Dengue is an arboviral infection that poses a substantial public health concern, with early diagnosis being a critical factor in effective management. However, limited diagnostic expertise in developing countries contributes to the under-reporting of dengue cases. This review compares the accuracy of rapid diagnostic tests (RDTs) and the tourniquet test (TT) in diagnosing dengue fever (DF) in non-laboratory-based settings. Relevant original articles on the use of RDTs and TT for dengue diagnosis were retrieved from PubMed, Scopus, and ScienceDirect. The STARD and QUADAS-2 tools were employed to evaluate the methodological quality of the included studies. Search terms included combinations of ‘fever’, ‘dengue’, and ‘“diagnosis’. In total, 23 articles were eligible for inclusion. The RDTs demonstrated mean sensitivities and specificities of 76.2% (SD = 13.8) and 91.5% (SD = 10.3), respectively, while the TT showed mean sensitivity and specificity values of 48.6% (SD = 24.9) and 79.5% (SD = 14.9), respectively. Overall, RDTs exhibited superior diagnostic performance compared to the TT. Our findings suggest that the TT is an inadequate stand-alone diagnostic tool for dengue. RDTs should be prioritized for dengue diagnosis in resource-limited settings. However, in situations where RDTs are unavailable, the TT may serve as a supplementary option.

Dengue, the most prevalent urban arbovirus in the world, has triggered recurrent epidemics in Rio de Janeiro, Brazil, since the 1980s. This study aimed to describe the spatial–temporal patterns of dengue spread during the epidemic years of 2002, 2008, 2011, 2012, 2013, and 2024 in Rio de Janeiro. This is an ecological study using secondary data on notified confirmed dengue cases aggregated by neighbourhood. The incidence rates were estimated via the local empirical Bayes method. The local spatial autocorrelation indicators assessed incidence clusters, and the monthly geographic trajectory was outlined for each year. The results revealed changes in the spatial distribution of dengue over time, with clusters of high incidences predominating in the northern and central neighbourhoods in 2002 and 2008, and in the western zone in 2011, 2012, and 2013. In 2024, the distribution was predominant throughout the city, with emphasis in the central and western zones. The monthly geographic centre of dengue cases shifted from the west to the north during the peak of the epidemic. These results highlight the heterogeneous nature of dengue transmission in Rio de Janeiro. The incorporation of spatial and temporal analyses in epidemiological studies can enhance targeted and localized dengue control strategies.

Recent increases in dengue cases across the region of the Americas have underscored the need for an integrated and collaborative One Health approach to address the potential of widespread autochthonous dengue in the continental USA. Improvements in the public health, social and health sectors are paramount in ensuring that communities are better protected. Furthermore, communities would benefit from effective adaptive strategies in the event of autochthonous dengue outbreaks. There is an opportunity to address existing challenges in the control of mosquitoes, public health infrastructure and funding that are necessary to recover from threats from climate-sensitive pathogens. Each component will improve preparedness toward widespread autochthonous dengue. This review provides an outline of adaptive and mitigating strategies and offers opportunities to address challenges through a One Health lens.

The escalating dengue crisis in Peru demands immediate action from global health organizations, health care authorities, and government officials. Endemic to Peru, dengue has seen a drastic increase in cases, with the largest outbreak on record occurring in the first half of 2023, resulting in 139 366 confirmed cases and 381 deaths. Despite efforts to contain the outbreak through integrated surveillance and response strategies, the crisis worsened in 2024 due to drastic climate changes, exacerbating conditions for dengue transmission. Heavy rains since December 2023 have caused flooding and landslides, creating ideal breeding grounds for dengue vectors. Overwhelmed local authorities, especially in areas with limited access to public services due to floods and landslides, struggle to manage the crisis. With more than half the population at risk of dengue infection, urgent measures are required to control the spread of dengue and mitigate increasing mortality rates. Targeted interventions in areas with limited health care access are crucial, considering underreporting and limitations of health systems, to accurately assess the true burden of the disease and prevent further escalation of the crisis.

