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Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China

This study explored how internet queries vary in facilitating monitoring of pertussis, and the effects of sociodemographic characteristics on such variation by city in Shandong province, China. We collected weekly pertussis notifications, Baidu Index (BI) data and yearly sociodemographic data at the...

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Autores principales: Zhang, Yuzhou, Bambrick, Hilary, Mengersen, Kerrie, Tong, Shilu, Feng, Lei, Zhang, Li, Liu, Guifang, Xu, Aiqiang, Hu, Wenbiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873159/
https://www.ncbi.nlm.nih.gov/pubmed/31727192
http://dx.doi.org/10.1017/S0950268819001924
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author Zhang, Yuzhou
Bambrick, Hilary
Mengersen, Kerrie
Tong, Shilu
Feng, Lei
Zhang, Li
Liu, Guifang
Xu, Aiqiang
Hu, Wenbiao
author_facet Zhang, Yuzhou
Bambrick, Hilary
Mengersen, Kerrie
Tong, Shilu
Feng, Lei
Zhang, Li
Liu, Guifang
Xu, Aiqiang
Hu, Wenbiao
author_sort Zhang, Yuzhou
collection PubMed
description This study explored how internet queries vary in facilitating monitoring of pertussis, and the effects of sociodemographic characteristics on such variation by city in Shandong province, China. We collected weekly pertussis notifications, Baidu Index (BI) data and yearly sociodemographic data at the city level between 1 January 2009 and 31 December 2017. Spearman's correlation was performed for temporal risk indices, generalised linear models and regression tree models were developed to identify the hierarchical effects and the threshold between sociodemographic factors and internet query data with pertussis surveillance. The BI was correlated with pertussis notifications, with a strongly spatial variation among cities in temporal risk indices (composite temporal risk metric (CTRM) range: 0.59–1.24). The percentage of urban population (relative risk (RR): 1.05, 95% confidence interval (CI) 1.03–1.07), the proportion of highly educated population (RR: 1.27, 95% CI 1.16–1.39) and the internet access rate (RR: 1.04, 95% CI 1.02–1.05) were correlated with CTRM. Higher RRs in the three identified sociodemographic factors were associated with higher stratified CTRM. The percentage of highly educated population was the most important determinant in the BI with pertussis surveillance. The findings may lead to spatially-specific criteria to inform development of an early warning system of pertussis infections using internet query data.
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spelling pubmed-68731592019-12-04 Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China Zhang, Yuzhou Bambrick, Hilary Mengersen, Kerrie Tong, Shilu Feng, Lei Zhang, Li Liu, Guifang Xu, Aiqiang Hu, Wenbiao Epidemiol Infect Original Paper This study explored how internet queries vary in facilitating monitoring of pertussis, and the effects of sociodemographic characteristics on such variation by city in Shandong province, China. We collected weekly pertussis notifications, Baidu Index (BI) data and yearly sociodemographic data at the city level between 1 January 2009 and 31 December 2017. Spearman's correlation was performed for temporal risk indices, generalised linear models and regression tree models were developed to identify the hierarchical effects and the threshold between sociodemographic factors and internet query data with pertussis surveillance. The BI was correlated with pertussis notifications, with a strongly spatial variation among cities in temporal risk indices (composite temporal risk metric (CTRM) range: 0.59–1.24). The percentage of urban population (relative risk (RR): 1.05, 95% confidence interval (CI) 1.03–1.07), the proportion of highly educated population (RR: 1.27, 95% CI 1.16–1.39) and the internet access rate (RR: 1.04, 95% CI 1.02–1.05) were correlated with CTRM. Higher RRs in the three identified sociodemographic factors were associated with higher stratified CTRM. The percentage of highly educated population was the most important determinant in the BI with pertussis surveillance. The findings may lead to spatially-specific criteria to inform development of an early warning system of pertussis infections using internet query data. Cambridge University Press 2019-11-15 /pmc/articles/PMC6873159/ /pubmed/31727192 http://dx.doi.org/10.1017/S0950268819001924 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Paper
Zhang, Yuzhou
Bambrick, Hilary
Mengersen, Kerrie
Tong, Shilu
Feng, Lei
Zhang, Li
Liu, Guifang
Xu, Aiqiang
Hu, Wenbiao
Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China
title Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China
title_full Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China
title_fullStr Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China
title_full_unstemmed Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China
title_short Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China
title_sort association of sociodemographic factors and internet query data with pertussis infections in shandong, china
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873159/
https://www.ncbi.nlm.nih.gov/pubmed/31727192
http://dx.doi.org/10.1017/S0950268819001924
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