Assessing public health risk due to extremely high temperature events: climate and social parameters

Abstract

The growing recognition of the need to plan institutional responses to the effects of climate change makes it essential to develop research support strategies and tools not only at global but also at regional scales. This paper analyses the feasibility and potential of a risk assessment framework for studies of regional impact of and adaptation to climate change. We assess the potential impact of high temperature events on humans in southern Quebec. We integrate climate variables and socio-economic parameters via a geographic information system (GIS) tool to produce maps of estimated present and future public health risk. A comparison of risk maps for present and future conditions shows that the number of locations where population will be at threat due to high temperature events will dramatically increase in Quebec over the next few decades. KEY WORDS: Public health risk · High temperature events · Southern QuebecResale or republication not permitted without written consent of the publisher Clim Res 30: 71-78, 2005 tional adaptation actions should be anticipatory and well-planned so as to minimize costs and optimize profitability (IPCC 2001a).Premature mortality and morbidity are the greatest social costs generated by heat waves in northern temperate countries. Deaths resulting from heat waves in several European, American and Japanese large cities have spurred growing research interest in prevention (Rooney et al. 1995, Semenza et al. 1996, Whitman et al. 1997, Besancenot 2002, Diaz et al. 2002, Curriero 2003, Vanhems et al. 2003, Cassadou et al. 2004, Hemon & Jougla 2004, Ledrans et al. 2004). High temperature events induce an increase in morbidity, i.e. a decline in health of people affected by cardiovascular, cerebrovascular, and respiratory disorders (McMichael et al. 1996, Haines & Patz 2004, Hemon & Jougla 2004, Knowlton et al. 2004, McMichael & Woodruff 2004. In Canada, climate projections show a significant warming for the future decades (IPCC 2001c). This is of special concern since in cooler regions people are less prepared for heat waves (Ballester et al. 1997, Curriero 2003. Consequently, there could be a significant increase in mortality, particularly among high risk groups such as elderly persons and urban dwellers with low income (IPCC 2001c, Diaz et al. 2002, Sheridan & Dolney 2003, Davis et al. 2004, Ledrans et al. 2004). The strongest correlation factors between impacts of high temperature events on mortality and morbidity and social factors include age (Besancenot 2002, Diaz et al. 2002, poverty (INSERM 2003), social isolation (Besancenot 2002) and education level (Ballester et al. 1997). These factors are often combined and sensitivity rises due to synergetic effects.We undertake a risk factor analysis for heat waves based on 2 components: climate hazard and social vulnerability. The methodology developed for this study was inspired by the NOAA (1999) vulnerability assessment tutorial, the EPA (1998) Guidelines for Ecological Risk Assessment, Cutter & Scott (1997), Schiegg (2...

New climate and socio-economic scenarios for assessing global human health challenges due to heat risk

“…Several vulnerability indices of environmental hazards have been proposed, such as the SoVI (Cutter et al 2003), EHVI (Johnson et al 2012), and PVI (Adger 2006). A number of social vulnerability factors have been identified in local-or city-level heat health risk assessments, such as age, poverty, social isolation, education, ethnicity, and access to transportation (Schwartz 2005;Semenza et al 1996;Vescovi et al 2005). In this paper, we have identified four indicators of the presence of a vulnerable population:…”

“…Multiple studies have used the equal weight method to calculate vulnerability (e.g., Collins et al 2009;Tomlinson et al 2011;Vescovi et al 2005;Dong et al 2014). To compare the influence of the weight variance of vulnerability factors on heat risk, we computed the global mean risk under the condition that the weight of Aged ranges from 0.1 to 0.9 (step: 0.1) by the ratio of weight (GDP) and weight (edu) ranges from 0.1 to 0.9 (step: 0.1) and 1 to 10 (step: 1).…”

“…High population density regions have more human activity such as vehicle and air-conditioning use that contributes to the local heat island (Luber and McGeehin 2008;Smith et al 2009). (2) Elderly people have lower adaptation ability and higher mortality rates (Poumadère et al 2005;Vescovi et al 2005;CDC 2002;Pan et al 1995). Older people have decreasing regulatory abilities for intrinsic homeostasis, making them insensitive to temperature changes and unaware of becoming ill (Koppe et al 2004).…”

“…(4) Education level is an indicator of vulnerability (Cutter et al 2003;Johnson et al 2009;Vescovi et al 2005), because educational attainment can significantly affect individuals' resilience, as it is related to a higher awareness and better knowledge of hazard prevention. It is also assumed that people with higher education levels can find better employment and access to assistance programs (Morrow 1999).…”

“…(1), UNDRO 1991;Tomlinson et al 2011;Vescovi et al 2005) using the geographic information system (GIS).…”