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The primary aim of this article is to propose an effective dengue disease monitoring system by integrating deep learning models with Internet of Things (IoT) and fog computing. In this context, the disease related parameters are collected using IoT devices and further, the reports are securely transmitted to the healthcare facilities utilizing fog computing. In this article, the misdiagnosis error is reduced utilizing attention based long short term memory (ALSTM) network with coati optimization algorithm (COA). The Attention model allocates higher weight to significant parameters and pay additional consideration while training the model. Therefore, the conventional LSTM network is combined with a self‐attention mechanism for enabling this model to focus on relevant parts of the input sequences for precise dengue disease prediction. The Attention Model differs from the conventional model since it delivers higher amount of data into the decoder and improves additional stages to the attention decoder before making its output. Furthermore, the COA is integrated with the ALSTM network for optimal hyper‐parameter selection. The ALSTM‐COA model evaluates the dengue related parameters like nausea, vomiting, skin rash, joint pain, muscle pain, soft bleeding, temperature of water‐sites, humidity of water‐sites, and so forth, for timely dengue disease diagnosis and clinical decision‐making. The experiments performed on a real time dataset state that the ALSTM‐COA model achieves significant prediction results by utilizing different performance measures like recall, accuracy, fall‐out, miss rate, training time, and testing time. The ALSTM‐COA model obtains an accuracy of 99.27%, latency of 0.03 s, and time complexity of 8 s for 500 health records, which are superior to the comparative deep learning models. [ABSTRACT FROM AUTHOR]

Abstract Background Fogging is a conventional technique used to combat Aedes mosquitoes and prevent dengue disease. It is often implemented in outbreak areas or areas harbouring a high density of Aedes mosquitoes. Currently, studies on stakeholders' attitudes towards fogging are still limited in number. Therefore, this study aims to assess Malaysian attitudes, and identify the predicting factors influencing such attitudes. Methods A validated instrument was used to interview 399 randomly selected respondents from the public (n = 202, 50.6%) and scientists (n = 197, 49.4%) in the Klang Valley region of Malaysia. The data were analysed using PLS-SEM involving Smart-PLS software. Results The results confirmed that stakeholder attitudes toward fogging should be viewed in terms of a multi-dimensional association. The stakeholders surveyed were highly positive with regard to the application of fogging to control dengue but professed moderate concerns as to associated risks. The PLS-SEM analyses demonstrated that the perceived benefit was the most important factor influencing attitudes, followed by trust in key players. Conclusions This result provides a good insight from the perspective of education and unravels the underlying fundamentals of stakeholders' attitudes toward the fogging technique. The findings also provide a positive indicator to the responsible parties involved to continue the usage of this technique in conjunction with improvements with regard to its safety aspects, and possibly in combination with other environmental-friendly alternatives in order to achieve a healthy environment without dengue in Malaysia.

Background: Fogging is a conventional technique used to combat Aedes mosquitoes and prevent dengue disease. It is often implemented in outbreak areas or areas harbouring a high density of Aedes mosquitoes. Currently, studies on stakeholders' attitudes towards fogging are still limited in number. Therefore, this study aims to assess Malaysian attitudes, and identify the predicting factors influencing such attitudes. Methods: A validated instrument was used to interview 399 randomly selected respondents from the public (n = 202, 50.6%) and scientists (n = 197, 49.4%) in the Klang Valley region of Malaysia. The data were analysed using PLS-SEM involving Smart-PLS software. Results: The results confirmed that stakeholder attitudes toward fogging should be viewed in terms of a multi-dimensional association. The stakeholders surveyed were highly positive with regard to the application of fogging to control dengue but professed moderate concerns as to associated risks. The PLS-SEM analyses demonstrated that the perceived benefit was the most important factor influencing attitudes, followed by trust in key players. Conclusions: This result provides a good insight from the perspective of education and unravels the underlying fundamentals of stakeholders' attitudes toward the fogging technique. The findings also provide a positive indicator to the responsible parties involved to continue the usage of this technique in conjunction with improvements with regard to its safety aspects, and possibly in combination with other environmental-friendly alternatives in order to achieve a healthy environment without dengue in Malaysia. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new dynamical system model pertaining to Dengue transmission, and investigate its consequent morphology. We present and study various ramifications of our mathematical model for Dengue spread, encapsulated in a spatio-temporal differential system made of reaction–diffusion equations. Diffusion terms are incorporated into the said model by using specific derivations for infected mosquitoes, and infected humans, as well. Moreover, mechanisms for the nearest neighbor(s) infections are integrated into the model. Furthermore, using adaptive multigrid finite difference with decoupling and quasi-linearization techniques, we investigate two main factors for Dengue spatial propagation. We determine the effects of temperature variations, and the mobility of infectious agents, be they mosquitoes or humans. Finally, the proposed model-based analytico-numerical results are obtained, and rendered in graphical profiles, which show the major role the climate temperature and the mobility of infected humans have on the spread and speed of the disease. The consequent proposed model outcomes and health-based ramifications are then raised, discussed, and then validated. [ABSTRACT FROM AUTHOR]

