Dengue outbreaks in the COVID-19 era: Alarm raised for Asia

Upsurge of dengue outbreaks in several WHO regions: Public awareness, vector control activities, and international collaborations are key to prevent spread

Background

Dengue, the world's fastest-growing vector-borne disease, has skyrocketed in the 21st century. Dengue has harmed human health since its first known cases among Spanish soldiers in the Philippines to its 21st-century outbreaks in Southeast Asia, the Pacific, and the Americas. In light of the current circumstances, it is imperative to investigate its origin and prevalence, enabling the implementation of effective interventions to curb the upsurge.

Methods

Our study examines the history of dengue outbreaks, and evolving impact on public health, aiming to offer valuable insights for a more resilient public health response worldwide. In this comprehensive review, we incorporated data from renowned databases such as PubMed, Google Scholar, and Scopus to provide a thorough analysis of dengue outbreaks.

Results

Recent dengue outbreaks are associated with rapid urbanization, international travel, climatic change, and socioeconomic factors. Rapid urbanization and poor urban design and sanitation have created mosquito breeding places for dengue vectors. Also, international travel and trade have spread the pathogen. Climate change in the past two decades has favored mosquito habitats and outbreaks. Socioeconomic differences have also amplified the impact of dengue outbreaks on vulnerable communities. Dengue mitigation requires vector control, community engagement, healthcare strengthening, and international cooperation.

Conclusion

Climate change adaptation and urban planning are crucial. Although problems remain, a comprehensive vector control and community involvement plan may reduce dengue epidemics and improve public health in our interconnected world.

The effects of the COVID-19 pandemic on dengue cases in Malaysia

Background

Globally, the COVID-19 pandemic has affected the transmission dynamics and distribution of dengue. Therefore, this study aims to describe the impact of the COVID-19 pandemic on the geographic and demographic distribution of dengue incidence in Malaysia.

Methods

This study analyzed dengue cases from January 2014 to December 2021 and COVID-19 confirmed cases from January 2020 to December 2021 which was divided into the pre (2014 to 2019) and during COVID-19 pandemic (2020 to 2021) phases. The average annual dengue case incidence for geographical and demographic subgroups were calculated and compared between the pre and during the COVID-19 pandemic phases. In addition, Spearman rank correlation was performed to determine the correlation between weekly dengue and COVID-19 cases during the COVID-19 pandemic phase.

Results

Dengue trends in Malaysia showed a 4-year cyclical trend with dengue case incidence peaking in 2015 and 2019 and subsequently decreasing in the following years. Reductions of 44.0% in average dengue cases during the COVID-19 pandemic compared to the pre-pandemic phase was observed at the national level. Higher dengue cases were reported among males, individuals aged 20-34 years, and Malaysians across both phases. Weekly dengue cases were significantly correlated (ρ = -0.901) with COVID-19 cases during the COVID-19 pandemic.

Conclusion

There was a reduction in dengue incidence during the COVID-19 pandemic compared to the pre-pandemic phase. Significant reductions were observed across all demographic groups except for the older population (>75 years) across the two phases.

Tracing down the Updates on Dengue Virus-Molecular Biology, Antivirals, and Vaccine Strategies

BACKGROUND

Nearly half of the world is at risk of developing dengue infection. Dengue virus is the causative agent behind this public healthcare concern. Millions of dengue cases are reported every year, leading to thousands of deaths. The scientific community is working to develop effective therapeutic strategies in the form of vaccines and antiviral drugs against dengue.

METHODS

In this review, a methodological approach has been used to gather data from the past five years to include the latest developments against the dengue virus.

RESULTS

Different therapeutics and antiviral targets against the dengue virus are at different stages of development, but none have been approved by the FDA. Moreover, various vaccination strategies have also been discussed, including attenuated virus vaccines, recombinant subunit vaccines, viral vector vaccines, DNA vaccines, nanotechnology, and plant-based vaccines, which are used to develop effective vaccines for the dengue virus. Many dengue vaccines pass the initial phases of evaluation, but only two vaccines have been approved for public use. DENGVAXIA is the only FDA-approved vaccine against all four stereotypes of the dengue virus, but it is licensed for use only in individuals 6-16 years of age with laboratory-confirmed previous dengue infection and living in endemic countries. Takeda is the second vaccine approved for use in the European Union, the United Kingdom, Brazil, Argentina, Indonesia, and Thailand. It produced sustained antibody responses against all four serotypes of dengue virus, regardless of previous exposure and dosing schedule. Other dengue vaccine candidates at different stages of development are TV-003/005, TDENV PIV, V180, and some DNA vaccines.

