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Feasibility Assessment Report

Internet-based Heat Evaluation and Assessment Tool (I-HEAT)

Susan Maxwell (PI), Robert Rommel, Geoffrey Jacquez - BioMedware, Inc.

Marie O’Neill, Kathryn Conlon, Natalie Sampson - University of Michigan School of Public Health

Executive Summary Introduction

Background Project overview Purpose of report

Satellite Imagery

Background Methods Conclusions

Systems Architecture User Survey

User survey methods User survey findings

Summary and Next Steps References Appendices

Appendix A. Publications and Presentations from the I-HEAT project

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Executive Summary Over the past two decades heat waves were responsible for more deaths in the U.S. than any other natural hazard (e.g., floods, winter storms, hurricanes). The U.S. Global Change Research Program identified mapping and modeling tools for identifying populations vulnerable to climate changes as an important need. This project developed and evaluated the feasibility of a computer software tool, the Internet-based Heat Evaluation and Assessment Tool (I-HEAT) to assist health professionals in determining populations most vulnerable to extreme heat events. The I-HEAT study was funded by the National Aeronautics and Space Administration (NASA) from June 2011 to June 2013 under contract NNH11CD21C to assess the feasibility of providing health professionals and risk assessors with an advanced geospatial web-based system for preparing and responding to emergency heat events, developing mitigation strategies, and educating the public. The concept was to integrate temperature and vegetation data derived from Landsat satellite imagery with demographic data and a previously developed vulnerability index within a browser-based software package to map heat-related morbidity and mortality risks at the neighborhood level. The aims of the study were to: 1) Develop and test a prototype system for accessing and incorporating NASA Web-Enabled Landsat Data (WELD) with existing demographic, socio-economic, and health data using web-based software , and 2) test the system in Detroit, Michigan through evaluation with end-users. The I-Heat software consists of both a web client and server architecture. The client runs in any web browser supporting the Adobe Flash platform. The client interface primarily contains a mapping interface designed to be familiar to users who have experience using Google Maps or other common web-mapping tools. The I-HEAT application can be accessed at: http://www.biomedware.com/I-Heat/IHeatViewer.html. Although Landsat data are now freely available through the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, the data are not provided in a format that can be easily imported and used without intermediate analysis by a remote sensing expert with access to high-end computing facilities. We originally proposed to use the NASA/USGS Web-Enabled Landsat Data (WELD) product for our study. This image dataset provides nationally consistent Landsat data that has been temporally composited, mosaiced, and converted to geo-physical and bio-physical products providing a “ready-to-use” data product. We found that the WELD data products needed for our study (Weekly image product) were not suitable because the images were not gap-filled (an artifact of the failure of the scan-line corrector on the Landsat 7 sensor). We utilized Landsat 5 imagery for our project which required

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additional effort to mosaic, radiometrically correct, and transform to NDVI and surface temperature prior to use in the I-HEAT system. Landsat 5 stopped collecting imagery in November 2011 due to technical problems. Landsat 8 is scheduled for launch in February 2013. We recommend utilizing Landsat 8 data when available to enable current imagery to be used in addition to the higher spatial resolution of the thermal band. Software tools will need to be developed to mosaic and convert the imagery to NDVI and surface temperature for use in the I-HEAT system. On May 2, 2012, the research team held a day-long workshop: Heat & Health in Michigan: An Interactive Workshop on the Development of Risk Assessment Resources to introduce and evaluate the I-HEAT system. This workshop was organized in collaboration with researchers from Michigan State University (MSU), the Michigan Department of Environmental Quality, and the Michigan Department of Community Health. Through this collaborative network, individuals who were most likely to make decisions about heat-related health interventions were identified and invited, representing local health departments and emergency preparedness agencies. Participants were asked to take part in discussions to assess their personal and professional attitudes about heat and health, as well as to assess the performance and features of I-HEAT. Participants offered feedback through a 12-question survey with seven quantitative, Likert-scale questions and five qualitative, open-ended questions after interacting with I-HEAT, as well as a short set of semi-structured, focus group questions at the end of the workshop. Questions pertained to terminology, opportunities for decision-making, limitations of the tool, and satisfaction with various aspects of the tool. Important conclusions from the workshop include:

- Participants were satisfied with the types of data used in I-HEAT, user-friendliness of the web interface, general appearance of the web interface, and the graphics of the application.

