Public Health Surveillance Systems: Recent Advances in Their Use and Evaluation

Annual Review of Public Health

Volumn 38, Issue , 2017, Pages 57-79

  Groseclose, Samuel L ^a   Buckeridge, David L ^b  

^a CENTERS FOR DISEASE CONTROL AND PREVENTION   (United States)

^b MCGILL UNIVERSITY   (Canada)

Author keywords

Public health surveillance; Public health surveillance systems; Surveillance evaluation; Surveillance indicators; Surveillance objectives; Surveillance system monitoring

Indexed keywords

CASE STUDY; DATA ANALYSIS; DATA PROCESSING; HEALTH SURVEY; HUMAN; MEDICAL INFORMATICS; MEDICAL RESEARCH; NONHUMAN; PRIORITY JOURNAL; PUBLIC HEALTH; PUBLIC HEALTH SERVICE; REVIEW; SYSTEMATIC REVIEW (TOPIC); FORECASTING;

FORECASTING; HUMANS; POPULATION SURVEILLANCE; PUBLIC HEALTH;

EID: 85017174189     PISSN: 01637525     EISSN: 15452093     Source Type: Book Series    
DOI: 10.1146/annurev-publhealth-031816-044348     Document Type: Review

References (90)

1. Althouse BM, Ng YY, Cummings DAT. 2011. Prediction of dengue incidence using search query surveillance. PLOS Negl. Trop. Dis. 5:e1258
2. Althouse BM, Scarpino SV, Meyers LA, Ayers JW, Bargsten M, et al. 2015. Enhancing disease surveillance with novel data streams: challenges and opportunities. EPJ Data Sci. 4:17. https://doi.org/ 10.1140/epjds/s13688-015-0054-0
3. Anderson BD, Ma M, Xia Y, Wang T, Shu B, et al. 2016. Bioaerosol sampling in modern agriculture: a novel approach for emerging pathogen surveillance? J. Infect. Dis. 214:537-45. https://doi.org/ 10.1093/infdis/jiw180
4. Bajardi P, Vespignani A, Funk S, Eames KT, Edmunds WJ, et al. 2014. Determinants of follow-up participation in the Internet-based European influenza surveillance platform Influenzanet. J. Med. Internet Res. 16:e78. https://doi.org/10.2196/jmir.3010
5. Baker MA, Nguyen M, Cole DV, Lee GM, Lieu TA. 2013. Post-licensure rapid immunization safety monitoring program (PRISM) data characterization. Vaccine 31(Suppl):K98-112
6. Bednarczyk RA, OrensteinWA, Omer SB. 2016. Estimating the number of measles-susceptible children and adolescents in the United States using data from the National Immunization Survey-Teen (NISTeen). Am. J. Epidemiol. 184:148-56. https://doi.org/10.1093/aje/kwv320
7. Bernstein JA, Friedman C, Jacobson P, Rubin JC. 2015. Ensuring public health's future in a national-scale learning health system. Am. J. Prev. Med. 48: 480-87
8. Biggerstaff M, Alper D, Dredze M, Fox S, Fung IC, et al. 2016. Results from the Centers for Disease Control and Prevention's Predict the 2013-2014 Influenza Season Challenge. BMC Infect. Dis. 16:357. https://doi.org/10.1186/s12879-016-1669-x
9. Birkhead GS, Klompas M, Shah NR. 2015. Uses of electronic health records for public health surveillance to advance public health. Annu. Rev. Public Health 36: 345-59
10. BlondinKJ, GilesCM, Cradock AL, Gortmaker SL, LongMW.2016. US state childhood obesity surveillance practices and recommendations for improving them, 2014-2015. Prev. Chronic Dis. 13:160060. https://doi.org/10.5888/pcd13.160060
11. Bowen MD, Mijatovic-Rustempasic S, Esona MD, Teel EN, Gautam R, et al. 2016. Rotavirus strain trends during the postlicensure vaccine era: United States, 2008-2013. J. Infect. Dis. 214:732-38. https://doi.org/10.1093/infdis/jiw233
12. Broniatowski DA, Paul MJ, Dredze M. 2013. National and local influenza surveillance through Twitter: an analysis of the 2012-2013 influenza epidemic. PLOS ONE 8:e83672. https://doi.org/ 10.1371/journal.pone.0083672
13. Brownson RC, Fielding JE, Maylahn CM. 2009. Evidence-based public health: a fundamental concept for public health practice. Annu. Rev. Public Health 30:175-201
