Virus antibody dynamics in primary and secondary dengue infections

Exploring the therapeutic potential of DV-B-120 as an inhibitor of dengue virus infection

Dengue fever, an infectious disease prevalent in subtropical and tropical regions, currently lacks effective small-molecule drugs as treatment. In this study, we used a fluorescence peptide cleavage assay to screen seven compounds to assess their inhibition of the dengue virus (DENV) NS2B-NS3 protease. DV-B-120 demonstrated superior inhibition of NS2B-NS3 protease activity and lower toxicity compared to ARDP0006. The selectivity index of DV-B-120 was higher than that of ARDP0006. In vivo assessments of the antiviral efficacy of DV-B-120 against DENV replication demonstrated delayed mortality of suckling mice treated with the compound, with 60-80% protection against life-threatening effects, compared to the outcomes of DENV-infected mice treated with saline. The lower clinical scores of DENV-infected mice treated with DV-B-120 indicated a reduction in acute-progressive illness symptoms, underscoring the potential therapeutic impact of DV-B-120. Investigations of DV-B-120's ability to restore the antiviral type I IFN response in the brain tissue of DENV-infected ICR suckling mice demonstrated its capacity to stimulate IFN and antiviral IFN-stimulated gene expression. DV-B-120 not only significantly delayed DENV-2-induced mortality and illness symptoms but also reduced viral numbers in the brain, ultimately restoring the innate antiviral response. These findings strongly suggest that DV-B-120 holds promise as a therapeutic agent against DENV infection and highlight its potential contribution in addressing the current lack of effective treatments for this infectious disease.IMPORTANCEThe prevalence of dengue virus (DENV) infection in tropical and subtropical regions is escalating due to factors like climate change and mosquito vector expansion. With over 300 million annual infections and potentially fatal outcomes, the urgent need for effective treatments is evident. While the approved Dengvaxia vaccine has variable efficacy, there are currently no antiviral drugs for DENV. This study explores seven compounds targeting the NS2B-NS3 protease, a crucial protein in DENV replication. These compounds exhibit inhibitory effects on DENV-2 NS2B-NS3, holding promise for disrupting viral replication and preventing severe manifestations. However, further research, including animal testing, is imperative to assess therapeutic efficacy and potential toxicity. Developing safe and potent treatments for DENV infection is critical in addressing the rising global health threat posed by this virus.

Global stability of secondary DENV infection models with non-specific and strain-specific CTLs

Dengue virus (DENV) is a highly perilous virus that is transmitted to humans through mosquito bites and causes dengue fever. Consequently, extensive efforts are being made to develop effective treatments and vaccines. Mathematical modeling plays a significant role in comprehending the dynamics of DENV within a host in the presence of cytotoxic T lymphocytes (CTL) immune response. This study examines two models for secondary DENV infections that elucidate the dynamics of DENV under the influence of two types of CTL responses, namely non-specific and strain-specific responses. The first model encompasses five compartments, which consist of uninfected monocytes, infected monocytes, free DENV particles, non-specific CTLs, and strain-specific CTLs. In the second model, latently infected cells are introduced into the model. We posit that the CTL responsiveness is determined by a combination of self-regulating CTL response and a predator-prey-like CTL response. The model's solutions are verified to be nonnegativity and bounded and the model possesses two equilibrium states: the uninfected equilibrium EQ 0 and the infected equilibrium EQ ⁎ . Furthermore, we calculate the basic reproduction number R 0 , which determines the existence and stability of the model's equilibria. We examine the global stability by constructing suitable Lyapunov functions. Our analysis reveals that if R 0 ≤ 1 , then EQ 0 is globally asymptotically stable (G.A.S), and if R 0 > 1 , then EQ 0 is unstable while EQ ⁎ is G.A.S. To illustrate our findings analytically, we conduct numerical simulations for each model. Additionally, we perform sensitivity analysis to demonstrate how the parameter values of the proposed model impact R 0 given a set of data. Finally, we discuss the implications of including the CTL immune response and latently infected cells in the secondary DENV infection model. Our study demonstrates that incorporating the CTL immune response and latently infected cells diminishes R 0 and enhances the system's stability around EQ 0 .

