Spread Of Zika Virus Research Articles

Modeling Zika Virus Disease Dynamics with Control Strategies

In this research, we formulated a fractional-order model for the transmission dynamics of Zika virus, incorporating three control strategies: health education campaigns, the use of insecticides, and preventive measures. We conducted a theoretical analysis of the model, obtaining the disease-free equilibrium and the basic reproduction number, and analyzing the existence and uniqueness of the model. Additionally, we performed model parameter estimation using real data on Zika virus cases reported in Colombia. We found that the fractional-order model provided a better fit to the real data compared to the classical integer-order model. A sensitivity analysis of the basic reproduction number was conducted using computed partial rank correlation coefficients to assess the impact of each parameter on Zika virus transmission. Furthermore, we performed numerical simulations to determine the effect of memory on the spread of Zika virus. The simulation results showed that the order of derivatives significantly impacts the dynamics of the disease. We also assessed the effect of the control strategies through simulations, concluding that the proposed interventions have the potential to significantly reduce the spread of Zika virus in the population.

Unsupervised learning analysis on the proteomes of Zika virus

Background The Zika virus (ZIKV), which is transmitted by mosquito vectors to nonhuman primates and humans, causes devastating outbreaks in the poorest tropical regions of the world. Molecular epidemiology, supported by clustering phylogenetic gold standard studies using sequence data, has provided valuable information for tracking and controlling the spread of ZIKV. Unsupervised learning (UL), a form of machine learning algorithm, can be applied on the datasets without the need of known information for training. Methods In this work, unsupervised Random Forest (URF), followed by the application of dimensional reduction algorithms such as principal component analysis (PCA), Uniform Manifold Approximation and Projection (UMAP), t-distributed stochastic neighbor embedding (t-SNE), and autoencoders were used to uncover hidden patterns from polymorphic amino acid sites extracted on the proteome ZIKV multi-alignments, without the need of an underlying evolutionary model. Results The four UL algorithms revealed specific host and geographical clustering patterns for ZIKV. Among the four dimensionality reduction (DR) algorithms, the performance was better for UMAP. The four algorithms allowed the identification of imported viruses for specific geographical clusters. The UL dimension coordinates showed a significant correlation with phylogenetic tree branch lengths and significant phylogenetic dependence in Abouheif’s Cmean and Pagel’s Lambda tests (p value < 0.01) that showed comparable performance with the phylogenetic method. This analytical strategy was generalizable to an external large dengue type 2 dataset. Conclusion These UL algorithms could be practical evolutionary analytical techniques to track the dispersal of viral pathogens.

Ad26.M.Env ZIKV vaccine protects pregnant rhesus macaques and fetuses against Zika virus infection

At the start of the Zika virus (ZIKV) epidemic in 2015, ZIKV spread across South and Central America, and reached parts of the southern United States placing pregnant women at risk for fetal microcephaly, fetal loss, and other adverse pregnancy outcomes associated with congenital ZIKA syndrome (CZS). For this reason, testing of a safe and efficacious ZIKV vaccine remains a global health priority. Here we report that a single immunization with Ad26.M.Env ZIKV vaccine, when administered prior to conception, fully protects pregnant rhesus macaques from ZIKV viral RNA in blood and tissues with no adverse effects in dams and fetuses. Furthermore, vaccination prevents ZIKV distribution to fetal tissues including the brain. ZIKV associated neuropathology was absent in offspring of Ad26.M.Env vaccinated dams, although pathology was limited in fetuses from non-immunized, challenged dams. Vaccine efficacy is associated with induction of ZIKV neutralizing antibodies in pregnant rhesus macaques. These data suggest the feasibility of vaccine prevention of CZS in humans.

A novel radial basis neural network for the Zika virus spreading model

The motive of current investigations is to design a novel radial basis neural network stochastic structure to present the numerical representations of the Zika virus spreading model (ZVSM). The mathematical ZVSM is categorized into humans and vectors based on the susceptible S(q), exposed E(q), infected I(q) and recovered R(q), i.e., SEIR. The stochastic performances are designed using the radial basis activation function, feed forward neural network, twenty-two numbers of neurons along with the optimization of Bayesian regularization in order to solve the ZVSM. A dataset is achieved using the explicit Runge-Kutta scheme, which is used to reduce the mean square error (MSE) based on the process of training for solving the nonlinear ZVSM. The division of the data is categorized into training, which is taken as 78 %, while 11 % for both authentication and testing. Three different cases of the nonlinear ZVSM have been taken, while the scheme’s correctness is performed through the matching of the results. Furthermore, the reliability of the scheme is observed by applying different performances of regression, MSE, error histograms and state transition.

