메뉴 건너뛰기




Volumn 5, Issue 1, 2018, Pages

Infoveillance of infectious diseases in USA: STDs, tuberculosis, and hepatitis

Author keywords

Big data; Chlamydia; Gonorrhea; Google trends; Health informatics; Hepatitis; Infodemiology; Infoveillance; Internet behavior; Public health; Sexually transmitted diseases; Syphilis; Tuberculosis

Indexed keywords

DATA ANALYTICS; DISEASE CONTROL; DISEASES; FORECASTING; GEOGRAPHICAL DISTRIBUTION; MEDICAL INFORMATICS; PUBLIC HEALTH;

EID: 85052882960     PISSN: None     EISSN: 21961115     Source Type: Journal    
DOI: 10.1186/s40537-018-0140-9     Document Type: Article
Times cited : (18)

References (57)
  • 1
    • 67651237086 scopus 로고    scopus 로고
    • Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the internet
    • Eysenbach G. Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the internet. J Med Internet Res. 2009;11(1):e11
    • (2009) J Med Internet Res , vol.11 , Issue.1
    • Eysenbach, G.1
  • 2
    • 85047247936 scopus 로고    scopus 로고
    • Integrating Smart Health in the US Health Care system: infodemiology Study of asthma monitoring in the Google era
    • Mavragani A, Sampri A, Sypsa K, Tsagarakis KP. Integrating Smart Health in the US Health Care system: infodemiology Study of asthma monitoring in the Google era. JMIR Public Health Surveill. 2018;4(1):e24
    • (2018) JMIR Public Health Surveill , vol.4 , Issue.1
    • Mavragani, A.1    Sampri, A.2    Sypsa, K.3    Tsagarakis, K.P.4
  • 5
    • 85021824287 scopus 로고    scopus 로고
    • Researching mental health disorders in the era of social media: systematic review
    • Wongkoblap A, Vadillo AM, Curcin V. Researching mental health disorders in the era of social media: systematic review. J Med Internet Res. 2017;19(6):e228
    • (2017) J Med Internet Res , vol.19 , Issue.6
    • Wongkoblap, A.1    Vadillo, A.M.2    Curcin, V.3
  • 6
    • 85041040814 scopus 로고    scopus 로고
    • Accurate influenza monitoring and forecasting using novel internet data streams: a case study in the Boston Metropolis
    • Lu SF, Hou S, Baltrusaitis K, Shah M, Leskovec J, Sosic R, et al. Accurate influenza monitoring and forecasting using novel internet data streams: a case study in the Boston Metropolis. JMIR Public Health Surveill. 2018;4(1):e4
    • (2018) JMIR Public Health Surveill , vol.4 , Issue.1
    • Lu, S.F.1    Hou, S.2    Baltrusaitis, K.3    Shah, M.4    Leskovec, J.5    Sosic, R.6
  • 7
    • 85183978719 scopus 로고    scopus 로고
    • Accessed 8 May
    • Google Trends. https://trends.google.com/trends/explore. Accessed 8 May 2018
    • (2018)
    • Trends, G.1
  • 9
    • 84969262146 scopus 로고    scopus 로고
    • YES or NO: predicting the 2015 GReferendum results using Google Trends
    • Mavragani A, Tsagarakis KP. YES or NO: predicting the 2015 GReferendum results using Google Trends. Technol Forecast Soc. 2016;109:1–5
    • (2016) Technol Forecast Soc , vol.109 , pp. 1-5
    • Mavragani, A.1    Tsagarakis, K.P.2
  • 10
    • 84954599738 scopus 로고    scopus 로고
    • Seasonal trends in sleep-disordered breathing: evidence from Internet search engine query data
    • Ingram DG, Matthews CK, Plante DT. Seasonal trends in sleep-disordered breathing: evidence from Internet search engine query data. Sleep Breath. 2015;19(1):79–84
    • (2015) Sleep Breath , vol.19 , Issue.1 , pp. 79-84
    • Ingram, D.G.1    Matthews, C.K.2    Plante, D.T.3
  • 11
