Literature DB >> 27311388

Clinical and spatial features of Zika virus in Mexico.

Ubydul Haque1, Jacob D Ball2, Wenyi Zhang3, Md Mobarak Hossain Khan4, Jesús A Treviño C5.   

Abstract

BACKGROUND: Zika virus (ZIKV) is an emerging arbovirus transmitted to humans by Aedes mosquitoes, the same vectors that transmit dengue virus and chikungunya. Recent work has suggested that prior infection with dengue could lead to more severe clinical disease in ZIKV patients. Here, we describe the spatial distribution of and clinical symptoms experienced by ZIKV cases in Mexico.
METHODS: We performed Fisher's Exact test and Pearson's Chi-Square tests on data from Mexico's national surveillance system on the demographic and clinical characteristics of ZIKV patients (N=84), and then a multivariate logistic regression analysis to determine demographic risk factors for patients presenting with at least 9 symptoms. We also mapped the cases to describe the spatial distribution of ZIKV in Mexico.
RESULTS: Results from the multivariate logistic regression analysis indicate that, controlling for all covariates, sex (male) is a significant protective factor in reporting a high number of symptoms (OR=0.36, 95% CI: 0.14, 0.92), and that a one-year increase in age is associated with a 4% increase in odds of having at least 9 symptoms (95% CI: 1.00, 1.08). Spatial analysis revealed more than 50% cases reported within 50km of railways.
CONCLUSION: We found that sex and age are both significant risk factors for ZIKV infection severity, using number of reported symptoms as a proxy. The presence of cases along railways indicates that transportation networks within Mexico may be relevant for the national and international spread of the disease.
Copyright © 2016 Elsevier B.V. All rights reserved.

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Year:  2016        PMID: 27311388     DOI: 10.1016/j.actatropica.2016.06.010

Source DB:  PubMed          Journal:  Acta Trop        ISSN: 0001-706X            Impact factor:   3.112


  5 in total

1.  Seroprevalence, risk factor, and spatial analyses of Zika virus infection after the 2016 epidemic in Managua, Nicaragua.

Authors:  José Victor Zambrana; Fausto Bustos Carrillo; Raquel Burger-Calderon; Damaris Collado; Nery Sanchez; Sergio Ojeda; Jairo Carey Monterrey; Miguel Plazaola; Brenda Lopez; Sonia Arguello; Douglas Elizondo; William Aviles; Josefina Coloma; Guillermina Kuan; Angel Balmaseda; Aubree Gordon; Eva Harris
Journal:  Proc Natl Acad Sci U S A       Date:  2018-08-27       Impact factor: 11.205

2.  Online platform for applying space-time scan statistics for prospectively detecting emerging hot spots of dengue fever.

Authors:  Chien-Chou Chen; Yung-Chu Teng; Bo-Cheng Lin; I-Chun Fan; Ta-Chien Chan
Journal:  Int J Health Geogr       Date:  2016-11-25       Impact factor: 3.918

3.  Zika virus: Epidemiological surveillance of the Mexican Institute of Social Security.

Authors:  Concepción Grajales-Muñiz; Víctor Hugo Borja-Aburto; David Alejandro Cabrera-Gaytán; Teresita Rojas-Mendoza; Lumumba Arriaga-Nieto; Alfonso Vallejos-Parás
Journal:  PLoS One       Date:  2019-02-11       Impact factor: 3.240

4.  The impact of COVID-19 on globalization.

Authors:  Nistha Shrestha; Muhammad Yousaf Shad; Osman Ulvi; Modasser Hossain Khan; Ajlina Karamehic-Muratovic; Uyen-Sa D T Nguyen; Mahdi Baghbanzadeh; Robert Wardrup; Nasrin Aghamohammadi; Diana Cervantes; Kh Md Nahiduzzaman; Rafdzah Ahmad Zaki; Ubydul Haque
Journal:  One Health       Date:  2020-10-13

5.  Prediction of dengue outbreak in Selangor Malaysia using machine learning techniques.

Authors:  Nurul Azam Mohd Salim; Yap Bee Wah; Caitlynn Reeves; Madison Smith; Wan Fairos Wan Yaacob; Rose Nani Mudin; Rahmat Dapari; Nik Nur Fatin Fatihah Sapri; Ubydul Haque
Journal:  Sci Rep       Date:  2021-01-13       Impact factor: 4.379

  5 in total

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