Tornadoes are severe wind storms that produce forceful rotating winds and form funnel-shaped vortexes1. In Canada, the peak of the tornado season is between June and August2. Predominantly, Canadian tornadoes have maximum wind speeds of less than 180 km/h, but a small number of them can be substantially stronger and have devastating impact wherever they touch down2.
Goderich, a town located in Huron County in the Canadian province of Ontario, is located on the eastern shore of Lake Huron. At the time of the tornado, the town had 7521 inhabitants3. A powerful and violent F3 tornado passed through Goderich around 4.00 pm on Sunday, 21 August 20114. Wind speeds reached between 250 and 300 km/h4. At its widest, over downtown, the tornado was estimated to be 1.5 km across, and its path was an estimated 20 km long4. The tornado caused devastating damage to the town's port and historic downtown center, as well as to several blocks of residential homes. Forty people were injured and one person was killed by Ontario's strongest tornado since 19964,5.
Freedy and Simpson estimated that the use of primary healthcare services typically increases for 12 or more months following a major disaster7. However, the acute and subacute impacts of tornadoes in the medium-term, as in the 30-day period on a community hospital's emergency department (ED), close to the tornado strike zone, have not been investigated, to date. During this time period following a disaster, outside sources of help might be unavailable or unreliable6, particularly in a rural area, so the availability and functioning of the local ED is crucial to a community's wellbeing. It would be expected that the nature and quantity of ED visits during the 30 days following a tornado may be altered as compared to a similar 30-day period not following a natural disaster. Approximately 80 tornadoes are reported in Canada each year, and Southern Ontario is considered a high-risk zone19, so it is very possible that a disaster like this could affect another community in this region in the future. Given the impact of tornadoes, an understanding of ED resource requirements to respond to such disasters in the medium term, as well as the short- and long-term, is paramount. Obtaining a greater understanding of what resources are required following these events could better prepare both healthcare and emergency relief teams to provide better access to the services that are most needed.
In this study, the utilization of the ED services of the Alexandra Marine and General Hospital (AMGH) in Goderich, the closest hospital to the Goderich Tornado area, was measured to determine the urgent medical needs of a rural Southwestern Ontario community, affected by a tornado, during the 30 days following the disaster.
Informal interviews with physicians, who worked in the AMGH ED during the 30-day period after the tornado, generated the following hypotheses for the research. In the 30-day period following the tornado, medical conditions presented to the ED would differ from usual presentations at that time of year, reflecting the types of injury expected to be a consequence of the hazards presented by the tornado event and the related disruption of community services. For example, increased rates of soft tissue injuries, laceration and contaminated wounds, bee stings, fractures, acute stress reaction, alcohol abuse, anxiety, depression, and failure to cope at home were expected. Also anticipated was the need for follow-up care and requests to refill medications lost or destroyed during the tornado, particularly for the reason that physicians' practices in the community were inaccessible after the tornado.
A retrospective medical chart review of all the patients who presented to the AMGH emergency department in the first 30 days following the tornado, between 21 August 2011 and 20 September 2011 (known as the After Tornado 2011 group), was conducted. Data, including age and gender (demographic variables) and diagnoses (dependent variables), were collected on all patients who visited the ED during the study timeframe. In addition, two control groups were established: Before Tornado 2011 and Seasonal 2010. The Before Tornado 2011 group data included medical diagnoses and demographic data of all patients who presented to the ED in the 30 days prior to the event, between 22 July and 21 August 2011 (primary control group). The Seasonal 2010 group data were for all patient encounters made in the corresponding time period in the previous year, between 21 August 2010 and 20 September 2010, to establish whether the changes that occurred after the tornado were in any way related to the time of year in which the tornado had occurred, rather than to the event itself.
The International Classification of Diseases, 10th Revision (ICD-10) was used to code the diagnoses to standardize the data20. ICD-10 coding system breaks down patients' diagnoses into 26 categories (based on similar diagnoses amongst the categories) that are designated by a letter of the alphabet (A-Z)20. ICD-10 diagnostic criteria comparisons did not include the diagnoses of those patients who left the ED without being seen (their diagnoses were not available).
