Background: Severe dengue is a life-threatening complication; rapid identification of these cases, followed by adequate management is crucial to improve the clinical prognosis. Therefore, this study aimed to identify risk factors and predictors of severe dengue. Methods: A literature search for studies reporting risk factors of severe dengue among individuals with dengue virus infection was conducted in PubMed, Scopus and Web of Science database from inception to December 31, 2020. Pooled odds ratios (ORs) for patients’ demographic characteristics, co-morbidities, and warning signs were estimated using an inverse variance heterogeneity model. Results: We included 143 articles in the meta-analysis from a total of 13 090 articles retrieved from the literature search. The risk factors of severe dengue were: being a child [OR = 1.96; 95% confidence interval (CI): 1.22–3.13], secondary infection (OR = 3.23; 95% CI: 2.28–4.57), and patients with pre-existing diabetes (OR = 2.88; 95% CI: 1.72–4.81) and renal disease (OR = 4.54; 95% CI: 1.55–13.31). Warning signs strongly associated with severe disease were increased haematocrit with a concurrent decrease in platelet count (OR = 5.13; 95% CI: 1.61–16.34), abdominal pain (OR = 2.00; 95% CI: 1.49–2.68), lethargy (OR = 2.73; 95% CI: 1.05–7.10), vomiting (OR = 1.80; 95% CI: 1.43–2.26), hepatomegaly (OR = 5.92; 95% CI: 3.29–10.66), ascites (OR = 6.30; 95% CI: 3.75–10.60), pleural effusion (OR = 5.72; 95% CI: 3.24–10.10) and melena (OR = 4.05; 95% CI: 1.64–10.00). Conclusions: Our meta-analysis identified children, secondary infection, diabetes and renal disease(s) as important predictors of severe dengue. Our finding also supports the predictive ability of the WHO warning signs to identify severe dengue. These findings are useful for clinicians to identify severe dengue for management and timely interventions.

Dengue poses a significant health and economic burden in the WHO South-East Asia Region. Approaches for control need to be aligned with current knowledge on the epidemiology of dengue in the region. Such knowledge will ensure improved targeting of interventions to reduce dengue incidence and its socioeconomic impact. This review was undertaken to describe the contemporary epidemiology of dengue and critically analyse the existing surveillance strategies in the region. Over recent decades, dengue incidence has continued to increase with geographical expansion. The region has now become hyper-endemic for multiple dengue virus serotypes/genotypes. Every epidemic cycle was associated with a change of predominant serotype/genotype and this was often associated with severe disease with intense transmission. Classical larval indices are widely used in vector surveillance and adult mosquito samplings are not implemented as a part of routine surveillance. Further, there is a lack of integration of entomological and disease surveillance systems, often leading to inaction or delays in dengue prevention and control. Disease surveillance does not capture all cases, resulting in under-reporting, and has thus failed to adequately represent the true burden of disease in the region. Possible solutions include incorporating adult mosquito sampling into routine vector surveillance, the establishment of laboratory-based sentinel surveillance, integrated vector and dengue disease surveillance and climate-based early warning systems using available technologies like mobile apps.

Background: Dengue is the most common arboviral disease in the tropical and sub-tropical regions of the world. Like other regions, dengue-endemic areas have faced the additional public health and socio-economic impact of the ongoing coronavirus disease 2019 (COVID-19) pandemic. COVID-19 and dengue co-infections have been reported, with complicated patient management and care requirements. This review aimed to collate and synthesise current knowledge on the clinical features and outcomes of COVID-19 and dengue virus co-infection, a potentially important new dimension to be considered in public health management of the COVID-19 pandemic. Methods: A systematic literature review was conducted using PubMed, Web of Science and Scopus databases from 1st January to 21st November 2020. The key search terms used were “dengue” and “coronavirus”. Descriptive analysis with graphical illustrations were used to present the clinical and laboratory parameters of the co-infection. Results: Thirteen published papers and four news articles were included in the review. Most studies were case reports with a detailed description of the clinical and laboratory characteristics of the co-infection. All cases were in adults with the exception of a six-year old child. The common symptoms of co-infection were fever, dyspnea, headache, and cough. Common laboratory results included thrombocytopenia, lymphocytopenia, elevated transaminases, and leukopenia. Serious outcomes of co-infection included septic shock, acute respiratory disease syndrome and multi-organ failure, leading to death in some patients. Conclusions: COVID-19 and dengue co-infection was associated with severe disease and fatal outcomes. The correct diagnosis and treatment of co-infection poses a substantial challenge due to the overlapping clinical and laboratory parameters. Therefore, confirmative diagnostic tests are necessary for accurate and timely diagnosis and patient management.

