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Volume 21, Number 2—February 2015
Research

Quantifying Reporting Timeliness to Improve Outbreak Control

Axel Bonačić MarinovićComments to Author , Corien Swaan, Jim van Steenbergen, and Mirjam Kretzschmar
Author affiliations: National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands (A. Bonačić Marinović, C. Swaan, J. van Steenbergen, M. Kretzschmar); University Medical Centre Utrecht, Utrecht, the Netherlands (A. Bonačić Marinović, M. Kretzschmar); Leiden University Medical Centre, Leiden, the Netherlands (J. van Steenbergen)

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Table 1

Parameters for reporting delay models, by disease*

Disease Serial interval distribution, median days (SD) Symptom onset distribution, median days (SD) Reporting delay distribution, median days (SD) Reproduction number, R (range)† References
Hepatitis A 27.5 (4) 28 (9) 8.6 (11.9) 3.33 (3–4) (7–10)
Hepatitis B 47.5 (20) 80 (35) 14.7 (24.3) 1.75 (1–2.5) (7–9,11)
Measles 11.6 (2.4) 11.5 (2.5) 9.0 (12) 8 (8–30) (7–10,12)
Mumps 19.1 (5.4) 19.5 (2.3) 9.0 (13.8) 5.5 (4–7) (7–10)
Pertussis 16 (13) 9 (2.5) 40.8 (24.4) 5.5 (5–6.5) (7–10,13,14)
Shigellosis‡ 5 (3.5) 2.5 (1.5) 14.6 (13.8) 3.5 (2–5) (7–9)

*All distributions are fitted to log-normal distributions with medians and standard deviations as indicated. Reporting delay distribution of pertussis is an exception, which is fitted to a gamma distribution.
†The reproduction numbers are those used for outbreak control calculations, and the ranges in brackets are those found in the literature.
‡For shigellosis, an average transmission period (serial interval distribution) of 1 wk (median 5 d) was assumed, although in practice shedding continues after that.

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References
  1. Jajosky  RA, Groseclose  S. Evaluation of reporting timeliness of public health surveillance systems for infectious diseases. BMC Public Health. 2004;4:29. DOIPubMedGoogle Scholar
  2. Yoo  H-S, Park  O, Park  H-K, Lee  E-G, Jeong  E-K, Lee  J-K, Timeliness of national notifiable diseases surveillance system in Korea: a cross-sectional study. BMC Public Health. 2009;9:93. DOIPubMedGoogle Scholar
  3. Reijn  E, Swaan  CM, Kretzschmar  ME, van Steenbergen  JE. Analysis of timeliness of infectious disease reporting in the Netherlands. BMC Public Health. 2011;11:409. DOIPubMedGoogle Scholar
  4. Bogaards  JA, Putter  H, Jan Weverling  G, ter Meulen  J, Goudsmit  J. The potential of targeted antibody prophylaxis in SARS outbreak control: a mathematic analysis. Travel Med Infect Dis. 2007;5:70–8. DOIPubMedGoogle Scholar
  5. Yoo  HS, Cho  SI, Lee  JK, Park  HK, Lee  EG, Kwon  JW. A new surveillance indicator identifying optimal timeliness and accuracy: application to the Korean National Notifiable Disease Surveillance System for 2001–2007. Epidemiol Infect. 2013;141:2634–43. DOIPubMedGoogle Scholar
  6. Fraser  C, Riley  S, Anderson  RM, Ferguson  NM. Factors that make an infectious disease outbreak controllable. Proc Natl Acad Sci U S A. 2004;101:6146–51. DOIPubMedGoogle Scholar
  7. Richardson  M, Elliman  D, Maguire  H, Simpson  J, Nicoll  A. Evidence base of incubation periods, periods of infectiousness and exclusion policies for the control of communicable diseases in schools and preschools. Pediatr Infect Dis J. 2001;20:380–91. DOIPubMedGoogle Scholar
  8. Heymann  DL, Association  APH. Control of communicable diseases manual. Washington (DC): American Public Health Association; 2008.
  9. National Institute for Public Health and the Environment (RIVM). Guidelines for infectious diseases, 2010. Bilthoven (the Netherlands): The Institute; 2010.
  10. Vink  MA, Bootsma  MCJ, Wallinga  J. Serial intervals of respiratory infectious diseases: a systemic review and analysis. Am J Epidemiol. 2014;180:865–75 .DOIPubMedGoogle Scholar
  11. Ganem  D, Prince  AM. Hepatitis B virus infection—natural history and clinical consequences. N Engl J Med. 2004;350:1118–29. DOIPubMedGoogle Scholar
  12. Klinkenberg  D, Nishiura  H. The correlation between infectivity and incubation period of measles, estimated from households with two cases. J Theor Biol. 2011;284:52–60. DOIPubMedGoogle Scholar
  13. Stocks  P. Some epidemiological features of whooping-cough: a statistical investigation. Lancet. 1933;221:265–9. DOIGoogle Scholar
  14. Kretzschmar  M, Teunis  PFM, Pebody  RG. Incidence and reproduction numbers of pertussis: estimates from serological and social contact data in five European countries. PLoS Med. 2010;7:e1000291. DOIPubMedGoogle Scholar
  15. Wallinga  J, Lipsitch  M. How generation intervals shape the relationship between growth rates and reproductive numbers. Proc Biol Sci. 2007;274:599–604. DOIPubMedGoogle Scholar
  16. Anderson  RM, May  RM. Infectious diseases of humans: dynamics and control. New York: Oxford University Press, Inc. 1991.
  17. Diekmann  O, Heesterbeek  JAP. Mathematical epidemiology of infectious diseases: model building, analysis, and interpretation. Hoboken (NJ): John Wiley and Sons; 2000.
  18. Fine  PEM. The interval between successive cases of an infectious disease. Am J Epidemiol. 2003;158:1039–47. DOIPubMedGoogle Scholar
  19. Meynell  GG, Meynell  EW. The growth of micro-organisms in vivo with particular reference to the relation between dose and latent period. J Hyg (Lond). 1958;56:323–46. DOIPubMedGoogle Scholar

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Page updated: January 20, 2015
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