In vitro and in vivo inhibition of the host TRPC4 channel attenuates Zika virus infection

Zika virus (ZIKV) infection may lead to severe neurological consequences, including seizures, and early infancy death. However, the involved mechanisms are still largely unknown. TRPC channels play an important role in regulating nervous system excitability and are implicated in seizure development. We investigated whether TRPCs might be involved in the pathogenesis of ZIKV infection. We found that ZIKV infection increases TRPC4 expression in host cells via the interaction between the ZIKV-NS3 protein and CaMKII, enhancing TRPC4-mediated calcium influx. Pharmacological inhibition of CaMKII decreased both pCREB and TRPC4 protein levels, whereas the suppression of either TRPC4 or CaMKII improved the survival rate of ZIKV-infected cells and reduced viral protein production, likely by impeding the replication phase of the viral life cycle. TRPC4 or CaMKII inhibitors also reduced seizures and increased the survival of ZIKV-infected neonatal mice and blocked the spread of ZIKV in brain organoids derived from human-induced pluripotent stem cells. These findings suggest that targeting CaMKII or TRPC4 may offer a promising approach for developing novel anti-ZIKV therapies, capable of preventing ZIKV-associated seizures and death.

Recurrent neural network for the dynamics of Zika virus spreading

<abstract> <p>Recurrent Neural Networks (RNNs), a type of machine learning technique, have recently drawn a lot of interest in numerous fields, including epidemiology. Implementing public health interventions in the field of epidemiology depends on efficient modeling and outbreak prediction. Because RNNs can capture sequential dependencies in data, they have become highly effective tools in this field. In this paper, the use of RNNs in epidemic modeling is examined, with a focus on the extent to which they can handle the inherent temporal dynamics in the spread of diseases. The mathematical representation of epidemics requires taking time-dependent variables into account, such as the rate at which infections spread and the long-term effects of interventions. The goal of this study is to use an intelligent computing solution based on RNNs to provide numerical performances and interpretations for the SEIR nonlinear system based on the propagation of the Zika virus (SEIRS-PZV) model. The four patient dynamics, namely susceptible patients S(y), exposed patients admitted in a hospital E(y), the fraction of infective individuals I(y), and recovered patients R(y), are represented by the epidemic version of the nonlinear system, or the SEIR model. SEIRS-PZV is represented by ordinary differential equations (ODEs), which are then solved by the Adams method using the Mathematica software to generate a dataset. The dataset was used as an output for the RNN to train the model and examine results such as regressions, correlations, error histograms, etc. For RNN, we used 100% to train the model with 15 hidden layers and a delay of 2 seconds. The input for the RNN is a time series sequence from 0 to 5, with a step size of 0.05. In the end, we compared the approximated solution with the exact solution by plotting them on the same graph and generating the absolute error plot for each of the 4 cases of SEIRS-PZV. Predictions made by the model appeared to be become more accurate when the mean squared error (MSE) decreased. An increased fit to the observed data was suggested by this decrease in the MSE, which suggested that the variance between the model's predicted values and the actual values was dropping. A minimal absolute error almost equal to zero was obtained, which further supports the usefulness of the suggested strategy. A small absolute error shows the degree to which the model's predictions matches the ground truth values, thus indicating the level of accuracy and precision for the model's output.</p> </abstract>

Study on Viral Transmission Impact on Human Population Using Fractional Order Zika Virus Model

This work comprises the spread of Zika virus between humans and mosquitoes as a mathematical simulation under fractional order, which also incorporates the asymptotically infected human population. For determining the solution of the model the fuzzy Laplace transform technique is utilized. By combining fuzzy logic with the Laplace transform, we can analyze systems even when we lack precise information. Further, the sensitivity analysis is performed to validate the model. On top of that the population dynamics of both human and mosquito populations are discussed using numerical data and the graphical result of the model is presented. The main objective of this work is to study the dynamics of the Zika virus and to examine the effect of virus on humans when the transmission occurs between humans and from mosquitoes, under fractional order. The outcome of these comparisons suggests that even by reducing a minute fractional part of transmission through mosquitoes results in a greater reduction of Zika exposed population. The comparisons improve the understanding of fractional level transmission resulting in more effective drug administration to patients. The Hyers-Ulam stability method is a mathematical technique used to study the stability of functional equations. Eventually, Ulam Hyers and Ulam Hyers Rassias stability are employed to assess the stability of the proposed model.