In this paper, an SIR-SI mathematical model in the form of a system of integral equations describing the transmission of dengue disease between human and mosquitoes is proposed and analyzed. Age-dependent functions are used to describe the survival of individuals in human and mosquito populations. The basic reproduction number is derived and its relationship to the equilibria is also explored. The results show that the existence of the positive endemic equilibrium is determined by a threshold number. This threshold number is also the same one that determines the global stability of the equilibrium. The threshold acts like the known basic reproduction number in the counterpart differential equations model and also follows the same rule for the critical level of intervention. Furthermore, as an application, the effect of wolbachia infection is explored, such as how this infection changes the resulting threshold and what the consequence of its presence is in the dynamics of the disease. In this case, the decrease of the mosquitoes' life expectancy and biting rate are used to reflect the effect of wolbachia bacterial infection on the mosquitoes. In other words, a mosquito which is infected by wolbachia has a lower life expectancy than a normal mosquito. The results, both from mathematical analysis and numerical examples, show that the presence of wolbachia has the potential as a biological control agent to eliminate the dengue in the human population. A comparison of the wolbachia introduction into the mosquito population with the existing strategy, such as vaccination, is also presented. [ABSTRACT FROM AUTHOR]

Dengue fever has earned the title of a rapidly growing global epidemic since the disease-causing mosquito has adapted to colder countries, breaking the notion of dengue being a tropical/subtropical disease only. This infectious time bomb demands timely and proper treatment as it affects vital body functions, often resulting in multiple organ failures once thrombocytopenia and internal bleeding manifest in the patients, adding to morbidity and mortality. In this paper, a tool is used for data collection and analysis for predicting dengue infection presence and estimating risk levels to identify which group of dengue infections the patient suffers from, using a machine-learning-based tertiary classification technique. Based on symptomatic and clinical investigations, the system performs real-time diagnosis. It uses warning indicators to alert the patient of possible internal hemorrhage, warning them to seek medical assistance in case of this disease-related emergency. The proposed model predicts infection levels in a patient based on the classification provided by the World Health Organization, i.e., dengue fever, dengue hemorrhagic fever, and dengue shock syndrome, acquiring considerably high accuracy of over 90% along with high sensitivity and specificity values. The experimental evaluation of the proposed model acknowledges performance efficiency and utilization through statistical approaches. [ABSTRACT FROM AUTHOR]

Dengue disease has become a major public health problem. Accurate and precise identification, prediction and mapping of high-risk areas are crucial elements of an effective and efficient early warning system in countering the spread of dengue disease. In this paper, we present the fusion area-cell spatiotemporal generalized geoadditive-Gaussian Markov random field (FGG-GMRF) framework for joint estimation of an area-cell model, involving temporally varying coefficients, spatially and temporally structured and unstructured random effects, and spatiotemporal interaction of the random effects. The spatiotemporal Gaussian field is applied to determine the unobserved relative risk at cell level. It is transformed to a Gaussian Markov random field using the finite element method and the linear stochastic partial differential equation approach to solve the "big n" problem. Sub-area relative risk estimates are obtained as block averages of the cell outcomes within each sub-area boundary. The FGG-GMRF model is estimated by applying Bayesian Integrated Nested Laplace Approximation. In the application to Bandung city, Indonesia, we combine low-resolution area level (district) spatiotemporal data on population at risk and incidence and high-resolution cell level data on weather variables to obtain predictions of relative risk at subdistrict level. The predicted dengue relative risk at subdistrict level suggests significant fine-scale heterogeneities which are not apparent when examining the area level. The relative risk varies considerably across subdistricts and time, with the latter showing an increase in the period January–July and a decrease in the period August–December. [ABSTRACT FROM AUTHOR]

