengue at our hospital setting. Frontend development was undertaken by a specialist UX designer with regular feedback from the research team and clinical end-users. Based on our previous work, the desired features for the CDSS identified were: i) patient organisation, ii) availability of guidelines and calculators with easy access, iii) display of results and iv) inference models for dengue diagnosis on admission AUCROC 0.86 (IQR, 0.84 — 0.86) and further risk stratification for hospitalised patients based on possible complications AUCROC 0.83 (CI, 0.76 — 0.85). A web-based reactive framework suitable for display on computers and tablets was produced. Priority was placed on usability and modularity so that the system can be repurposed. Dengue Clinical Decision Support Application (D-CASS) is a bespoke and rapidly scalable CDSS produced following clinical pathways, clinician's needs, and usability in mind. Further work will focus on prospective evaluation and iterative improvement of the CDSS including (i) end-user testing and (ii) prospective model performance. If successful, the CDSS will be implemented and deployed to evaluate its clinical utility. [ABSTRACT FROM AUTHOR]

Background: The escalation of dengue fever (DF) cases in recent years and the occurrence of a large-scale DF outbreak in 2017 underline the importance of dengue vaccines in Vietnam. Given the potential benefits of the dengue vaccines and the need for copayment by the private sector, this study aims to evaluate the willingness to pay (WTP) for the dengue vaccines in patients with DF in Northern Vietnam. Methods: A cross-sectional study was conducted on 330 in-and-out patients with DF admitted to the Bach Mai Hospital. We used the contingent valuation method to evaluate the WTP for dengue vaccines. Socioeconomic and clinical characteristics were also investigated. Multivariate interval and logistic regression models were used to estimate the average amount of WTP and identify the factors associated with the WTP. Results: Around 77.3% patients were willing to pay an average amount of US$ 67.4 (95% CI=57.4–77.4) for the vaccine. People of higher ages, those having health insurance, those traveling in the past 15 days or suffering from anxiety/depression were less likely to be willing to pay for the dengue vaccine. However, people having a longer duration of DF or having problems with mobility were positively associated with WTP for the dengue vaccine. Patients educated to more than high school levels (Coeff.=31.31; 95% CI=3.26–59.35), those in the richest quintile (Coeff.=62.76; 95% CI=25.40; 100.13), or those having a longer duration of the disease (Coeff.=6.18; 95% CI=0.72–11.63) were willing to pay a higher amount. Conclusion: This study highlights a relatively high rate and amount of WTP for the dengue vaccine among patients with DF. Psychological counseling services as well as educational campaigns should be undertaken to improve the WTP for the vaccine. Moreover, government subsidies should be given to increase the coverage of the vaccine in the future, especially for the poor. [ABSTRACT FROM AUTHOR]

Background After new analysis, Sanofi Pasteur now recommends their dengue vaccine (Dengvaxia) should only be given to individuals previously infected with dengue and the World Health Organization’s recommendations regarding its use are currently being revised. As a result, the potential costs of performing large-scale individual dengue screening and/or dengue serosurveys have become an important consideration for decision making by policymakers in dengue-endemic areas. Methods We used an ingredients-based approach to estimate the financial costs for conducting both a school-based dengue serosurvey and school-based individual dengue screening within a typical province in Vietnam, using an existing commercial indirect immunoglobulin G enzyme-linked immunosorbent assay kit. This costing is hypothetical and based on estimates regarding the resources that would be required to perform such activities. Results We estimated that performing a school-based individual screening of 9-year-olds would cost US$9.25 per child tested or US$197,827 in total for a typical province. We also estimated that a school-based serosurvey would cost US$10,074, assuming one class from each of the grades that include 8- to 11-year-olds are sampled at each of the 12 selected schools across the province. Conclusions The study indicates that using this vaccine safely on a large-scale will incur noteworthy operational costs. It is crucial that these be considered in future cost-effectiveness analyses informing how and where the vaccine is deployed. [ABSTRACT FROM AUTHOR]

Background. Dengue can cause increased vascular permeability that may lead to hypovolemic shock. Endothelial dysfunction may underlie this; however, the association of endothelial nitric oxide (NO) pathways with disease severity is unknown. Methods. We performed a prospective observational study in 2 Vietnamese hospitals, assessing patients presenting early (<72 hours of fever) and patients hospitalized with warning signs or severe dengue. The reactive hyperemic index (RHI), which measures endothelium-dependent vasodilation and is a surrogate marker of endothelial function and NO bioavailability, was evaluated using peripheral artery tonometry (EndoPAT), and plasma levels of l-arginine, arginase-1, and asymmetric dimethylarginine were measured at serial time-points. The main outcome of interest was plasma leakage severity. Results. Three hundred fourteen patients were enrolled; median age of the participants was 21(interquartile range, 13-30) years. No difference was found in the endothelial parameters between dengue and other febrile illness. Considering dengue patients, the RHI was significantly lower for patients with severe plasma leakage compared to those with no leakage (1.46 vs 2.00; P < .001), over acute time-points, apparent already in the early febrile phase (1.29 vs 1.75; P = .012). RHI correlated negatively with arginase-1 and positively with l-arginine (P = .001). Conclusions. Endothelial dysfunction/NO bioavailability is associated with worse plasma leakage, occurs early in dengue illness and correlates with hypoargininemia and high arginase-1 levels. [ABSTRACT FROM AUTHOR]