Within-host models of dengue virus transmission with immune response

Dengue fever is an infectious viral fever. The complex behavior of the virus within the body can be explained through mathematical models to understand the virus’s dynamics. We propose two different with-in host models of dengue virus transmission with humoral immune response. The proposed models differ from one another because one of the models assumes that newly formed viruses infect healthy cells again. To understand the dynamics of the proposed models, we perform a comparative study of stability analysis, numerical simulation, and sensitivity analysis. The basic reproduction number (BRN) of the two models is computed using next-generation matrix method. The local stability (l.s) analysis is discussed using the linearization method. The Lyapunov’s direct method is used to check the global stability (g.s) of the models. It has been found that both the equilibrium states for both the models, namely, virus-free equilibrium state and endemic equilibrium state, are globally stable, based on the value of BRN. Results show the influence of immune response on the cell dynamics and virus particles. The virus neutralization rate by antibodies and rate that affects the antibody growth are highly sensitive for the two models. Optimal control is applied to explore the possible control strategies to prevent virus spread in the host system. It is evident from the results that the strategy to administrate antibiotic drugs and home remedies slow down the virus spread in the host.

Within-host modeling to measure dynamics of antibody responses after natural infection or vaccination: A systematic review

BACKGROUND

Within-host models describe the dynamics of immune cells when encountering a pathogen, and how these dynamics can lead to an individual-specific immune response. This systematic review aims to summarize which within-host methodology has been used to study and quantify antibody kinetics after infection or vaccination. In particular, we focus on data-driven and theory-driven mechanistic models.

MATERIALS

PubMed and Web of Science databases were used to identify eligible papers published until May 2022. Eligible publications included those studying mathematical models that measure antibody kinetics as the primary outcome (ranging from phenomenological to mechanistic models).

RESULTS

We identified 78 eligible publications, of which 8 relied on an Ordinary Differential Equations (ODEs)-based modelling approach to describe antibody kinetics after vaccination, and 12 studies used such models in the context of humoral immunity induced by natural infection. Mechanistic modeling studies were summarized in terms of type of study, sample size, measurements collected, antibody half-life, compartments and parameters included, inferential or analytical method, and model selection.

CONCLUSIONS

Despite the importance of investigating antibody kinetics and underlying mechanisms of (waning of) the humoral immunity, few publications explicitly account for this in a mathematical model. In particular, most research focuses on phenomenological rather than mechanistic models. The limited information on the age groups or other risk factors that might impact antibody kinetics, as well as a lack of experimental or observational data remain important concerns regarding the interpretation of mathematical modeling results. We reviewed the similarities between the kinetics following vaccination and infection, emphasising that it may be worth translating some features from one setting to another. However, we also stress that some biological mechanisms need to be distinguished. We found that data-driven mechanistic models tend to be more simplistic, and theory-driven approaches lack representative data to validate model results.

Mathematical modeling the dynamics of SARS-CoV-2 infection with antibody-dependent enhancement

The advent and swift global spread of the novel coronavirus (COVID-19) transmitted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have caused massive deaths and economic devastation worldwide. Antibody-dependent enhancement (ADE) is a common phenomenon in virology that directly affects the effectiveness of the vaccine, and there is no fully effective vaccine for diseases. In order to study the potential role of ADE on SARS-CoV-2 infection, we establish the SARS-CoV-2 infection dynamics model with ADE. The basic reproduction number is computed. We prove that when R 0 < 1 , the infection-free equilibrium is globally asymptotically stable, and the system is uniformly persistent when R 0 > 1 . We carry out the sensitivity analysis by the partial rank correlation coefficients and the extended version of the Fourier amplitude sensitivity test. Numerical simulations are implemented to illustrate the theoretical results. The potential impact of ADE on SARS-CoV-2 infection is also assessed. Our results show that ADE may accelerate SARS-CoV-2 infection. Furthermore, our findings suggest that increasing antibody titers can have the ability to control SARS-CoV-2 infection with ADE, but enhancing the neutralizing power of antibodies may be ineffective to control SARS-CoV-2 infection with ADE. Our study presumably contributes to a better understanding of the dynamics of SARS-CoV-2 infection with ADE.