Spatio-temporal disease mapping models can be used to describe the geographical pattern of disease incidence across space and time. This paper discusses the development and application of spatio-temporal disease models based on generalized linear mixed models (GLMM) incorporating spatially correlated random effects, temporal effects and space–time interaction. Further, the models are fitted within a hierarchical Bayesian framework with Integrated Nested Laplace Approximation (INLA) methodology. The main objectives of this study are to choose the model that best represents the pattern of dengue incidence in Peninsular Malaysia from 2015 to 2017, to estimate the relative risk of disease based on the model selected and to visualize the risk spatial pattern and temporal trend. The models were applied to weekly dengue fever data at the district level in Peninsular Malaysia as reported to the Ministry of Health Malaysia from 2015 to 2017. In conclusion, it can be seen that there was a difference in dengue trend for every district for 2015–2017 and the models used was effective in identifying the high and low risk areas of dengue incidence. [ABSTRACT FROM AUTHOR]

In this review, we discuss how IgG antibodies can modulate inflammatory signaling during viral infections with a focus on CD16a-mediated functions. We describe the structural heterogeneity of IgG antibody ligands, including subclass and glycosylation that impact binding by and downstream activity of CD16a, as well as the heterogeneity of CD16a itself, including allele and expression density. While inflammation is a mechanism required for immune homeostasis and resolution of acute infections, we focus here on two infectious diseases that are driven by pathogenic inflammatory responses during infection. Specifically, we review and discuss the evolving body of literature showing that afucosylated IgG immune complex signaling through CD16a contributes to the overwhelming inflammatory response that is central to the pathogenesis of severe forms of dengue disease and coronavirus disease 2019 (COVID-19). [ABSTRACT FROM AUTHOR]

Dengue is one of the major health problems in Bangladesh and many people are died in recent years due to the severity of this disease. Therefore, in this paper, a SIRS model for the human and SI model for vector population with saturated incidence rate and constant treatment function has been presented to describe the transmission of dengue. The equilibrium points and the basic reproduction number have been computed. The conditions which lead the disease free equilibrium and the endemic equilibrium have been determined. The local stability for the equilibrium points has been established based on the eigenvalues of the Jacobian matrix and the global stability has been analyzed by using the Lyapunov function theory. It is found that the stability of equilibrium points can be controlled by the reproduction number. In order to calculate the infection rate, data for infected human populations have been collected from several health institutions of Bangladesh. Numerical simulations of various compartments have been generated using MATLAB to investigate the influence of the key parameters for the transmission of the disease and to support the analytical results. The effect of treatment function over the infected compartment has been illustrated. The sensitivity of the reproduction number concerning the parameters of the model has been analyzed. Finally, the most sensitive parameter that has the highest effect over reproduction number has been identified.

Host immune responses contribute to dengue’s pathogenesis and severity, yet the possibility that failure in endogenous inflammation resolution pathways could characterise the disease has not been contemplated. The pro-resolving protein Annexin A1 (AnxA1) is known to counterbalance overexuberant inflammation and mast cell (MC) activation. We hypothesised that inadequate AnxA1 engagement underlies the cytokine storm and vascular pathologies associated with dengue disease. Levels of AnxA1 were examined in the plasma of dengue patients and infected mice. Immunocompetent, interferon (alpha and beta) receptor one knockout (KO), AnxA1 KO, and formyl peptide receptor 2 (FPR2) KO mice were infected with dengue virus (DENV) and treated with the AnxA1 mimetic peptide Ac2-26 for analysis. In addition, the effect of Ac2-26 on DENV-induced MC degranulation was assessed in vitro and in vivo. We observed that circulating levels of AnxA1 were reduced in dengue patients and DENV-infected mice. Whilst the absence of AnxA1 or its receptor FPR2 aggravated illness in infected mice, treatment with AnxA1 agonistic peptide attenuated disease manifestationsatteanuated the symptoms of the disease. Both clinical outcomes were attributed to modulation of DENV-mediated viral load-independent MC degranulation. We have thereby identified that altered levels of the pro-resolving mediator AnxA1 are of pathological relevance in DENV infection, suggesting FPR2/ALX agonists as a therapeutic target for dengue disease.