Mosquito-borne diseases have emerged in North Borneo in Malaysia due to rapid changes in the forest landscape, and mosquito surveillance is key to understanding disease transmission. However, surveillance programmes involving sampling and taxonomic identification require well-trained personnel, are time-consuming and labour-intensive. In this study, we aim to use a deep leaning model (DL) to develop an application capable of automatically detecting mosquito vectors collected from urban and suburban areas in North Borneo, Malaysia. Specifically, a DL model called MobileNetV2 was developed using a total of 4880 images of Aedes aegypti, Aedes albopictus and Culex quinquefasciatus mosquitoes, which are widely distributed in Malaysia. More importantly, the model was deployed as an application that can be used in the field. The model was fine-tuned with hyperparameters of learning rate 0.0001, 0.0005, 0.001, 0.01 and the performance of the model was tested for accuracy, precision, recall and F1 score. Inference time was also considered during development to assess the feasibility of the model as an app in the real world. The model showed an accuracy of at least 97%, a precision of 96% and a recall of 97% on the test set. When used as an app in the field to detect mosquitoes with the elements of different background environments, the model was able to achieve an accuracy of 76% with an inference time of 47.33 ms. Our result demonstrates the practicality of computer vision and DL in the real world of vector and pest surveillance programmes. In the future, more image data and robust DL architecture can be explored to improve the prediction result.

In addition to the well-known differences among the four dengue serotypes, intra-serotypic antigenic diversity has been proposed to play a role in viral evolution and epidemic fluctuation. A replacement of genotype II by genotype III of dengue virus serotype 3 (DENV3) occurred in Thailand during 2007–2014, raising questions about the role of intra-serotypic antigenic differences in this genotype shift. We characterized the antigenic difference of DENV3 of genotypes II and III in Thailand, utilizing a neutralizing antibody assay with DENV3 vaccine sera and monotypic DENV3 sera. Although there was significant antigenic diversity among the DENV3, it did not clearly associate with the genotype. Our data therefore do not support the role of intra-serotypic antigenic difference in the genotype replacement. Amino acid alignment showed that eight positions are potentially associated with diversity between distinct antigenic subgroups. Most of these amino acids were found in envelope domain II. Some positions (aa81, aa124, and aa172) were located on the surface of virus particles, probably involving the neutralization sensitivity. Notably, the strains of both genotypes II and III showed clear antigenic differences from the vaccine genotype I strain. Whether this differencewill affect vaccine efficacy requires further studies.

Dengue, chikungunya, and Zika are arboviruses that cause 390 million infections annually. Risk factors for hospitalization are poorly understood. Communities affected by these diseases have an escalating prevalence of allergies and obesity, which are linked to immune dysfunction. We assessed the association of allergies or body mass with hospitalization for an arbovirus infection. From 2014 to 2017, we recruited participants with a clinical diagnosis of arbovirus infection. Arbovirus infections were laboratory-confirmed and allergies were self-reported. Mid-upper arm circumference (MUAC), weight, and height were measured. We used two logistic regression models to assess the relationships between hospitalization and allergies and between hospitalization and body mass (MUAC for participants <20 years old and body mass index (BMI) for adults ≥20 years old). Models were stratified by age group and adjusted for confounders. For allergies, 41 of 265 were hospitalized. There was no association between allergies and hospitalization. For body mass, 34 of 251 were hospitalized. There was a 43% decrease in hospitalization odds for each additional centimetre MUAC among children (aOR 0.566, 95% CI 0.252–1.019) and a 12% decrease in hospitalization odds for each additional BMI unit among adults (aOR 0.877, 95% CI 0.752–0.998). Our work encourages the exploration of the underlying mechanisms.

Following the report of the first COVID-19 case in Nepal on 23 January 2020, three major waves were documented between 2020 and 2021. By the end of July 2022, 986 596 cases of confirmed COVID-19 and 11 967 deaths had been reported and 70.5% of the population had received at least two doses of a COVID-19 vaccine. Prior to the pandemic, a large dengue virus (DENV) epidemic affected 68 out of 77 districts, with 17 932 cases and six deaths recorded in 2019. In contrast, the country's Epidemiology and Disease Control Division reported 530 and 540 dengue cases in the pandemic period (2020 and 2021), respectively. Furthermore, Kathmandu reported just 63 dengue cases during 2020 and 2021, significantly lower than the 1463 cases reported in 2019. Serological assay showed 3.2% positivity rates for anti-dengue immunoglobulin M antibodies during the pandemic period, contrasting with 26.9–40% prior to it. Real-time polymerase chain reaction for DENV showed a 0.5% positive rate during the COVID-19 pandemic which is far lower than the 57.0% recorded in 2019. Continuing analyses of dengue incidence and further strengthening of surveillance and collaboration at the regional and international levels are required to fully understand whether the reduction in dengue incidence/transmission were caused by movement restrictions during the COVID-19 pandemic.

