Figure 1.

Deriving multiplication factors from the morbidity surveillance pyramid. A: The morbidity surveillance pyramid is often used to illustrate the availability of morbidity data at each surveillance level. With each ascending level (from the community, to healthcare institutions (GPs, hospital, laboratory), to regional and national public health agencies); data availability shrinks and only a fraction of cases from the level below is captured [7-9]. In contrast to the narrow tip of the pyramid which represents data held by national public health agencies, the base is wide as it holds all infections in the community. The difference between the number at the tip and base can be considered cases lost to 'underestimation’ (UE). B: The proportions of infections that are symptomatic, that attend healthcare, and that are reported are represented in this decision tree model. Here, only 55% of all infected individuals attending healthcare are reported through the notification system. If 1000 cases were reported then a MF of 1.8 (=100/55) could be derived and would correct for those underreported cases. The true number attending healthcare would be 1800 cases. Likewise, if only 60% of symptomatic cases attended healthcare, then a MF of 1.7 (=100/60) would correct for under-ascertainment of symptomatic cases. The true number of cases attending healthcare would be 3000 symptomatic cases (=1.7*1800). Finally, since 90% of infections were symptomatic, a MF of 1.1 (=100/90) would correct for under-ascertainment of asymptomatic cases. The true number of infections would be 3300 (=1.1*3000). A MF to correct for total underestimation of symptomatic cases in one step would be 3.06 (=1.8*1.7) and for all infections 3.4 (=1.8*1.7*1.1). 'All infections’ shaded in orange in Figure  1A represents the same population as the orange box in Figure  1B. 'Cases reported’ in blue in Figure  1A represents the same population as the blue box in Figure  1B.

Gibbons et al. BMC Public Health 2014 14:147   doi:10.1186/1471-2458-14-147
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