Readings

An improved cumulative sum-based procedure for prospective disease surveillance for count data in multiple regions

Dassanayake, S., & French, J. P. (2016). An improved cumulative sum-based procedure for prospective disease surveillance for count data in multiple regions. Statistics in Medicine. https://doi.org/10.1002/sim.6887

  • Cumulative counts are created from neighbouring areas for monitoring/detecting diseases outbreaks
  • prospective surveillance
    • decisions made at regular intervals about incidence, c.f. analysing the whole dataset retrospectively
    • so possible multiple comparisons issues?
  • For CUSUM-based methods, the in-control distribution can be estimated via bootstrap
    • p-values for exceeding CUSUM threshold can then be calculated
    • why p-values?
    • is this another case for going Bayesian to get posterior probabilities
  • Provides discussion on standard Poisson CUSUM
    • parameters controlling the process are calculated via average run length (ARL)
    • ARL: desired average time between two false alarms when the process is \‘in control\’
    • this seems to be a difficult concept to set a limit for
  • spatial CUSUM modifies counts and control parameters by a weighted average of all counts
    • weights are based on the distance between areas
  • Justification for the procedure is that p-values are preferred over test statistics
    • why? surely there\’s a one-to-one correspondence?
    • false discovery rate is used for error control
      • this seems fine, but I\’m not sure I understand the procedure fully
      • FDR = 1 - PPV, which makes that point a bit clearer
  • In the application, the authors use the first two years of data to estimate the in-control distribution
    • this is because \‘… there were no unusually high disease counts reported from any of the states during this period\’
    • this is clearly problematic: is this the eyeball test
    • the results will clearly depend on this choice, so a sensitivity analysis would be important
  • I found this somewhat difficult to read overall
    • this could be due to my lack of knowledge in the area though!