14. Buckeridge DL. 2007. Outbreak detection through automated surveillance: a review of the determinants of detection. J. Biomed. Inform. 40:370-79
15. Buckeridge DL, Burkom H, Campbell M, HoganWR, Moore AW. 2005. Algorithms for rapid outbreak detection: a research synthesis. J. Biomed. Inform. 38:99-113
16. Buckeridge DL, Charland K, Labban A, Ma Y. 2014. A method for neighborhood-level surveillance of food purchasing. Ann. N. Y. Acad. Sci. 1331:270-77. https://doi.org/10.1111/nyas.12332
17. Buckeridge DL, OwensDK, Switzer P, Frank J, MusenMA. 2006. Evaluating detection of an inhalational anthrax outbreak. Emerg. Infect. Dis. 12:1942-49
18. Burris S, Hitchcock L, Ibrahim J, PennM, Ramanathan T. 2016. Policy surveillance: a vital public health practice comes of age. J. Health Polit. Policy Law. In press. https://doi.org/10.1215/03616878-3665931
19. Cadieux G, Buckeridge DL, Jacques A, Libman M, Dendukuri N, Tamblyn R. 2012. Patient, physician, encounter, and billing characteristics predict the accuracy of syndromic surveillance case definitions. BMC Public Health 12:166
20. Carroll LN, Au AP, Detwiler LT, Fu T, Painter IS, Abernethy NF. 2014. Visualization and analytics tools for infectious disease epidemiology: a systemic review. J. Biomed. Inform. 51:287-98
21. CDC (Cent. Dis. Control Prev). 2001. Updated guidelines for evaluating public health surveillance systems: recommendations from the guidelines working group. Morb. Mortal. Wkly. Rep. Recomm. Rep. 50( 13):1-35
22. Chapman WW, Dowling JN, Wagner MM. 2005. Classification of emergency department chief complaints into 7 syndromes: a retrospective analysis of 527, 228 patients. Ann. Emerg. Med. 46:445-55
23. Chriqui JF, O'Connor JC, Chaloupka FJ. 2011. What gets measured, gets changed: evaluating law and policy for maximum impact. J. Law Med. Ethics 39(Suppl. 1):21-26
24. Condell O, Midgley S, Christiansen CB, Chen M, Chen Nielsen X, et al. 2016. Evaluation of the enterovirus laboratory surveillance system in Denmark, 2010 to 2013. Euro Surveill. 21(18):30218. https://doi.org/10.2807/1560-7917.ES.2016.21.18.30218
25. Doyle TJ, Ma H, Groseclose SL, Hopkins RS. 2005. PHSkb: a knowledgebase to support notifiable disease surveillance. BMC Med. Inform. Decis. Mak. 5:27
26. Drewe JA, Hoinville LJ, Cook AJC, Floyd T, Stark KDC. 2012. Evaluation of animal and public health surveillance systems: a systematic review. Epidemiol. Infect. 140:575-90
27. Eur. Cent. Dis. Prev. Control. 2014. Data Quality Monitoring and Surveillance System Evaluation: A Handbook of Methods and Applications. Stockholm, Swed.: Eur. Cent. Dis. Prev. Control. http://ecdc.europa. eu/en/publications/publications/data-quality-monitoring-surveillance-system-evaluation-sept-2014.pdf
28. Foege WH, Hogan RC, Newton LH. 1976. Surveillance projects for selected diseases. Int. J. Epidemiol. 5(1):29-37
29. Freifeld CC, Mandl KD, Reis BY, Brownstein JS. 2008. HealthMap: global infectious disease monitoring through automated classification and visualization of Internet media reports. J. Am. Med. Inform. Assoc. 15:150-57
30. Friede A, Blum HL, McDonald M. 1995. Public health informatics: how information-age technology can strengthen public health. Annu. Rev. Public Health 16:239-52
31. Groseclose SL, German RR, Nsubuga P. 2010. Evaluating public health surveillance. In Principles and Practice of Public Health Surveillance, ed. LM Lee, SM Teutsch, ME St. Louis, SB Thacker, pp. 166-197. New York: Oxford Univ. Press. 3rd ed
32. Hall HI, Mokotoff ED. 2007. Setting standards and an evaluation framework for human immunodeficiency virus/acquired immunodeficiency syndrome surveillance. J. Public Health Manag. Pract. 13:519-23
