Open AccessInternet-based biosurveillance methods for vector-borne diseases: Are they novel public health tools or just novelties?
Author(s) -
Simon Pollett,
Benjamin M. Althouse,
Brett M. Forshey,
George W. Rutherford,
Richard G. Jarman
Publication year - 2017
Publication title -
plos neglected tropical diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.99
H-Index - 135
eISSN - 1935-2735
pISSN - 1935-2727
DOI - 10.1371/journal.pntd.0005871
Subject(s) - the internet , big data , data science , dengue fever , public health surveillance , chikungunya , neglected tropical diseases , public health , vector (molecular biology) , disease , disease surveillance , computer science , internet privacy , medicine , biology , data mining , virology , world wide web , pathology , biochemistry , gene , recombinant dna
Internet-based surveillance methods for vector-borne diseases (VBDs) using “big data” sources such as Google, Twitter, and internet newswire scraping have recently been developed, yet reviews on such “digital disease detection” methods have focused on respiratory pathogens, particularly in high-income regions. Here, we present a narrative review of the literature that has examined the performance of internet-based biosurveillance for diseases caused by vector-borne viruses, parasites, and other pathogens, including Zika, dengue, other arthropod-borne viruses, malaria, leishmaniasis, and Lyme disease across a range of settings, including low- and middle-income countries. The fundamental features, advantages, and drawbacks of each internet big data source are presented for those with varying familiarity of “digital epidemiology.” We conclude with some of the challenges and future directions in using internet-based biosurveillance for the surveillance and control of VBD.