CONCLUSION

There is a need to put more effort into developing effective vaccines and therapeutics for dengue, as already approved vaccines and therapeutics have limitations. DENGVAXIA is approved for use in children and teenagers who are 6-16 years of age and have confirmed dengue infection, while Takeda is approved for use in certain countries, and it has withdrawn its application for FDA approval.

Attitude towards dengue control efforts with the potential of digital technology during COVID-19: partial least squares-structural equation modeling

Background: Dengue fever is still a public health issue in Indonesia, and during the coronavirus disease 2019 (COVID-19) pandemic, integrated digital technology will be required for its control. This study aims to identify critical indicators influencing attitudes towards dengue control related to the potential for implementing digital technology. Methods: This was a cross-sectional survey, with 515 people willing to fill out an online questionnaire. The analysis was conducted using Partial Least Square-Structural Equation Modelling (PLS-SEM). There were 46 indicators used to assess attitudes toward dengue control, which were organized into six variables: the need for digital information systems, perceptions of being threatened with dengue, the benefits of dengue control programs, program constraints, environmental factors and attitudes in dengue control. Results:  The source of information needed for dengue control was mainly through social media. There was a positive relationship between perception of environmental factors to perception of dengue threat, perception of program constraints, perception of program benefits, and perception of digital technology needs. Perception of program benefits and threatened perception of dengue have a positive relationship with perception of digital technology needs. Conclusions: This model showed the variables perception of digital technology and perception of benefits had a positive association with attitude towards dengue control.

Rapid Diagnostic Tests for the Detection of the Four Dengue Virus Serotypes in Clinically Relevant Matrices

The efficient and accurate diagnosis of dengue, a major mosquito-borne disease, is of primary importance for clinical care, surveillance, and outbreak control. The identification of specific dengue virus serotype 1 (DENV-1) to DENV-4 can help in understanding the transmission dynamics and spread of dengue disease. The four rapid low-resource serotype-specific dengue tests use a simple sample preparation reagent followed by reverse transcription-isothermal recombinase polymerase amplification (RT-RPA) combined with lateral flow detection (LFD) technology. Results are obtained directly from clinical sample matrices in 35 min, requiring only a heating block and pipettes for liquid handling. In addition, we demonstrate that the rapid sample preparation step inactivates DENV, improving laboratory safety. Human plasma and serum were spiked with DENV, and DENV was detected with analytical sensitivities of 333 to 22,500 median tissue culture infectious doses (TCID₅₀)/mL. The analytical sensitivities in blood were 94,000 to 333,000 TCID₅₀/mL. Analytical specificity testing confirmed that each test could detect multiple serotype-specific strains but did not respond to strains of other serotypes, closely related flaviviruses, or chikungunya virus. Clinical testing on 80 human serum samples demonstrated test specificities of between 94 and 100%, with a DENV-2 test sensitivity of 100%, detecting down to 0.004 PFU/μL, similar to the sensitivity of the PCR test; the other DENV tests detected down to 0.03 to 10.9 PFU/μL. Collectively, our data suggest that some of our rapid dengue serotyping tests provide a potential alternative to conventional labor-intensive RT-quantitative PCR (RT-qPCR) detection, which requires expensive thermal cycling instrumentation, technical expertise, and prolonged testing times. Our tests provide performance and speed without compromising specificity in human plasma and serum and could become promising tools for the detection of high DENV loads in resource-limited settings. IMPORTANCE The efficient and accurate diagnosis of dengue, a major mosquito-borne disease, is of primary importance for clinical care, surveillance, and outbreak control. This study describes the evaluation of four rapid low-resource serotype-specific dengue tests for the detection of specific DENV serotypes in clinical sample matrices. The tests use a simple sample preparation reagent followed by reverse transcription-isothermal recombinase polymerase amplification (RT-RPA) combined with lateral flow detection (LFD) technology. These tests have several advantages compared to RT-qPCR detection, such as a simple workflow, rapid sample processing and turnaround times (35 min from sample preparation to detection), minimal equipment needs, and improved laboratory safety through the inactivation of the virus during the sample preparation step. The low-resource formats of these rapid dengue serotyping tests have the potential to support effective dengue disease surveillance and enhance the diagnostic testing capacity in resource-limited countries with both endemic dengue and intense coronavirus disease 2019 (COVID-19) transmission.

