Can Vaccination Save a Zika Virus Epidemic?

Zika virus (ZIKV) is a vector-borne disease that has rapidly spread during the year 2016 in more than 50 countries around the world. If a woman is infected during pregnancy, the virus can cause severe birth defects and brain damage in their babies. The virus can be transmitted through the bites of infected mosquitoes as well as through direct contact from human to human (e.g., sexual contact and blood transfusions). As an intervention for controlling the spread of the disease, we study a vaccination model for preventing Zika infections. Although there is no formal vaccine for ZIKV, The National Institute of Allergy and Infectious Diseases (part of the National Institutes of Health) has launched a vaccine trial at the beginning of August 2016 to control ZIKV transmission, patients who received the vaccine are expected to return within 44 weeks to determine if the vaccine is safe. Since it is important to understand ZIKV dynamics under vaccination, we formulate a vaccination model for ZIKV spread that includes mosquito as well as sexual transmission. We calculate the basic reproduction number of the model to analyze the impact of relatively, perfect and imperfect vaccination rates. We illustrate several numerical examples of the vaccination model proposed as well as the impact of the basic reproduction numbers of vector and sexual transmission and the effect of vaccination effort on ZIKV spread. Results show that high levels of sexual transmission create larger cases of infection associated with the peak of infected humans arising in a shorter period of time, even when a vaccine is available in the population. However, a high level of transmission of Zika from vectors to humans compared with sexual transmission represents that ZIKV will take longer to invade the population providing a window of opportunities to control its spread, for instance, through vaccination.     

Spatial and temporal invasion dynamics of the 2014–2017 Zika and chikungunya epidemics in Colombia

Zika virus (ZIKV) and chikungunya virus (CHIKV) were recently introduced into the Americas resulting in significant disease burdens. Understanding their spatial and temporal dynamics at the subnational level is key to informing surveillance and preparedness for future epidemics. We analyzed anonymized line list data on approximately 105,000 Zika virus disease and 412,000 chikungunya fever suspected and laboratory-confirmed cases during the 2014–2017 epidemics. We first determined the week of invasion in each city. Out of 1,122, 288 cities met criteria for epidemic invasion by ZIKV and 338 cities by CHIKV. We analyzed risk factors for invasion using linear and logistic regression models. We also estimated that the geographic origin of both epidemics was located in Barranquilla, north Colombia. We assessed the spatial and temporal invasion dynamics of both viruses to analyze transmission between cities using a suite of (i) gravity models, (ii) Stouffer’s rank models, and (iii) radiation models with two types of distance metrics, geographic distance and travel time between cities. Invasion risk was best captured by a gravity model when accounting for geographic distance and intermediate levels of density dependence; Stouffer’s rank model with geographic distance performed similarly well. Although a few long-distance invasion events occurred at the beginning of the epidemics, an estimated distance power of 1.7 (95% CrI: 1.5–2.0) from the gravity models suggests that spatial spread was primarily driven by short-distance transmission. Similarities between the epidemics were highlighted by jointly fitted models, which were preferred over individual models when the transmission intensity was allowed to vary across arboviruses. However, ZIKV spread considerably faster than CHIKV.     

Preventing Zika Virus Infection during Pregnancy Using a Seasonal Window of Opportunity for Conception

It has come to light that Zika virus (ZIKV) infection during pregnancy can result in trans-placental transmission to the fetus along with fetal death, congenital microcephaly, and/or Central Nervous System (CNS) malformations. There are projected to be >9,200,000 births annually in countries with ongoing ZIKV transmission. In response to the ZIKV threat, the World Health Organization (WHO) is strategically targeting prevention of infection in pregnant women and funding contraception in epidemic regions. I propose that the damaging effects of ZIKV can be reduced using a seasonal window of opportunity for conception that may minimize maternal exposure. Like other acute viral infections—including the related flavivirus, dengue virus (DENV)—the transmission of ZIKV is anticipated to be seasonal. By seasonally planning pregnancy, this aspect of pathogen ecology can be leveraged to align sensitive periods of gestation with the low-transmission season.     