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It is eminent that the epidemiological patterns of dengue are threatening for both the global economy and human health. The experts in the field are always in search to have better mathematician models in order to understand the transmission dynamics of epidemics models and to suggest possible control or the minimization of the infection from the community. In this research, we construct a new fractional-order system for dengue infection with carrier and partially immune classes to visualize the intricate dynamics of dengue. By using the basics of fractional theory, we determine the fundamental results of the proposed fractional-order dengue model. We obtain the basic reproduction number $R_0$ by next generation method and present the results based on it. The stability results are established for the infection-free state of the system. Moreover, sensitivity of $R_0$ is analyzed through partial rank correlation coefficient(PRCC) method to show the importance of different parameters in $R_0$. The influence of different input factors is shown on the output of basic reproduction number $R_0$ numerically. Our result showed that the threshold parameter $R_0$ can be decreased by increasing vaccination and treatment in the system. Finally, we illustrate the solution of the suggested dengue system through a numerical scheme to notice the influence of the fractional-order $\vartheta$ on the system. We observed that the fractional-order dynamics can explain the complex system of dengue infection more precisely and accurately rather than the integer-order dynamics. In addition, we noticed that the index of memory and biting rate of vector can play a significant part in the prevention of the infection.

In this paper, an SIR-SI mathematical model in the form of a system of integral equations describing the transmission of dengue disease between human and mosquitoes is proposed and analyzed. Age-dependent functions are used to describe the survival of individuals in human and mosquito populations. The basic reproduction number is derived and its relationship to the equilibria is also explored. The results show that the existence of the positive endemic equilibrium is determined by a threshold number. This threshold number is also the same one that determines the global stability of the equilibrium. The threshold acts like the known basic reproduction number in the counterpart differential equations model and also follows the same rule for the critical level of intervention. Furthermore, as an application, the effect of wolbachia infection is explored, such as how this infection changes the resulting threshold and what the consequence of its presence is in the dynamics of the disease. In this case, the decrease of the mosquitoes’ life expectancy and biting rate are used to reflect the effect of wolbachia bacterial infection on the mosquitoes. In other words, a mosquito which is infected by wolbachia has a lower life expectancy than a normal mosquito. The results, both from mathematical analysis and numerical examples, show that the presence of wolbachia has the potential as a biological control agent to eliminate the dengue in the human population. A comparison of the wolbachia introduction into the mosquito population with the existing strategy, such as vaccination, is also presented.

Dengue viruses (DENV) are the wildest transmitted arbovirus members of the family Flaviviridae, genus Flavivirus. Dengue viruses are composed of four serotypes, DENV1, 2, 3, and 4, and these viruses can cause dengue fever and dengue haemorrhagic fever or dengue shock syndrome, when infecting humans. RNA interference (RNAi) is a self-defence mechanism, which can be used to prevent invasions of RNA viruses to the host. Genetically engineering a host with an RNAi molecule that targets a single virus serotype may develop escape mutants, and can cause unusual dominance over other serotypes. Therefore, the simultaneous targeting of multiple serotypes is necessary to block DENV transmission. Here, we report the development of transgenic Aedes aegypti based on a bioinformatically designed multiple miRshRNA (microRNA-based shRNA) DNA sequence under the control of a blood-meal induced promoter, Carboxypeptidase A, to induce RNAi for DENV in Aedes aegypti, and demonstrate the expression of a synthetic multiple shRNA polycistronic cluster having RNA interference sequences to target DENV genomes. The transgenic mosquitoes have lower rates of infection, dissemination, and transmission for DENV2 and DENV4 compared to wild mosquitoes, with a significant reduction of dengue copy number and antigen levels in the midgut. These levels of DENV were low enough to make transgenic mosquitoes stop the DENV transmission from infected host to a susceptible host and refractory to DENV2 and DENV4 infection. Such multiple resistance in Ae. aegypti has not been documented previously. Laboratory fitness measurement of transgenic Ae. aegypti showed results comparable to other reported transgenic mosquitoes. [ABSTRACT FROM AUTHOR]

Dengue disease has serious health and socio-economic consequences. Mapping its occurrence at a fine spatiotemporal scale is a crucial element in the preparation of an early warning system for the prevention and control of dengue and other viral diseases. This paper presents a Bayesian spatiotemporal random effects (pure) model of relative dengue disease risk estimated by integrated nested Laplace approximation. Continuous isopleth mapping based on inverse distance weighting is applied to visualize the disease's geographical evolution. The model is applied to data for 30 districts in the city of Bandung, Indonesia, for the period January 2009 to December 2016. We compared the Poisson and the negative binomial distributions for the number of dengue cases, both combined with a model which included structured and unstructured spatial and temporal random effects and their interactions. Using several Bayesian and classical model performance criteria and stepwise backward selection, we chose the negative binomial distribution and the temporal model with spatiotemporal interaction for forecasting. The estimation results show that the relative risk decreased generally from 2014. However, it consistently increased in the north-western districts because of environmental and socio-economic conditions. We also found that every district has a different temporal pattern, indicating that district characteristics influence the temporal variation across space. [ABSTRACT FROM AUTHOR]

