Evacuation decisions in a chemical air pollution incident: cross sectional survey

Questionnaire

We modified the questionnaire from model questionnaires produced by the Chemical Incident Response Service (Guy's and St Thomas' Hospital, London) and National Focus for Chemical Incidents (Department of Health, Cardiff). The questions related to demographic factors; places of residence over the 48 hour period after the incident; time spent outdoors; and likely symptoms of ill health and existing health status, such as medical conditions and smoking habits. We asked respondents to report health symptoms if they had occurred at all and if they persisted at the time of completion of the questionnaire (persistent symptoms). The questionnaire went out at the end of the first week of the incident, and a reminder was delivered at six weeks through an article in the local newspaper. A repeat questionnaire with a reminder went to people who had not replied at two months.

Defining exposure and outcome

We identified the exposed population on the map by drawing a semicircular arc from the incident site in the direction of the greatest density of smoke, which we established by chemical meteorological data. Where the arc intercepted small streets, we either included or excluded the whole street, whichever the greater proportion. The maximum distance from the factory that was permissible for inclusion in the study was 1000 metres.

Since we did not have any direct measures of individual exposure we used two proxy measures: distance of the place of residence from the factory and an objective measure of relative exposure at each of the places where the respondents stayed. We used easting (distance east) and northing (distance north) grid references for each postcode including the factory, to calculate the distances in straight lines (in metres) by using a formula based on the Pythagoras theorem. For the objective exposure, the Met Office undertook atmospheric dispersion modelling, using the Numerical Atmospheric dispersion Modelling Environment (NAME III).8 We used real time meteorological data from the nearby meteorological station to run the model to predict relative concentrations of pollutants over the 48 hour duration of the incident. We swapped the relative concentrations of pollutants at each of the postcodes on the geographical information system ArcView, version 3.0 (ESRI, Redlands, California, USA) for two time frames (the initial six hours and 48 hours); six hours being the median time to evacuation.

For our analyses, we considered the exposure score for the initial six hours as the primary exposure, since it represents the actual exposure before the intervention, on which the decision was based. We also calculated a cumulative exposure score over 48 hours by adding exposures over time spent by the participant at each of the postcodes. Of the people who were evacuated, roughly two thirds went to the designated evacuation site (leisure centre), and the remaining third went to other convenient places, such as homes of friends and family. We asked people who were evacuated to provide the address and postcode of the place where they stayed, if different from the leisure centre, and substituted these postcodes accordingly. If the evacuation postcode was also in the exposed area then we used the exposure score for that postcode; otherwise they were given a null value. The cumulative, 48 hour exposure score is difficult to interpret as it constitutes an inherent element of intervention, in addition to the participants being generally indoors (and so not necessarily exposed to that level of pollutants in the environment).

Acute symptoms produced by chemical smoke exposure are generally similar to those caused by common viral respiratory illnesses. Because of this lack of specificity of symptoms, we decided to define cases on the basis of number of symptoms. We established baseline prevalence of symptoms for the period (winter) by simultaneously administering the questionnaire to a random 10% sample (n = 1000) of residents from a neighbouring town with a similar demographic and socioeconomic profile. We calculated the mean symptom score (total number of symptoms per person) for the residents of the unexposed town and regarded all those with a symptom score greater than 2 standard deviations of the mean as cases. We defined persistent cases similarly, but with symptoms persisting at the time of completing the questionnaire (which was at least two weeks from the time of the incident). The symptoms considered were runny eyes, swollen eyelids, sore throat or nose, shortness of breath, cough, skin rash, skin burns, nausea, vomiting, abdominal pain, diarrhoea, fever, wheezing or asthma, palpitations, headache, lightheadedness, and blurred vision. We gave each symptom an equal weighting of one (present) or zero (absent).