Burden of cytokines storm on prognosis of SARS-CoV-2 infection through immune response: dynamic analysis and optimal control with immunomodulatory therapy

Immune responses have a crucial role to play against SARS-CoV-2 virus as the adaptive and innate immune systems of the human body help restoring the body to a healthy stage by annihilating this deadly viral infection. Cytokines also play a significant role in modulating a balance between innate and adaptive immune responses but excess of it can have a detrimental affect on critically ill patients. Therefore, this paper is a novel attempt to formulate a within-host mathematical model showing the impact of cytokines storm on healthy cells. The dynamics of the system is analysed which involves basic reproduction number, steady state solutions and global dynamics for disease-free point and endemic equilibrium using geometric approach. Further, an optimal control problem is discussed considering immunomodulatory therapy (targeting cytokines signaling) as control using linear feedback control method to increase the level of healthy cells, which provides vitality for our system. Through numerical simulations, analytic solutions are validated followed by the curve-fit for the cytokines using real data and an optimization algorithm for optimal fit. Finally, sensitivity analysis for the basic reproduction number and the rate of change of healthy cells using Latin Hypercube Sampling method (LHS) is performed. Our finding suggests that immunomodulatory therapy (tocilizumab) can act as a key component to control cytokines storm for critically ill patients to restore the body to a healthy state.

Within Host Dynamics of SARS-CoV-2 in Humans: Modeling Immune Responses and Antiviral Treatments

In December 2019, a newly discovered SARS-CoV-2 virus was emerged from China and propagated worldwide as a pandemic, resulting in about 3–5% mortality. Mathematical models can provide useful scientific insights about transmission patterns and targets for drug development. In this study, we propose a within-host mathematical model of SARS-CoV-2 infection considering innate and adaptive immune responses. We analyze the equilibrium points of the proposed model and obtain an expression of the basic reproduction number. We then numerically show the existence of a transcritical bifurcation. The proposed model is calibrated to real viral load data of two COVID-19 patients. Using the estimated parameters, we perform global sensitivity analysis with respect to the peak of viral load. Finally, we study the efficacy of antiviral drugs and vaccination on the dynamics of SARS-CoV-2 infection. Results suggest that blocking the virus production from infected cells can be an effective target for antiviral drug development. Finally, it is found that vaccination is more effective intervention as compared to the antiviral treatments.

Modeling Dengue Immune Responses Mediated by Antibodies: A Qualitative Study

Simple Summary

With more than one-third of the world population at risk of acquiring the disease, dengue fever is a major public health problem. Caused by four antigenically distinct but related serotypes, disease severity is associated with the immunological status of the individual, seronegative or seropositive, prior to a natural dengue infection. While a primary natural dengue infection is often asymptomatic or mild, individuals experiencing a secondary dengue infection with a heterologous serotype have higher risk of developing the severe form of the disease, linked to the antibody-dependent enhancement (ADE) process. We develop a modeling framework to describe the dengue immune responses mediated by antibodies. Our model framework can describe qualitatively the dynamic of the viral load and antibodies production for scenarios of primary and secondary infections, as found in the empirical immunology literature. Studies such as the one described here serve as a baseline to further model extensions. Future refinements of our framework will be of use to evaluate the impact of imperfect dengue vaccines.

Abstract

Dengue fever is a viral mosquito-borne infection and a major international public health concern. With 2.5 billion people at risk of acquiring the infection around the world, disease severity is influenced by the immunological status of the individual, seronegative or seropositive, prior to natural infection. Caused by four antigenically related but distinct serotypes, DENV-1 to DENV-4, infection by one serotype confers life-long immunity to that serotype and a period of temporary cross-immunity (TCI) to other serotypes. The clinical response on exposure to a second serotype is complex with the so-called antibody-dependent enhancement (ADE) process, a disease augmentation phenomenon when pre-existing antibodies to previous dengue infection do not neutralize but rather enhance the new infection, used to explain the etiology of severe disease. In this paper, we present a minimalistic mathematical model framework developed to describe qualitatively the dengue immunological response mediated by antibodies. Three models are analyzed and compared: (i) primary dengue infection, (ii) secondary dengue infection with the same (homologous) dengue virus and (iii) secondary dengue infection with a different (heterologous) dengue virus. We explore the features of viral replication, antibody production and infection clearance over time. The model is developed based on body cells and free virus interactions resulting in infected cells activating antibody production. Our mathematical results are qualitatively similar to the ones described in the empiric immunology literature, providing insights into the immunopathogenesis of severe disease. Results presented here are of use for future research directions to evaluate the impact of dengue vaccines.