    • 84948980822 scopus 로고    scopus 로고
    • Forecasting the incidence of dementia and dementia-related outpatient visits with google trends: evidence from Taiwan
    • Wang HW, Chen DR, Yu HW, Chen YM. Forecasting the incidence of dementia and dementia-related outpatient visits with google trends: evidence from Taiwan. J Med Internet Res. 2015;17(11):e264
    • (2015) J Med Internet Res , vol.17 , Issue.11
    • Wang, H.W.1    Chen, D.R.2    Yu, H.W.3    Chen, Y.M.4
  • 13
    • 84890529891 scopus 로고    scopus 로고
    • Infodemiology and Infoveillance of Multiple Sclerosis in Italy
    • Bragazzi NL. Infodemiology and Infoveillance of Multiple Sclerosis in Italy. Multiple Scler Int. 2013;2013:9
    • (2013) Multiple Scler Int , vol.2013 , pp. 9
    • Bragazzi, N.L.1
  • 14
    • 84954469928 scopus 로고    scopus 로고
    • Infodemiology of status epilepticus: a systematic validation of the Google Trends-based search queries
    • Bragazzi NL, Bacigaluppi S, Robba C, Nardone R, Trinka E, Brigo F. Infodemiology of status epilepticus: a systematic validation of the Google Trends-based search queries. Epilepsy Behav. 2016;55:120–3
    • (2016) Epilepsy Behav , vol.55 , pp. 120-123
    • Bragazzi, N.L.1    Bacigaluppi, S.2    Robba, C.3    Nardone, R.4    Trinka, E.5    Brigo, F.6
  • 15
    • 79960729298 scopus 로고    scopus 로고
    • Tuberculosis surveillance by analyzing google trends
    • Zhou X, Ye J, Feng Y. Tuberculosis surveillance by analyzing google trends. IEEE Trans Biomed Eng. 2011;58(8):2247–54
    • (2011) IEEE Trans Biomed Eng , vol.58 , Issue.8 , pp. 2247-2254
    • Zhou, X.1    Ye, J.2    Feng, Y.3
  • 16
    • 84891587363 scopus 로고    scopus 로고
    • A comparison of internet search trends and sexually transmitted infection rates using google trends
    • Johnson AK, Mehta SD. A comparison of internet search trends and sexually transmitted infection rates using google trends. Sex Transm Dis. 2014;41(1):61–3
    • (2014) Sex Transm Dis , vol.41 , Issue.1 , pp. 61-63
    • Johnson, A.K.1    Mehta, S.D.2
  • 17
    • 85006802603 scopus 로고    scopus 로고
    • Disease surveillance based on Internet-based linear models: an Australian case study of previously unmodeled infection diseases
    • Rohart F, Milinovich GJ, Avril SMR, Lê Cao K-A, Tong S, Hu W. Disease surveillance based on Internet-based linear models: an Australian case study of previously unmodeled infection diseases. Sci Rep. 2016;6:38522
    • (2016) Sci Rep , vol.6 , pp. 38522
    • Rohart, F.1    Milinovich, G.J.2    Avril, S.M.R.3    Lê Cao, K.-A.4    Tong, S.5    Hu, W.6
  • 18
    • 85047276389 scopus 로고    scopus 로고
    • Forecasting AIDS prevalence in the united states using online search traffic data
    • Mavragani A, Ochoa G. Forecasting AIDS prevalence in the united states using online search traffic data. J Big Data. 2018;5:17
    • (2018) J Big Data , vol.5 , pp. 17
    • Mavragani, A.1    Ochoa, G.2
  • 19
    • 85047259083 scopus 로고    scopus 로고
    • The internet and the anti-vaccine movement: tracking the 2017 EU measles outbreak
    • Mavragani A, Ochoa G. The internet and the anti-vaccine movement: tracking the 2017 EU measles outbreak. Big Data Cog Comput. 2018;2(1):2
    • (2018) Big Data Cog Comput , vol.2 , Issue.1 , pp. 2
    • Mavragani, A.1    Ochoa, G.2
  • 20
    • 84962424457 scopus 로고    scopus 로고
    • Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes
    • Alicino C, Bragazzi NL, Faccio V, Amicizia D, Panatto D, Gasparini R, et al. Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes. Infect Dis Poverty. 2015;4(1):54
    • (2015) Infect Dis Poverty , vol.4 , Issue.1 , pp. 54
    • Alicino, C.1    Bragazzi, N.L.2    Faccio, V.3    Amicizia, D.4    Panatto, D.5    Gasparini, R.6
  • 22
    • 84983631311 scopus 로고    scopus 로고
    • Risk of MERS importation and onward transmission: a systematic review and analysis of cases reported to WHO
    • Poletto C, Bolle PY, Colizza V. Risk of MERS importation and onward transmission: a systematic review and analysis of cases reported to WHO. BMC Infect Dis. 2016;16(1):448
    • (2016) BMC Infect Dis , vol.16 , Issue.1 , pp. 448
    • Poletto, C.1    Bolle, P.Y.2    Colizza, V.3
  • 23
    • 85042123421 scopus 로고    scopus 로고
    • Associations of topics of discussion on twitter with survey measures of attitudes, knowledge, and behaviors related to Zika: probabilistic study in the United States
    • Farhadloo M, Winneg K, Chan MPS, Albarracin D. Associations of topics of discussion on twitter with survey measures of attitudes, knowledge, and behaviors related to Zika: probabilistic study in the United States. JMIR Public Health Surveill. 2018;4(1):e16
    • (2018) JMIR Public Health Surveill , vol.4 , Issue.1
    • Farhadloo, M.1    Winneg, K.2    Chan, M.P.S.3    Albarracin, D.4
  • 24
    • 84989912096 scopus 로고    scopus 로고
    • Utilizing nontraditional data sources for near real-time estimation of transmission dynamics during the 2015–2016 Colombian Zika virus disease outbreak
    • Majumder SM, Santillana M, Mekaru RS, McGinnis PD, Khan K, Brownstein SJ. Utilizing nontraditional data sources for near real-time estimation of transmission dynamics during the 2015–2016 Colombian Zika virus disease outbreak. JMIR Public Health Surveill. 2016;2(1):e30
    • (2016) JMIR Public Health Surveill , vol.2 , Issue.1
    • Majumder, S.M.1    Santillana, M.2    Mekaru, R.S.3    McGinnis, P.D.4    Khan, K.5    Brownstein, S.J.6
  • 25
    • 84995611289 scopus 로고    scopus 로고
    • The impact of heterogeneity and awareness in modeling epidemic spreading on multiplex networks
    • Scatà M, Di Stefano A, Liò P, La Corte A. The impact of heterogeneity and awareness in modeling epidemic spreading on multiplex networks. Sci Rep. 2016;6:37105
    • (2016) Sci Rep , vol.6 , pp. 37105
    • Scatà, M.1    Di Stefano, A.2    Liò, P.3    La Corte, A.4
  • 26
    • 84947998511 scopus 로고    scopus 로고
    • Accurate estimation of influenza epidemics using Google search data via ARGO
    • Yang S, Santillana M, Kou SC. Accurate estimation of influenza epidemics using Google search data via ARGO. Proc Natl Acad Sci. 2015;112(47):14473
    • (2015) Proc Natl Acad Sci , vol.112 , Issue.47 , pp. 14473
    • Yang, S.1    Santillana, M.2    Kou, S.C.3
  • 27
    • 84872867329 scopus 로고    scopus 로고
    • Using Google Trends for influenza surveillance in South China
    • Kang M, Zhong H, He J, Rutherford S, Yang F. Using Google Trends for influenza surveillance in South China. PLoS ONE. 2013;8(1):e55205
    • (2013) PLoS ONE. , vol.8 , Issue.1
    • Kang, M.1    Zhong, H.2    He, J.3    Rutherford, S.4    Yang, F.5
  • 28
    • 84943642162 scopus 로고    scopus 로고
    • Age-related differences in the accuracy of web query-based predictions of Influenza-Like Illness
