Heat Policy Revision for Georgia High School Football Practices Based on Data-Driven Research
Interscholastic heat policies for football have not been evidence based. Therefore, their effectiveness in mitigating exertional heat illness has not been assessed. To discuss the development of the Georgia High School Association heat policy and assess the effectiveness of revised guidelines. Descriptive epidemiology study. Georgia high schools. Interscholastic football players in grades 9 through 12. Heat syncope and heat exhaustion (HS/HE) illness rates (IRs) were calculated per 1000 athlete-exposures (AEs), and relative risk (RR) was calculated as a ratio of postpolicy (POST) IR divided by prepolicy (PRE) IR. A total of 214 HS/HE cases (172 PRE, 42 POST) and 341 348 AEs (178 230 PRE, 163 118 POST) were identified. During the first 5 days of the PRE period, approximately 50% of HS/HE illnesses occurred; HS/HE IRs doubled when practice sessions increased from 2 to 2.5 hours and tripled for practices ≥3 hours. The HS/HE IRs in the PRE period increased from 0.44/1000 AEs for wet-bulb globe temperatures (WBGTs) of <82°F (<27.8°C) to >2.0/1000 AEs for WBGTs from 87°F (30.6°C) to 89.9°F (32.2°C). The RRs comparing PRE and POST policy periods were 0.29 for WBGTs of <82.0°F (<27.80°C), 0.65 for WBGTs from 82.0°F (27.8°C) to 86.9°F (30.5°C), and 0.23 for WBGTs from 87.0°F (30.6°C) to 89.9°F (32.2°C). No HS/HE illnesses occurred in the POST period for WBGTs at >90°F (>32.3°C). Results from the PRE period guided the Georgia High School Association to revise its heat and humidity policy to include a mandated 5-day acclimatization period when no practices may exceed 2 hours and the use of WBGT-based activity-modification categories. The new policy reduced HS/HE IRs by 35% to 100%, depending on the WBGT category. Our results may be generalizable to other states with hot and humid climates similar to that of Georgia.Context
Objective
Design
Setting
Patients or Other Participants
Main Outcome Measure(s)
Results
Conclusions
American football is a widely popular sport among high school athletes in the United States, with >10 000 schools offering football programs and hundreds of thousands of participants across the nation.1 Exertional heat illnesses (EHIs) are a common hazard for football players, who are 11 times more likely to sustain an EHI than athletes in all other sports combined.2 Most importantly, EHIs are among the top 3 causes of sudden death in these athletes.3 In Georgia, awareness of the dangers of EHI peaked after the 2006 death of a Georgia high school football player, which received extensive media coverage, and with the knowledge that, over a 30-year period (1980–2009), Georgia led the country in heat-related deaths of interscholastic football players.4,5
Before 2012, heat safety guidelines for interscholastic football programs in Georgia were vague and offered no standardized practice recommendations for coaches to follow6 (Appendix 1). For example, the 2010–2011 Georgia High School Association (GHSA) heat policy6 required each school district to have its own written heat practice policy. This policy needed to include an environmental assessment to dictate when practices should be cancelled. However, the GHSA provided no evidence-based guidance for devising this policy.
In 2008, the GHSA decided to help develop a more comprehensive, data-driven heat policy. A 3-year study was funded to examine the relationship between environmental and practice conditions and EHI rates (illness rates [IRs]). In this investigation, environmental conditions that affect heat gains and losses and the frequency of exposure to hot environmental conditions, which influences acclimatization, were found to be key factors controlling EHI IRs. The results were used to develop a new evidence-based heat policy for preseason and regular season practices. The new heat policy7 (Appendix 2) was implemented in the 2012 season and was applied uniformly to all GHSA member high schools. After the initial 3-year study was completed, GHSA funded another 3-year study to determine the effectiveness of the new policy in mitigating the risk of EHIs. The aims of this study were to (1) describe how the new evidence-based policy was developed and the data used in its design and (2) assess the performance of the new policy on EHI IRs between the prepolicy (PRE) and postpolicy (POST) periods.
