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.

Circulation of multiple dengue virus (DENV) serotypes in a locale has resulted in individuals becoming infected with mixed serotypes. This research was undertaken to study the clinical presentation, presence of DENV serotypes and serological characteristics of DENV infected patients with co-infections from three Provinces of Sri Lanka where DENV-1 and -2 predominated during the study. A reverse transcription polymerase chain reaction was performed on 1249 patient samples and 301 were positive for DENV (24.1%). DENV-1 was the predominant serotype detected in 137 (45.51%) followed by DENV-2 in 65 (21.59%), DENV-3 in 59 (19.6%) and DENV-4 in 4 (1.32%) patients with mono-infections. Thirty-three patients (10.96%) had DENV co-infections with two or more serotypes. The highest number of co-infections was noted between DENV-1 and DENV-2 (57.57%) suggesting co-infection is driven by the frequency of the circulating serotypes. Platelet counts were significantly higher in DENV co-infected patients although clinical disease severity or white blood cell count, packed cell volume or viraemia were not significantly different in the co-infected compared to the mono-infected patients. Thus co-infection with multiple DENV serotypes does occur but with the exception of improved platelet counts in co-infected patients, there is no evidence that clinical or laboratory measures of disease are altered.

Currently, dengue control relies largely on reactive vector control programmes. Proactive vector-control using a rational, well-balanced integrated vector management approach may prove more successful for dengue control. As part of the development of a cluster randomized controlled epidemiological trial, a study was conducted in Johor Bahru, Malaysia. The study included one control site (three buildings) and three intervention sites which were treated as follows: targeted outdoor residual spraying only (TORS site, two buildings); deployment of autodissemination devices only (ADD site, four buildings); and the previous two treatments combined (TORS + ADD site, three buildings). The primary entomological measurement was per cent of positive ovitraps—ovitrap index (OI). The effect of each intervention on OI was analyzed by a modified ordinary least squares regression model. Relative to the control site, the TORS and ADD sites showed a reduction in the Aedes OI (−6.5%, P = 0.04 and −8.3%, P = 0.10, respectively). Analysis by species showed that, relative to control, the Ae. aegypti OI was lower in ADD (−8.9%, P = 0.03) and in TORS (−10.4%, P = 0.02). No such effect was evident in the TORS + ADD site. The present study provides insights into the methods to be used for the main trial. The combination of multiple insecticides with different modes of action in one package is innovative, although we could not demonstrate the additive effect of TORS + ADD. Further work is required to strengthen our understanding of how these interventions impact dengue vector populations and dengue transmission.

Dengue is a widespread vector-borne disease believed to affect between 100 and 390 million people every year. The interaction between vector, host and pathogen is influenced by various climatic factors and the relationship between dengue and climatic conditions has been poorly explored in India. This study explores the relationship between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and dengue cases in India. Additionally, distributed lag non-linear model was used to assess the delayed effects of climatic factors on dengue cases. The weekly dengue cases reported by the Integrated Disease Surveillance Program (IDSP) over India during the period 2010–2017 were analysed. The study shows that dengue cases usually follow a seasonal pattern, with most cases reported in August and September. Both temperature and rainfall were positively associated with the number of dengue cases. The precipitation shows the higher transmission risk of dengue was observed between 8 and 15 weeks of lag. The highest relative risk (RR) of dengue was observed at 60 mm rainfall with a 12-week lag period when compared with 40 and 80 mm rainfall. The RR of dengue tends to increase with increasing mean temperature above 24 °C. The largest transmission risk of dengue was observed at 30 °C with a 0–3 weeks of lag. Similarly, the transmission risk increases more than twofold when the minimum temperature reaches 26 °C with a 2-week lag period. The dengue cases and El Niño were positively correlated with a 3–6 months lag period. The significant correlation observed between the IOD and dengue cases was shown for a 0–2 months lag period.

Dengue fever is a disease with increasing incidence, now occurring in some regions which were not previously affected. Ribeirão Preto and São Paulo, municipalities in São Paulo state, Brazil, have been highlighted due to the high dengue incidences especially after 2009 and 2013. Therefore, the current study aims to analyse the temporal behaviour of dengue cases in the both municipalities and forecast the number of disease cases in the out-of-sample period, using time series models, especially SARIMA model. We fitted SARIMA models, which satisfactorily meet the dengue incidence data collected in the municipalities of Ribeirão Preto and São Paulo. However, the out-of-sample forecast confidence intervals are very wide and this fact is usually omitted in several papers. Despite the high variability, health services can use these models in order to anticipate disease scenarios, however, one should interpret with prudence since the magnitude of the epidemic may be underestimated.