Prevalence of individual brain and eye defects potentially related to Zika virus in pregnancy in 22 U.S. states and territories, January 2016 - June 2017

During the Centers for Disease Control and Prevention’s Zika Virus Response, birth defects surveillance programs adapted to monitor birth defects potentially related to Zika virus (ZIKV) infection during pregnancy. Pregnancy outcomes occurring during January 2016-June 2017 in 22 U.S. states and territories were used to estimate the prevalence of those brain and eye defects potentially related to ZIKV. Jurisdictions were divided into three groups: areas with widespread ZIKV transmission, areas with limited local ZIKV transmission, and areas without local ZIKV transmission. Prevalence estimates for selected brain and eye defects and microcephaly per 10,000 live births were estimated. Prevalence ratios (PRs) and 95% confidence intervals (CIs) were estimated using Poisson regression for areas with widespread and limited ZIKV transmission compared to areas without local ZIKV transmission. Defects with significantly higher prevalence in areas of widespread transmission were pooled, and PRs were calculated by quarter, comparing subsequent quarters to the first quarter (January – March 2016). Nine defects had significantly higher prevalence in areas of widespread transmission. The highest PRs were seen in intracranial calcifications (PR=12.6, 95% CI [7.4, 21.3]), chorioretinal abnormalities (12.5 [7.1, 22.3]), brainstem abnormalities (9.3, [4.7, 18.4]), and cerebral/cortical atrophy (6.7, [4.2, 10.8]). The PR of the nine pooled defects was significantly higher in three quarters in areas with widespread transmission. The largest difference in prevalence was observed for defects consistently reported in infants with congenital ZIKV infection. Birth defects surveillance programs could consider monitoring a subset of birth defects potentially related to ZIKV in pregnancy.

Zika virus baculovirus-expressed envelope protein elicited humoral and cellular immunity in immunocompetent mice

Zika virus (ZIKV) is a mosquito-borne virus that has a high risk of inducing Guillain–Barré syndrome and microcephaly in newborns. Because vaccination is considered the most effective strategy against ZIKV infection, we designed a recombinant vaccine utilizing the baculovirus expression system with two strains of ZIKV envelope protein (MR766, Env_M; ZBRX6, Env_Z). Animals inoculated with Env_M and Env_Z produced ZIKV-specific antibodies and secreted effector cytokines such as interferon-γ, tumor necrosis factor-α, and interleukin-12. Moreover, the progeny of immunized females had detectable maternal antibodies that protected them against two ZIKV strains (MR766 and PRVABC59) and a Dengue virus strain. We propose that the baculovirus expression system ZIKV envelope protein recombinant provides a safe and effective vaccine strategy.

Zika Virus Prediction Using AI-Driven Technology and Hybrid Optimization Algorithm in Healthcare

The Zika virus presents an extraordinary public health hazard after spreading from Brazil to the Americas. In the absence of credible forecasts of the outbreak's geographic scope and infection frequency, international public health agencies were unable to plan and allocate surveillance resources efficiently. An RNA test will be done on the subjects if they are found to be infected with Zika virus. By training the specified characteristics, the suggested Hybrid Optimization Algorithm such as multilayer perceptron with probabilistic optimization strategy gives forth a greater accuracy rate. The MATLAB program incorporates numerous machine learning algorithms and artificial intelligence methodologies. It reduces forecast time while retaining excellent accuracy. The projected classes are encrypted and sent to patients. The Advanced Encryption Standard (AES) and TRIPLE Data Encryption Standard (TEDS) are combined to make this possible (DES). The experimental outcomes improve the accuracy of patient results communication. Cryptosystem processing acquires minimal timing of 0.15 s with 91.25 percent accuracy.

Incidência dos casos de Dengue (2011-2017), Zika e Febre Chikungunya (2016-2017) em Balsas, Maranhão

As arboviroses são doenças causadas pelos arbovírus, dentre elas inclui-se o vírus da Dengue, Zika, febre Chikungunya e engloba todos aqueles transmitidos por artrópodes, (insetos e aracnídeos). Neste estudo foram analisadas duas variáveis: a incidência dos casos de Dengue, Zika e febre Chikungunya por mesmo mês, e a mensal de índice pluviométrico do município de Balsas Maranhão, através do site do Instituto Nacional de Meteorologia. Pelo estudo de gráficos observou-se a precipitação média relacionada aos casos das três doenças em questão. Notou-se que a quantidade de chuva foi um item importante relacionado à incidência dos casos: Zika vírus e febre Chikungunya tiveram uma maior frequência no período de estiagem enquanto a incidência do vírus da Dengue foi maior no período chuvoso. Como Balsas é destaque por ser um dos grandes centros urbanos do sul da Maranhão, e contar com atendimento hospitalar de cidadãos de municípios vizinhos, é importante que haja a interiorização de laboratórios de referência para detecção de agentes etiológicos dos vetores assim como ações contínuas de vigilância e controle epidemiológico do A. egypti.

In silico construction of a multiepitope Zika virus vaccine using immunoinformatics tools

Zika virus (ZIKV) is an arbovirus from the Flaviviridae family and Flavivirus genus. Neurological events have been associated with ZIKV-infected individuals, such as Guillain-Barré syndrome, an autoimmune acute neuropathy that causes nerve demyelination and can induce paralysis. With the increase of ZIKV infection incidence in 2015, malformation and microcephaly cases in newborns have grown considerably, which suggested congenital transmission. Therefore, the development of an effective vaccine against ZIKV became an urgent need. Live attenuated vaccines present some theoretical risks for administration in pregnant women. Thus, we developed an in silico multiepitope vaccine against ZIKV. All structural and non-structural proteins were investigated using immunoinformatics tools designed for the prediction of CD4 + and CD8 + T cell epitopes. We selected 13 CD8 + and 12 CD4 + T cell epitopes considering parameters such as binding affinity to HLA class I and II molecules, promiscuity based on the number of different HLA alleles that bind to the epitopes, and immunogenicity. ZIKV Envelope protein domain III (EDIII) was added to the vaccine construct, creating a hybrid protein domain-multiepitope vaccine. Three high scoring continuous and two discontinuous B cell epitopes were found in EDIII. Aiming to increase the candidate vaccine antigenicity even further, we tested secondary and tertiary structures and physicochemical parameters of the vaccine conjugated to four different protein adjuvants: flagellin, 50S ribosomal protein L7/L12, heparin-binding hemagglutinin, or RS09 synthetic peptide. The addition of the flagellin adjuvant increased the vaccine's predicted antigenicity. In silico predictions revealed that the protein is a probable antigen, non-allergenic and predicted to be stable. The vaccine’s average population coverage is estimated to be 87.86%, which indicates it can be administered worldwide. Peripheral Blood Mononuclear Cells (PBMC) of individuals with previous ZIKV infection were tested for cytokine production in response to the pool of CD4 and CD8 ZIKV peptide selected. CD4 + and CD8 + T cells showed significant production of IFN-γ upon stimulation and IL-2 production was also detected by CD8 + T cells, which indicated the potential of our peptides to be recognized by specific T cells and induce immune response. In conclusion, we developed an in silico universal vaccine predicted to induce broad and high-coverage cellular and humoral immune responses against ZIKV, which can be a good candidate for posterior in vivo validation.