METHODS
Participants
Data were collected for 6 consecutive football seasons (2009–2014) from 25 public and private interscholastic institutions that were member schools of the GHSA (Figure 1). Fall football seasons for the years 2009–2011 were designated as the PRE period and for the years 2012–2014 as the POST period. A number of considerations were used to identify the participating schools. First, all schools were required to have a full-time athletic trainer (AT) on site. Second, schools were selected to provide a representative sample both geographically and by school classification and enrollment. Therefore, schools were selected from among 5 geographic reporting regions in the state (ie, North, Metro [Atlanta], Central, Southeast, and Southwest), as determined by the Georgia Athletic Trainers' Association Executive Council. The size of each school was assessed based on the GHSA classification, ranging from A (smallest enrollment) to AAAAAA (largest enrollment) and included junior varsity and varsity athletes in grades 9 through 12. All regions were assigned an equal number of schools (n = 5) with equivalent enrollment numbers at the onset of the study. Every attempt was made to keep the number of participating schools and enrollments consistent per region. Two schools in the North and Central regions dropped out before the end of the 6-year study and were replaced with schools of equal enrollment, giving those 2 regions 7 schools each that participated at some point in the study.
Citation: Journal of Athletic Training 55, 7; 10.4085/1062-6050-542-18
Practice Variables
Practice variables were practice duration, practice day (eg, first, second), and session number if multiple sessions occurred in a single day.
Exertional Heat Illness and Athlete-Exposure Definitions
We defined EHIs by using the National Athletic Trainers' Association (NATA) position statement on EHI8 and applied the definitions throughout the entire 6-year study period. The position statement defined the various EHIs, including exercise-associated muscle cramps, heat syncope (HS), heat exhaustion (HE), exertional heat stroke, and exertional hyponatremia (Table 1). A reportable athlete-exposure (AE) followed the National Collegiate Athletic Association definition of an individual participating in 1 team session.9,10 A reportable EHI was an event determined by the AT to result in a loss of participation such that the athlete was not capable of returning to play during that practice. The AT for each participating institution was responsible for documenting all EHIs, AEs, and wet-bulb globe temperature (WBGT) measurements during the practice session. These data were uploaded to a centralized data-management system via a Web-based portal.
Environmental Data
We used WBGT to measure environmental heat stress for the state of Georgia. Environmental assessment based on the heat index was determined to be inadequate. The heat index is calculated from ambient air temperature and humidity, assuming that the measurements are taken in the shade (ie, no radiant heating) for a person who is 5 ft, 7 in (1.70 m) tall; 147 lb (66.15 kg); wearing long pants and a short-sleeved shirt; and walking at 3 mi/h (1.34 m/s).11 These assumptions do not represent football players or the practice conditions (eg, sun exposure and practice intensity) in which they engage. The WBGT is widely used in athletics as an accepted standard by the American College of Sports Medicine,12 Sports Medicine Australia,13 American Academy of Pediatrics,14 and US Department of Defense.15 The WBGT provides a more comprehensive measure of heat stress by including ambient air temperature, humidity, and radiant heat, which are important environmental factors influencing heat stress.8 It also implicitly accounts for wind speed, which influences the wet-bulb temperatures. As a strictly environmental measure, the WBGT must be coupled with activity modification. Therefore, the WBGT was used to determine equipment modifications, number of rest breaks, and duration of practice sessions, as indicated in Table 2. QuestTemp-34 instruments (model QT-34; Quest Technologies, Oconomowoc, WI) were supplied to all participating schools for environmental assessment. Every 2 years, all sensors were recalibrated by the manufacturer to ensure instrument reliability and accuracy. The QT-34 measures WBGT, which is based on 3 environmental assessments: ambient air or dry-bulb temperature (DB), wet-bulb temperature (WB), and globe temperature (G). The WBGT was calculated as a weighted average of the 3 temperature measurements16,17: WBGT = 0.7WB + 0.2G + 0.1DB. The WBGT monitor was placed on a tripod 36 in (91.44 cm) above the ground, adjacent to the practice field to best capture heat-exposure conditions. The WBGT monitor stored environmental data on an internal memory card that was downloaded and transmitted to the research team. The data were recorded every 15 minutes from the beginning to the end of a scheduled session. For analysis, the average WBGT for the session was used.
Procedures
Data were collected from the first official day of football practice (typically August 1 in the PRE period and July 25 in the POST period) until the last active calendar day in September. All schools adhered to the 2009–2011 GHSA heat and humidity policy in the PRE period and implemented the revised guidelines in the POST period. Both the environmental and EHI datasets were uploaded to a centralized database via a Web-based portal. The 2 datasets were merged and evaluated for accuracy; erroneous or duplicate data were removed.