Background: A previous genome-wide association study identified 2 susceptibility loci for severe dengue at MICB rs3132468 and PLCE1 rs3740360 and further work showed these mutations to be also associated with less severe clinical presentations. The aim of this study was to determine if these specific loci were associated with laboratory features of dengue that correlate with clinical severity with the aim of elucidating the functional basis of these genetic variants.Methods: This was a case-only analysis of laboratory-confirmed dengue patients obtained from 2 prospective cohort studies and 1 randomised clinical trial in Vietnam (Trial registration: ISRCTN ISRCTN03147572. Registered 24th July 2012). 2742 dengue cases were successfully genotyped at MICB rs3132468 and PLCE1 rs3740360. Laboratory variables were compared between genotypes and stratified by DENV serotype.Results: The analysis showed no association between MICB and PLCE1 genotype and early viraemia level, platelet nadir, white cell count nadir, or maximum haematocrit in both overall analysis and in analysis stratified by serotype.Discussion: The lack of an association between genotype and viremia level may reflect the sampling procedures within the included studies. The study findings mean that the functional basis of these mutations remains unclear.Trial Registration: ISRCTN ISRCTN03147572 . Registered 24th July 2012. [ABSTRACT FROM AUTHOR]

Background: In Vietnam, dengue fever (DF) is still a leading cause of hospitalization. The main objective of this study was to evaluate the seasonality and association with climate factors (temperature and precipitation) on the incidences of DF in four provinces where the highest incidence rates were observed from 1994 to 2013 in Vietnam.Methods: Incidence rates (per 100,000) were calculated on a monthly basis from during the study period. The seasonal-decomposition procedure based on loess (STL) was used in order to assess the trend and seasonality of DF. In addition, a seasonal cycle subseries (SCS) plot and univariate negative binomial regression (NBR) model were used to evaluate the monthly variability with statistical analysis. Lastly, a generalized estimating equation (GEE) was used to assess the relationship between monthly incidence rates and weather factors (temperature and precipitation).Results: We found that increased incidence rates were observed in the second half of each year (from May through December) which is the rainy season in each province. In Hanoi, the final model showed that 1 °C rise of temperature corresponded to an increase of 13% in the monthly incidence rate of DF. In Khanh Hoa, the final model displayed that 1 °C increase in temperature corresponded to an increase of 17% while 100 mm increase in precipitation corresponded to an increase of 11% of DF incidence rate. For Ho Chi Minh City, none of variables were significant in the model. In An Giang, the final model showed that 100 mm increase of precipitation in the preceding and same months corresponded to an increase of 30% and 22% of DF incidence rate.Conclusion: Our findings provide insight into understanding the seasonal pattern and associated climate risk factors. [ABSTRACT FROM AUTHOR]

Background: Dengue is a public health problem in the Indo-Pacific countries. There are concerns over the facilitators and barriers to community engagement in health service research aimed at dengue control. The objective of his study was to identify and synthesize facilitators and barriers to community engagement in health service research aimed at dengue control., Methodology: The Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) checklist was used to perform this review. Health-related databases including PubMed, Ovid, and Google Scholar were searched for relevant studies. A consolidated framework with five domains was developed after undertaking a six-phase reflective thematic assessment of the data., Results: Thirteen studies were identified, spanning eight low-and middle-income countries of the Indo-Pacific region including Cambodia, India, Indonesia, Myanmar, Philippines, Sri Lanka, Thailand, and Vietnam. The studies in this review covered the period from 2002 to 2021. A broad range of study designs and objectives were revealed across these 13 studies. An array of communities such as the local government, project-related health staff, local health services staff, community leaders, local communities/residences/general public, heads of households, community health volunteers, school teachers, and schoolchildren participated in these dengue related studies. The five Consolidated Framework for Implementation Research (CFIR) domains of 'intervention characteristics', 'inner setting', 'outer setting',' individual characteristics', and 'program implementations' were used to identify and describe barriers and facilitators., Conclusions: The findings indicate a range of barriers and facilitators to community engagement in dengue control in the selected LMIC in the Indo-Pacific countries. Future health services research on dengue control approaches should be carefully planned, methodologically constructed, aligned with community engagement principles, and involve considerable community participation at all stages of the research., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background The cost of treatment for infectious shock in intensive care in Vietnam is unknown. Methods We prospectively investigated hospital bills for adults treated for septic and dengue shock in Vietnam and calculated the proportion who faced catastrophic health care expenditures. Results The median hospital bills were US$617 for septic shock (n=100) and US$57 for dengue shock (n=88). Catastrophic payments were incurred by 47% (47/100) and 13% (11/88) of patients with septic shock and dengue shock, respectively, and 56% (25/45) and 84% (5/6) fatal cases of septic shock and dengue shock respectively. Conclusions Further advocacy is required to moderate insurance co-payments for costly critical care interventions. [ABSTRACT FROM AUTHOR]