A Study of Within-Host Dynamics of Dengue Infection incorporating both Humoral and Cellular Response with a Time Delay for Production of Antibodies

a. Background: Dengue is an acute illness caused by a virus. The complex behaviour of the virus in human body can be captured using mathematical models. These models helps us to enhance our understanding on the dynamics of the virus.

b. Objectives: We propose to study the dynamics of within-host epidemic model of dengue infection which incorporates both innate immune response and adaptive immune response (Cellular and Humoral). The proposed model also incorporates the time delay for production of antibodies from B cells. We propose to understand the dynamics of the this model using the dynamical systems approach by performing the stability and sensitivity analysis.

c. Methods used: The basic reproduction number (R0) has been computed using the next generation matrix method. The standard stability analysis and sensitivity analysis were performed on the proposed model.

d. Results: The critical level of the antibody recruitment rate(q) was found to be responsible for the existence and stability of various steady states. The stability of endemic state was found to be dependent on time delay(τ). The sensitivity analysis identified the production rate of antibodies (q) to be highly sensitive parameter.

e. Conclusions: The existence and stability conditions for the equilibrium points have been obtained. The threshold value of time delay (τ0) has been computed which is critical for change in stability of the endemic state. Sensitivity analysis was performed to identify the crucial and sensitive parameters of the model.

Modeling the Relationship Between Antibody-Dependent Enhancement and Disease Severity in Secondary Dengue Infection

Sequential infections with different dengue serotypes (DENV-1, 4) significantly increase the risk of a severe disease outcome (fever, shock, and hemorrhagic disorders). Two hypotheses have been proposed to explain the severity of the disease: (1) antibody-dependent enhancement (ADE) and (2) original T cell antigenic sin. In this work, we explored the first hypothesis through mathematical modeling. The proposed model reproduces the dynamic of susceptible and infected target cells and dengue virus in scenarios of infection-neutralizing and infection-enhancing antibody competition induced by two distinct serotypes of the dengue virus during secondary infection. The enhancement and neutralization functions are derived from basic concepts of chemical reactions and used to mimic binding to the virus by two distinct populations of antibodies. The analytic study of the model showed the existence of two equilibriums: a disease-free equilibrium and an endemic one. Using the concept of the basic reproduction number [Formula: see text], we performed the asymptotic stability analysis for the two equilibriums. To measure the severity of the disease, we considered the maximum value of infected cells as well as the time when this maximum is reached. We observed that it corresponds to the time when the maximum enhancing activity for the infection occurs. This critical time was calculated from the model to be a few days after the occurrence of the infection, which corresponds to what is observed in the literature. Finally, using as output [Formula: see text], we were able to rank the contribution of each parameter of the model. In particular, we highlighted that the cross-reactive antibody responses may be responsible for the disease enhancement during secondary heterologous dengue infection.

Autoantibody Profiling in Plasma of Dengue Virus-Infected Individuals

Dengue is an arboviral disease caused by dengue virus (DENV) with high prevalence in tropical and sub-tropical regions. Autoimmune syndromes following dengue can be observed in long term follow up. Anti-DENV antibodies are cross-reactive with surface antigens on endothelial cells or platelets and could be involved in the pathogenesis of dengue. However, no studies have analyzed the autoantibody repertoire and its roles in dengue pathogenesis. Hence, we aimed to describe the autoantibody profile in dengue patients with different disease severities. We utilized a protein array with 128 putative autoantigens to screen for IgM and IgG reactivity in plasma obtained from healthy donors (n = 8), asymptomatic individuals infected with DENV (n = 11) and hospitalized dengue patients (n = 21). Even though the patient cohort is small, we show that 80 IgM and 6 IgG autoantibodies were elevated in DENV infected patients compared to age-matched healthy donors. Individuals undergoing a primary DENV infection showed higher amounts of IgG autoantibodies, not IgM autoantibodies, compared to individuals undergoing secondary infection. No differences were observed between asymptomatic and hospitalized dengue patients. Nineteen autoantibodies, which react against several coagulation and complement components, correlated with platelet counts in severe dengue patients. This current study provides a framework to explore a possible role of candidate autoantibodies in dengue immunopathogenesis.