Statistical Analyses
We recorded EHIs for all practice sessions. The data analyses focused on the more critical heat illnesses: HS, HE, and exertional heat stroke. During the 6-year study, no cases of exertional heat stroke were reported. Given the low numbers of HS and HE illnesses, these variables were combined to form 1 variable (HS/HE). The IRs were then calculated as HS/HE occurrences divided by 1000 AEs. The RRs of HS/HE IRs were used to evaluate the differences between the PRE and POST periods. We assessed RRs by GHSA WBGT categories to control for any differences in heat exposure during the 2 periods (Table 2).
The RR was computed as follows: \(\def\upalpha{\unicode[Times]{x3B1}}\)\(\def\upbeta{\unicode[Times]{x3B2}}\)\(\def\upgamma{\unicode[Times]{x3B3}}\)\(\def\updelta{\unicode[Times]{x3B4}}\)\(\def\upvarepsilon{\unicode[Times]{x3B5}}\)\(\def\upzeta{\unicode[Times]{x3B6}}\)\(\def\upeta{\unicode[Times]{x3B7}}\)\(\def\uptheta{\unicode[Times]{x3B8}}\)\(\def\upiota{\unicode[Times]{x3B9}}\)\(\def\upkappa{\unicode[Times]{x3BA}}\)\(\def\uplambda{\unicode[Times]{x3BB}}\)\(\def\upmu{\unicode[Times]{x3BC}}\)\(\def\upnu{\unicode[Times]{x3BD}}\)\(\def\upxi{\unicode[Times]{x3BE}}\)\(\def\upomicron{\unicode[Times]{x3BF}}\)\(\def\uppi{\unicode[Times]{x3C0}}\)\(\def\uprho{\unicode[Times]{x3C1}}\)\(\def\upsigma{\unicode[Times]{x3C3}}\)\(\def\uptau{\unicode[Times]{x3C4}}\)\(\def\upupsilon{\unicode[Times]{x3C5}}\)\(\def\upphi{\unicode[Times]{x3C6}}\)\(\def\upchi{\unicode[Times]{x3C7}}\)\(\def\uppsy{\unicode[Times]{x3C8}}\)\(\def\upomega{\unicode[Times]{x3C9}}\)\(\def\bialpha{\boldsymbol{\alpha}}\)\(\def\bibeta{\boldsymbol{\beta}}\)\(\def\bigamma{\boldsymbol{\gamma}}\)\(\def\bidelta{\boldsymbol{\delta}}\)\(\def\bivarepsilon{\boldsymbol{\varepsilon}}\)\(\def\bizeta{\boldsymbol{\zeta}}\)\(\def\bieta{\boldsymbol{\eta}}\)\(\def\bitheta{\boldsymbol{\theta}}\)\(\def\biiota{\boldsymbol{\iota}}\)\(\def\bikappa{\boldsymbol{\kappa}}\)\(\def\bilambda{\boldsymbol{\lambda}}\)\(\def\bimu{\boldsymbol{\mu}}\)\(\def\binu{\boldsymbol{\nu}}\)\(\def\bixi{\boldsymbol{\xi}}\)\(\def\biomicron{\boldsymbol{\micron}}\)\(\def\bipi{\boldsymbol{\pi}}\)\(\def\birho{\boldsymbol{\rho}}\)\(\def\bisigma{\boldsymbol{\sigma}}\)\(\def\bitau{\boldsymbol{\tau}}\)\(\def\biupsilon{\boldsymbol{\upsilon}}\)\(\def\biphi{\boldsymbol{\phi}}\)\(\def\bichi{\boldsymbol{\chi}}\)\(\def\bipsy{\boldsymbol{\psy}}\)\(\def\biomega{\boldsymbol{\omega}}\)\(\def\bupalpha{\bf{\alpha}}\)\(\def\bupbeta{\bf{\beta}}\)\(\def\bupgamma{\bf{\gamma}}\)\(\def\bupdelta{\bf{\delta}}\)\(\def\bupvarepsilon{\bf{\varepsilon}}\)\(\def\bupzeta{\bf{\zeta}}\)\(\def\bupeta{\bf{\eta}}\)\(\def\buptheta{\bf{\theta}}\)\(\def\bupiota{\bf{\iota}}\)\(\def\bupkappa{\bf{\kappa}}\)\(\def\buplambda{\bf{\lambda}}\)\(\def\bupmu{\bf{\mu}}\)\(\def\bupnu{\bf{\nu}}\)\(\def\bupxi{\bf{\xi}}\)\(\def\bupomicron{\bf{\micron}}\)\(\def\buppi{\bf{\pi}}\)\(\def\buprho{\bf{\rho}}\)\(\def\bupsigma{\bf{\sigma}}\)\(\def\buptau{\bf{\tau}}\)\(\def\bupupsilon{\bf{\upsilon}}\)\(\def\bupphi{\bf{\phi}}\)\(\def\bupchi{\bf{\chi}}\)\(\def\buppsy{\bf{\psy}}\)\(\def\bupomega{\bf{\omega}}\)\(\def\bGamma{\bf{\Gamma}}\)\(\def\bDelta{\bf{\Delta}}\)\(\def\bTheta{\bf{\Theta}}\)\(\def\bLambda{\bf{\Lambda}}\)\(\def\bXi{\bf{\Xi}}\)\(\def\bPi{\bf{\Pi}}\)\(\def\bSigma{\bf{\Sigma}}\)\(\def\bPhi{\bf{\Phi}}\)\(\def\bPsi{\bf{\Psi}}\)\(\def\bOmega{\bf{\Omega}}\)\begin{equation}{\rm{RR}} = {{{\rm{IR}}\_{\rm{POST}}} \over {{\rm{IR}}\_{\rm{PRE}}}}{\rm {.}}\end{equation}