Context: Nutritional interventions substantially improve tuberculosis (TB) treatment outcomes and prevent complications. However, there is limited evidence about the connections between having nutritional support and TB treatment adherence. Objective: The aim of this study was to determine the effectiveness of nutritional support in improving treatment adherence among patients with TB. Data Sources: Databases, including PubMed, Embase (Ovid), Web of Science, and Scopus, were comprehensively reviewed to identify relevant studies reporting the impacts of nutritional support on TB treatment adherence. Data Extraction: Two authors independently screened the title, abstracts, and full article texts to identify eligible studies and assess the risk of bias. Observational and interventional studies were included. Data Analysis: A narrative synthesis approach was used to summarize the findings qualitatively. Results: From the search, 3059 publications were identified; of these, 8 studies were included in this systematic review. Three types of nutritional interventions were identified: food baskets (eg, energy, micronutrient- or macronutrient-enriched food support), nutritional advice and guidance, and incentives for buying foods. Although 5 studies reported that nutritional support significantly improved treatment adherence in patients with TB, 3 studies showed that nutritional support had no effect on TB treatment adherence. Conclusions: Providing nutritional support may improve adherence to TB treatment. However, more well-powered, high-quality trials are warranted to demonstrate the effect of nutrition support on cost-effectively improving adherence to TB treatment. Systematic Review Registration: PROSPERO registration no. CRD42023392162.

Dengue is an important emerging vector-borne disease in Bhutan. This study aimed to quantify the spatial and temporal patterns of dengue and their relationship to environmental factors in dengue-affected areas at the sub-district level. A multivariate zero-inflated Poisson regression model was developed using a Bayesian framework with spatial and spatiotemporal random effects modelled using a conditional autoregressive prior structure. The posterior parameters were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling. A total of 708 dengue cases were notified through national surveillance between January 2016 and June 2019. Individuals aged ≤14 years were found to be 53% (95% CrI: 42%, 62%) less likely to have dengue infection than those aged >14 years. Dengue cases increased by 63% (95% CrI: 49%, 77%) for a 1°C increase in maximum temperature, and decreased by 48% (95% CrI: 25%, 64%) for a one-unit increase in normalized difference vegetation index (NDVI). There was significant residual spatial clustering after accounting for climate and environmental variables. The temporal trend was significantly higher than the national average in eastern sub-districts. The findings highlight the impact of climate and environmental variables on dengue transmission and suggests prioritizing high-risk areas for control strategies.

Background: Dengue is the most rapidly spreading vector-borne disease globally, with a 30-fold increase in global incidence over the last 50 years. In Bhutan, dengue incidence has been on the rise since 2004, with numerous outbreaks reported across the country. The aim of this study was to identify and map areas that are vulnerable to dengue in Bhutan.Methodology/Principal findings: We conducted a multicriteria decision analysis (MCDA) using a weighted linear combination (WLC) to obtain a vulnerability map of dengue. Risk factors (criteria) were identified and assigned with membership values for vulnerability according to the available literature. Sensitivity analysis and validation of the model was conducted to improve the robustness and predictive ability of the map. Our study revealed marked differences in geographical vulnerability to dengue by location and season. Low-lying areas and those located along the southern border were consistently found to be at higher risk of dengue. The vulnerability extended to higher elevation areas including some areas in the Capital city Thimphu during the summer season. The higher risk was mostly associated with relatively high population density, agricultural and built-up landscapes and relatively good road connectivity.Conclusions: Using MCDA, our study identified vulnerable areas in Bhutan during specific seasons when and where the transmission of dengue is most likely to occur. This study provides evidence for the National Vector-borne Disease Control programme to optimize the use of limited public health resources for surveillance and vector control, to mitigate the public health threat of dengue.