A generalized within-host model of dengue infection with a non-constant monocyte production rate

In this paper, we generalize a previous model of within-host dengue infection with a nonconstant monocyte production rate. We establish the existence of three equilibria and give some local stability results. We then estimate three parameters in the model from clinical data for dengue virus serotype 2. It is then shown that the model can exhibit behaviours that are not possible under the assumption of constant monocyte production. Lastly, we perform a sensitivity analysis of the model in two contexts, antiviral treatment and immunostimulatory treatment. The results predict that antiviral treatments that reduce the viral replication rate in infected monocytes are the most effective, while immunostimulatory treatments that increase the rate at which infected monocytes are removed are best.

Within-host mechanisms of immune regulation explain the contrasting dynamics of two helminth species in both single and dual infections

Variation in the intensity and duration of infections is often driven by variation in the network and strength of host immune responses. While many of the immune mechanisms and components are known for parasitic helminths, how these relationships change from single to multiple infections and impact helminth dynamics remains largely unclear. Here, we used laboratory data from a rabbit-helminth system and developed a within-host model of infection to investigate different scenarios of immune regulation in rabbits infected with one or two helminth species. Model selection suggests that the immunological pathways activated against Trichostrongylus retortaeformis and Graphidium strigosum are similar. However, differences in the strength of these immune signals lead to the contrasting dynamics of infections, where the first parasite is rapidly cleared and the latter persists with high intensities. In addition to the reactions identified in single infections, rabbits with both helminths also activate new pathways that asymmetrically affect the dynamics of the two species. These new signals alter the intensities but not the general trend of the infections. The type of interactions described can be expected in many other host-helminth systems. Our immune framework is flexible enough to capture different mechanisms and their complexity, and provides essential insights to the understanding of multi-helminth infections.

Modelling the impact of antibody-dependent enhancement on disease severity of Zika virus and dengue virus sequential and co-infection

Human infections with viruses of the genus Flavivirus, including dengue virus (DENV) and Zika virus (ZIKV), are of increasing global importance. Owing to antibody-dependent enhancement (ADE), secondary infection with one Flavivirus following primary infection with another Flavivirus can result in a significantly larger peak viral load with a much higher risk of severe disease. Although several mathematical models have been developed to quantify the virus dynamics in the primary and secondary infections of DENV, little progress has been made regarding secondary infection of DENV after a primary infection of ZIKV, or DENV-ZIKV co-infection. Here, we address this critical gap by developing compartmental models of virus dynamics. We first fitted the models to published data on dengue viral loads of the primary and secondary infections with the observation that the primary infection reaches its peak much more gradually than the secondary infection. We then quantitatively show that ADE is the key factor determining a sharp increase/decrease of viral load near the peak time in the secondary infection. In comparison, our simulations of DENV and ZIKV co-infection (simultaneous rather than sequential) show that ADE has very limited influence on the peak DENV viral load. This indicates pre-existing immunity to ZIKV is the determinant of a high level of ADE effect. Our numerical simulations show that (i) in the absence of ADE effect, a subsequent co-infection is beneficial to the second virus; and (ii) if ADE is feasible, then a subsequent co-infection can induce greater damage to the host with a higher peak viral load and a much earlier peak time for the second virus, and for the second peak for the first virus.