33. Hall HI, Song R, Gerstle JE, Lee LM. 2006. Assessing the completeness of reporting of human immunodeficiency virus diagnoses in 2002-2003: capture-recapture methods. Am. J. Epidemiol. 164:391-97
34. Harris JK, Mansour R, Choucair B, Olson J, Nissen C, Bhatt J. 2014. Health department use of social media to identify foodborne illness-Chicago, Illinois, 2013-2014. Morb. Mortal. Wkly. Rep. 63:681-85
35. Harrison C, Jorder M, Stern H, Stavinsky F, Reddy V, et al. 2014. Using online reviews by restaurant patrons to identify unreported cases of foodborne illness-New York City, 2012-2013. Morb. Mortal. Wkly. Rep. 63:441-45
36. Hemming K, Lilford R, Girling AJ. 2015. Stepped-wedge cluster randomised controlled trials: a generic framework including parallel and multiple-level designs. Stat. Med. 34:181-96. https://doi.org/ 10.1002/sim.6325
37. Hopkins RS. 2005. Design and operation of state and local infectious disease surveillance systems. J. Public Health Manag. Pract. 11:184-90
38. Hulth A, Andrews N, Ethelberg S, Dreesman J, Faensen D, et al. 2010. Practical usage of computersupported outbreak detection in five European countries. Euro Surveill. 15(36):19658
39. Inst. Med. 1988. The Future of Public Health. Washington, DC: Natl. Acad. Press. doi:10.17226/1091
40. Jim MA, Arias E, Seneca DS, Hoopes MJ, Jim CC, et al. 2014. Racial misclassification of American Indians and Alaska Natives by Indian Health Service contract health service delivery area. Am. J. Public Health 104:S295-302. https://doi.org/10.2105/AJPH.2014.301933
41. Jorm L, Gruszin S, Churches T. 2009. A multidimensional classification of public health activity in Australia. Aust. N. Z. Health Policy 6:9. https://doi.org/10.1186/1743-8462-6-9
42. Karch DL, Chen M, Tang T. 2014. Evaluation of the National Human Immunodeficiency Virus Surveillance System for the 2011 diagnosis year. J. Public Health Manag. Pract. 20:598-607
43. Kass-Hout TA, Xu Z, Mohebbi M, Nelsen H, Baker A, et al. 2016. OpenFDA: an innovative platform providing access to a wealth of FDA's publicly available data. J. Am. Med. Inform. Assoc. 23:596-600. https://doi.org/10.1093/jamia/ocv153
44. Kempf AM, Remington PL. 2007. New challenges for telephone survey research in the twenty-first century. Annu. Rev. Public Health 28:113-26
45. Kirkcaldy RD, Harvey A, Papp JR, Rio C, Soge OO, et al. 2016. Neisseria gonorrhoeae antimicrobial susceptibility surveillance\-The Gonococcal Isolate Surveillance Project, 27 sites, United States, 2014. Morb. Mortal. Wkly. Rep. Surveill. Summ. 65(7):1-19
46. Kleinman KP, Abrams AM. 2008. Assessing the utility of public health surveillance using specificity, sensitivity, and lives saved. Stat. Med. 27:4057-68
47. Kukafka R, Yasnoff WA. 2007. Public health informatics. J. Biomed. Inform. 40:365-69
48. Langley G, Schaffner W, Farley MM, Lynfield R, Bennett NM, et al. 2015. Twenty years of Active Bacterial Core surveillance. Emerg. Infect. Dis. 21:1520-28
49. Lazarus R, Klompas M, Campion FX, NcNabb SJN, Hou X, et al. 2009. Electronic support for public health: validated case finding and reporting for notifiable diseases using electronic medical data. J. Am. Med. Inform. Assoc. 16:18-24. https://doi.org/10.1197/jamia.M2848.a
50. Lewis B, Eubank S, Abrams AM, Kleinman K. 2013. In silico surveillance: evaluating outbreak detection with simulation models. BMC Med. Inform. Decis. Mak. 13:12
51. Lobb R, Colditz GA. 2013. Implementation science and its application to population health. Annu. Rev. Public Health 34:235-51
52. Ma H, Rolka H, Mandl K, Buckeridge D, Fleischauer A, Pavlin J. 2005. Implementation of laboratory order data in BioSense Early Event Detection and Situation Awareness System. Morb. Mortal. Wkly. Rep. 54(Suppl):27-30