Rapid Appraisals of the Transformation Strategy Required to Sustain Dengue Vector Control During and After the COVID-19 Pandemic in Indonesia

Purpose

This research aimed to observe the gap for improvement in dengue vector control during COVID-19, considering two stakeholders: the government and society. We formulated two research questions: 1) How is the government managing dengue vector control during the COVID-19 pandemic? 2) What is the situation of dengue disease, its vectors, and vector control in the community?

Methods

This study uses multiple approaches: policy review, social listening using Twitter analysis, and interviews. A policy review was employed to capture the journey of dengue vector control in Indonesia from dengue found in Indonesia until the COVID-19 pandemic. Twitter data captured public opinions through social media about dengue and vector control. Interviews involved program implementers that consider knowing the situation in the field of dengue and its vector control. The informant was selected through purposive sampling.

Results

To control dengue disease, the Indonesian government has released regulations about dengue vector control that adjusts the COVID-19 situation, but vector control is still not running optimally, resulting in the data supply for policy not running well.

Conclusion

Dengue cases continued during the COVID-19 pandemic, even in some places stated an outbreak occurred. Vector control does not work correctly during the COVID-19 pandemic due to social restrictions. It is recommended to encourage the implementation of community empowerment through one house, one jumantik, which is equipped with self-reporting to mitigate and respond to similar situations as the pandemic.

Correlations between COVID-19 and dengue obtained via the study of South America, Africa and Southeast Asia during the 2020s

A dramatic increase in the number of outbreaks of dengue has recently been reported, and climate change is likely to extend the geographical spread of the disease. In this context, this paper shows how a neural network approach can incorporate dengue and COVID-19 data as well as external factors (such as social behaviour or climate variables), to develop predictive models that could improve our knowledge and provide useful tools for health policy makers. Through the use of neural networks with different social and natural parameters, in this paper we define a Correlation Model through which we show that the number of cases of COVID-19 and dengue have very similar trends. We then illustrate the relevance of our model by extending it to a Long short-term memory model (LSTM) that incorporates both diseases, and using this to estimate dengue infections via COVID-19 data in countries that lack sufficient dengue data.

Community-based mosquito surveillance: an automatic mosquito-on-human-skin recognition system with a deep learning algorithm

BACKGROUND

Public community engagement is crucial for mosquito surveillance programs. To support community participation, one of the approaches is assisting the public in recognizing the mosquitoes that carry pathogens. Therefore, this study aims to build an automatic recognition system to identify mosquitos at the public community level. We construct a customized image dataset consisting of three mosquito species in either damaged or un-damaged body conditions. To distinguish the mosquito in harsh conditions, we explore two state-of-the-art deep learning (DL) architectures: (i) a freezing convolutional base, with partial trainable weights, and (ii) training the entire model with most of the trainable weights. We project a weighted feature map on different layers of the model to visualize the morphological region used by the model in classification and compared it with the morphological key used by the expert.

RESULT

It was found that the model with architecture two and the Adam optimizer achieves at least 98% accuracy in mosquito and conditions identification and when implemented on an independent dataset, the Xception model generalizes the best result with an accuracy of 0.7775 and 0.795 precision. Moreover, most of the morphological regions used by the model are able to match those of the human expert.

CONCLUSION

We report a customized DL model for performing pest mosquito taxonomy identification, and through visualization, some regions using computers to discriminate mosquito species could be adopted later in systematic identification. © 2022 Society of Chemical Industry.