Biological control is one of the methods available for control of Aedes aegypti populations. We used experimental microcosms to evaluate the effects of actual predation and predation risk by dragonfly larvae (Odonata) on larval development, adult longevity, and adult size of Ae. aegypti. We used six treatments: control, removal, variable density cues (Cues VD), fixed density cues (Cues FD), variable density predator (Predator VD), and fixed density predator (Predator FD) (n = 5 each). Predator treatments received one dragonfly larva. Cue treatments were composed of crushed Ae. aegypti larvae released into the microcosm. For the FD treatments, we maintained a larval density of 200 individuals. The average mortality of Ae. aegypti larvae in the Predator VD treatment was used as the standard mortality for the other treatments. Mosquitoes from the Predator VD and Cues VD treatments developed faster, and adults were larger and had greater longevity compared to all other treatments, likely due to the higher food availability from larval density reduction. High larval density negatively affected larval developmental time, adult size, and longevity. Males were less sensitive to density-dependent effects. Results from this study suggest that the presence of predators may lead to the emergence of adult mosquitoes with greater fitness, causing an overall positive effect on Ae. aegypti population growth rates.

This case illustrates acute myocarditis with complete heart block in a 13-year-old teenager as a rare complication of acute dengue illness. He required urgent temporary pacing with inotropic support and antifailure medications. Complete heart block in dengue myocarditis is an acute but reversible condition. A similar presentation in a dengue-endemic country or with a history of travelling to tropical countries warrants a suspicion of dengue infection.

In 2015–2016, simultaneous circulation of dengue, Zika and chikungunya in the municipality of Rio de Janeiro (Brazil) was reported. We conducted an ecological study to analyse the spatial distribution of dengue, Zika and chikungunya cases and to investigate socioeconomic factors associated with individual and combined disease incidence in 2015–2016. We then constructed thematic maps and analysed the bivariate global Moran indices. Classical and spatial models were used. A distinct spatial distribution pattern for dengue, Zika and chikungunya was identified in the municipality of Rio de Janeiro. The bivariate global Moran indices (P < 0.05) revealed negative spatial correlations between rates of dengue, Zika, chikungunya and combined arboviruses incidence and social development index and mean income. The regression models (P < 0.05) identified a negative relationship between mean income and each of these rates and between sewage and Zika incidence rates, as well as a positive relationship between urban areas and chikungunya incidence rates. In our study, spatial analysis techniques helped to identify high-risk and social determinants at the local level for the three arboviruses. Our findings may aid in backing effective interventions for the prevention and control of epidemics of these diseases.

The role of anthropometric status on dengue is uncertain. We investigated the relations between anthropometric characteristics (height, body mass index and waist circumference (WC)) and two dengue outcomes, seropositivity and hospitalisation, in a cross-sectional study of 2038 children (aged 2–15 years) and 408 adults (aged 18–72 years) from Bucaramanga, Colombia. Anthropometric variables were standardised by age and sex in children. Seropositivity was determined through immunoglobulin G antibodies; past hospitalisation for dengue was self-reported. We modelled the prevalence of each outcome by levels of anthropometric exposures using generalised estimating equations with restricted cubic splines. In children, dengue seropositivity was 60.8%; 9.9% of seropositive children reported prior hospitalisation for dengue. WC was positively associated with seropositivity in girls (90th vs. 10th percentile adjusted prevalence ratio (APR) = 1.19; 95% confidence interval (CI) 1.03–1.36). Among adults, dengue seropositivity was 95.1%; 8.1% of seropositive adults reported past hospitalisation. Height was inversely associated with seropositivity (APR = 0.90; 95% CI 0.83–0.99) and with hospitalisation history (APR = 0.19; 95% CI 0.04–0.79). WC was inversely associated with seropositivity (APR = 0.89; 95% CI 0.81–0.98). We conclude that anthropometry correlates with a history of dengue, but could not determine causation. Prospective studies are warranted to enhance causal inference on these questions.