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Disparities in digital reporting of illness: A demographic and socioeconomic assessment

Although digital reports of disease are currently used by public health officials for disease surveillance and decision making, little is known about environmental factors and compositional characteristics that may influence reporting patterns. The objective of this study is to quantify the associat...

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Autores principales: Henly, Samuel, Tuli, Gaurav, Kluberg, Sheryl A., Hawkins, Jared B., Nguyen, Quynh C., Anema, Aranka, Maharana, Adyasha, Brownstein, John S., Nsoesie, Elaine O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5553633/
https://www.ncbi.nlm.nih.gov/pubmed/28528170
http://dx.doi.org/10.1016/j.ypmed.2017.05.009
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author Henly, Samuel
Tuli, Gaurav
Kluberg, Sheryl A.
Hawkins, Jared B.
Nguyen, Quynh C.
Anema, Aranka
Maharana, Adyasha
Brownstein, John S.
Nsoesie, Elaine O.
author_facet Henly, Samuel
Tuli, Gaurav
Kluberg, Sheryl A.
Hawkins, Jared B.
Nguyen, Quynh C.
Anema, Aranka
Maharana, Adyasha
Brownstein, John S.
Nsoesie, Elaine O.
author_sort Henly, Samuel
collection PubMed
description Although digital reports of disease are currently used by public health officials for disease surveillance and decision making, little is known about environmental factors and compositional characteristics that may influence reporting patterns. The objective of this study is to quantify the association between climate, demographic and socio-economic factors on digital reporting of disease at the US county level. We reference approximately 1.5 million foodservice business reviews between 2004 and 2014, and use census data, machine learning methods and regression models to assess whether digital reporting of disease is associated with climate, socio-economic and demographic factors. The results show that reviews of foodservice businesses and digital reports of foodborne illness follow a clear seasonal pattern with higher reporting observed in the summer, when most foodborne outbreaks are reported and to a lesser extent in the winter months. Additionally, factors typically associated with affluence (such as, higher median income and fraction of the population with a bachelor's degrees) were positively correlated with foodborne illness reports. However, restaurants per capita and education were the most significant predictors of illness reporting at the US county level. These results suggest that well-known health disparities might also be reflected in the online environment. Although this is an observational study, it is an important step in understanding disparities in the online public health environment.
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spelling pubmed-55536332018-08-01 Disparities in digital reporting of illness: A demographic and socioeconomic assessment Henly, Samuel Tuli, Gaurav Kluberg, Sheryl A. Hawkins, Jared B. Nguyen, Quynh C. Anema, Aranka Maharana, Adyasha Brownstein, John S. Nsoesie, Elaine O. Prev Med Article Although digital reports of disease are currently used by public health officials for disease surveillance and decision making, little is known about environmental factors and compositional characteristics that may influence reporting patterns. The objective of this study is to quantify the association between climate, demographic and socio-economic factors on digital reporting of disease at the US county level. We reference approximately 1.5 million foodservice business reviews between 2004 and 2014, and use census data, machine learning methods and regression models to assess whether digital reporting of disease is associated with climate, socio-economic and demographic factors. The results show that reviews of foodservice businesses and digital reports of foodborne illness follow a clear seasonal pattern with higher reporting observed in the summer, when most foodborne outbreaks are reported and to a lesser extent in the winter months. Additionally, factors typically associated with affluence (such as, higher median income and fraction of the population with a bachelor's degrees) were positively correlated with foodborne illness reports. However, restaurants per capita and education were the most significant predictors of illness reporting at the US county level. These results suggest that well-known health disparities might also be reflected in the online environment. Although this is an observational study, it is an important step in understanding disparities in the online public health environment. 2017-05-17 2017-08 /pmc/articles/PMC5553633/ /pubmed/28528170 http://dx.doi.org/10.1016/j.ypmed.2017.05.009 Text en http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Henly, Samuel
Tuli, Gaurav
Kluberg, Sheryl A.
Hawkins, Jared B.
Nguyen, Quynh C.
Anema, Aranka
Maharana, Adyasha
Brownstein, John S.
Nsoesie, Elaine O.
Disparities in digital reporting of illness: A demographic and socioeconomic assessment
title Disparities in digital reporting of illness: A demographic and socioeconomic assessment
title_full Disparities in digital reporting of illness: A demographic and socioeconomic assessment
title_fullStr Disparities in digital reporting of illness: A demographic and socioeconomic assessment
title_full_unstemmed Disparities in digital reporting of illness: A demographic and socioeconomic assessment
title_short Disparities in digital reporting of illness: A demographic and socioeconomic assessment
title_sort disparities in digital reporting of illness: a demographic and socioeconomic assessment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5553633/
https://www.ncbi.nlm.nih.gov/pubmed/28528170
http://dx.doi.org/10.1016/j.ypmed.2017.05.009
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