53. Makam AN, Nguyen OK, Moore B, Ma Y, Amarasingham R. 2013. Identifying patients with diabetes and the earliest data of diagnosis in real time: an electronic health record case-finding algorithm. BMC Med. Inform. Decis. Mak. 13:81
54. McNabb SJN, Surdo AM, Redmond A, Cobb J, Wiley J, et al. 2004. Applying a new conceptual framework to evaluate tuberculosis surveillance and action performance andmeasure the costs, HillsboroughCounty, Florida, 2002. Ann. Epidemiol. 14:640-45
55. Mokdad AH. 2009. The Behavioral Risk Factor Surveillance System: past, present, and future. Annu. Rev. Public Health 30:43-54
56. Morrison KT, Shaddick G, Henderson SB, Buckeridge DL. 2016. A latent process model for forecasting multiple time series in environmental public health surveillance. Stat. Med. 35:3085-100
57. Myslín M, Zhu SH, Chapman W, Conway M. 2013. Using Twitter to examine smoking behavior and perceptions of emerging tobacco products. J. Med. Internet Res. 15(8):e174
58. Nsoesie EO, Buckeridge DL, Brownstein JS. 2014. Guess who's not coming to dinner? Evaluating online restaurant reservations for disease surveillance. J. Med. Internet Res. 16(1):e22
59. Okhmatovskaia A, Shaban-Nejad A, Lavigne M, Buckeridge DL. 2014. Addressing the challenge of encoding causal epidemiological knowledge in formal ontologies: a practical perspective. Stud. Health Technol. Inform. 205:1125-29
60. Osborne JD, Wyatt M, Westfall AO, Willig J, Bethard S, Gordon G. 2016. Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning. J. Am. Med. Inform. Assoc. In press. https://doi.org/10.1093/jamia/ocw006
61. Parton HB, Mathes R, Abdelnabi J, Alleyne L, Econome A, et al. 2016. Investigating a syndromic surveillance signal with complementary data systems. Online J. Public Health Inform. 8(1):e152
62. Patwardhan A, Bilkovski R. 2012. Comparison: flu prescription sales data from a retail pharmacy in the US with Google flu trends and US ILINet (CDC) data as flu activity indicator. PLOS ONE 7(8):e43611
63. Pinner RW, Lynfield R, Hadler JL, Schaffner W, Farley MM, et al. 2015. Cultivation of an adaptive domestic network for surveillance and evaluation of emerging infections. Emerg. Infect. Dis. 21:1499-509
64. Pollack KM, D'Angelo J, Green G, Conte S, Fealy S, et al. 2016. Developing and implementing Major League Baseball's health and injury tracking system. Am. J. Epidemiol. 183:490-96
65. Powell GE, Seifert HA, Reblin T, Burstein PJ, Blowers J, et al. 2016. Social media listening for routine post-marketing safety surveillance. Drug Saf. 39:443-54
66. Presley D, Reinstein T, Webb-Barr D, Burris S. 2015. Creating legal data for public health monitoring and evaluation: Delphi standards for policy surveillance. J. Law Med. Ethics 43:27-31
67. Prue CE, Lackey C, Swenarski L, Gantt JM. 2003. Communication monitoring: shaping CDC's emergency risk communication efforts. J. Health Commun. 8(Suppl. 1):35-49
68. Puckett M, Neri A, Rohan E, Clerkin C, Underwood JM, et al. 2016. Evaluating early case capture of pediatric cancers in seven central cancer registries in the United States, 2013. Public Health Rep. 131:126-36
69. Roush SW. 2011. Surveillance indicators. In Manual for the Surveillance of Vaccine-Preventable Diseases, ed. Cent. Dis. Control Prev. Atlanta, GA: Cent. Dis. Control Prev. 5th ed. http://www.cdc.gov/ vaccines/pubs/surv-manual/chpt18-surv-indicators.pdf
70. Sabbe M, Berger N, Blommaert A, Ogunjimi B, Grammens T, et al. 2016. Sustained low rotavirus activity and hospitalization rates in the post-vaccination era in Belgium, 2007 to 2014. Euro Surveill. 21(27):30273
71. Salathe M, Friefeld CC, Mekaru SR, Tomasulo AF, Brownstein JS. 2013. Influenza A (H7N9) and the importance of digital epidemiology. N. Engl. J. Med. 369:401-4
