Page 118 - Timeliness of Infectious Disease Notification & Response Systems - Corien Swaan

116 Chapter 5
patients were retrospectively diagnosed with extreme delay.
Alerts regarding pandemic influenza A(H1N1) were not included as the dis- ease was only temporarily notifiable and no comparison with delays before and
after the outbreak could be made.
Software
Delays were analysed using SPSS (version 24). For statistical analyses of delays across periods, R (version 3.5.1) was used.
Ethical statement
In accordance with Dutch law, no informed consent was required for this study using anonymised routine surveillance data.
Results
In total, 144,066 notifications of 28 different infectious diseases were included: 50,541 in period 1, 47,163 in period 2 and 46,362 in period 3. Numbers of in- cluded notifications per disease per period, numbers of cases for which delays could be calculated, median disease identification delay D1X, notification delay D3 and reporting delay D6, per disease and for all cases are displayed for each period in Table 1. As the MHS did not provide all dates for every case, Table 1 shows only cases that had dates available to calculate the delay. For all three delays, the medians for all cases together decreased over time (D1X from 29 to 23 days, D3 from 2 to 0 days, D6 from 1 to 0 days). The mathematical averages of median delays of all individual diseases decreased as well, but to a lesser extent (Table 1).