A χ2 test, assuming that equal proportions were expected during each period, was used to compare the total number of patients who visited the ED in each of the three time periods. A one-way analysis of variance (ANOVA) test was used for among-group age comparisons. A Dunnett's t-test21 was used to compare the two control time periods against the 30-day period following the tornado. For gender, a χ2 test was used to make among-group comparisons. Among-group comparisons of individual alphabetic ICD-10 categories were made using either a χ2 test or, where applicable, a Fisher's exact test22. When the overall ICD-10 alphabetic categories comparisons were statistically significant, the After Tornado 2011 group was compared with each of the Before Tornado 2011 and Seasonal 2010 groups with a Bonferroni correction. ICD-10 categories, in which difference in the frequency of diagnoses showed significance, were further subdivided to identify particular diagnoses or groups of diagnoses that were responsible for this significance. Among-group comparisons of subcategories were made using either χ2 test or, where applicable, Fisher's exact test with a Bonferroni correction for making pairwise comparisons.
All statistical analyses were conducted using Statistical Analysis System software v9.3 (SAS Institute, v9.3; http://www.sas.com). Hypothesis tests were conducted using a two-tailed level of significance, and results were declared significant at the 5% critical level (p<0.05).
Ethics approval was obtained from the Health Sciences Research Ethics Board of the University of Western Ontario (#18699E).
The number and demographic characteristics of patients presenting in each of the three time periods are presented in Table 3. The number of patients visiting the ED differed across the time periods (p<0.001). Significantly fewer patients visited the ED after the tornado (After Tornado 2011 group) than presented to the ED before the tornado in 2011 (Before Tornado 2011 group - primary control group), and in the same calendar period in 2010 (2010 Seasonal control group). Regarding demographic characteristics, there were differences across the three time periods in terms of age (p<0.001), with patients visiting the ED following the tornado being significantly older than those in the two control groups. Although there were proportionally more males presenting following the tornado in 2011, the difference was not significant (p=0.264).
Table 3: Comparison of demographics and numbers of Alexandra Marine and General Hospital emergency department visits across three time periods
The ICD-10 categorical diagnoses of patients who presented to the ED between 21 August and 20 September 2011 and involved in the primary and seasonal control groups are presented in Table 4.
Table 4: Comparison of ICD-10 category diagnoses among three time periods
Based on the study's grouped ICD-10 coding system, five diagnostic categories were identified as significant across all three study time periods. They were A-B, H, R, W-X, and Y-Z. ICD-10 categories that were found to be statistically significant were further subdivided to particular diagnoses or groups of diagnoses as shown in in Tables 5 to 10.
ICD-10 category A-B included all cases of bacterial, viral, fungal, and parasitic infections. This category was further subdivided. After the tornado, it was noted that the percentage of patients diagnosed with sexually transmitted infections was proportionally greater than that of both control groups, and the percentage of skin infections was proportionally lower. However, there was no evidence that the proportions reported with these particular diagnoses significantly differed across the three time periods (p=0.450, Table 5).
Table 5: Distribution of diagnoses ICD-10 categories A-B among the three time periods
Category H included all cases of ear and eye complaints. Significantly fewer of these cases presented to the ED after the tornado in 2011 than in both the primary and seasonal control periods. This category is further subdivided in Table 6 to determine if there was a difference in the proportions of any particular diagnoses within this category. Relatively fewer trauma-related eye complaints, more non-trauma related eye complaints, and more non-infection related ear diseases were identified after the tornado than in both the primary and the seasonal control periods. However, the difference in proportions of cases reporting with ICD-10 category H was not statistically significant across the three time periods (p=0.241).
Table 6: Distribution of diagnoses ICD-10 categories H among the three time periods
Category R included symptoms, signs, abnormal results of clinical or other investigative procedures, and ill-defined conditions for which classifiable diagnoses were not recorded elsewhere. Practically all diagnoses in category R could be designated as 'not otherwise specified', 'unknown etiology', or 'transient'. Breakdown of the R category revealed that the proportions of cases reported with the same category differed across the three time periods (p=0.030, Table 7). Although these proportions did not differ significantly between the After Tornado 2011 and the Before Tornado 2011 groups they did differ significantly between the After Tornado 2011 and Seasonal 2010 groups, with a greater proportion of cases of undiagnosed general and medical conditions related to circulatory and respiratory systems being observed in the After Tornado 2011 group.
