Serial intervals of respiratory infectious diseases: a systematic review and analysis

Am J Epidemiol. 2014 Nov 1;180(9):865-75. doi: 10.1093/aje/kwu209. Epub 2014 Oct 7.


The serial interval of an infectious disease represents the duration between symptom onset of a primary case and symptom onset of its secondary cases. A good evidence base for such values is essential, because they allow investigators to identify epidemiologic links between cases and serve as an important parameter in epidemic transmission models used to design infection control strategies. We reviewed the literature for available data sets containing serial intervals and for reported values of serial intervals. We were able to collect data on outbreaks within households, which we reanalyzed to infer a mean serial interval using a common statistical method. We estimated the mean serial intervals for influenza A(H3N2) (2.2 days), pandemic influenza A(H1N1)pdm09 (2.8 days), respiratory syncytial virus (7.5 days), measles (11.7 days), varicella (14.0 days), smallpox (17.7 days), mumps (18.0 days), rubella (18.3 days), and pertussis (22.8 days). For varicella, we found an evidence-based value that deviates substantially from the 21 days commonly used in transmission models. This value of the serial interval for pertussis is, to the best of our knowledge, the first that is based on observations. Our review reveals that, for most infectious diseases, there is very limited evidence to support the serial intervals that are often cited.

Keywords: generation interval; generation time; respiratory infectious diseases; serial interval.

Publication types

  • Meta-Analysis
  • Review
  • Systematic Review

MeSH terms

  • Disease Outbreaks*
  • Family Characteristics
  • Humans
  • Influenza, Human / epidemiology
  • Models, Statistical*
  • Respiratory Syncytial Virus Infections / epidemiology
  • Respiratory Tract Infections / epidemiology*
  • Respiratory Tract Infections / transmission
  • Severe Acute Respiratory Syndrome / epidemiology
  • Virus Diseases / epidemiology