ZIKV induction of tristetraprolin in endothelial and Sertoli cells post-transcriptionally inhibits IFNβ/λ expression and promotes ZIKV persistence.

Our findings define a novel role for ZIKV-induced TTP expression in regulating IFNβ/IFNλ production in primary hBMECs and Sertoli cells. These cells comprise key physiological barriers subverted by ZIKV to access brain and testicular compartments and serve as reservoirs for persistent replication and dissemination. We demonstrate for the first time that the ARE-binding protein TTP is virally induced and post-transcriptionally regulates IFNβ/IFNλ secretion. In ZIKV-infected hBMEC and Sertoli cells, TTP knockout increased IFNβ/IFNλ secretion, while TTP expression blocked IFNβ/IFNλ secretion. The TTP-directed blockade of IFN secretion permits ZIKV spread and persistence in hBMECs and Sertoli cells and may similarly augment ZIKV spread across IFNλ-protected placental barriers. Our work highlights the importance of post-transcriptional ZIKV regulation of IFN expression and secretion in cells that regulate viral access to protected compartments and defines a novel mechanism of ZIKV-regulated IFN responses which may facilitate neurovirulence and sexual transmission.

Molecular characterization and geographical distribution of Zika virus worldwide from 1947 to 2022

ObjectivesWe conducted molecular characterization, demonstrated the geographical distribution of Zika virus (ZIKV) circulating worldwide from 1947 to 2022 and explored the potential genetic recombination site in the Thailand ZIKV genomes. MethodsWe constructed phylogenetic trees based on ZIKV coding sequences (CDS) and determined the geographical distribution of the representative viruses by genetic relationship and timeline. We determined genetic recombination among ZIKV and between ZIKV and other flaviviruses using similarity plot and bootscan analyzes, together with the phylogeny encompassing the CDS and eight subgenomic regions. ResultsThe phylogenetic trees comprising 717 CDS showed two distinct African and Asian lineages. ZIKV in the African lineage formed two sublineages, and ZIKV in the Asian lineage diversified into the Asian and American sublineages. The 1966 Malaysian isolate was designated the prototype of the Asian sublineage and formed a node of only one member, while the newer viruses formed a distinct node. We detected no genetic recombination in the Thailand ZIKV. ConclusionFive Thailand isolates discovered in 2006 were the second oldest ZIKV after the Malaysian prototype. Our result suggested two independent routes of ZIKV spread from Southeast Asia to Micronesia in 2007 and French Polynesia in 2013 before further spreading to South American countries.

Investigation of Zika virus methyl transferase inhibitors using steered molecular dynamics

Zika virus (ZIKV) spread is considered a major public health threat by the World Health Organization (WHO). There are no vaccines or drugs available to control the infection of the Zika virus, therefore a highly effective medicinal molecule is urgently required. In this study, a computationally intensive investigation was performed to identify a potent natural compound that could inhibit the ZIKV NS5 methyltransferase. This research approach is based on target-based drug identification principles where the native inhibitor SAH (S-adenosylhomocysteine) of ZIKV NS5 methyltransferase was selected as a reference. High-throughput virtual screening and tanimoto similarity coefficient were applied to the natural compound library for ranking the potential candidates. The top five compounds were selected for interaction analysis, MD simulation, total binding free energy through MM/GBSA, and steered MD simulation. Among these compounds, Adenosine 5'-monophosphate monohydrate, Tubercidin, and 5-Iodotubercidin showed stable binding to the protein compared to the native compound, SAH. These three compounds also showed less fluctuations in RMSF in contrast to native compound. Additionally, the same interacting residues observed in SAH also made strong interactions with these three compounds. Adenosine 5'-monophosphate monohydrate and 5-Iodotubercidin had greater total binding free energies than the reference ligand. Moreover, the dissociation resistance of all three compounds was equivalent to that of the reference ligand. This study suggested binding properties of three-hit compounds that could be used to develop drugs against Zika virus infections. Communicated by Ramaswamy H. Sarma

Analyses of Early ZIKV Genomes Are Consistent with Viral Spread from Northeast Brazil to the Americas.