Table 7: Distribution of diagnoses ICD-10 categories R among the three time periods
Categories W and X contained all cases of accidental injury by external causes, including insect and animal bites, falls and other injuries. The proportions of particular diagnoses, which were consistent with category W and X, differed significantly across the three time periods (p=0.009, Table 8). Although the proportions did not differ significantly between the After Tornado 2011 and the Before Tornado 2011 groups, there were significantly higher proportions of insect and animal bites in the After Tornado 2011 group than in the Seasonal 2010 group. Conversely, greater proportions of other injuries (particularly falls) were identified in the Seasonal 2010 group than in the two groups in 2011.
Table 8: Distribution of diagnoses ICD-10 categories W-X among the three time periods
Category Y and Z included all visits primarily seeking various health services, including medication administration, laboratory tests, and follow-up visits. These services are further subdivided in Table 9. Overall there was a difference in the proportions across the three time periods (p<0.001). The proportions of particular services included in Category Y and Z did not differ significantly between the After Tornado 2011 and the Before Tornado 2011 groups. However, there were significantly greater proportions of patients who requested prescription refills, medication administration, or needed medical procedures in the After Tornado 2011 group than in the Seasonal 2010 group.
Table 9: Distribution of diagnoses ICD-10 categories Y-Z among the three time periods
Finally, it should be noted that only one patient left the ED without being seen by a healthcare professional following the tornado in 2011. This number was less than what was observed in both the primary and seasonal control periods (p<0.001, Table 10).
Table 10: Patient who left the ED without being seen by a healthcare professional
Overall, the study findings were unexpected and are, therefore, an important addition to the current literature. According to previous literature reports, the hospitals closest to a disaster area are often compromised because of structural damage and are easily overwhelmed by accepting a large number of victims19. Fortunately, the AMGH was north of the tornado's trajectory in Goderich and sustained limited damage. In addition, the hospital's generator allowed the AMGH to continue functioning during the 32-hour electrical shortage experienced in the surrounding region. Considering the magnitude of the destruction in Goderich, it is remarkable that the tornado resulted in only one death and did not result in a significant increase in the presentation of trauma or infectious illness in the days following the event. In fact, the total volume of patients that presented to the ED following the tornado was significantly lower than what would be expected for that time of year. A related finding was that only one individual who presented to the ED left without being seen, and this number was unmatched in both our study's primary and seasonal control periods. This suggests that the patients may have actually received more efficient and timely treatment following the tornado.
There are multiple possible explanations for the reduced number of patients presenting to the ED. First, there are four other hospitals within 50 km of Goderich, the nearest of which is only 20 km away, in Clinton, Ontario. It is possible that less critical patients decided to attend one of these neighboring facilities in order to reduce the burden on their own hospital. Indeed, as a consequence of road closures and debris left in the wake of the tornado, those living in the south end of town may actually have found it easier to travel to another community than to navigate through the debris left in the wake of the tornado to get to the north end of Goderich, where the AMGH is located. These obstructions lasted for several weeks after the disaster. Second, it is possible that the decrease in the number of tourists in Goderich after the tornado played a role in fewer visits to the ED. Tourists, who generally flood the Goderich area during the summer, could not get to the town because of the blocked roads. The Goderich Tourism Information Center received 10 350 calls and visits in 2011. This number was significantly lower than the 13 582 calls and visits it received in 2010 (23.8% reduction)4. Third, it is also possible that those who were not critically ill decided not to seek any treatment. Last, it might be that the Goderich Tornado did not cause a significant impact on the residents' health, or significantly change the demand for medical care in the community. These four hypotheses cannot be confirmed without determining the changes in patient volume and reasons for presenting to the ED observed in neighboring hospitals in the area during the study timeframe.
Only one individual who presented to the emergency department left without being seen. This is consistent with other research on ED use indicating that delay in assessment is the most common reason for patients to leave an ED without being seen23. In the timeframe of the study, the total number of patients presenting was significantly less than for primary and seasonal control periods, and the department's staffing was enhanced as per AMGH emergency department disaster protocols. This may have resulted in shorter wait times, and hence fewer patients left without being seen. It is also possible that those patients who did visit the ED following the tornado were more urgently in need of treatment than the patients in the control groups and therefore less likely to leave. This conclusion is further supported by the finding that the age of patients presenting to the hospital after the tornado was significantly greater than the age of those presenting prior to the storm. It has been previously identified that both minor and severe morbidity rates following a tornado increase with age, and this result is independent of the propensity for elderly patients to seek medical attention9. This is believed to be due to the greater susceptibility of elderly people to trauma, decreased mobility, and increased number of co-morbid conditions9. Thus, it is likely that the cohort presenting after the tornado was older because it represented those most in need.