- Users found I-HEAT to be a tool that was “quick” and “user-friendly” with a simple interface, making it “easy to see what’s going on and help prioritize.”

- Three primary aspects of I-HEAT software that participants noted as useful were 1) localized analysis, 2) spatial visualization, and 3) integration of multiple types of data.

- Many participants noted that a resource with this combination of characteristics is not currently “readily available,” and I-HEAT would help planning, policy-making, identification of resources, and targeting of services for both climate mitigation (e.g., increasing tree canopy density, green roof installation) and adaptation (e.g., cooling centers, health education, block group programs, transportation, emergency care).

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- Participants highlighted how the amount and types of data were useful, enabling a local understanding of relative risk and spatial variability among the variables. Participants liked inclusion of historical data, as well as local scale temperature and vegetative cover data. They commented how these data were more informative than simply using the often insufficient weather data frequently collected at airports, or health data frequently collected at zip code or county levels.

- Survey respondents had many useful suggestions for improving I-HEAT related to its performance, terminology, and information the software provides to users.

- Respondents envisioned local health and planning departments using I-HEAT to identify areas of the city where vulnerable populations are likely to be found.

- Respondents discussed at length the potential utility of I-HEAT in developing both mitigation and adaptation activities (e.g., tree-planting, cooling center siting) during off-season times to ensure well-planned emergency response.

To further validate I-HEAT, we assessed how our tool and feedback from participants aligned with findings from a recent study funded by the Centers for Disease Control and Prevention (CDC), Reducing Social Disparities of Heatwave Impacts in a Changing Climate (R18 EH00348). In this four-city case study, a team of researchers led by Dr. Marie O’Neill (co-investigator on this NASA-funded study) interviewed more than 170 community leaders and members in Detroit, Michigan; Philadelphia, Pennsylvania; Phoenix, Arizona; and New York City, New York to understand behavioral responses to heat and the local programming that exists to address heat-related health issues. Drawing on user survey data from the piloting of I-HEAT, we describe how I-HEAT may fill gaps in risk management strategies or align with emergent heat preparedness efforts described by interviewees in the CDC study. The CDC study highlighted that a diversity of decision-makers are responsible for heat preparedness, and I-HEAT may be a tool to guide cross-sector communication among varied sectors. In the CDC study, different cities highlighted different strategies for communication to plan prior to, and coordinate during, heat events. I-HEAT was tested by diverse pilot users drawn from city, county and state health department staff, emergency planners, and local non-profit and research leaders working on environmental issues. The consensus deemed I-HEAT to be a useful and user-friendly platform. The CDC-funded researchers learned that heat-related health programs are minimally evaluated, thus showcasing a potential for I-HEAT to assist future evaluation and research efforts within municipal heat-health programs. While many programs were not routinely evaluated, CDC interviewees referenced indicators on which they informally collected data, or would like to collect data (e.g., cooling center attendance, transportation usage, etc.). The current version of I-HEAT does not include this contextual data, but does provide a base map and ready mechanisms for doing so.

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We suggest the following next steps to further the development of the I-HEAT system:

- Evaluate the new Landsat 8 sensor data (available February 2013), - Upgrade I-HEAT software based on user feedback, - Demonstrate the revised I-HEAT system to users who were unable to attend the

workshop but who had indicated interest, - Pursue additional collaborations and funding opportunities, - Publish further on the findings of our research.