Identification, Validation and Standardization of Bioactive Molecules Using UPLC/MS-QToF, UHPLC and HPTLC in Divya-Denguenil-Vati: A Penta-Herbal Formulation for Dengue Fever

For the last fifty years, Dengue has been one of the most common mosquito-borne arboviral infections which has spread over the tropical and subtropical world. Divya-Denguenil-Vati (DNV) has been formulated by blending five specific herbs for effective resolution of Dengue fever. In the present study, we aimed to identify, develop, validate, and standardize methods for Divya-Denguenil-Vati (DNV), on UHPLC and HPTLC analytical platforms, with rapid, sensitive, accurate and rugged attributes. At first, 97 phyto-constituents were identified by UPLC/MS-QToF in Divya-Denguenil-Vati. UHPLC method was then developed and validated for simultaneous determination of gallic acid, 5-HMF, protocatechuic acid, magnoflorine, methyl gallate, berberine, rutin, ellagic acid, β-ecdysone and rosmarinic acid in DNV. Four selected markers, gallic acid, rosmarinic acid, magnoflorine and rutin were further developed and validated on HPTLC. Analytical processes were validated as per ICH Q2 (R1) guidelines; and were found linear (r² > 0.99), sensitive, precise (%RSD < 5%), and accurate, as indicated by high recovery values (88–105%). The limit of detection and quantification were also established for these phyto-metabolites, with their respective RSDs within 5% limits. Finally, these validated methods were employed to test twenty six different commercial batches of DNV. The quality, reproducibility and consistency of DNV have been well established using these developed and reliable analytical tools. These analytical strategies successfully set a path forward for robust quality evaluation and standardization of Divya-Denguenil-Vati, and other related herbal formulations.

Text mining in mosquito-borne disease: A systematic review

Mosquito-borne diseases are emerging and re-emerging across the globe, especially after the COVID19 pandemic. The recent advances in text mining in infectious diseases hold the potential of providing timely access to explicit and implicit associations among information in the text. In the past few years, the availability of online text data in the form of unstructured or semi-structured text with rich content of information from this domain enables many studies to provide solutions in this area, e.g., disease-related knowledge discovery, disease surveillance, early detection system, etc. However, a recent review of text mining in the domain of mosquito-borne disease was not available to the best of our knowledge. In this review, we survey the recent works in the text mining techniques used in combating mosquito-borne diseases. We highlight the corpus sources, technologies, applications, and the challenges faced by the studies, followed by the possible future directions that can be taken further in this domain. We present a bibliometric analysis of the 294 scientific articles that have been published in Scopus and PubMed in the domain of text mining in mosquito-borne diseases, from the year 2016 to 2021. The papers were further filtered and reviewed based on the techniques used to analyze the text related to mosquito-borne diseases. Based on the corpus of 158 selected articles, we found 27 of the articles were relevant and used text mining in mosquito-borne diseases. These articles covered the majority of Zika (38.70%), Dengue (32.26%), and Malaria (29.03%), with extremely low numbers or none of the other crucial mosquito-borne diseases like chikungunya, yellow fever, West Nile fever. Twitter was the dominant corpus resource to perform text mining in mosquito-borne diseases, followed by PubMed and LexisNexis databases. Sentiment analysis was the most popular technique of text mining to understand the discourse of the disease and followed by information extraction, which dependency relation and co-occurrence-based approach to extract relations and events. Surveillance was the main usage of most of the reviewed studies and followed by treatment, which focused on the drug-disease or symptom-disease association. The advance in text mining could improve the management of mosquito-borne diseases. However, the technique and application posed many limitations and challenges, including biases like user authentication and language, real-world implementation, etc. We discussed the future direction which can be useful to expand this area and domain. This review paper contributes mainly as a library for text mining in mosquito-borne diseases and could further explore the system for other neglected diseases.

Efficacy of rupatadine in reducing the incidence of dengue haemorrhagic fever in patients with acute dengue: A randomised, double blind, placebo-controlled trial

BACKGROUND

Rupatadine was previously shown to reduce endothelial dysfunction in vitro, reduced vascular leak in dengue mouse models and to reduce the extent of pleural effusions and thrombocytopenia in patients with acute dengue. Therefore, we sought to determine the efficacy of rupatadine in reducing the incidence of dengue haemorrhagic fever (DHF) in patients with acute dengue.

