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

Masato G, Bone A, Charlton-Perez A, Cavany S, Neal R, Dankers R, Dacre H, Carmichael K, Murray V - PLoS ONE (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: University of Reading, Meteorology Dept., Earley Gate, Reading, United Kingdom.

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.

No MeSH data available.


Related in: MedlinePlus

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.
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pone.0137804.g001: 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.

Mentions: There are three major challenges with the existing system. Firstly, although the cold weather and heatwave alert systems are broadly similar, they are not consistent with the current system used for the National Severe Weather Warning Service (NSWWS) of the Met Office (MO) [17], potentially leading to confusing or contradictory messages. The NSWWS provides warnings about rain, wind, fog, snow and ice, but not temperature extremes and uses a traffic light system based on a matrix of predicted impact and likelihood (Fig 1A), thus taking a different approach to the ‘get ready, go’ approach of the heatwave and cold weather alert services.


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

Masato G, Bone A, Charlton-Perez A, Cavany S, Neal R, Dankers R, Dacre H, Carmichael K, Murray V - PLoS ONE (2015)

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.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4592211&req=5

pone.0137804.g001: 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.
Mentions: There are three major challenges with the existing system. Firstly, although the cold weather and heatwave alert systems are broadly similar, they are not consistent with the current system used for the National Severe Weather Warning Service (NSWWS) of the Met Office (MO) [17], potentially leading to confusing or contradictory messages. The NSWWS provides warnings about rain, wind, fog, snow and ice, but not temperature extremes and uses a traffic light system based on a matrix of predicted impact and likelihood (Fig 1A), thus taking a different approach to the ‘get ready, go’ approach of the heatwave and cold weather alert services.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: University of Reading, Meteorology Dept., Earley Gate, Reading, United Kingdom.

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.

No MeSH data available.


Related in: MedlinePlus