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Introduction Background Over the past two decades heat waves were responsible for more deaths in the U.S. than any other natural hazard (e.g., floods, winter storms, hurricanes) (Borden and Cutter, 2008; National Weather Service, 2010). In 1995 at least 700 deaths were attributed to the heat wave in Chicago (Semenza et al, 1996). Western Europe experienced an unusually intense heat wave during the summer of 2003 with over 70,000 heat-related deaths (Robine et al, 2008). In Paris alone, 4,867 excess deaths were reported during the 2003 heat wave (Dousset, 2009). A recent report by the Intergovernmental Panel on Climate Change (IPCC) (IPCC, 2007) concluded that climate warming is unequivocal and scientists agree that the likelihood of the continuing warming trend is “virtually certain” (IPCC, 2007). Health professionals need to plan and prepare for heat-related emergencies as future climate changes are expected to increase the frequency, duration, and magnitude of heat waves (Meehl and Tebaldi, 2004; IPCC, 2007). The U.S. Global Change Research Program identified mapping and modeling tools for identifying populations vulnerable to climate changes as an important need. A recent report published by the Trust For America’s Health (TFAH) foundation concluded that special efforts must be made to address the impact of climate change on at-risk and vulnerable communities (TFAH, 2009). The report recommends that all state and local health departments should include public health considerations as part of their climate change preparedness. Yet, this report notes, only five states in the U.S. have developed a strategic climate change plan that includes a public health response, and effective software tools are almost entirely lacking. Impacts of climate change on human health vary by region, vulnerability of population groups, duration of exposure, and ability to adapt or cope with the changes (Ebi et al, 2008; English et al, 2009). Elderly populations (≥ 65 years) are particularly vulnerable to the effects of extreme heat (Semenza et al, 1996; Kovats and Hajat, 2008; Schifano, 2009) due to factors including physiology, disability, and medication use (Ebi and Meehl, 2007). To identify populations vulnerable to heat waves, demographic data such as age and poverty status need to be linked with local-scale environmental data such as land cover and temperature (English et al, 2009; Rinner et al, 2010). An extensive review of heat-wave impacts on human health (Wilhelmi et al, 2004) concluded that geospatial and remote sensing technologies provide a key capability for mitigating heat-related deaths. In particular, understanding the dynamics between urban heat islands and vulnerable populations is critical to reducing heat-related deaths (Wilhelmi, 2004).

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Project Overview We proposed to develop a computer software tool, the Internet-based Heat Evaluation and Assessment Tool (I-HEAT), which would be designed to assist health professionals in identifying populations most vulnerable to extreme heat events. The I-HEAT study was funded by the National Aeronautics and Space Administration (NASA) from June 2011 to June 2013 under contract NNH11CD21C to assess the feasibility of providing health professionals and risk assessors with an advanced geospatial web-based system for preparing and responding to emergency heat events, developing mitigation strategies, and educating the public. The concept was to integrate temperature and vegetation data derived from Landsat satellite imagery with demographic data and a previously developed vulnerability index within a browser-based software package to map heat-related morbidity and mortality risks at the neighborhood level. The aims of the study were to: 1) Develop and test a prototype system for accessing and incorporating NASA Web-Enabled Landsat Data (WELD) with existing demographic, socio-economic, and health data using web-based software, and 2) test the system in Detroit, Michigan through evaluation with end-users. I-HEAT was designed and tested using Detroit, Michigan as the initial case study. Detroit provided an ideal experimental setting for evaluating this comprehensive heat-risk mapping tool since it lacks a heat wave health warning system and has significant racial/ethnic and socio-economic disparities in heat exposure and heat-related health effects (O’Neill et al, 2003; Schwartz, 2005). Climate change models predict this region will experience some of the highest temperature increases in the future (Meehl and Tebaldi, 2004). Purpose of this Report The purpose of this report is to present the results of our study to evaluate the feasibility of implementing a web-based heat assessment tool to support health professionals in identifying populations vulnerable to extreme heat events. This report is divided into four sections: 1) satellite imagery, 2) systems architecture, 3) end-user evaluation, and 4) overall conclusions and next steps. Each section documents the methods applied, results, and conclusions with the last sections providing an overall summary of the project and next steps.

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Satellite Imagery Background Local surface temperature, derived from satellite data, has been found to be a significant predictor of heat-related mortality (Vandentorren et al, 2006; Johnson et al, 2009; Smargiassi et al, 2009). Landsat satellite imagery provides data at the appropriate spatial resolution (30-120 meter) and temporal repeat cycle (8-16 days) needed for modeling heat risk in urban environments (UHI, 2010). Although Landsat data are now freely available through the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, the data are not provided in a format that can be easily imported and used without intermediate analysis by a remote sensing expert with access to high-end computing facilities. We originally proposed to use the NASA/USGS Web-Enabled Landsat Data (WELD) product for our study. This image dataset provides nationally consistent Landsat data that has been temporally composited, mosaiced, and converted to geo-physical and bio-physical products (Roy et al, 2010). Methods WELD data was downloaded for the spatial area covering Wayne County, MI from the website: http://weld.cr.usgs.gov/index.php. Options for Weekly data (original Landsat imagery without gap-fill), Monthly Composites, and Seasonal Composites (i.e., Summer (June-August) were available. Several monthly and seasonal composited images were selected for evaluation spanning the summer periods of 2007-2010. Closer inspection of the data revealed that anomalies existed in the imagery in gap-filled pixels (Figure 1, middle and right images). These issues were discussed with the WELD project coordinator (Dr. David Roy). Dr. Roy recommended using the Weekly WELD product since the gap-fill process in the thermal composite images is based on maximum NDVI (i.e., not thermal image based). Unfortunately the WELD Weekly image product is not gap-filled (Figure 1, left image) and there were no plans at that time to provide a gap-filled product (personal communication, David Roy, September 2011).