    • Domnich A, Panatto D, Signori A, Lai PL, Gasparini R, Amicizia D. Age-related differences in the accuracy of web query-based predictions of Influenza-Like Illness. PLoS ONE. 2015;10(5):e0127754
    • (2015) PLoS ONE. , vol.10 , Issue.5
    • Domnich, A.1    Panatto, D.2    Signori, A.3    Lai, P.L.4    Gasparini, R.5    Amicizia, D.6
  • 29
    • 85009253242 scopus 로고    scopus 로고
    • How often people google for vaccination: qualitative and quantitative insights from a systematic search of the web-based activities using Google Trends
    • Bragazzi NL, Barberis I, Rosselli R, Gianfredi V, Nucci D, Moretti M, et al. How often people google for vaccination: qualitative and quantitative insights from a systematic search of the web-based activities using Google Trends. Hum Vaccines Immunotherap. 2017;13(2):464–9
    • (2017) Hum Vaccines Immunotherap. , vol.13 , Issue.2 , pp. 464-469
    • Bragazzi, N.L.1    Barberis, I.2    Rosselli, R.3    Gianfredi, V.4    Nucci, D.5    Moretti, M.6
  • 30
    • 85032277497 scopus 로고    scopus 로고
    • Measles, social media and surveillance in Baltimore City
    • Warren KE, Wen LS. Measles, social media and surveillance in Baltimore City. J Public Health. 2017;39(3):e73–8
    • (2017) J Public Health. , vol.39 , Issue.3 , pp. e73-e78
    • Warren, K.E.1    Wen, L.S.2
  • 32
    • 85041087721 scopus 로고    scopus 로고
    • Merchant RM relationship between state-level google online search volume and cancer incidence in the united states: retrospective study
    • Phillips CA, Barz Leahy A, Li Y, Schapira MM, Bailey LC. Merchant RM relationship between state-level google online search volume and cancer incidence in the united states: retrospective study. J Med Internet Res. 2018;20(1):e6
    • (2018) J Med Internet Res , vol.20 , Issue.1
    • Phillips, C.A.1    Barz Leahy, A.2    Li, Y.3    Schapira, M.M.4    Bailey, L.C.5
  • 34
    • 84925003431 scopus 로고    scopus 로고
    • Information seeking regarding tobacco and lung cancer: effects of seasonality
    • Zhang Z, Zheng X, Zeng DD, Leischow SJ. Information seeking regarding tobacco and lung cancer: effects of seasonality. PLoS ONE. 2015;10(3):e0117938
    • (2015) PLoS ONE. , vol.10 , Issue.3
    • Zhang, Z.1    Zheng, X.2    Zeng, D.D.3    Leischow, S.J.4
  • 35
    • 84989912361 scopus 로고    scopus 로고
    • Googling for Cancer: An Infodemiological Assessment of Online Search Interests in Australia, Canada, New Zealand, the United Kingdom, and the United States
    • Foroughi F, Lam KYA, Lim SCM, Saremi N, Ahmadvand A. Googling for Cancer: An Infodemiological Assessment of Online Search Interests in Australia, Canada, New Zealand, the United Kingdom, and the United States. JMIR Cancer. 2016;2(1):e5
    • (2016) JMIR Cancer. , vol.2 , Issue.1
    • Foroughi, F.1    Lam, K.Y.A.2    Lim, S.C.M.3    Saremi, N.4    Ahmadvand, A.5
  • 37
    • 84960158428 scopus 로고    scopus 로고
    • Tracking search engine queries for suicide in the United Kingdom, 2004–2013
    • Arora VS, Stuckler D, McKee M. Tracking search engine queries for suicide in the United Kingdom, 2004–2013. Public Health. 2016;137:147–53
    • (2016) Public Health. , vol.137 , pp. 147-153
    • Arora, V.S.1    Stuckler, D.2    McKee, M.3
  • 38
    • 84938749563 scopus 로고    scopus 로고
    • ®: ready for real-time suicide prevention or just a Zeta-Jones effect? An exploratory study
    • ®: ready for real-time suicide prevention or just a Zeta-Jones effect? An exploratory study. Psychiatry Res. 2015;228(3):913–7