Carter et al. reported that gastroenteritis, self-limited viral syndrome, and vector-borne illness are common post-disaster health problems8. Interestingly in this case, there was no significant increase in these medical conditions. This situation is likely explained by the fact that despite the significant destruction caused to the town's electrical utility and infrastructure, no problems were reported with the tap water supply or sewer system4. Access to clean water and sanitation is crucial for prevention of water contamination and thus water-borne and other communicable infectious diseases24.
Similarly, eye- and ear-related concerns and infectious and parasitic diseases all significantly decreased following the tornado compared to the control periods. However, this significance was not apparent when broken down into infectious and parasitic illnesses and ear and eye diseases. Based on the research data, the Goderich Tornado did not result in a significant infectious disease outbreak, traumatic and non-traumatic eye or ear problems for the affected population.
Injuries were hypothesized to be the category with the greatest significant increase in emergency visits following the tornado. Although injured people did present to the ED after the storm, in greater numbers than prior to the tornado, it was not higher than what would be expected for that time of year as suggested by the seasonal control. This result may be explained by the fact that injuries are known to be more prevalent during the summer months than at other times of the year13,25-30. Thus, it is possible that this increase was in keeping with the normal volume of injuries during the time of year in which the tornado occurred.
Cases presenting to the ED involving external causes of injuries, including insect and animal bites, were not significantly greater following the tornado. Statistical analysis showed no difference in those medical problems between the After Tornado 2011 group and the Before Tornado 2011 group; however, in the After Tornado 2011 group there were a significantly higher proportion of insect and animal bites than in the Seasonal 2010 group. This result differs from those reported in previous literature, which suggested that the displacement of domesticated animals, rats, insects, snakes, and reptiles following a natural disaster often results in an increased incidence in bites31-33. In particular, animal bites are largely due to volunteers helping to return displaced animals to their homes. Indeed, it is likely that this displacement also accounts for the increased number of insect bites that occur following a tornado. Based on previous literature, almost half of all the volunteers on clean-up crews following a disaster in the USA are afflicted by insect bites34. Given the extreme damage done to the town's flora, the season in which the tornado occurred, and the great number of individuals who volunteered to assist with the clean-up efforts, it is difficult to explain the lower-than-expected number of citizens who experienced insect and animal bites in the period following the storm. Once again, it is likely that the ED only witnessed the most extreme reactions to these bites.
The present research revealed a significant increase in the category of undiagnosed general conditions and the category of circulatory and respiratory system conditions compared with the Seasonal 2010 group. These findings coincide with previously reported observations that medically unexplained physical symptoms are common following a disaster7. These unexplained or undiagnosed symptoms are also associated with mental health problems (such as depression, post-traumatic stress disorder, and other anxiety disorders) or with somatic complaints without organic cause7.
Significantly more patients visited the ED following the tornado for various health services normally provided in a family practice setting, particularly for medication requests. This was expected as it has been previously reported that people who seek relief at shelters following a disaster because of the severe damage inflicted on their homes often do not bring their medications with them7,14. Furthermore, when prescriptions are retained in such circumstances, it is possible that the local pharmacy's supplies are insufficient to fulfill the population's increased demands following a destructive storm27. Thus, healthcare facilities, as well as pharmacies, should anticipate this increased need for medications following a disaster and make the appropriate adjustments to address this need as much as possible.
The type of medium-term demands on an ED following a severe weather event will vary depending on predominant health issues in the area prior to the event, the type of injuries subsequent to the event, and the impact of the event on community infrastructure and resources. In this case, when other primary healthcare delivery systems were disrupted in a small community, an intact ED was called upon to provide and coordinate a wider range of healthcare services than they normally would.
The authors would like to acknowledge the contributions of Connie McMillan, Nancy Larabee, Heather Skirten, Wendy MacKenzie, Joanne McCallum, Mary Schreinert, Jennifer Beaudry, Alana Ross, and Alice Koopmans to the study's data collection. The authors would like to thank the Gateway Rural Health Research Institute for support and assistance with conducting the study.
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