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Figure 1. WELD NDVI images for weekly (Week 37, 2010), monthly composite (August, 2010), and Seasonal composite (Summer, 2010) products (Detroit, MI). Providing a gap-filled Landsat image product was beyond the scope of our study. We decided to continue the project using Landsat 5 imagery. Accordingly, Landsat images for September 1, 2002 Path 20 Rows 30 and 31 were downloaded from the USGS GLOVIS website (http://glovis.usgs.gov/). Both images were required to cover our entire study area. Bands 3 (red visible) and 4 (near infrared) were used to calculate the NDVI, and Band 61 (thermal) was used to calculate brightness temperature using Chander et al. (2009) algorithms. The USGS NLCD map (http://landcover.usgs.gov/natllandcover.php) was used to identify water. Image processing was performed using a combination of ERDAS Imagine software and Perl software scripts. NDVI images were color scaled from yellow (low NDVI) to green (high NDVI) (Figure 2). The temperature imagery was rescaled to nine temperature groups with colors ranging from yellow (representing temperatures 60 to 69 degrees Fahrenheit) to dark red (representing temperatures 110 to 115 degrees Fahrenheit) (Figure 3).

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Figure 2. NDVI image for Detroit, MI, September 1, 2002 overlaid with cooling center locations (blue snowflakes).

Figure 3. Brightness temperature image for Detroit, MI, September 1, 2002 overlaid with cooling center locations (blue snowflakes).

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Conclusions Our original intent was to use imagery from the WELD product. However we found that the monthly and seasonal composites were not of acceptable quality for the I-HEAT application and the weekly product was not gap-filled. The advantages of having “ready-to-use” image data would be very beneficial for quickly implementing the I-HEAT software tool. We utilized Landsat 5 imagery for our project which required additional effort to mosaic, radiometrically correct, and transform to obtain the NDVI and thermal products required for the I-HEAT tool. A new Landsat satellite (Landsat 8) is being launched in February 2013 which will have similar spectral bands to Landsat 7. Barring any technical problems, the new Landsat imagery should be suitable for deriving the NDVI and temperature data required for this application. Systems Architecture The I-HEAT software was engineered using a web client and server architecture. The client runs in any web browsers supporting the Adobe Flash platform. The client interface primarily contains a mapping interface designed to be familiar to users who have experience using Google Maps or another common web-mapping tool. The client can be accessed at: http://www.biomedware.com/I-Heat/IHeatViewer.html. The interface begins by displaying the areas of greatest risk for an adverse heat-related health event since this is the area of the software likely to be used the most. A series of tabs atop the interface are used to change the map view. Other map views display the satellite data and temperature data used to predict the risk of a heat-related event. One tab provides a small online documentation to explain the mapped data. In all map views a background map is shown to provide context. While it is well-known that elevated temperature is associated with heat-related health events, and various demographic factors (e.g., age, poverty) are markers of special susceptibility to heat-events, the relative strength of these two factors in determining the risk of a heat-related health event has not been quantified for our study area. Since quantifying this was outside the scope of our project and would require extensive health data we adopted a simplified approach. We used a model that assumes that risk depends on these factors (heat exposure and population susceptibility) and allows the user to specify what he or she thinks the relative weight of each is. For the I-HEAT application, we used the Heat Vulnerability Index developed by (Reid et al. 2009) as our major indicator of susceptibility, as discussed below. We used a linear scale between normalized values of the two factors with the two extremes being completely composed