    • (2015) Psychiatry Res , vol.228 , Issue.3 , pp. 913-917
    • Fond, G.1    Gaman, A.2    Brunel, L.3    Haffen, E.4    Llorca, P.M.5
  • 39
    • 85011333549 scopus 로고    scopus 로고
    • Forecasting state-level premature deaths from alcohol, drugs, and suicides using Google Trends data
    • Parker J, Cuthbertson C, Loveridge S, Skidmore M, Dyar W. Forecasting state-level premature deaths from alcohol, drugs, and suicides using Google Trends data. J Affect Disord. 2017;213:9–15
    • (2017) J Affect Disord , vol.213 , pp. 9-15
    • Parker, J.1    Cuthbertson, C.2    Loveridge, S.3    Skidmore, M.4    Dyar, W.5
  • 40
    • 85003422192 scopus 로고    scopus 로고
    • Quantifying the UK online interest in substances of the EU watch list for water monitoring: diclofenac, estradiol, and the macrolide antibiotics
    • Mavragani A, Sypsa K, Sampri A, Tsagarakis KP. Quantifying the UK online interest in substances of the EU watch list for water monitoring: diclofenac, estradiol, and the macrolide antibiotics. Water. 2016;8(11):542
    • (2016) Water , vol.8 , Issue.11 , pp. 542
    • Mavragani, A.1    Sypsa, K.2    Sampri, A.3    Tsagarakis, K.P.4
  • 41
    • 79952115109 scopus 로고    scopus 로고
    • Using search engine query data to track pharmaceutical utilization: a study of statins
    • Schuster NM, Rogers MA, McMahon LF Jr. Using search engine query data to track pharmaceutical utilization: a study of statins. Am J Manag Care. 2010;16(8):e215–9
    • (2010) Am J Manag Care , vol.16 , Issue.8 , pp. e215-e219
    • Schuster, N.M.1    Rogers, M.A.2    McMahon, L.F.3
  • 42
    • 84947019745 scopus 로고    scopus 로고
    • Linking annual prescription volume of antidepressants to corresponding web search query data: a possible proxy for medical prescription behavior?
    • Gahr M, Uzelac Z, Zeiss R, Connemann BJ, Lang D, Schönfeldt-Lecuona C. Linking annual prescription volume of antidepressants to corresponding web search query data: a possible proxy for medical prescription behavior? J Clin Psychopharmacol. 2015;35(6):681–5
    • (2015) J Clin Psychopharmacol , vol.35 , Issue.6 , pp. 681-685
    • Gahr, M.1    Uzelac, Z.2    Zeiss, R.3    Connemann, B.J.4    Lang, D.5    Schönfeldt-Lecuona, C.6
  • 43
    • 84989966226 scopus 로고    scopus 로고
    • Tracking dabbing using search query surveillance: A case study in the United States
    • Zhang Z, Zheng X, Zeng DD, Leischow SJ. Tracking dabbing using search query surveillance: A case study in the United States. J Med Internet Res. 2016. 10.2196/jmir.5802
    • (2016) J Med Internet Res
    • Zhang, Z.1    Zheng, X.2    Zeng, D.D.3    Leischow, S.J.4
  • 44
    • 84928945101 scopus 로고    scopus 로고
    • Internet search and Krokodil in the Russian Federation: an infoveillance study
    • Zheluk A, Quinn C, Meylakhs P. Internet search and Krokodil in the Russian Federation: an infoveillance study. J Med Internet Res. 2014. 10.2196/jmir.3203
    • (2014) J Med Internet Res
    • Zheluk, A.1    Quinn, C.2    Meylakhs, P.3
  • 45
    • 85052846953 scopus 로고    scopus 로고
    • Accessed 1 June 2018
    • Centers for Disease Control and Prevention. National notifiable diseases surveillance system (NNDSS). About notifiable infectious diseases and conditions data. https://wwwn.cdc.gov/nndss/infectious.html. Accessed 1 June 2018
    • About Notifiable Infectious Diseases and Conditions Data
