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High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea.

ABSTRACT: The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26, 2015 using the Korean government MERS portal. The daily trends observed via Google search and Twitter during the same time period were also ascertained using Google Trends and Topsy. Correlations among the data were then examined using Spearman correlation analysis. We found high correlations (>0.7) between Google search and Twitter results and the number of confirmed MERS cases for the previous three days using only four simple keywords: "MERS", "" ("MERS (in Korean)"), "" ("MERS symptoms (in Korean)"), and "" ("MERS hospital (in Korean)"). Additionally, we found high correlations between the Google search and Twitter results and the number of quarantined cases using the above keywords. This study demonstrates the possibility of using a digital surveillance system to monitor the outbreak of MERS.

SUBMITTER: Shin SY

PROVIDER: S-EPMC5011762 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea.

Shin Soo-Yong SY Seo Dong-Woo DW An Jisun J Kwak Haewoon H Kim Sung-Han SH Gwack Jin J Jo Min-Woo MW

Scientific reports 20160906

The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26, 2015 using the Korean government MERS portal. The daily trends observed via Google search and Twitter d ...[more]

PMID: 27595921

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Project description:UNLABELLED:The Middle East respiratory syndrome coronavirus (MERS-CoV) was first documented in the Kingdom of Saudi Arabia (KSA) in 2012 and, to date, has been identified in 180 cases with 43% mortality. In this study, we have determined the MERS-CoV evolutionary rate, documented genetic variants of the virus and their distribution throughout the Arabian peninsula, and identified the genome positions under positive selection, important features for monitoring adaptation of MERS-CoV to human transmission and for identifying the source of infections. Respiratory samples from confirmed KSA MERS cases from May to September 2013 were subjected to whole-genome deep sequencing, and 32 complete or partial sequences (20 were ? 99% complete, 7 were 50 to 94% complete, and 5 were 27 to 50% complete) were obtained, bringing the total available MERS-CoV genomic sequences to 65. An evolutionary rate of 1.12 × 10(-3) substitutions per site per year (95% credible interval [95% CI], 8.76 × 10(-4); 1.37 × 10(-3)) was estimated, bringing the time to most recent common ancestor to March 2012 (95% CI, December 2011; June 2012). Only one MERS-CoV codon, spike 1020, located in a domain required for cell entry, is under strong positive selection. Four KSA MERS-CoV phylogenetic clades were found, with 3 clades apparently no longer contributing to current cases. The size of the population infected with MERS-CoV showed a gradual increase to June 2013, followed by a decline, possibly due to increased surveillance and infection control measures combined with a basic reproduction number (R0) for the virus that is less than 1. IMPORTANCE:MERS-CoV adaptation toward higher rates of sustained human-to-human transmission appears not to have occurred yet. While MERS-CoV transmission currently appears weak, careful monitoring of changes in MERS-CoV genomes and of the MERS epidemic should be maintained. The observation of phylogenetically related MERS-CoV in geographically diverse locations must be taken into account in efforts to identify the animal source and transmission of the virus.

Project description:BackgroundSalmonella infection (salmonellosis) is a common infectious disease leading to gastroenteritis, dehydration, uveitis, etc. Internet search is a new method to monitor the outbreak of infectious disease. An internet-based surveillance system using internet data is logistically advantageous and economical to show term-related diseases. In this study, we tried to determine the relationship between salmonellosis and Google Trends in the USA from January 2004 to December 2017.MethodsWe downloaded the reported salmonellosis in the USA from the National Outbreak Reporting System (NORS) from January 2004 to December 2017. Additionally, we downloaded the Google search terms related to salmonellosis from Google Trends in the same period. Cross-correlation analysis and multiple regression analysis were conducted.ResultsThe results showed that 6 Google Trends search terms appeared earlier than reported salmonellosis, 26 Google Trends search terms coincided with salmonellosis, and 16 Google Trends search terms appeared after salmonellosis were reported. When the search terms preceded outbreaks, "foods" (t = 2.927, P = 0.004) was a predictor of salmonellosis. When the search terms coincided with outbreaks, "hotel" (t = 1.854, P = 0.066), "poor sanitation" (t = 2.895, P = 0.004), "blueberries" (t = 2.441, P = 0.016), and "hypovolemic shock" (t = 2.001, P = 0.047) were predictors of salmonellosis. When the search terms appeared after outbreaks, "ice cream" (t = 3.077, P = 0.002) was the predictor of salmonellosis. Finally, we identified the most important indicators of Google Trends search terms, including "hotel" (t = 1.854, P = 0.066), "poor sanitation" (t = 2.895, P = 0.004), "blueberries" (t = 2.441, P = 0.016), and "hypovolemic shock" (t = 2.001, P = 0.047). In the future, the increased search activities of these terms might indicate the salmonellosis.ConclusionWe evaluated the related Google Trends search terms with salmonellosis and identified the most important predictors of salmonellosis outbreak.

Project description:BackgroundEpidemiologic parameters are important in planning infection control policies during the outbreak of emerging infections. Korea experienced an outbreak of Middle East Respiratory Syndrome coronavirus (MERS-CoV) infection in 2015, which was characterized by superspreading events in healthcare settings. We aimed to estimate the epidemiologic parameters over time during the outbreak to assess the effectiveness of countermeasures.Materials and methodsPublicly available data pertaining to the MERS outbreak in Korea were collected. We estimated the incubation periods of 162 cases whose sources of exposure were identified and the temporal trend was evaluated. Factors influencing incubation duration were analyzed. The generational reproduction number (Rg ) and case reproduction number (R(c) ) were estimated over time.ResultsThe estimated median incubation period was 7.4 days (95% CI, 6.9-8.0). Median incubation periods tended to be longer over time as the disease generation progressed: 6.16 days (95% CI, 5.38-6.97), 7.68 days (95% CI, 7.04-8.44), and 7.95 days (95% CI, 6.25-9.88) in the first, second, and third generations, respectively. The number of days of illness in the source cases at the time of exposure inversely correlated with the incubation periods in the receiving cases (HR 0.91 [95% CI, 0.84-0.99] per one illness day increase; P=0.026). This relationship was consistent (HR 0.83 [95% CI, 0.74-0.93] per one illness day increase) in the multivariable analysis incorporating clinical characteristics, the order of generation, and a link to superspreaders. Because the third generation cases were exposed to their source cases in the early stage (median one day) compared to the second generation cases (median 6 days), the temporal trend of incubation periods appears to be influenced by early isolation of symptomatic cases and reduction of potential exposure to source cases in the later stage. Rg declined rapidly from 28 to 0.23 in two generations. R(c) dropped below the epidemic threshold at one on May 31, 2015, which approximately coincided with the initiation of the stringent countermeasures.ConclusionsDespite the initial delay, the stringent countermeasures targeted towards second generation cases appeared to effectively contain the MERS outbreak in Korea as suggested by the decline of R(c) shortly after implementation. Except for superspreading events, the transmission potential for MERS-CoV seems to be low. Further research should be focused on characterizing superspreaders in comparison to non-transmitting cases with regard to environmental, behavioral, and virologic and host genetic factors in order to better prepare for future outbreaks of MERS-CoV.

Dataset Information

High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea.

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High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea.

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