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of either factor. This is then displayed on the map and a relative scale is used, depicting areas at highest risk in red. A slider control in the top right of the interface allows the user to adjust the relative strength of the two factors. The linear equation used to combine the two factors into a risk estimate is: where V' is the standardized vulnerability index and T' is the standardized observed temperature at a location. The demographic component we used to quantify the risk of an adverse heat-related health event was a composite vulnerability index derived by Reid et al. (2009). It is a composite of many variables including vegetation cover, diabetes prevalence, air conditioning availability, percent below the poverty line, percent non-white, percent greater than or equal to 65 years of age, percent greater than or equal to 65 years of age and living alone, and percent without a high school education. The latter 5 individual variables are available to the user in one of the tabs to help determine where to focus an intervention based on where certain demographic groups reside. User Survey User survey methods On May 2, 2012, the research team held a daylong workshop: Heat & Health in Michigan: An Interactive Workshop on the Development of Risk Assessment Resources to introduce and evaluate I-HEAT. This workshop was organized in collaboration with researchers from Michigan State University (MSU), the Michigan Department of Environmental Quality, and the Michigan Department of Community Health. Through this collaborative network, individuals who were most likely to make decisions about heat-related health interventions were identified and invited, representing local health departments and emergency preparedness agencies. Local decision-makers from across mid-Michigan were invited, with an over-sampling of Detroit decision-makers, given that the data in the prototype were Detroit-specific. During the day, participants were asked to take part in discussions to assess their personal and professional attitudes about heat and health, as well as to assess the performance and features of I-HEAT. Participants were introduced to the I-HEAT web interface through a presentation before working in small groups. Question prompts

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were provided to these groups to guide discussions and simulate real world uses of I-HEAT:

• Find a location where there is high risk during an extreme event. Are the areas near this location also at high risk? Repeat this for a low risk area.

• Find a location with a high poverty rate. Does this location have a high or low risk?

• Find a location that lacks vegetation cover? Does this location have a high or low risk?

• Pick a location that is important to you. Does it have a high or low risk? Why do you think this is?

• Explore another question that is important for you that you think I-Heat might be able to address.

Participants offered feedback through a 12-question survey with seven quantitative, Likert-scale questions and five qualitative, open-ended questions after interacting with I-HEAT, as well as a short set of semi-structured, focus group questions at the end of the workshop. Questions pertained to terminology, opportunities for decision-making, limitations of the tool, and satisfaction with various aspects of the tool. This evaluation was determined exempt from human subjects regulation by the University of Michigan Institutional Review Board. However, to ensure ethical standards, participants were asked to complete informed consent forms at the beginning of the workshop. User survey findings Including researchers, 28 participants attended the workshop. Among the participants, 23 completed surveys and 26 participated in the focus group. Participants represented state agencies (n=5), academic institutions (n=11), non-profit organizations (n=5), private research organizations (n=2), local health departments (n=4), and the National Weather Service (n=1). As summarized in Table 1, on average, participant satisfaction with I-HEAT fell closest to ‘satisfied’ regarding the types of data (mean = 3.86), user-friendliness of the web interface (mean = 3.64), general appearance of the web interface (mean = 4.09), and the graphics of the application (mean = 3.86). On average, participants were between ‘unsatisfied’ and ‘neither satisfied or unsatisfied’ with the performance, or speed, of the application. We did encounter, during the workshop, a problem with the server on which I-HEAT is housed, which limited the number of simultaneous users. Scores in the performance and speed category likely reflect this experience.

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What aspects of I-HEAT are most useful for local decision-makers? In brief, pilot users found I-HEAT to be a tool that was “quick” and “user-friendly” with a simple interface, making it “easy to see what’s going on and help prioritize.” Three primary aspects of I-HEAT software were noted as useful by participants: 1) localized analysis, 2) spatial visualization, and 3) integration of multiple types of data. According to many participants, a resource with this combination of characteristics is not currently “readily available,” and I-HEAT would help planning, policy-making, identification of resources, and targeting of services for both climate mitigation (e.g., tree canopy density, green roof installation) and adaptation (e.g., cooling centers, health education, block group programs, transportation, emergency care) within jurisdictions. The software allowed them to understand “the where” of heat health risks and maintain a “strong sense of place,” which they deemed to be key contributions of the software. Participants commented they would be more likely to use tools such as I-HEAT with its localized data to determine where “predictors [of heat-related health outcomes] converge”, rather than those providing smaller scale, regional information. Participant comments included:

Table 1. Participant Satisfaction with I-HEAT Data, Appearance, and Performance (n=22)

Mean (Standard Deviation)