  • 46
    • 85184013361 scopus 로고    scopus 로고
    • National notifiable diseases surveillance system (NNDSS)
    • Accessed 1 June
    • Centers for Disease Control and Prevention. National notifiable diseases surveillance system (NNDSS). surveillance case definitions. https://wwwn.cdc.gov/nndss/case-definitions.html. Accessed 1 June 2018
    • (2018) Surveillance Case Definitions
  • 47
    • 85052884379 scopus 로고    scopus 로고
    • Accessed 1 June
    • Centers for Disease Control and Prevention. Sexually transmitted diseases (STDs). Chlamydia. Available at: https://www.cdc.gov/std/stats16/chlamydia.htm. Accessed 1 June 2018
    • (2018) Sexually Transmitted Diseases (Stds). Chlamydia
  • 48
    • 85052884379 scopus 로고    scopus 로고
    • Accessed 1 June
    • Centers for Disease Control and Prevention. Sexually transmitted diseases (STDs). Gonorrhea. https://www.cdc.gov/std/gonorrhea/stdfact-gonorrhea.htm. Accessed 1 June 2018
    • (2018) Sexually Transmitted Diseases (Stds). Gonorrhea
  • 49
    • 85052884379 scopus 로고    scopus 로고
    • Accessed 1 June
    • Centers for Disease Control and Prevention. Sexually transmitted diseases (STDs). Syphilis. https://www.cdc.gov/std/syphilis/stdfact-syphilis-detailed.htm. Accessed 1 June 2018
    • (2018) Sexually Transmitted Diseases (Stds). Syphilis
  • 51
    • 85052875637 scopus 로고    scopus 로고
    • Accessed 1 June
    • Centers for Disease Control and Prevention. Viral Hepatitis. https://www.cdc.gov/hepatitis/index.htm. Accessed 1 June 2018
    • (2018) Viral Hepatitis
  • 52
    • 85184003652 scopus 로고    scopus 로고
    • Accessed 22 May
    • Google Trends. How data is adjusted. https://support.google.com/trends/answer/4365533?hl=en. Accessed 22 May 2018
    • (2018) Google Trends. How Data is Adjusted
  • 53
    • 85184011608 scopus 로고    scopus 로고
    • Centers for Disease Control and Prevention. NCHHSTP Atlas Plus, Accessed 8 May
    • Centers for Disease Control and Prevention. NCHHSTP Atlas Plus. https://www.cdc.gov/nchhstp/atlas/index.htm. Accessed 8 May 2018
    • (2018)
  • 54
    • 85052875637 scopus 로고    scopus 로고
    • Accessed 30 May
    • Centers for Disease Control and Prevention. Viral hepatitis. https://www.cdc.gov/hepatitis/outbreaks/2016/hav-hawaii.htm. Accessed 30 May 2018
    • (2018) Viral Hepatitis
  • 55
    • 85020316091 scopus 로고    scopus 로고
    • Is Google Trends a reliable tool for digital epidemiology? Insights from different clinical settings
    • Cervellin G, Comelli I, Lippi G. Is Google Trends a reliable tool for digital epidemiology? Insights from different clinical settings. J Epidemiol Global Health. 2017;7:185–9
    • (2017) J Epidemiol Global Health , vol.7 , pp. 185-189
    • Cervellin, G.1    Comelli, I.2    Lippi, G.3
  • 56
    • 84896056107 scopus 로고    scopus 로고
    • Big data. The parable of Google Flu: traps in big data analysis
    • Lazer D, Kennedy R, King G, Vespignani A. Big data. The parable of Google Flu: traps in big data analysis. Science. 2017;343(6176):1203–5
    • (2017) Science , vol.343 , Issue.6176 , pp. 1203-1205
    • Lazer, D.1    Kennedy, R.2    King, G.3    Vespignani, A.4
  • 57
    • 85183956484 scopus 로고    scopus 로고
    • Accessed 8 Aug
    • Google Flu Trends. https://www.google.org/flutrends/about/. Accessed 8 Aug 2018
    • (2018) Google Flu Trends


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.