Dengue disease is caused by four serotypes of the dengue virus: DEN-1, DEN-2, DEN-3, and DEN-4. The chimeric yellow fever dengue tetravalent dengue vaccine (CYD-TDV) is a vaccine currently used in Thailand. This research investigates what the optimal control is when only individuals having documented past dengue infection history are vaccinated. This is the present practice in Thailand and is the latest recommendation of the WHO. The model used is the Susceptible-Infected-Recovered (SIR) model in series configuration for the human population and the Susceptible-Infected (SI) model for the vector population. Both dynamical models for the two populations were recast as optimal control problems with two optimal control parameters. The analysis showed that the equilibrium states were locally asymptotically stable. The numerical solution of the control systems and conclusions are presented.

Zinc deficiency is highly prevalent in low-income countries, with dramatic consequences to child health, in particular by impairing the immune system resulting in infection. This cross-sectional study aimed to determine the prevalence of zinc deficiency in Thai children who were admitted to hospital with a diagnosis of the dengue viral infection. Standard cut-off values according to age, sex, time of blood collection, and fasting status were used to define zinc levels. 32 patients were included in the analysis: The mean age was 7.3 years, of whom 56.3% were males. 11 (34.4%) patients were diagnosed with dengue hemorrhagic fever and the remaining had dengue fever. The prevalence of zinc deficiency was 46.7%, with boys having a higher risk of zinc deficiency than girls (OR=7.3: 95%CI: 1.5-36.6). Fever duration and length of hospital stay were longer in children with zinc deficiency compared to those who had normal levels, albeit without a significant difference. The results of this study provide the rationale for larger studies that will better elucidate the relationship between zinc levels and the clinical outcomes of dengue disease. [ABSTRACT FROM AUTHOR]

A reaction‐diffusion system with free boundary is proposed to describe the transmission of the dengue disease from mosquitoes to humans. In addition to the classical basic reproduction number R0, the spatial‐temporal basic reproduction number R 0 F ( t ) is introduced to determine the persistence and eradication of the disease. Some sufficient conditions for the disease vanishing or spreading are obtained. The disease will go extinct under one of the conditions: the classical basic reproduction number R0 < 1 and the spatial‐temporal basic reproduction number R 0 F ( 0 ) < 1 < R 0 with small expanding capability. The spread of the disease in the whole area is possible if R 0 F ( t ) > 1 for some t≥0. Numerical simulations are also given to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Abstract Population genetics theory predicted that rare frequent markers would be the main contributors for heritability of complex diseases, but meta-analyses of genome-wide association studies are revealing otherwise common markers, present in all population groups, as the identified candidate genes. In this work, we applied a population-genetics informed meta-analysis to 10 markers located in seven genes said to be associated with dengue fever disease. Seven markers (in PLCE1 , CD32 , CD209 , OAS1 and OAS3 genes) have high-frequency and the other three (in MICB and TNFA genes) have intermediate frequency. Most of these markers have high discriminatory power between population groups, but their frequencies follow the rules of genetic drift, and seem to have not been under strong selective pressure. There was a good agreement in directional consistency across trans-ethnic association signals, in East Asian and Latin American cohorts, with heterogeneity generated by randomness between studies and especially by low sample sizes. This led to confirm the following significant associations: with DF, odds ratio of 0.67 for TNFA -rs1800629-A; with DHF, 0.82 for CD32 -rs1801274-G; with DSS, 0.55 for OAS3 -rs2285933-G, 0.80 for PLCE1 -rs2274223-G and 1.32 for MICB -rs3132468-C. The overall genetic risks confirmed sub-Saharan African populations and descendants as the best protected against the severer forms of the disease, while Southeast and Northeast Asians are the least protected ones. European and close neighbours are the best protected against dengue fever, while, again, Southeast and Northeast Asians are the least protected ones. These risk scores provide important predictive information for the largely naïve European and North American regions, as well as for Africa where misdiagnosis with other hemorrhagic diseases is of concern. Highlights • The 10 dengue fever-associated markers present high- and intermediate-frequencies. • There was directional consistency across trans-ethnic association signals. • Significant associations were phenotype-specific, and mainly for DSS. • Sub-Saharan African populations are the best protected against DSS. • Southeast and Northeast Asians are the least protected against DSS and DF. [ABSTRACT FROM AUTHOR]