The types of data (e.g., temperature, vulnerability, demographics) decision-makers can select to view

3.86 (0.64)

The user-friendliness of the web interface (5=easy to use, 1=too complicated) 3.64 (1.09)

The general appearance of the web interface 4.09 (0.68)

The graphics of the application (e.g., the map outputs) 3.86 (0.79)

The performance (speed) of the application 2.65 (1.11)

Possible responses: Extremely unsatisfied ‘1’, Unsatisfied ‘2’, Neither satisfied or unsatisfied ‘3’, Satisfied ‘4’, Extremely satisfied ‘5’

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“I think the vulnerability map is extremely useful, not only in relation to heat but for other public health issues. Being able to identify areas with high senior populations, for example, and show that visually could be very useful.” “The spatial aspect of heat vulnerability is critical, and this is a unique tool to address that. It could help researchers/practitioners to localize areas of concern/priority.” “Spatial information is a critical part of the heat event impacts on human health; good to have navigable tool that addresses this.”

Specifically, participants highlighted how the amount and types of data were useful, enabling a local understanding of relative risk and spatial variability among the variables. Participants liked inclusion of historical data, as well as local scale temperature and vegetative cover data. They commented how these data were more informative than simply using the often insufficient weather data frequently collected at airports, or health data frequently collected at zip code or county levels. Finally, some participants noted that I-HEAT’s variables depicted cumulative and additive relationships of multiple risk factors well. How can I-HEAT be improved? Survey respondents had many useful suggestions for improving I-HEAT related to its performance, terminology, and information the software provides to users. The hands-on demonstration of I-HEAT involved small groups of workshop participants sharing computers and working through example case studies. Due to numerous simultaneous users on the site at once, the performance for some groups was significantly limited. The workshop participants who were in these groups voiced their frustration with being unable to access the tool. Survey respondents stressed the importance of upgrading I-HEAT’s bandwidth to avoid web interface and data loading interference. This issue was resolved after the workshop, and the current version of I-HEAT has bandwidth for multiple simultaneous users. Second, within the tool, the terms, ‘Risk’ and ‘Vulnerability,’ which are each a map layer for users to view, could be further clarified. Respondents raised the ambiguity of the term ‘risk’, noting that, depending on the audience type (e.g., community leaders, local health departments, policymakers), ‘risk’ can have numerous meanings. Similarly, respondents commented on the term ‘vulnerability’ as both a tab within the tool and an information layer displayed in the tool. Confusion on the difference between ‘risk’ and ‘vulnerability’ can be addressed by providing detailed, specific definitions within the tool, particularly in each instance where the terms are present. This terminology was clarified in the release of I-HEAT

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that implemented workshop recommendations. Lastly, survey respondents voiced concerns over the data used to create the numerous tabs and layers within I-HEAT. For instance, participants were wary of the vulnerability tab, in which a heat vulnerability index – composed of health, demographic, socioeconomic, and environmental variables – was mapped at the census tract level within the tool geography. This concern is being addressed by providing improved descriptions of the data in the “About” tab in the I-HEAT software. In what ways may local decision-makers use I-HEAT? As shown in Table 2, participants indicated, on average, that they were likely to use the software in their work (mean = 3.71) and more likely if their suggestions were integrated into the software (mean= 4.18). To better understand the potential of I-HEAT, participants were also asked to describe how they foresaw using the software in their work. Respondents envisioned local health and planning departments using I-HEAT to identify areas of the city where, based on historical demographic and environmental data, vulnerable populations are likely to be found. In using this information prior to the spring and summer seasons when high temperatures can surprise public health and emergency response systems, the support systems in place can activate responses to the known vulnerable populations. Additionally, respondents discussed at length the potential utility of I-HEAT in developing adaptation activities (e.g., tree-planting, cooling center siting) during off-season times to ensure well-planned emergency response. Although I-HEAT was presented within the city boundaries of Detroit, the largest metropolitan area in Michigan, pilot users saw potential in the tool’s capacity to visualize heat vulnerability across the state, in an effort to plan for heat-health events within the context of an ever-changing (and hotter) Michigan climate.