Infection severity across scales in multi-strain immuno-epidemiological Dengue model structured by host antibody level

Infection by distinct Dengue virus serotypes and host immunity are intricately linked. In particular, certain levels of cross-reactive antibodies in the host may actually enhance infection severity leading to Dengue hemorrhagic fever (DHF). The coupled immunological and epidemiological dynamics of Dengue calls for a multi-scale modeling approach. In this work, we formulate a within-host model which mechanistically recapitulates characteristics of antibody dependent enhancement in Dengue infection. The within-host scale is then linked to epidemiological spread by a vector-host partial differential equation model structured by host antibody level. The coupling allows for dynamic population-wide antibody levels to be tracked through primary and secondary infections by distinct Dengue strains, along with waning of cross-protective immunity after primary infection. Analysis of both the within-host and between-host systems are conducted. Stability results in the epidemic model are formulated via basic and invasion reproduction numbers as a function of immunological variables. Additionally, we develop numerical methods in order to simulate the multi-scale model and assess the influence of parameters on disease spread and DHF prevalence in the population.

Mathematical modeling and analysis of innate and humoral immune responses to dengue infections

Dengue is an acute arthropode-borne virus, belonging to the family Flaviviridae. Currently, there are no vaccines or treatments available against dengue. Thus it is important to understand the dynamics of dengue in order to control the infection. In this paper, we study the long-term dynamics of the model that is presented in [S. D. Perera and S. S. N. Perera, Simulation model for dynamics of dengue with innate and humoral immune responses, Comput. Math. Methods Med. 2018 (2018) 8798057, 18 pp. https://doi.org/10.1155/2018/8798057 ] which describes the interaction of virus with infected and uninfected cells in the presence of innate and humoral immune responses. It was found the model has three equilibria, namely: infection free equilibrium, no immune equilibrium and endemic equilibrium, then analyzed its stability analytically. The analytical findings of each model have been exemplified by numerical simulations. Given the fact that intensity of dengue virus replication at early times of infection could determine clinical outcomes, it is important to understand the impact of innate immunity, which is believed to be the first line of defense against an invading pathogen. For this we carry out a simulation case study to investigate the importance of innate immune response on dengue virus dynamics. A comparison was done assuming that innate immunity was active; innate immunity was in quasi-steady state and innate immunity was inactive during the virus replication process. By a further analysis of the qualitative behavior of the quasi-steady state, it was observed that innate immune response plays a pivotal role in dengue virus dynamics. It can change the dynamical behavior of the system and is essential for the virus clearance.

Modelling the Host Immune Response to Mature and Immature Dengue Viruses

Immature dengue virions contained in patient blood samples are essentially not infectious because the uncleaved surface protein prM renders them incompetent for membrane fusion. However, the immature virions regain full infectivity when they interact with anti-prM antibodies, and once opsonised virion fusion into Fc receptor-expressing cells is facilitated. We propose a within-host mathematical model for the immune response which takes into account the dichotomy between mature infectious and immature noninfectious dengue virions. The model accounts for experimental observations on the different interactions of plasmacytoid dendritic cells with infected cells producing virions with different infectivity. We compute the basic reproduction number as a function of the proportion of infected cells producing noninfectious virions and use numerical simulations to compare the host's immune response in a primary and a secondary dengue infections. The results can be placed in the immunoregulatory framework with plasmacytoid dendritic cells serving as a bridge between the innate and adaptive immune response, and pose questions for potential experimental work to validate hypothesis about the evolutionary context whereby the virus strives to maximise its chance for transmission from the human host to the mosquito vector.

A simple mathematical model to describe antibody-dependent enhancement in heterologous secondary infection in dengue

We develop a mathematical model to describe the role of antibody-dependent enhancement (ADE) in heterologous secondary infections, assuming that antibodies specific to primary dengue virus (DENV) infection are being produced by immunological memory. The model has a virus-free equilibrium (VFE) and a unique virus-presence equilibrium (VPE). VFE is asymptotically stable when VPE is unstable; and unstable, otherwise. Additionally, there is an asymptotic attractor (not a fixed point) due to the fact that the model assumes unbounded increase in memory cells. In the analysis of the model, ADE must be accounted in the initial stage of infection (a window of time of few days), period of time elapsed from the heterologous infection until the immune system mounting an effective response against the secondary infection. We apply the results yielded by model to evaluate ADE phenomonon in heterologous DENV infection. We also associate the possible occurrence of severe dengue with huge viremia mediated by ADE phenomenon.