The Americas, particularly Brazil, were greatly impacted by the widespread Zika virus (ZIKV) outbreak in 2015 and 2016. Efforts were made to implement genomic surveillance of ZIKV as part of the public health responses. The accuracy of spatiotemporal reconstructions of the epidemic spread relies on the unbiased sampling of the transmission process. In the early stages of the outbreak, we recruited patients exhibiting clinical symptoms of arbovirus-like infection from Salvador and Campo Formoso, Bahia, in Northeast Brazil. Between May 2015 and June 2016, we identified 21 cases of acute ZIKV infection and subsequently recovered 14 near full-length sequences using the amplicon tiling multiplex approach with nanopore sequencing. We performed a time-calibrated discrete phylogeographic analysis to trace the spread and migration history of the ZIKV. Our phylogenetic analysis supports a consistent relationship between ZIKV migration from Northeast to Southeast Brazil and its subsequent dissemination beyond Brazil. Additionally, our analysis provides insights into the migration of ZIKV from Brazil to Haiti and the role Brazil played in the spread of ZIKV to other countries, such as Singapore, the USA, and the Dominican Republic. The data generated by this study enhances our understanding of ZIKV dynamics and supports the existing knowledge, which can aid in future surveillance efforts against the virus.

Viral Protein Accumulation of Zika Virus Variants Links with Regulation of Innate Immunity for Differential Control of Viral Replication, Spread, and Response to Interferon.

Asian lineage Zika virus (ZIKV) strains emerged globally, causing outbreaks linked with critical clinical disease outcomes unless the virus is effectively restricted by host immunity. We have previously shown that retinoic acid-inducible gene-I (RIG-I) senses ZIKV to trigger innate immunity to direct interferon (IFN) production and antiviral responses that can control ZIKV infection. However, ZIKV proteins have been demonstrated to antagonize IFN. Here, we conducted in vitro analyses to assess how divergent prototypic ZIKV variants differ in virologic properties, innate immune regulation, and infection outcome. We comparatively assessed African lineage ZIKV/Dakar/1984/ArD41519 (ZIKV/Dakar) and Asian lineage ZIKV/Malaysia/1966/P6740 (ZIKV/Malaysia) in a human epithelial cell infection model. De novo viral sequence determination identified amino acid changes within the ZIKV/Dakar genome compared to ZIKV/Malaysia. Viral growth analyses revealed that ZIKV/Malaysia accumulated viral proteins and genome copies earlier and to higher levels than ZIKV/Dakar. Both ZIKV strains activated RIG-I/IFN regulatory factor (IRF3) and NF-κB pathways to induce inflammatory cytokine expression and types I and III IFNs. However, ZIKV/Malaysia, but not ZIKV/Dakar, potently blocked downstream IFN signaling. Remarkably, ZIKV/Dakar protein accumulation and genome replication were rescued in RIG-I knockout (KO) cells late in acute infection, resulting in ZIKV/Dakar-mediated blockade of IFN signaling. We found that RIG-I signaling specifically restricts viral protein accumulation late in acute infection where early accumulation of viral proteins in infected cells confers enhanced ability to limit IFN signaling, promoting viral replication and spread. Our results demonstrate that RIG-I-mediated innate immune signaling imparts restriction of ZIKV protein accumulation, which permits IFN signaling and antiviral actions controlling ZIKV infection. IMPORTANCE ZIKV isolates are classified under African or Asian lineages. Infection with emerging Asian lineage-derived ZIKV strains is associated with increased incidence of neurological symptoms that were not previously reported during infection with African or preemergent Asian lineage viruses. In this study, we utilized in vitro models to compare the virologic properties of and innate immune responses to two prototypic ZIKV strains from distinct lineages: African lineage ZIKV/Dakar and Asian lineage ZIKV/Malaysia. Compared to ZIKV/Dakar, ZIKV/Malaysia accumulates viral proteins earlier, replicates to higher levels, and robustly blocks IFN signaling during acute infection. Early accumulation of ZIKV/Malaysia NS5 protein confers enhanced ability to antagonize IFN signaling, dampening innate immune responses to promote viral spread. Our data identify the kinetics of viral protein accumulation as a major regulator of host innate immunity, influencing host-mediated control of ZIKV replication and spread. Importantly, these findings provide a novel framework for evaluating the virulence of emerging variants.

Zika Virus from the Perspective of Observational Studies: a Review.

