Improving the Health Forecasting Alert System for Cold Weather and Heat-Waves In England: A Proof-of-Concept Using Temperature-Mortality Relationships

Abstract

Objectives: In this study a prototype of a new health forecasting alert system is developed, which is aligned to the approach used in the Met Office's (MO) National Severe Weather Warning Service (NSWWS). This is in order to improve information available to responders in the health and social care system by linking temperatures more directly to risks of mortality, and developing a system more coherent with other weather alerts. The prototype is compared to the current system in the Cold Weather and Heatwave plans via a case-study approach to verify its potential advantages and shortcomings.

Method: The prototype health forecasting alert system introduces an "impact vs likelihood matrix" for the health impacts of hot and cold temperatures which is similar to those used operationally for other weather hazards as part of the NSWWS. The impact axis of this matrix is based on existing epidemiological evidence, which shows an increasing relative risk of death at extremes of outdoor temperature beyond a threshold which can be identified epidemiologically. The likelihood axis is based on a probability measure associated with the temperature forecast. The new method is tested for two case studies (one during summer 2013, one during winter 2013), and compared to the performance of the current alert system.

Conclusions: The prototype shows some clear improvements over the current alert system. It allows for a much greater degree of flexibility, provides more detailed regional information about the health risks associated with periods of extreme temperatures, and is more coherent with other weather alerts which may make it easier for front line responders to use. It will require validation and engagement with stakeholders before it can be considered for use.

Fig 1. a) Schematic of the impact vs likelihood matrix, derived from the NSWWS. The alert code depends on both the uncertainty of the forecast (along the columns) and the strength of the impact (along the rows); b) Schematic showing the relation between the RR (excess deaths) and the temperature during summer (in degrees C).

The temperature range is adjusted to reproduce a RR between 1.0 and 1.16 by using the linear relationship.

Fig 2. Case study for August 2013.

The first guess alerts generated by the prototype system are shown along each row (for the day after up to 4 days ahead). The days are rearranged to be always the same along the columns. The color scheme is explained with the matrix at the bottom right of the figure (where the forecast lead time is used as a proxy for forecast uncertainty). The bottom left panel illustrates an example of a detailed regional alert for the South-West. Scotland, Wales and Northern Ireland are left blank as they do not share the same alert system for health forecasting.

Fig 3. As in Fig 2, but for the case during March 2013.

Fig 4. Semi-operational first guess alerts for summer 2014.

As in Figs 2 and 3, the forecast dates are along the top, and the issue dates down the side. “Z” refers to Zulu Time as is the same as UTC. Dates with alerts are circled in the figure. The image in the bottom left shows the local forecast for South East England on 18–19 July, issued on 17 July. In the top right of the smaller image one can see the matrix indicating the most severe type of event forecast in that region. Note that forecasts issued on 16 July are missing due to the system going down on that day.