METHODS AND FINDINGS

A phase 2, randomised, double blind, placebo controlled clinical trial was carried out in patients with acute dengue in Sri Lanka in an outpatient setting. Patients with ≤3 days since the onset of illness were either recruited to the treatment arm of oral rupatadine 40mg for 5 days (n = 123) or the placebo arm (n = 126). Clinical and laboratory features were measured daily to assess development of DHF and other complications. 12 (9.7%) patients developed DHF in the treatment arm compared to 22 (17.5%) who were on the placebo although this was not significant (p = 0.09, relative risk 0.68, 95% CI 0.41 to 1.08). Rupatadine also significantly reduced (p = 0.01) the proportion of patients with platelet counts <50,000 cells/mm3 and significantly reduced (p = 0.04) persisting vomiting, headache and hepatic tenderness (p<0.0001) in patients. There was a significant difference in the duration of illness (p = 0.0002) although the proportion of individuals who required hospital admission in both treatment arms. Only 2 patients on rupatadine and 3 patients on the placebo developed shock, while bleeding manifestations were seen in 6 patients on rupatadine and 7 patients on the placebo.

CONCLUSIONS

Rupatadine appeared to be safe and well tolerated and showed a trend towards a reducing proportion of patients with acute dengue who developed DHF. Its usefulness when used in combination with other treatment modalities should be explored.

TRIAL REGISTRATION

International Clinical Trials Registration Platform: SLCTR/2017/024.

Effects of COVID-19 Non-Pharmacological Interventions on Dengue Infection: A Systematic Review and Meta-Analysis

Non-pharmacological interventions (NPIs) implemented during the coronavirus disease 2019 (COVID-19) pandemic have demonstrated significant positive effects on other communicable diseases. Nevertheless, the response for dengue fever has been mixed. To illustrate the real implications of NPIs on dengue transmission and to determine the effective measures for preventing and controlling dengue, we performed a systematic review and meta-analysis of the available global data to summarize the effects comprehensively. We searched Embase, PubMed, and Web of Science in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines from December 31, 2019, to March 30, 2022, for studies of NPI efficacy on dengue infection. We obtained the annual reported dengue cases from highly dengue-endemic countries in 2015–2021 from the European Centre for Disease Prevention and Control to determine the actual change in dengue cases in 2020 and 2021, respectively. A random-effects estimate of the pooled odds was generated with the Mantel-Haenszel method. Between-study heterogeneity was assessed using the inconsistency index (I²) and subgroup analysis according to country (dengue-endemic or non-endemic) was conducted. This review was registered with PROSPERO (CRD42021291487). A total of 17 articles covering 32 countries or regions were included in the review. Meta-analysis estimated a pooled relative risk of 0.39 (95% CI: 0.28–0.55), and subgroup revealed 0.06 (95% CI: 0.02-0.25) and 0.55 (95% CI: 0.44-0.68) in dengue non-endemic areas and dengue-endemic countries, respectively, in 2020. The majority of highly dengue-endemic countries in Asia and Americas reported 0–100% reductions in dengue cases in 2020 compared to previous years, while some countries (4/20) reported a dramatic increase, resulting in an overall increase of 11%. In contrast, there was an obvious reduction in dengue cases in 2021 in almost all countries (18/20) studied, with an overall 40% reduction rate. The overall effectiveness of NPIs on dengue varied with region and time due to multiple factors, but most countries reported significant reductions. Travel-related interventions demonstrated great effectiveness for reducing imported cases of dengue fever. Internal movement restrictions of constantly varying intensity and range are more likely to mitigate the entire level of dengue transmission by reducing the spread of dengue fever between regions within a country, which is useful for developing a more comprehensive and sustainable strategy for preventing and controlling dengue fever in the future.