Since 1952 when Zika Virus (ZIKV): a Flavivirus, was first discovered in humans, it has not received enough scientific research compared to some of the other members of the family Flaviviridae; like Dengue Virus (DENV). However, this has not stopped the virus from infecting the human population globally. In particular, the global spread of ZIKV has led to a surge in observational studies. Regarding recently published ZIKV-related literature, we are not aware of any reviews strictly focusing on ZIKV from the perspective of observational studies. Therefore, we reviewed recently published observational studies exploring the global spread of ZIKV and its association with Congenital ZIKV Infection (CZI) and clinical manifestations in adults. Online databases including google scholar, PubMed and Elsevier were used for retrieving relevant studies. ZIKV cases have been reported in different parts of the world, with certain regions reporting more cases than the rest, like Brazil. ZIKV causes a wide spectrum of diseases and disorders including microcephaly, developmental disorders, and Guillain-Barre syndrome to name a few. Furthermore, CZI in neonates mainly manifests into neurological disorders and diseases, whereas ZIKV in adults' targets various organs. ZIKV poses a serious threat to human population and observational studies provide a different perspective on the damaging capabilities of ZIKV in real-life settings. Moreover, there are gaps in the literature regarding ZIKV-related-complications that future experimental studies need to address. These complications include in-utero transmission, Guillain-Barre syndrome, cross-reactivity, sexual transmission, along with its persistence in the male reproductive tract.

Zika virus spreads through infection of lymph node-resident macrophages.

To disseminate through the body, Zika virus (ZIKV) is thought to exploit the mobility of myeloid cells, in particular monocytes and dendritic cells. However, the timing and mechanisms underlying shuttling of the virus by immune cells remains unclear. To understand the early steps in ZIKV transit from the skin, at different time points, we spatially mapped ZIKV infection in lymph nodes (LNs), an intermediary site en route to the blood. Contrary to prevailing hypotheses, migratory immune cells are not required for the virus to reach the LNs or blood. Instead, ZIKV rapidly infects a subset of sessile CD169+ macrophages in the LNs, which release the virus to infect downstream LNs. Infection of CD169+ macrophages alone is sufficient to initiate viremia. Overall, our experiments indicate that macrophages that reside in the LNs contribute to initial ZIKV spread. These studies enhance our understanding of ZIKV dissemination and identify another anatomical site for potential antiviral intervention.

The World Health Organization's Disease Outbreak News: A retrospective database.

The World Health Organization (WHO) notifies the global community about disease outbreaks through the Disease Outbreak News (DON). These online reports tell important stories about both outbreaks themselves and the high-level decision making that governs information sharing during public health emergencies. However, they have been used only minimally in global health scholarship to date. Here, we collate all 2,789 of these reports from their first use through the start of the Covid-19 pandemic (January 1996 to December 2019), and develop an annotated database of the subjective and often inconsistent information they contain. We find that these reports are dominated by a mix of persistent worldwide threats (particularly influenza and cholera) and persistent epidemics (like Ebola virus disease in Africa or MERS-CoV in the Middle East), but also document important periods in history like the anthrax bioterrorist attacks at the turn of the century, the spread of chikungunya and Zika virus to the Americas, or even recent lapses in progress towards polio elimination. We present three simple vignettes that show how researchers can use these data to answer both qualitative and quantitative questions about global outbreak dynamics and public health response. However, we also find that the retrospective value of these reports is visibly limited by inconsistent reporting (e.g., of disease names, case totals, mortality, and actions taken to curtail spread). We conclude that sharing a transparent rubric for which outbreaks are considered reportable, and adopting more standardized formats for sharing epidemiological metadata, might help make the DON more useful to researchers and policymakers.

Numerical Computation of SEIR Model for the Zika Virus Spreading

The purpose of this study is to present the numerical performances and interpretations of the SEIR nonlinear system based on the Zika virus spreading by using the stochastic neural networks based intelligent computing solver. The epidemic form of the nonlinear system represents the four dynamics of the patients, susceptible patients S(y), exposed patients hospitalized in hospital E(y), infected patients I(y), and recovered patients R(y), i.e., SEIR model. The computing numerical outcomes and performances of the system are examined by using the artificial neural networks (ANNs) and the scaled conjugate gradient (SCG) for the training of the networks, i.e., ANNs-SCG. The correctness of the ANNs-SCG scheme is observed by comparing the proposed and reference solutions for three cases of the SEIR model to solve the nonlinear system based on the Zika virus spreading dynamics through the knacks of ANNs-SCG procedure based on exhaustive experimentations. The outcomes of the ANNs-SCG algorithm are found consistently in good agreement with standard numerical solutions with negligible errors. Moreover, the procedure’s constancy, dependability, and exactness are perceived by using the values of state transitions, error histogram measures, correlation, and regression analysis.