Co-infection of Dengue,Zika and Chikungunya in a group of pregnant women from Tuxtla Gutiérrez,Chiapas: Preliminary data. 2019

IntroductionDengue, Zika and Chikungunya are RNA Arboviruses present in some areas of Mexico, mainly in the endemic state of Chiapas that is characterized by presence of the vector that transmit them and an ecology that favors high transmission. According to the national epidemiological surveillance system, Dengue has intensified since 2018 and outbreaks continue in various states while for Zika and Chikungunya a decrease in cases has been reported in recent years. The main objective of this study was to determine the incidence of Dengue, Zika and Chikungunya infections during pregnancy in the state of Chiapas.Principal findingsThe presence of previous and current infections and coinfections diagnosed by molecular (RT-PCR) and immunological (ELISA for IgG determination) techniques indicates a wide circulation of viruses in asymptomatic people, specifically in pregnant women showing that silent infections in dry season contributes to the preservation of viruses.ConclusionsFrom 136 studied samples, 27.7% tested positive for DENV, 8% for ZIKV and 24.1% for CHIKV by RTPCR and the values of IgG in sera show that 83.9% were positive for IgG antibodies against DENV, 65% against ZIKV and 59.1% against CHIKV. Results demonstrated presence of ZIKV and CHIKV, not detected by the epidemiological surveillance system, so the importance of establishing proactive epidemiological systems more strict, especially because these infections in pregnant women can cause severe health problems for newborn children.     

Transplacental Zika virus transmission in ex vivo perfused human placentas

A Zika virus (ZIKV) infection during pregnancy can result in severe birth defects such as microcephaly. To date, it is incompletely understood how ZIKV can cross the human placenta. Furthermore, results from studies in pregnant mice and non-human primates are conflicting regarding the role of cross-reactive dengue virus (DENV) antibodies on transplacental ZIKV transmission. Elucidating how ZIKV can cross the placenta and which risk factors contribute to this is important for risk assessment and for potential intervention strategies for transplacental ZIKV transmission. In this study we use an ex vivo human placental perfusion model to study transplacental ZIKV transmission and the effect that cross-reactive DENV antibodies have on this transmission. By using this model, we demonstrate that DENV antibodies significantly increase ZIKV uptake in perfused human placentas and that this increased uptake is neonatal Fc-receptor-dependent. Furthermore, we show that cross-reactive DENV antibodies enhance ZIKV infection in term human placental explants and in primary fetal macrophages but not in primary trophoblasts. Our data supports the hypothesis that presence of cross-reactive DENV antibodies could be an important risk factor for transplacental ZIKV transmission. Furthermore, we demonstrate that the ex vivo placental perfusion model is a relevant and animal friendly model to study transplacental pathogen transmission.     

A mathematical model for Zika virus transmission dynamics with a time-dependent mosquito biting rate

Background

Mathematical modeling has become a tool used to address many emerging diseases. One of the most basic and popular modeling frameworks is the compartmental model. Unfortunately, most of the available compartmental models developed for Zika virus (ZIKV) transmission were designed to describe and reconstruct only past, short-time ZIKV outbreaks in which the effects of seasonal change to entomological parameters can be ignored. To make an accurate long-term prediction of ZIKV transmission, the inclusion of seasonal effects into an epidemic model is unavoidable.

Methods

We developed a vector-borne compartmental model to analyze the spread of the ZIKV during the 2015–2016 outbreaks in Bahia, Brazil and to investigate the impact of two vector control strategies, namely, reducing mosquito biting rates and reducing mosquito population size. The model considered the influences of seasonal change on the ZIKV transmission dynamics via the time-varying mosquito biting rate. The model was also validated by comparing the model prediction with reported data that were not used to calibrate the model.

Results

We found that the model can give a very good fit between the simulation results and the reported Zika cases in Bahia (R-square?=?0.9989). At the end of 2016, the total number of ZIKV infected people was predicted to be 1.2087 million. The model also predicted that there would not be a large outbreak from May 2016 to December 2016 due to the decrease of the susceptible pool. Implementing disease mitigation by reducing the mosquito biting rates was found to be more effective than reducing the mosquito population size. Finally, the correlation between the time series of estimated mosquito biting rates and the average temperature was also suggested.

Conclusions

The proposed ZIKV transmission model together with the estimated weekly biting rates can reconstruct the past long-time multi-peak ZIKV outbreaks in Bahia.