The standard error (SE) and confidence intervals (CIs) were calculated according to Daly18 as follows: \begin{equation}{\rm{SE}}\left[ {\ln \left( {{\rm{RR}}} \right)} \right] = \sqrt {{1 \over a} + {1 \over c} - {1 \over {a + b}} - {1 \over {c + d}}} {\rm { ,}}\end{equation}where a is the number of HS/HE incidents in the POST period, c is the number of HS/HE incidents in the PRE period, a+b is the total AEs in the POST period, and c+d is the total AEs in the PRE period. The CIs were computed as follows: \begin{equation}{\rm{CI}} = {\rm{lnRR}} \ \pm \ Z \cdot {\rm{SE}}({\rm{lnRR}}){\rm {,}}\end{equation}where Z is 1.645 for the 90% CIs and 1.96 for the 95% CIs. We observed no HS or HE incidents in the POST period for WBGTs from 90.0°F (32.3°C) through 92.0°F (33.4°C) and, therefore, could not calculate an RR for that category.
RESULTS
Policy Development of the GHSA
At the request of the GHSA, we collected data for 3 years (PRE period) to better understand the EHI risk among high school football players. In March 2012, a heat summit attended by members of the GHSA and experts in the EHI field was held on the campus of The University of Georgia to examine the findings. The key variables considered in developing a revised GHSA heat and humidity policy were practice day, practice duration, and WBGT measures, which had discernable effects on the EHI incidence. The first 5 days accounted for almost half of all HS/HE incidents over the 3-year PRE period (Figure 2). Additionally, we observed that, in the first 5 days, the HS/HE IRs doubled for practices lasting >2 hours and tripled for those lasting ≥3 hours compared with practices lasting <2 hours (Figure 3). On days 6 through 10, players could practice 30 minutes longer before a large increase in the HS/HE IR occurred (ie, 91–120 minutes on days 1–5 and 121–150 minutes on days 6–10; Figure 3). We also observed greater HS/HE IRs for practices lasting >3.5 hours for days 6 through 10 than for days 1 through 5 but speculate this may have been related to athletes wearing full equipment, which was allowed after day 5 in the original GHSA heat policy. We believe the greater HS/HE IRs for practices lasting >3.5 hours were higher for days 6 through 10 than for days 1 through 5 because the athletes were wearing full equipment and had no limitations on practice length or frequency, as allowed after day 5 in the original GHSA heat policy. Ultimately, we determined that practice sessions 1 through 5 should be no longer than 2 hours to mitigate EHI occurrences and allow for acclimatization. This period is consistent with the NATA acclimatization guidelines.19
Citation: Journal of Athletic Training 55, 7; 10.4085/1062-6050-542-18
Citation: Journal of Athletic Training 55, 7; 10.4085/1062-6050-542-18
Weather-based activity-modification thresholds were guided by the relationship between HS/HE IRs and WBGT. We reviewed HS/HE IRs in 1°F WBGT increments from <82°F (<27.8°C) to 92°F (33.4°C). For WBGTs of <82°F (<27.8°C), we found HS/HE IRs of <0.6/1000 AEs. As the WBGT increased from 82°F (27.8°C) to 86°F (30.0°C), we demonstrated greater IRs from 1.0 to 1.3/1000 AEs and a notable jump to >2.0/1000 AEs for WBGTs from 87°F (30.6°C) to 90°F (32.3°C). We observed a decrease in HS/HE IRs in the 90°F (32.3°C) to 92°F (33.4°C) category relative to the 87°F (30.6°C) to 89°F (31.7°C) category, which is likely due to a decrease in exposures, as many schools canceled outdoor practices. Therefore, we developed thresholds as shown in Table 2. Within these categories, we incorporated the recommendations set forth in the NATA position statement on fluid replacement for the physically active20 and research conducted with US Marine Corps recruit trainees15 to establish work-to-rest ratios for our WBGT categories. For example, three 3-minute rest breaks per hour were required for WBGTs from 82°F (27.8°C) to 86.9°F (30.5°C), with breaks increasing to 4 minutes per hour for WBGTs from 87°F (30.6°C) to 89.9°F (32.2°C).