Objective Our objective was to describe the risk of hospital admission for virologically confirmed dengue (VCD) and the risk of clinically severe hospitalized VCD occurring up to 4 years after the first dose (years 1 to 4) in three randomized clinical trials comparing tetravalent dengue vaccine with placebo. Methods The relative risks (RR) for hospitalized VCD from first dose to year 4 were estimated by year and age-group in individual and combined studies. Results Overall, from Year 1 to Year 4, 233 and 228 participants had at least one episode of hospitalized VCD in the vaccinated ( n = 22 603) and placebo ( n = 11 301) groups, respectively (RR = 0.511, 95% CI 0.42–0.62). Among these, 48 and 47 cases, respectively, were classified as clinically severe. In children aged ≥9 years, 88 and 136 participants had at least one episode of hospitalized VCD in the vaccinated ( n = 17 629) and placebo ( n = 8821) groups, respectively (RR = 0.324; 95% CI 0.24–0.43). In vaccinated participants aged <9 years, particularly in those aged 2–5 years, there were more hospitalized VCD cases compared with the control participants in Year 3 but not in Year 4. The overall RR in those aged <9 years for Year 1 to Year 4 was 0.786 (95% CI 0.60–1.03), with a higher protective effect in the 6–8 year olds than in the 2–5 year olds. Conclusions The overall benefit-risk remained positive in those aged ≥9 years up to year 4, although the protective effect was lower in years 3 and 4 than in years 1 and 2. [ABSTRACT FROM AUTHOR]

Dengue, also known as break-bone fever, is a tropical disease transmitted by mosquitoes. If the similarity between dengue infected users can be identified, it can help government's health agencies to manage the outbreak more effectively. To find similarity between cases affected by Dengue, user's personal and health information are the two fundamental requirements. Identification of similar symptoms, causes, effects, predictions and treatment procedures, is important. In this paper, an effective framework is proposed which finds similar patients suffering from dengue using keyword aware domain thesaurus and case base reasoning method. This paper focuses on the use of ontology dependent domain thesaurus technique to extract relevant keywords and then build cases with the help of case base reasoning method. Similar cases can be shared with users, nearby hospitals and health organizations to manage the problem more adequately. Two million case bases were generated to test the proposed similarity method. Experimental evaluations of proposed framework resulted in high accuracy and low error rate for finding similar cases of dengue as compared to UPCC and IPCC algorithms. The framework developed in this paper is for dengue but can easily be extended to other domains also. [ABSTRACT FROM AUTHOR]

In the study of disease mapping, relative risk estimation is the focus of analysis. Many methods have been introduced to estimate relative risk. In this paper, one of the common spatial models known as Besag, York and Mollié (BYM) model is discussed, and its application to dengue data for epidemiology weeks 1 to 52 of the year 2013 for 16 states in Malaysia is studied. Findings show that Selangor has the highest relative risk of dengue in comparison with other states. Data on the estimated relative risks are presented in the form of risk maps which can be used as a tool for the prevention and control of dengue. [ABSTRACT FROM AUTHOR]

Infection with any of the 4 dengue virus serotypes results in a diverse range of symptoms, from mild undifferentiated fever to life-threatening hemorrhagic fever and shock. Given that dengue virus infection elicits such a broad range of clinical symptoms, early and accurate laboratory diagnosis is essential for appropriate patient management. Virus detection and serological conversion have been the main targets of diagnostic assessment for many years, however cross-reactivity of antibody responses among the flaviviruses has been a confounding issue in providing a differential diagnosis. Furthermore, there is no single, definitive diagnostic biomarker that is present across the entire period of patient presentation, particularly in those experiencing a secondary dengue infection. Nevertheless, the development and commercialization of point-of-care combination tests capable of detecting markers of infection present during different stages of infection (viral nonstructural protein 1 and immunoglobulin M) has greatly simplified laboratory-based dengue diagnosis. Despite these advances, significant challenges remain in the clinical management of dengue-infected patients, especially in the absence of reliable biomarkers that provide an effective prognostic indicator of severe disease progression. This review briefly summarizes some of the complexities and issues surrounding clinical dengue diagnosis and the laboratory diagnostic options currently available. [ABSTRACT FROM AUTHOR]