Hit-to-Lead Short Peptides against Dengue Type 2 Envelope Protein: Computational and Experimental Investigations

Data from the World Health Organisation show that the global incidence of dengue infection has risen drastically, with an estimated 400 million cases of dengue infection occurring annually. Despite this worrying trend, there is still no therapeutic treatment available. Herein, we investigated short peptide fragments with a varying total number of amino acid residues (peptide fragments) from previously reported dengue virus type 2 (DENV2) peptide-based inhibitors, DN58wt (GDSYIIIGVEPGQLKENWFKKGSSIGQMF), DN58opt (TWWCFYFCRRHHPFWFFYRHN), DS36wt (LITVNPIVTEKDSPVNIEAE), and DS36opt (RHWEQFYFRRRERKFWLFFW), aided by in silico approaches: peptide–protein molecular docking and 100 ns of molecular dynamics (MD) simulation via molecular mechanics using Poisson–Boltzmann surface area (MMPBSA) and molecular mechanics generalised Born surface area (MMGBSA) methods. A library of 11,699 peptide fragments was generated, subjected to in silico calculation, and the candidates with the excellent binding affinity and shown to be stable in the DI-DIII binding pocket of DENV2 envelope (E) protein were determined. Selected peptides were synthesised using conventional Fmoc solid-phase peptide chemistry, purified by RP-HPLC, and characterised using LCMS. In vitro studies followed, to test for the peptides’ toxicity and efficacy in inhibiting the DENV2 growth cycle. Our studies identified the electrostatic interaction (from free energy calculation) to be the driving stabilising force for the E protein–peptide interactions. Five key E protein residues were also identified that had the most interactions with the peptides: (polar) LYS36, ASN37, and ARG350, and (nonpolar) LEU351 and VAL354; these residues might play crucial roles in the effective binding interactions. One of the peptide fragments, DN58opt_8-13 (PFWFFYRH), showed the best inhibitory activity, at about 63% DENV2 plague reduction, compared with no treatment. This correlates well with the in silico studies in which the peptide possessed the lowest binding energy (−9.0 kcal/mol) and was maintained steadily within the binding pocket of DENV2 E protein during the MD simulations. This study demonstrates the use of computational studies to expand research on lead optimisation of antiviral peptides, thus explaining the inhibitory potential of the designed peptides.

Dengue and COVID-19: Managing Undifferentiated Febrile Illness during a "Twindemic"

BACKGROUND

During the COVID-19 pandemic, distinguishing dengue from COVID-19 in endemic areas can be difficult, as both may present as undifferentiated febrile illness. COVID-19 cases may also present with false-positive dengue serology. Hospitalisation protocols for managing undifferentiated febrile illness are essential in mitigating the risk from both COVID-19 and dengue.

METHODS

At a tertiary hospital contending with COVID-19 during a dengue epidemic, a triage strategy of routine COVID-19 testing for febrile patients with viral prodromes was used. All febrile patients with viral prodromes and no epidemiologic risk for COVID-19 were first admitted to a designated ward for COVID-19 testing, from January 2020 to December 2021.

RESULTS

A total of 6103 cases of COVID-19 and 1251 cases of dengue were managed at our institution, comprising a total of 3.9% (6103/155,452) and 0.8% (1251/155,452) of admissions, respectively. A surge in dengue hospitalisations in mid-2020 corresponded closely with the imposition of a community-wide lockdown. A total of 23 cases of PCR-proven COVID-19 infection with positive dengue serology were identified, of whom only two were true co-infections; both had been appropriately isolated upon admission. Average length-of-stay for dengue cases initially admitted to isolation during the pandemic was 8.35 days (S.D. = 6.53), compared with 6.91 days (S.D. = 8.61) for cases admitted outside isolation (1.44 days, 95%CI = 0.58-2.30, p = 0.001). Pre-pandemic, only 1.6% (9/580) of dengue cases were admitted initially to isolation-areas; in contrast, during the pandemic period, 66.6% (833/1251) of dengue cases were initially admitted to isolation-areas while awaiting the results of SARS-CoV-2 testing.

CONCLUSIONS

During successive COVID-19 pandemic waves in a dengue-endemic country, coinfection with dengue and COVID-19 was uncommon. Routine COVID-19 testing for febrile patients with viral prodromes mitigated the potential infection-prevention risk from COVID-19 cases, albeit with an increased length-of-stay for dengue hospitalizations admitted initially to isolation.