     

The Asian Lineage of Zika Virus: Transmission and Evolution in Asia and the Americas

Since first isolation in 1947 from the Zika forest in Uganda, Zika virus(ZIKV) has been principally known as a benign agent associated with sporadic human infections in a restricted number of African countries. However, during 2015–2016,an Asian lineage of ZIKV caused an unprecedentedly large outbreak in the Americas and sizeable numbers of exported cases across the globe. In this review, we critically appraise the recent advances in molecular epidemiological studies of ZIKV performed to date, and we highlight the pivotal role played by genomic surveillance in elucidating the origins,dissemination and evolution of the Asian lineage of ZIKV in Asia and in the Americas.     

Ghost probiotics with a combined regimen: a novel therapeutic approach against the Zika virus,an emerging world threat

The Zika virus (ZIKV) used to be an obscure flavivirus closely related to dengue virus (DENV). Transmission of this epidemic pathogen occurs mainly via mosquitoes, but it is also capable of placental and sexual transmission. Although the characteristics of these viruses are well defined, infections are unpredictable in terms of disease severity, unusual clinical manifestations, unexpected methods of transmission, long-term persistence, and the development of new strains. Recently, ZIKV has gained huge medical attention following the large-scale epidemics around the world, and reported cases of congenital abnormalities associated with Zika virus infections which have created a public health emergency of international concern. Despite continuous research on ZIKV, no specific treatment or vaccine has been developed, excepting a preventive strategy for congenital ZIKV infection. Probiotics, known as GRAS, are bacteria that confer various health beneficial effects, and have been shown to be effective at curing a number of viral diseases by modulating the immune system. Furthermore, probiotic preparations consisting of dead cells and cellular metabolites, so-called “Ghost probiotics”, can also act as biological response modifiers. Here, we review available information on the epidemiology, transmission, and clinical features of ZIKV, and on treatment and prevention strategies. In addition, we emphasize the use of probiotics and plant-based natural remedies and describe their action mechanisms, and the green technologies for microbial conversion, which could contribute to the development of novel therapies that may reduce the pathogenicity of ZIKV. Accordingly, we draw attention to new findings, unanswered questions, unresolved issues, and controversies regarding ZIKV.     

Steady state analysis of influx and transbilayer distribution of ergosterol in the yeast plasma membrane

Mathematical modeling is now frequently used in outbreak investigations to understand underlying mechanisms of infectious disease dynamics, assess patterns in epidemiological data, and forecast the trajectory of epidemics. However, the successful application of mathematical models to guide public health interventions lies in the ability to reliably estimate model parameters and their corresponding uncertainty. Here, we present and illustrate a simple computational method for assessing parameter identifiability in compartmental epidemic models. We describe a parametric bootstrap approach to generate simulated data from dynamical systems to quantify parameter uncertainty and identifiability. We calculate confidence intervals and mean squared error of estimated parameter distributions to assess parameter identifiability. To demonstrate this approach, we begin with a low-complexity SEIR model and work through examples of increasingly more complex compartmental models that correspond with applications to pandemic influenza, Ebola, and Zika. Overall, parameter identifiability issues are more likely to arise with more complex models (based on number of equations/states and parameters). As the number of parameters being jointly estimated increases, the uncertainty surrounding estimated parameters tends to increase, on average, as well. We found that, in most cases, R0 is often robust to parameter identifiability issues affecting individual parameters in the model. Despite large confidence intervals and higher mean squared error of other individual model parameters, R0 can still be estimated with precision and accuracy. Because public health policies can be influenced by results of mathematical modeling studies, it is important to conduct parameter identifiability analyses prior to fitting the models to available data and to report parameter estimates with quantified uncertainty. The method described is helpful in these regards and enhances the essential toolkit for conducting model-based inferences using compartmental dynamic models.     