Table 2. Participant Mean Likelihood of Using I-HEAT Mean

(Standard Deviation)

How likely are you to use I-HEAT, if it were available to you? (n=20)

3.71 (0.90)

If your above suggestions were addressed, how likely are you to use I-HEAT software, if it were available for your region? (n=20)

4.18 (0.61)

Possible responses: Extremely unlikely ‘1’, Unlikely ‘2’, Not sure ‘3’, Likely ‘4’, Extremely likely ‘5’

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Risk Management for Reducing Social Disparities To further validate I-HEAT, we assessed how our tool and feedback from participants aligned with findings from a recent study funded by the Centers for Disease Control and Prevention (CDC), Reducing Social Disparities of Heatwave Impacts in a Changing Climate (R18 EH00348). In this four-city case study, a team of researchers led by Dr. Marie O’Neill (co-investigator on this NASA-funded study) interviewed community leaders and members in Detroit, Michigan; Philadelphia, Pennsylvania; Phoenix, Arizona; and New York City, New York to understand behavioral responses to heat and the local programming that exists to address heat-related health issues. Drawing on user survey data from the piloting of I-HEAT, we describe how I-HEAT may fill gaps in risk management strategies or align with emergent heat preparedness efforts described by interviewees in this CDC study. Over the course of more than 170 interviews, the CDC project researchers learned about a variety of existing programs among case study cities designed to address heat-health impacts, encompassing both climate mitigation and adaptation strategies. To mitigate human-induced warming at local and global scales, interviewees described a variety of plans to increase green space and reduce carbon emissions, and green or white roof programs to improve heat reflection, thus reducing the urban heat island effect. In terms of adapting to warming climates, collectively, local agencies opened cooling centers, set up water stations, distributed fans and air conditioners, provided utility assistance, offered weatherization programs to improve natural cooling in homes, and coordinated transportation to and from various cool places (e.g., shaded parks, senior centers, malls). Although I-HEAT pilot users were not prompted to highlight the software’s ability to improve both mitigation and adaptive efforts, they mentioned such programs as described by the CDC city interviewees. I-HEAT pilot participants were asked, “If you would consider using I-HEAT in your workplace, please provide a brief, specific example of how the software may assist you and your colleagues in planning, implementing, or evaluating heat-related interventions”. In response, most described ways they would use the spatial information to geographically target services such as cooling centers. Some participants also focused on and noted ways in which various map layers illustrating area vegetation and known risks could be used to indicate where additional tree planting could improve mitigation efforts. The CDC study also highlighted how a diversity of decision-makers are responsible for heat preparedness, and I-HEAT may be a tool to guide cross-sector communication among varied sectors. In the CDC study, different cities highlighted different strategies

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for communication to plan prior to and coordinate during heat events, including task forces, boards, and coalitions. I-HEAT was tested among city, county, and state health department staff, emergency planners, and local non-profit and research leaders working on environmental issues. Across these diverse pilot users, the software was determined user-friendly. Pilot users also offered many suggestions for improving terminology, definitions, and legends in the I-HEAT software interface. These suggestions are underway and will likely improve the ability of decision-makers to use a shared language to support collaboration. Finally, from the CDC study, researchers learned that heat-related health programs are minimally evaluated, thus showcasing a potential for I-HEAT to assist future evaluation and research efforts within municipal heat-health programs. While many programs were not routinely evaluated, CDC interviewees referenced indicators on which they informally collected data, or would like to collect data on (e.g., cooling center attendance, transportation usage, number and type of block group programs, air conditioner usage, changes in tree density, changes in temperature, etc.). The current version of I-HEAT does not include this contextual data, but may provide a base map for doing so or may provide information to generate hypotheses, explain spatial relationships, or determine how and where to implement evaluative procedures. For instance, local decision-makers could use I-HEAT to assess whether cooling center siting and usage aligned with high-risk areas and determine appropriate interventions based on the findings of this assessment. Another example, one pilot user explained, would be seeing I-HEAT “help evaluate the effects of interventions like tree planting in high risk areas” by using the tool over time with additional vegetation and temperature data. Conclusions and Next Steps While municipal heat preparedness has historically been under-evaluated and ad hoc throughout the U.S., many public health practitioners recognize its importance and are unable to act due to limited resources. Based on the needs, challenges, and existing efforts highlighted by the CDC study interviewees and pilot users, I-HEAT may be a tool to assist diverse sectors in communication and evaluating mitigation and adaptation efforts. The following next steps will ensure I-HEAT is feasible and functional: Satellite Imagery

- Evaluate Landsat 8 sensor data when available (February 2013).