Comparison of EHIs in the PRE Versus POST Policy Periods
We evaluated the HS/HE IRs in the PRE versus POST periods by WBGT category (Figure 4A). In all, 214 HS/HE incidents (172 PRE, 42 POST) occurred during 341 348 AEs (178 230 PRE, 163 118 POST). The HS/HE IRs in the PRE period increased by GHSA WBGT category from approximately 0.44/1000 AEs for WBGTs of <82°F (<27.8°C) to 0.95/1000 AEs in the 82°F (27.8°C) to 86.9°F (30.5°C) category and up to 2.10/1000 AEs in the 87°F (30.6°C) to 89.9°F (32.2°C) category. The HS/HE IRs for WBGTs from 90°F (32.3°C) to 92°F (33.4°C) were lower than those from 82°F (27.8°C) to 86°F (30.0°C) but had the next highest HS/HE rate at 1.70/1000 AEs. This result may be explained by reduced activity levels for some schools or even cancelled practice sessions when the WBGT was >90°F (32.3°C). The HS/HE IRs were uniformly lower in the POST period, with all IRs at <1.0/1000 AEs. The HS/HE IRs decreased in the POST relative to the PRE period by 35% to 100%, depending on the WBGT category (Figure 4B). Next, we assessed these changes in HS/HE IRs by using RRs and associated CIs (Table 3). An RR <1 indicated that the new policy reduced IRs. The RRs in the <82°F (27.8°C) and from 87°F (30.6°C) to 89.9°F (32.2°C) categories were 0.29 and 0.23, respectively, and were different at the 95% level. The RR in the 82.0°F (27.8°C) to 86.9°F (30.5°C) WBGT category was slightly greater (RR = 0.65) and different at the 90% level.
Citation: Journal of Athletic Training 55, 7; 10.4085/1062-6050-542-18
DISCUSSION
Heat-illness prevention strategies have been incorporated to successfully mitigate EHIs among US military personnel, as well as collegiate and professional athletes.15,21–23 To our knowledge, this was the first longitudinal study to examine how policy guidelines for high school athletic practices can be modified using evidence-based research and the resultant reduction in HS/HE IRs. With recent data showing a dramatic increase in US deaths due to exertional heat stroke over the past 30 years,1,24–26 this investigation was necessary to identify circumstances in which the EHI risk was elevated and determine mitigation strategies to prevent catastrophic EHIs among the interscholastic population. In earlier epidemiologic studies, researchers8,24–29 observed EHIs among interscholastic athletes, but none have evaluated the effect of practice policy changes on IRs. In the Translating Research into Injury Prevention Practice (TRIPP) model, Finch30 proposed that a well-developed injury-prevention program be based on a critical analysis of injury-surveillance data (TRIPP stage 1) that allows elucidation of factors associated with injury incidence (TRIPP stage 2). Through this project, in which the EHI risk from environmental factors, behavioral patterns, and organizational rules was evaluated, Finch30 identified where the risks were greatest and which variables could be changed or manipulated to reduce heat-related illnesses among participants.