Simulation Model for Dynamics of Dengue with Innate and Humoral Immune Responses

Dengue virus is a mosquito borne Flavivirus and the most prevalent arbovirus in tropical and subtropical regions around the world. The incidence of dengue has increased drastically over the last few years at an alarming rate. The clinical manifestation of dengue ranges from asymptomatic infection to severe dengue. Even though the viral kinetics of dengue infection is lacking, innate immune response and humoral immune response are thought to play a major role in controlling the virus count. Here, we developed a computer simulation mathematical model including both innate and adaptive immune responses to study the within-host dynamics of dengue virus infection. A sensitivity analysis was carried out to identify key parameters that would contribute towards severe dengue. A detailed stability analysis was carried out to identify relevant range of parameters that contributes to different outcomes of the infection. This study provides a qualitative understanding of the biological factors that can explain the viral kinetics during a dengue infection.

Challenges in dengue research: A computational perspective

The dengue virus is now the most widespread arbovirus affecting human populations, causing significant economic and social impact in South America and South-East Asia. Increasing urbanization and globalization, coupled with insufficient resources for control, misguided policies or lack of political will, and expansion of its mosquito vectors are some of the reasons why interventions have so far failed to curb this major public health problem. Computational approaches have elucidated on dengue's population dynamics with the aim to provide not only a better understanding of the evolution and epidemiology of the virus but also robust intervention strategies. It is clear, however, that these have been insufficient to address key aspects of dengue's biology, many of which will play a crucial role for the success of future control programmes, including vaccination. Within a multiscale perspective on this biological system, with the aim of linking evolutionary, ecological and epidemiological thinking, as well as to expand on classic modelling assumptions, we here propose, discuss and exemplify a few major computational avenues-real-time computational analysis of genetic data, phylodynamic modelling frameworks, within-host model frameworks and GPU-accelerated computing. We argue that these emerging approaches should offer valuable research opportunities over the coming years, as previously applied and demonstrated in the context of other pathogens.

Mathematical Modelling of Immune Parameters in the Evolution of Severe Dengue

Aims. Predicting the risk of severity at an early stage in an individual patient will be invaluable in preventing morbidity and mortality caused by dengue. We hypothesized that such predictions are possible by analyzing multiple parameters using mathematical modeling. Methodology. Data from 11 adult patients with dengue fever (DF) and 25 patients with dengue hemorrhagic fever (DHF) were analyzed. Multivariate statistical analysis was performed to study the characteristics and interactions of parameters using dengue NS1 antigen levels, dengue IgG antibody levels, platelet counts, and lymphocyte counts. Fuzzy logic fundamentals were used to map the risk of developing severe forms of dengue. The cumulative effects of the parameters were incorporated using the Hamacher and the OWA operators. Results. The operator classified the patients according to the severity level during the time period of 96 hours to 120 hours after the onset of fever. The accuracy ranged from 53% to 89%. Conclusion. The results show a robust mathematical model that explains the evolution from dengue to its serious forms in individual patients. The model allows prediction of severe cases of dengue which could be useful for optimal management of patients during a dengue outbreak. Further analysis of the model may also deepen our understanding of the pathways towards severe illness.

Arbovirosis and potential transmission blocking vaccines

Infectious diseases caused by arboviruses (viruses transmitted by arthropods) are undergoing unprecedented epidemic activity and geographic expansion. With the recent introduction of West Nile virus (1999), chikungunya virus (2013) and Zika virus (2015) to the Americas, stopping or even preventing the expansion of viruses into susceptible populations is an increasing concern. With a few exceptions, available vaccines protecting against arboviral infections are nonexistent and current disease prevention relies on vector control interventions. However, due to the emergence of and rapidly spreading insecticide resistance, different disease control methods are needed. A feasible method of reducing emerging tropical diseases is the implementation of vaccines that prevent or decrease viral infection in the vector. These vaccines are designated ‘transmission blocking vaccines’, or TBVs. Here, we summarize previous TBV work, discuss current research on arboviral TBVs and present several promising TBV candidates.

Secondary dengue virus infections during the 2009 outbreak in Buenos Aires

OBJECTIVES

To evaluate the occurrence of secondary dengue virus (DENV) infections during the 2009 outbreak in a non-endemic area. Viral loads were evaluated in serum from acute-phase patients, comparing primary and secondary infection.