72. Salmon D, Yih WK, Lee G, Rosofsky R, Brown J, et al. 2012. Success of program linking data sources to monitor H1N1 vaccine safety points to potential for even broader safety surveillance. Health Aff. 31:2518-27
73. SantillanaM, Nguyen AT, DredzeM, PaulMJ, Nsoesie EO, Brownstein JS. 2015. Combining search, social media, and traditional data sources to improve influenza surveillance. PLOS Comput. Biol. 11:e1004513
74. Savard N, Bédard L, Allard R, Buckeridge DL. 2015. Using age, triage score, and disposition data from emergency department electronic records to improve Influenza-like illness surveillance. J. Am. Med. Inform. Assoc. 22:688-96
75. Shaban-Nejad A, Lavigne M, Okhmatovskaia A, Buckeridge DL. 2016. PopHR: a knowledge-based platform to support integration, analysis and visualization of population health data. Ann. N. Y. Acad. Sci. In press
76. Signorini A, Segre AM, Polgreen PM. 2011. The use of Twitter to track levels of disease activity and public concern in the U.S. during the Influenza A H1N1 pandemic. PLOS ONE 6:e19467
77. Skoog G, Struwe J, Cars O, Hangerger H, Odenholt I, et al. 2016. Repeated nationwide point-prevalence surveys for antimicrobial use in Swedish hospitals: data for actions 2003-2010. Euro Surveill. 21:30264
78. Smith GE, Elliot AJ, Ibbotson S, Morbey R, Edeghere O, et al. 2016. Novel public health risk assessment process developed to support syndromic surveillance for the 2012 Olympic and Paralympic Games. J. Public Health. In press. https://doi.org/10.1093/pubmed/fdw054
79. Smith PF, Hadler JL, StanburyM, Rolfs RT, Hopkins RS. 2013. "Blueprint Version 2.0": updating public health surveillance for the 21st century. J. Public Health Manag. Pract. 19:231-39
80. Smolinski MS, Crawley AW, Baltrusaitis K, Chunara R, Olsen JM, et al. 2015. Flu Near You: crowdsourced symptom reporting spanning 2 influenza seasons. Am. J. Public Health 105:2124-30
81. Snider CJ, Diop OM, Tangermann RH, Wassilek SGF. 2016. Surveillance systems to track progress toward polio eradication-worldwide, 2014-2015. Morb. Mortal. Wkly. Rep. 65: 346-51
82. Somda ZC, Perry HN, Messonnier NR, Djingarey MH, Ki SO, Meltzer MI. 2010. Modeling the costeffectiveness of the Integrated Disease Surveillance and Response (ISDR) system: meningitis in Burkina Faso. PLOS ONE 5(9):e13044
83. Tebbens RJD, Sangrujee N, Thompson KM. 2006. The costs of future polio risk management policies. Risk Anal. 26:1507-31
84. Thacker SB, Berkelman RL. 1988. Public health surveillance in theUnited States. Epidemiol. Rev. 10:164-90
85. Thacker SB, Berkelman RL, Stroup DF. 1989. The science of public health surveillance. J. Public Health Policy 10:187-203
86. Thoroughman DA, Frederickson D, Cameron HD, Shelby LK, Cheek JE. 2002. Racial misclassification of American Indians inOklahoma state surveillance data for sexually transmitted diseases. Am. J. Epidemiol. 155:1137-41
87. van Noort SP, Codeco CT, Koppeschaar CE, van Ranst M, Paolotti D, Gomes MG. 2015. Ten-year performance of Influenzanet: ILI time series, risks, vaccine effects, and care-seeking behaviour. Epidemics 13:28-36
88. Wong WK, Moore A, Cooper G, Wagner MM. 2003. WSARE: What's Strange About Recent Events? J. Urban Health 80(Suppl. 1):66-75
89. Yasnoff WA, O'Carroll PW, Koo D, Linkins RW, Kilbourne EM. 2000. Public health informatics: improving and transforming public health in the information age. J. Public Health Manag. Pract. 6:67-75
90. Zinszer K, Jauvin C, Verma A, Bedard L, Allard R, et al. 2010. Residential address errors in public health surveillance data: a description and analysis of the impact on geocoding. Spat. Spatiotemporal Epidemiol. 1(2-3):163-68