Comparing methods for early detection systems for seasonal and pandemic influenza

Almuqrin, Muqrin and Robertson, Chris and Gray, Alison (2017) Comparing methods for early detection systems for seasonal and pandemic influenza. In: Royal Statistical Society Conference 2017, 2017-09-04 - 2017-09-07.

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Abstract

The aim of this work is to investigate established methods for early detection of seasonal and pandemic influenza, then to develop a new method for routine use. We investigate daily data for influenza-like illness (ILI) General Practice (GP) consultations, collected from all 14 spatially located Health Boards (HBs) in Scotland. We use these real data to generalise their applicability to any number of geographic areas. The National Health Service (NHS) provided data on ILI consultation data from 2009 to 2015. Our work is extending the Weekly Cases Ratio (WCR) method to develop an automatic system to raise an alarm when there is a sudden increase in ILI cases. The WCR method uses two terms: 1) the value of WCR, defined in week w as WCR(w)=ILI GP consultation rate in week w divided by the corresponding rate in week w-1, and 2) the number of health boards N(HB) which report an increase in ILI cases in week w compared to week w-1 (i.e. WCR(w)>1). We initially used the above Scottish data, then extended this to more than 14 HBs, by simulating data with similar structure but from a different number of HBs. We used a constant rate of consultations to determine a joint null distribution for (WCR, N(HB)) to use in a hypothesis testing approach to detect a rise in ILI cases. Using more than 3 million simulations of each data set, we found a relationship in all cases between WCR and N(HB), then modelled the relationship between each of the mean (µ) and standard deviation (σ) of WCR with N(HB) in each dataset to find a general equation for use with any number of HBs. Further work will compare our approach with the Moving Epidemic and Cumulative Sum methods. Some results of this work will be presented.