Dynamics and optimal control of a Zika model with sexual and vertical transmissions.

A new transmission model of Zika virus with three transmission routes including human transmission by mosquito bites, sexual transmission between males and females and vertical transmission is established. The basic reproduction number $ R_{0} $ is derived. When $ R_{0} < 1 $, it is proved that the disease-free equilibrium is globally stable. Furthermore, the optimal control and mitigation methods for transmission of Zika virus are deduced and explored. The MCMC method is used to estimate the parameters and the reasons for the deviation between the actual infection cases and the simulated data are discussed. In addition, different strategies for controlling the spread of Zika virus are simulated and studied. The combination of mosquito control strategies and internal human control strategies is the most effective way in reducing the risk of Zika virus infection.

The mechanisms underlying the immune control of Zika virus infection at the maternal-fetal interface.

Unlike other Flaviviruses, Zika virus (ZIKV) infection during the first trimester of pregnancy causes severe pregnancy outcomes including the devastating microcephaly and diseases associated with placental dysfunctions. We have previously reported that the maternal decidua basalis, the major maternal-fetal interface, serves as a replication platform enabling virus amplification before dissemination to the fetal compartment. However, the rate of congenital infection is quite low, suggesting the presence of a natural barrier against viral infection. Using primary cells from first-trimester pregnancy samples, we investigated in this study how the maternal decidua can interfere with ZIKV infection. Our study reveals that whether through their interactions with dNK cells, the main immune cell population of the first-trimester decidua, or their production of proinflammatory cytokines, decidual stromal cells (DSCs) are the main regulators of ZIKV infection during pregnancy. We also validate the functional role of AXL as a crucial receptor for ZIKV entry in DSCs and demonstrate that targeted inhibition of ligand-receptor interaction at the early stage of the infection is effective in drastically reducing virus pathogenesis at the maternal-fetal interface. Collectively, our results provide insights into the mechanisms through which ZIKV infection and spreading can be limited. The strategy of circumventing viral entry at the maternal-fetus interface limits virus dissemination to fetal tissues, thereby preventing congenital abnormalities.

DNA-PKcs restricts Zika virus spreading and is required for effective antiviral response.

Zika virus (ZIKV) is a single-strand RNA mosquito-borne flavivirus with significant public health impact. ZIKV infection induces double-strand DNA breaks (DSBs) in human neural progenitor cells that may contribute to severe neuronal manifestations in newborns. The DNA-PK complex plays a critical role in repairing DSBs and in the innate immune response to infection. It is unknown, however, whether DNA-PK regulates ZIKV infection. Here we investigated the role of DNA-PKcs, the catalytic subunit of DNA-PK, during ZIKV infection. We demonstrate that DNA-PKcs restricts the spread of ZIKV infection in human epithelial cells. Increased ZIKV replication and spread in DNA-PKcs deficient cells is related to a notable decrease in transcription of type I and III interferons as well as IFIT1, IFIT2, and IL6. This was shown to be independent of IRF1, IRF3, or p65, canonical transcription factors necessary for activation of both type I and III interferon promoters. The mechanism of DNA-PKcs to restrict ZIKV infection is independent of DSB. Thus, these data suggest a non-canonical role for DNA-PK during Zika virus infection, acting downstream of IFNs transcription factors for an efficient antiviral immune response.

A MATHEMATICAL MODEL FOR THE SEXUAL TRANSMISSION OF ZIKA VIRUS BASED ON GENDER AND SYMPTOMS

Zika virus is a member of Flaviviridae that also causes Japanese Encephalitis, dengue, yellow fever, and West Nile fever. General symptoms of the zika virus are low-grade fever (less than 38.5 o ), macula-papular rash, myalgia, asthenia, headache, and transient arthritis. Zika virus can cause congenital anomalies (such as microcephaly), Guillain-Barre syndrome, and other neurological and autoimmune disorders. In the present mathematical model, we observed the effect of sexual transmission on gender and symptoms based division of the infected human population. We proposed a theorem to check the local stability of disease free equilibrium state. To verify the theorem, we performed some numerical simulations. We also analyzed the global stability of disease free equilibrium state. Furthermore, we checked the effect of different sexual transmission rates on the population dynamics by calculating normalized sensitivity indices of R0. Results of the present study suggest that sexual transmission noticeably affects Zika dissemination and by controlling sexual transmission rates, we can restrict the Zika virus spread.