METHODS

Serum samples from patients with clinical diagnosis of suspected dengue were referred to the Virology Laboratory at 'Ricardo Gutiérrez' Children's Hospital. Dengue-positive samples were classified as primary or secondary DENV infections through serological methods (anti-DENV IgM and IgG). Viral loads were measured by quantitative real-time PCR (qRT-PCR) in samples obtained in the first 5 days of infection. Statistical analyses were performed to evaluate factors that might correlate with differences in the viral load of primary or secondary infection.

RESULTS

A total of 229 DENV cases were confirmed; among them, 22.7% were secondary infections. No significant differences were found between the viral load of primary and secondary infections.

CONCLUSION

We detected a high percentage of secondary DENV infections in a non-endemic area; this finding might correspond to socio-demographic characteristics of the group under study or indicate a previous cryptic DENV circulation causing inapparent infections.

Minimal within-host dengue models highlight the specific roles of the immune response in primary and secondary dengue infections

In recent years, the within-host viral dynamics of dengue infections have been increasingly characterized, and the relationship between aspects of these dynamics and the manifestation of severe disease has been increasingly probed. Despite this progress, there are few mathematical models of within-host dengue dynamics, and the ones that exist focus primarily on the general role of immune cells in the clearance of infected cells, while neglecting other components of the immune response in limiting viraemia. Here, by considering a suite of mathematical within-host dengue models of increasing complexity, we aim to isolate the critical components of the innate and the adaptive immune response that suffice in the reproduction of several well-characterized features of primary and secondary dengue infections. By building up from a simple target cell limited model, we show that only the innate immune response is needed to recover the characteristic features of a primary symptomatic dengue infection, while a higher rate of viral infectivity (indicative of antibody-dependent enhancement) and infected cell clearance by T cells are further needed to recover the characteristic features of a secondary dengue infection. We show that these minimal models can reproduce the increased risk of disease associated with secondary heterologous infections that arises as a result of a cytokine storm, and, further, that they are consistent with virological indicators that predict the onset of severe disease, such as the magnitude of peak viraemia, time to peak viral load, and viral clearance rate. Finally, we show that the effectiveness of these virological indicators to predict the onset of severe disease depends on the contribution of T cells in fuelling the cytokine storm.

Global stability analysis of humoral immunity virus dynamics model including latently infected cells

In this paper, we propose and analyse a virus dynamics model with humoral immune response including latently infected cells. The incidence rate is given by Beddington-DeAngelis functional response. We have derived two threshold parameters, the basic infection reproduction number R₀ and the humoral immune response activation number R₁ which completely determined the basic and global properties of the virus dynamics model. By constructing suitable Lyapunov functions and applying LaSalle's invariance principle we have proven that if R₀ ≤ 1, then the infection-free equilibrium is globally asymptotically stable (GAS), if R₁ ≤ 1 < R₀, then the chronic-infection equilibrium without humoral immune response is GAS, and if R₁ > 1, then the chronic-infection equilibrium with humoral immune response is globally asymptotically stable. These results are further illustrated by numerical simulations.

Within-host viral dynamics of dengue serotype 1 infection

Dengue, the most common mosquito-borne viral infection of humans, is endemic across much of the world, including much of tropical Asia and is increasing in its geographical range. Here, we present a mathematical model of dengue virus dynamics within infected individuals, detailing the interaction between virus and a simple immune response. We fit this model to measurements of plasma viral titre from cases of primary and secondary DENV 1 infection in Vietnam. We show that variation in model parameters governing the immune response is sufficient to create the observed variation in virus dynamics between individuals. Estimating model parameter values, we find parameter differences between primary and secondary cases consistent with the theory of antibody-dependent enhancement (namely enhanced rates of viral entry to target cells in secondary cases). Finally, we use our model to examine the potential impact of an antiviral drug on the within-host dynamics of dengue. We conclude that the impact of antiviral therapy on virus dynamics is likely to be limited if therapy is only started at the onset of symptoms, owing to the typically late stage of viral pathogenesis reached by the time symptoms are manifested and thus treatment is started.