A Clinical Review of Zika Virus (ZIKAV)
Volume 2, Issue 2, Page No 7-10, 2017
Author’s Name: Muhammad Hashim Razaa),1, Sarfraz Hussain2, Muhammad Abdul Rehman Tanveer3, Ayesha Zaman4
1Department of Bioinformatics and Biotechnology, International Islamic University, Islamabad, Pakistan.44000
2Department of Microbiology, University of Veterinary and Animal Sciences, Lahore, Pakistan.54000
3Department of Microbiology, University of Central Punjab, Lahore, Pakistan.54000
4Department of Microbiology, Abbottabad University of Science and Technology, Abbottabad, Pakistan.22010
Zika virus (ZIKAV) is a flavi-virus, first isolated in 1947 in the Zika Forest of Uganda. ZIKAV is a positive-sense single-stranded RNA virus. ZIKAV is made up of two noncoding regions (5′ and 3′) that verge an open reading frame, which put into code a polyprotein smote into the capsid, precursor of membrane, envelope, and 7 nonstructural proteins. Inoculation of a human host is by Mosquito. After cellular en¬try, the virus enters skin cells through cellular receptors, enabling migration to the lymph nodes and blood circulation. ZIKAV may also enter to skin fibroblasts, keratino¬cytes, and immature dendritic cells. Several entry and adhesion factors enable infection, and cellular autophagy, needed for flaviviral replication. Transmission is by infected mosquito dur¬ing a blood meal. After endorsement, the virus replicates and is pass on to a reservoir animal at the next blood mealtime. ZIKAV is also transmitted via congenital, perinatal, and sexual, possible transmission by blood transfusion, ani¬mal bite and intrauterine transmission. Trans-mission via breast-feeding has not been reported. Incubation period from mosquito bite to symptom commencement is 3–12 days. Infection is likely subclinical in 80% of cases. Symptoms, which last for almost two to seven days include fever, conjunctivitis, arthralgia, myalgia, and pervasive rash, which may be itchy. Headache, retro-orbital pain, peripheral oedema, and gastrointestinal fracas have also been witnessed. Diagnosis is directed by history and consideration. The symptoms and clinical signs do not have adequate positive or negative prognostic value, and therefore laboratory testing is needed for dependable diagnosis. Laboratory testing includes polymerase chain reaction (PCR) of ZIKAV RNA. There is formerly no vaccine against ZIKAV, nor definite antiviral for the management of ZIKAV. Treatment is suggestive. Vector control by insecticides and removal of small pools of still water, the breeding sites for Aedes, is being instituted on a local level.
Received: 15 January 2017, Accepted: 06 February 2017, Published Online: 25 February 2017
- Fekih,M., Bourabaa, A. and Mohamed, S. ,2013, Evaluation of two methods for estimation of evaporation from Dams water in arid and semi-arid areas in Algeria, International Journal of Application or Innovation in Engineering & Management (IJAIEM), 2, 376-381, ISSN 2319 – 4847.
- Benzaghta, M. A. , Mohammed, T. A. and Ekhmaj, A. I., 2012, Prediction of Evaporation from Algardabiya Reservoir, Libyan Agriculture Research Center Journal International ,3,120-128 , ISSN 2219-4304.
- Dalkiliç, Y., Okkan, U. and Baykan, N., 2014, Comparison of Different Ann Approaches in Daily Pan Evaporation Prediction, Journal of Water Resource and Protection, 6, 319-326. http://dx.doi.org/10.4236/jwarp.2014.64034.
- Goyal, M. K., Bharti, B., Quilty, J. c, Adamowski, J. and Pandey, A. ,2014, Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS, Expert Systems with Applications, 41 , 5267–5276.
- Behrooz Keshtegar, and Ozgur Kisi , 2016, A nonlinear modelling-based high-order response surface method for predicting monthly pan evaporations, Hydrol. Earth Syst. Sci. Manuscript under review , CC-BY 3.0 License.
- Wang, L., Kisi, O., Z.-Kermani, M., and, Gan, Y.,2016 , Comparison of six different soft computing methods in modeling evaporation in different climates, Hydrol. Earth Syst. Sci. Manuscript under review. CC-BY 3.0 License.
- Benzaghta, M. A. , Mohammed, T. A., Ghazali, A.H. and Soom, M. A.,2012 Prediction of evaporation in tropical climate using artificial neural network and climate based models , Scientific Research and Essays ,36, 3133-3148, ISSN 1992-2248 .
- Alsanusi, S., Bentaher, L. ,2015, Prediction of Compressive Strength of Concrete from Early Age Test Result Using Design of Experiments (RSM)”, International Journal of Civil, Environmental, Structural, Construction and Architectural Engineering, 9 ,1522-1526.
- Elmazoghi, H. G., Karakale, V. and Bentaher, L., 2016, Comparison of neural networks and neuro-fuzzy computing techniques for prediction of peak breach outflow, Journal of Hydroinformatics , 18,724-740.