Coupled small molecules target RNA interference and JAK/STAT signaling to reduce Zika virus infection in Aedes aegypti

The recent global Zika epidemics have revealed the significant threat that mosquito-borne viruses pose. There are currently no effective vaccines or prophylactics to prevent Zika virus (ZIKV) infection. Limiting exposure to infected mosquitoes is the best way to reduce disease incidence. Recent studies have focused on targeting mosquito reproduction and immune responses to reduce transmission. Previous work has evaluated the effect of insulin signaling on antiviral JAK/STAT and RNAi in vector mosquitoes. Specifically, insulin-fed mosquitoes resulted in reduced virus replication in an RNAi-independent, ERK-mediated JAK/STAT-dependent mechanism. In this work, we demonstrate that targeting insulin signaling through the repurposing of small molecule drugs results in the activation of both RNAi and JAK/STAT antiviral pathways. ZIKV-infected Aedes aegypti were fed blood containing demethylasterriquinone B1 (DMAQ-B1), a potent insulin mimetic, in combination with AKT inhibitor VIII. Activation of this coordinated response additively reduced ZIKV levels in Aedes aegypti. This effect included a quantitatively greater reduction in salivary gland ZIKV levels up to 11 d post-bloodmeal ingestion, relative to single pathway activation. Together, our study indicates the potential for field delivery of these small molecules to substantially reduce virus transmission from mosquito to human. As infections like Zika virus are becoming more burdensome and prevalent, understanding how to control this family of viruses in the insect vector is an important issue in public health.     

Recent Advances in Animal Models of Zika Virus Infection

An infection by Zika virus(ZIKV), a mosquito-borne flavivirus, broke out in South American regions in 2015, and recently showed a tendency of spreading to North America and even worldwide. ZIKV was first detected in 1947 and only 14 human infection cases were reported until 2007. This virus was previously observed to cause only mild flu-like symptoms.However, recent ZIKV infections might be responsible for the increasing cases of neurological disorders such as GuillainBarre′ syndrome and congenital defects, including newborn microcephaly. Therefore, researchers have established several animal models to study ZIKV transmission and pathogenesis, and test therapeutic candidates. This review mainly summarizes the reported animal models of ZIKV infection, including mice and non-human primates.     

寨卡疫苗研究进展

寨卡病毒系由伊蚊传播的黄病毒,超过20亿人在其流行区域生活。近几年,在中南美洲乃至世界范围内爆发的寨卡疫情已对全球公共卫生事业构成严重威胁。已有研究证实寨卡病毒感染为格林巴利综合征的病因之一;孕妇感染寨卡病毒后,可造成新生儿小头症。早日研制出安全有效的寨卡疫苗之重要性不言而喻。全球率先报道的寨卡疫苗为一款DNA疫苗,其在设计、制备和生产方面均较其他类型疫苗更加简易,且可避免可复制型疫苗因毒力回复而造成对孕妇和胎儿的健康威胁,在寨卡疫苗的研究中具有显著优势。其他传统类型疫苗和基于抗体的新型疫苗等均有研究机构开展研究,并已取得阶段性进展,本文将扼要综述寨卡疫苗的研究现状与进展。     

Comparing sources of mobility for modelling the epidemic spread of Zika virus in Colombia

Timely, accurate, and comparative data on human mobility is of paramount importance for epidemic preparedness and response, but generally not available or easily accessible. Mobile phone metadata, typically in the form of Call Detail Records (CDRs), represents a powerful source of information on human movements at an unprecedented scale. In this work, we investigate the potential benefits of harnessing aggregated CDR-derived mobility to predict the 2015-2016 Zika virus (ZIKV) outbreak in Colombia, when compared to other traditional data sources. To simulate the spread of ZIKV at sub-national level in Colombia, we employ a stochastic metapopulation epidemic model for vector-borne diseases. Our model integrates detailed data on the key drivers of ZIKV spread, including the spatial heterogeneity of the mosquito abundance, and the exposure of the population to the virus due to environmental and socio-economic factors. Given the same modelling settings (i.e. initial conditions and epidemiological parameters), we perform in-silico simulations for each mobility network and assess their ability in reproducing the local outbreak as reported by the official surveillance data. We assess the performance of our epidemic modelling approach in capturing the ZIKV outbreak both nationally and sub-nationally. Our model estimates are strongly correlated with the surveillance data at the country level (Pearson’s r = 0.92 for the CDR-informed network). Moreover, we found strong performance of the model estimates generated by the CDR-informed mobility networks in reproducing the local outbreak observed at the sub-national level. Compared to the CDR-informed networks, the performance of the other mobility networks is either comparatively similar or substantially lower, with no added value in predicting the local epidemic. This suggests that mobile phone data captures a better picture of human mobility patterns. This work contributes to the ongoing discussion on the value of aggregated mobility estimates from CDRs data that, with appropriate data protection and privacy safeguards, can be used for social impact applications and humanitarian action.     