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Software Upgrades - Based on feedback received from users at the workshop, we made several

immediate changes to the I-HEAT software to enhance the user experience. To improve user understanding of what they are seeing on the maps, we expanded and clarified the legend information for each display. To add context that can help support decision making, we added a visual indicator of where public cooling centers are located in the Detroit area to all displays. Lastly, several performance improvements were made to the server-side components to improve the user experience. We also evaluated using different hosted server architecture that would scale performance better with a high volume of users.

User Feedback

- Many of the workshop participants were unable to attend at the last minute. Contact those who could not attend and organize I-HEAT software demonstrations either at their facility or via internet.

Collaborations/Funding

- Pursue new collaborations and additional funding. Along these lines we have entered into discussions with Dr. Daniel Johnson, Chair of the IUPUI Department of Geography and Director of the Institute for Research on Social Issues at Indiana University – Purdue University at Indianapolis. Dr. Johnson specializes in climate change and its impact on the health of vulnerable populations. He is completing a NASA-funded project that is drawing together substantial data resources to document heat-related health effects. In our discussions we agreed that a strong collaboration may be formed that would apply the I-HEAT software as the visualization and mapping tool for analyzing the data collected by Dr. Johnson’s group. We are currently searching for appropriate funding mechanisms for this research collaboration.

Publications

- Publish the findings of our research. Katie Conlon is in the process of writing a paper summarizing the I-HEAT study which will be submitted to the journal Spatial and Spatio-Temporal Epidemiology.

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References

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Appendix A. Publications and Presentations from the I-HEAT project Websites:

- Overview of I-HEAT project; BioMedware website: http://www.biomedware.com/?module=Page&sID=i-heat .

Publications

- Maxwell SK, Rommel RG, Jacquez GM, O’Neill MS, 2011, Internet-based heat evaluation and assessment tool (I-HEAT), Section 2 – Transforming remote sensing data into information useful for public health research and applications, in Environmental Tracking for Public Health Surveillance, ed. Stan Morain.

Presentations - Maxwell SK (2011), “Internet-based Heat Evaluation and Assessment Tool (I-

HEAT) Feasibility Study” NASA Public Health Program Review meeting in Santa Fe, NM, September 14-16, 2011.

- Jacquez GM (2011), “Geohealth Analysis and Data Visualization: Assessing and demonstrating relationships between dynamic local environments and human health outcomes”, December 8, 2011, ESRI campus, Redlands California.

- Jacquez GM (2012), “Geohealth Analysis and Data Visualization: Assessing and demonstrating relationships between dynamic local environments and human health outcomes”, Population Health Data Analysis: From Infrastructure to Innovation Conference, Vancouver, British Columbia, February 8-10, 2012.

- Rommel RG, O’Neil MS, Conlon K (2012), presentations at the “Heat & Health in Michigan: A Workshop for Local Decision-Makers to Participate in Development of New Risk Assessment Resources” Workshop on May 2, 2012

- Conlon K (2012), “Communicating heat-health vulnerability in preparation for heat events: Development and assessment of the Internet-Based Heat Evaluation and Assessment Tool (I-HEAT)”, 24th Annual International Society for Environmental Epidemiology; August 27-31, 2012, Columbia, SC.

- Conlon K (2012), “Development and assessment of a public health application for decision-making in preparation for heat events: Internet-based heat evaluation and assessment tool (I-HEAT)”, 2nd Annual Joint Center for Control and Prevention and National Oceanic and Atmospheric Administration Science Symposium on Climate and Health, Sept 12-13, 2012, Atlanta, GA.

- Rommel RG (2012), “Internet-based Heat Evaluation and Assessment Tool (I-HEAT) Feasibility Study” NASA Health and Air Quality Applications Program Annual Review, September 18-20, 2012, Newport, RI

- Sampson N (2012), Risk Science Center Fellows Symposium. University of Michigan, Ann Arbor, December 3, 2012.

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Posters

- Kempler S, Benedict K, Ceccato P, Golden M, Maxwell S, Morain S, Soebiyanto R, Tong D (2011). “The Increasing Use of Remote Sensing Data in Studying the Climatological Impacts on Public Health”. Poster presented at the AGU Hydroepidemiology: Understanding Connections Between Hydrology and Human Health session, December 09, San Francisco, CA, USA