NDLI: Risk Factors Linked to Influenza-like Illness as Identified from the Mexican Participatory Surveillance System: Risk Factors in ILI

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Risk Factors Linked to Influenza-like Illness as Identified from the Mexican Participatory Surveillance System: Risk Factors in ILI

Content Provider	ACM Digital Library
Author	Mantilla-Berniers, Natalia B. Rodríguez-Ramírez, Rocio Garcia-Aguirre, Concepción Mireles, Victor Stephens, Christopher R. Hernández-López, Sergio Herrera-Ortiz, Juan Arturo
Abstract	Internet-based monitoring of influenza-like illnesses (ILI) has become more common since its beginnings nearly a decade ago, both through estimates based on the number of searches for influenza-related terms (e.g., Google flu trends), or by means of participatory surveillance systems. The latter, often seen as ways of engaging people in matters of scientific and public health importance, gather a wealth of potentially valuable epidemiological information complementary to that obtained through the established disease surveillance networks and also usually absent from search-based web algorithms. We present a statistical analysis of the data from the Mexican monitoring website "Reporta" by which the risk factors linked to reporting of ILI symptoms as outcome among its participants are determined, and interpret these results based on current knowledge of the factors that influence transmission of infection resulting in disease. Besides standard factors associated with enhanced susceptibility to infection some novel behavioral factors linked to high risk were: (i) use of public transport; (ii) frequent contact with animals, and (iii) use of non-standard interventions, such as homeopathy. While close contact with large groups of people in public transportation is generally assumed to be important in disease spread, frequent contact with animals is not. Our results are consistent with previous observations that animals may serve as mobile fomites and hence increase the propensity to develop disease. We conclude that analysis of rich information sets from Internet-based systems may suggest novel ideas on disease spread that are worth following up with field research.
Starting Page	147
Ending Page	154
Page Count	8
File Format	PDF
ISBN	9781450352499
DOI	10.1145/3079452.3079471
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-07-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Participatory surveillance system Influenza Risk factors
Content Type	Text
Resource Type	Article

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