Previous exposure to dengue virus is associated with increased Zika virus burden at the maternal-fetal interface in rhesus macaques

Concerns have arisen that pre-existing immunity to dengue virus (DENV) could enhance Zika virus (ZIKV) disease, due to the homology between ZIKV and DENV and the observation of antibody-dependent enhancement (ADE) among DENV serotypes. To date, no study has examined the impact of pre-existing DENV immunity on ZIKV pathogenesis during pregnancy in a translational non-human primate model. Here we show that macaques with a prior DENV-2 exposure had a higher burden of ZIKV vRNA in maternal-fetal interface tissues as compared to DENV-naive macaques. However, pre-existing DENV immunity had no detectable impact on ZIKV replication kinetics in maternal plasma, and all pregnancies progressed to term without adverse outcomes or gross fetal abnormalities detectable at delivery. Understanding the risks of ADE to pregnant women worldwide is critical as vaccines against DENV and ZIKV are developed and licensed and as DENV and ZIKV continue to circulate.     

Targeting the NTPase site of Zika virus NS3 helicase for inhibitor discovery

Abstract

The major threats linked to Zika virus (ZIKV) are microcephaly, Guillain-Barre syndrome, and the ability to transfer through sexual transmission. Despite these threats, Zika specific FDA approved drugs or vaccines are not available as of yet. Additionally, the involvement of pregnant women makes the drug screening process lengthy and complicated in terms of safety and minimum toxicity of the molecules. Since NS3 helicase of ZIKV performs the critical function of unwinding double-stranded RNA during replication, it is considered as a promising drug target to block ZIKV replication. In the present study, we have exploited the NTPase site of ZIKV NS3 helicase for screening potential inhibitor compounds by molecular docking, and molecular dynamics (MD) simulation approaches. NS3 helicase hydrolyzes the ATP to use its energy for unwinding RNA. We have chosen twenty natural compounds from ZINC library with known antiviral properties and a helicase focused library (HFL) of small molecules from Life Chemicals compounds. After going through docking, the top hit molecules from ZINC and HFL library were further analysed by MD simulations to find out stable binding poses. Finally, we have reported the molecules with potential of binding at NTPase pocket of ZIKV NS3 helicase, which could be further tested on virus through in vitro experiments to check their efficacy.

Communicated by Ramaswamy H. Sarma     

Dengue and Zika viruses: lessons learned from the similarities between these <Emphasis Type="Italic">Aedes</Emphasis> mosquito-vectored arboviruses

The currently spreading arbovirus epidemic is having a severe impact on human health worldwide. The two most common flaviviruses, dengue virus (DENV) and Zika virus (ZIKV), are transmitted through the same viral vector, Aedes spp. mosquitoes. Since the discovery of DENV in 1943, this virus has been reported to cause around 390 million human infections per year, approximately 500,000 of which require hospitalization and over 20,000 of which are lethal. The present DENV epidemic is primarily concentrated in Southeast Asia. ZIKV, which was discovered in 1952, is another important arthropod-borne flavivirus. The neurotropic role of ZIKV has been reported in infected newborns with microcephaly and in adults with Guillain-Barre syndrome. Despite DENV and ZIKV sharing the same viral vector, their complex pathogenic natures are poorly understood, and the infections they cause do not have specific treatments or effective vaccines. Therefore, this review will describe what is currently known about the clinical characteristics, pathogenesis mechanisms, and transmission of these two viruses. Better understanding of the interrelationships between DENV and ZIKV will provide a useful perspective for developing an effective strategy for controlling both viruses in the future.     

Characterization of Lethal Zika Virus Infection in AG129 Mice

BackgroundMosquito-borne Zika virus (ZIKV) typically causes a mild and self-limiting illness known as Zika fever, which often is accompanied by maculopapular rash, headache, and myalgia. During the current outbreak in South America, ZIKV infection during pregnancy has been hypothesized to cause microcephaly and other diseases. The detection of ZIKV in fetal brain tissue supports this hypothesis. Because human infections with ZIKV historically have remained sporadic and, until recently, have been limited to small-scale epidemics, neither the disease caused by ZIKV nor the molecular determinants of virulence and/or pathogenicity have been well characterized. Here, we describe a small animal model for wild-type ZIKV of the Asian lineage.Conclusions/SignificanceFoot pad injection of AG129 mice with ZIKV represents a biologically relevant model for studying ZIKV infection and disease development following wild-type virus inoculation without the requirement for adaptation of the virus or intracerebral delivery of the virus. This newly developed Zika disease model can be exploited to identify determinants of ZIKV virulence and reveal molecular mechanisms that control the virus-host interaction, providing a framework for rational design of acute phase therapeutics and for vaccine efficacy testing.     