Using data collected in the PRE period (eg, WBGT, practice day, and practice duration), we highlighted potential causes of EHIs and offered insight into ways to mitigate EHI risks beyond what is considered current best practice (TRIPP stage 3; Table 4).8,12–14 Our study, with approximately 50% of all HS/HEs occurring within the first 5 practice days, fully supports the importance of a 5-day acclimatization period, as indicated in the NATA's position statement on EHI8 (Figure 2). Furthermore, we found that HS/HE IRs increased markedly after 2 hours of continuous activity. Our results were consistent with the results of Tripp et al,31 who reported that long, multihour practices led to higher EHI rates among high school football players in Florida. Therefore, practice duration should be considered when developing practice policies for the 5-day acclimatization period. The last major consideration from the PRE data was the association of EHIs and weather conditions: HS/HE IRs were observed in all GHSA WBGT categories but increased substantially in the 87.0°F (30.6°C) to 89.9°F (32.2°C) category. Such findings support the importance of adjusting work-to-rest ratios and activity based on environmental conditions.32 Another unique part of our work was that the risks and subsequent mitigation strategies identified from the PRE period were addressed and tested in the POST period (TRIPP stage 4).30 Indeed, HS/HE IRs were uniformly lower in the POST period, with all IRs at <1.0/1000 AEs, suggesting success from the heat policy changes within the studied cohort. The last stage of TRIPP (stage 6) is to evaluate the effectiveness of heat policies in a larger context.30 The effectiveness of the 2009 NATA position statement on heat acclimatization was evaluated by Kerr et al,33 who compared states that mandated or did not mandate the heat-acclimatization recommendations. They reported EHI rates were lower in states that mandated the recommendations (adjusted IR ratio = 0.45; 95% CI = 0.23, 0.87).33 Similar analyses should be conducted in the future to evaluate the effectiveness of WBGT-based activity-modification guidelines in regions outside of Georgia that experience high EHI rates during interscholastic sport activity in the summer months.
Finally, a number of policy factors led to the widespread use of the policy and ultimately a reduction in EHIs among high school football players. It was important that the GHSA required all schools to adhere to a uniform heat-safety policy. Kerr et al33 noted that the use of exertional heat-stroke management strategies was greater in schools with state-mandated guidelines. In addition, experience from implementing concussion policies described by Lowrey et al34 indicated that state mandates and education are necessary but not sufficient; an enforcement mechanism is also needed to ensure compliance. In Georgia, the GHSA has the clear enforcement authority and may fine schools up to $2500 if practices do not conform to guidelines.35
CONCLUSIONS
We discussed the process by which the GHSA adopted a data-driven heat policy. Using results from a 3-year study (2009–2011) of HS/HE IRs among high school football players, the GHSA revised its policy to mandate a 5-day acclimatization period with no practices exceeding 2 hours and using WBGT-based activity-modification categories. A comparison of the effectiveness of this policy was undertaken for a subsequent 3-year period (2012–2014). The HS/HE IRs decreased by 35% to 100%, depending on the WBGT category. Indeed, since the implementation of the new heat policy (2012–2018), no heat-related deaths among GHSA schools have been recorded during fall football practice sessions. Although it is not possible to prevent all EHIs and catastrophic events, our data were used to help develop a highly effective approach for mitigating the risk from heat-related illness. Moving forward, we hope that both the process of close collaboration with stakeholders in policy development and the final evidence-based heat guidelines can be used as a model for other state athletic organizations.
Georgia High School Association regions (North, Metro, Central, Southeast, and Southwest) and participating high schools (circles).
Cumulative heat-syncope and heat-exhaustion incidents (percentages) over the first 20 practice days during the prepolicy period.
Heat-syncope and heat-exhaustion illness rate per 1000 athlete-exposures (AEs) during practice days 1 to 5 and 6 to 10 in the prepolicy period.
Comparison of, A, overall heat-syncope and heat-exhaustion illness rates in the prepolicy and postpolicy periods and, B, percentage of decrease in heat-syncope and heat-exhaustion illness rates in the postpolicy period relative to the prepolicy period.
Contributor Notes