Fetal loss in pregnant rhesus macaques infected with high-dose African-lineage Zika virus

Countermeasures against Zika virus (ZIKV), including vaccines, are frequently tested in nonhuman primates (NHP). Macaque models are important for understanding how ZIKV infections impact human pregnancy due to similarities in placental development. The lack of consistent adverse pregnancy outcomes in ZIKV-affected pregnancies poses a challenge in macaque studies where group sizes are often small (4–8 animals). Studies in small animal models suggest that African-lineage Zika viruses can cause more frequent and severe fetal outcomes. No adverse outcomes were observed in macaques exposed to 1x10⁴ PFU (low dose) of African-lineage ZIKV at gestational day (GD) 45. Here, we exposed eight pregnant rhesus macaques to 1x10⁸ PFU (high dose) of African-lineage ZIKV at GD 45 to test the hypothesis that adverse pregnancy outcomes are dose-dependent. Three of eight pregnancies ended prematurely with fetal death. ZIKV was detected in both fetal and placental tissues from all cases of early fetal loss. Further refinements of this exposure system (e.g., varying the dose and timing of infection) could lead to an even more consistent, unambiguous fetal loss phenotype for assessing ZIKV countermeasures in pregnancy. These data demonstrate that high-dose exposure to African-lineage ZIKV causes pregnancy loss in macaques and also suggest that ZIKV-induced first trimester pregnancy loss could be strain-specific.     

Socioeconomic disparities associated with symptomatic Zika virus infections in pregnancy and congenital microcephaly: A spatiotemporal analysis from Goiânia,Brazil (2016 to 2020)

The Zika virus (ZIKV) epidemic, which was followed by an unprecedented outbreak of congenital microcephaly, emerged in Brazil unevenly, with apparent pockets of susceptibility. The present study aimed to detect high-risk areas for ZIKV infection and microcephaly in Goiania, a large city of 1.5 million inhabitants in Central-West Brazil. Using geocoded surveillance data from the Brazilian Information System for Notifiable Diseases (SINAN) and from the Public Health Event Registry (RESP-microcefalia), we analyzed the spatiotemporal distribution and socioeconomic indicators of laboratory confirmed (RT-PCR and/or anti-ZIKV IgM ELISA) symptomatic ZIKV infections among pregnant women and clinically confirmed microcephaly in neonates, from 2016 to 2020. We investigated temporal patterns by estimating the risk of symptomatic maternal ZIKV infections and microcephaly per 1000 live births per month. We examined the spatial distribution of maternal ZIKV infections and microcephaly cases across the 63 subdistricts of Goiania by manually plotting the geographical coordinates. We used spatial scan statistics estimated by discrete Poisson models to detect high clusters of maternal ZIKV infection and microcephaly and compared the distributions by socioeconomic indicators measured at the subdistrict level. In total, 382 lab-confirmed cases of maternal ZIKV infections, and 31 cases of microcephaly were registered in the city of Goiania. More than 90% of maternal cases were reported between 2016 and 2017. The highest incidence of ZIKV cases among pregnant women occurred between February and April 2016. A similar pattern was observed in the following year, although with a lower number of cases, indicating seasonality for ZIKV infection, during the local rainy season. Most congenital microcephaly cases occurred with a time-lag of 6 to 7 months after the peak of maternal ZIKV infection. The highest estimated incidence of maternal ZIKV infections and microcephaly were 39.3 and 2.5 cases per 1000 livebirths, respectively. Districts with better socioeconomic indicators and with higher proportions of self-identified white inhabitants were associated with lower risks of maternal ZIKV infection. Overall, the findings indicate heterogeneity in the spatiotemporal patterns of maternal ZIKV infections and microcephaly, which were correlated with seasonality and included a high-risk geographic cluster. Our findings identified geographically and socio-economically underprivileged groups that would benefit from targeted interventions to reduce exposure to vector-borne infections.