Data from environmental sampling and healthcare services

Environmental samples, based on the expected emissions, were taken repeatedly over a 48 hour period. Among the gaseous emissions, samples we tested for included hydrogen chloride, hydrogen cyanide, hydrogen fluoride, isocyanides, and styrene. We used chemical tubes (Draeger, Aqua Air Industries, Louisiana, US) to carry out these tests. The first air testing started some 12 hours after onset of the fire, inside and immediately outside the burning factory, in dense acrid smoke, and 100 metres downwind within the smoke plume. Other environmental investigations included tests for acidity of surface water; asbestos fibre counts in air and on hard surfaces; and levels of dioxins and furans in soil, grass, debris, and water samples. We collected information about health effects from people seeking medical help as a result of exposure. We collected information from all relevant sources of medical advice including ambulance and emergency departments as well as the local general practitioners and telephone helplines.

Fig 1

Flow of participants through the study

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Statistical analysis

We used multiple logistic regression to estimate the likelihood of a person becoming a case for each of the independent risk factors. We used Stata, version 8 (StataCorp, College Station, Texas, USA), for our analyses.

Environmental sampling

The first air testing carried out 12 hours after the start of the incident, inside and immediately outside the burning factory, in dense acrid smoke showed the maximum concentration of 5 parts per million of hydrochloric acid. Concentrations of other gases tested were less than 1 part per million. Tests 100 metres downwind within the smoke plume detected 1 part per million of hydrochloric acid and other gases below detection levels. Further tests carried out at various distances and timings over the next two days found readings below detection levels. Tests for the pH carried out on puddle water in the area showed neutral readings. Counts for airborne asbestos fibres and other bulk and swab samples did not show any evidence of asbestos. Samples tested for dioxins and furans showed concentrations at or below those expected under normal circumstances.

Health effects identified from people seeking medical help as a result of the exposure

Information available from medical inquiries included emergency services personnel (n = 31) and local residents (n = 23). The symptoms described were consistent with the mild symptoms described above, such as sore throat, cough, runny eyes, and skin irritation. Two people were admitted to hospital, one for acute attack of bronchial asthma and the other for suspected angina. Both had been evacuated and were admitted at the time of evacuation.

Limitations of the study

The study has some limitations. An important concern is that the level and nature of smoke exposure could have been different between the evacuated and sheltered groups of residents. We have tried to estimate the exposure in two different ways: distance of the residence from the factory and atmospheric dispersion modelling of the pollutants by using the NAME III model. This model was originally designed for dispersion modelling of radioactive material, but it can also be used to model dispersion of chemicals in the atmosphere.8 Dispersion modelling of this type has some uncertainties—for example, we had no information about thermal buoyancy of the plume or the exact nature of the pollutants released. The NAME model, however, is widely used for dispersion modelling, and, given the closeness of the meteorological station, the results would be expected to be of reasonable accuracy.8 This type of work represents an improvement on standard methods of assessing exposure, such as simply using distance as a proxy for exposure.9^–11

Self reported symptoms in the people who had been evacuated could be the result of a combination of physical effects of the smoke and the psychological impact of evacuation.12 13 We did not include any instruments to assess the psychological impact of the incident and so were unable to separate the two. However, self reported symptoms could be considered appropriate in this context where the perception of ill health is as relevant as physical ill health itself, especially with regards to long term psychological impact and anxiety. This study has looked at early health outcomes only, which may differ from long term health outcomes. Clustering of the responses and health effects among members of the same household is a limitation of this study, but we did not have the required data to incorporate in the analyses. Results, in one previous study that accounted for clustering, remained largely unaltered.10

Comparison with other studies

No other comparative studies are available to which we could relate our findings. Previous studies looking at the health effects of chemical incidents have entailed either sheltering or evacuation.10 11 14^–16 In one previous study of a fire in a plastics factory, the residents were advised to shelter and did not report any serious side effects.14 The theoretical basis for expert advice favouring sheltering over evacuation is that protection offered by barriers between the exposure and the population is at least as effective as the protection offered by increasing the distance between the exposure and the population—that is, evacuation. Evacuations generally entail taking the population out of the barrier zone and moving them through a much higher exposure, albeit for a shorter duration. Our results show that direct exposure to smoke is a more important determinant of ill health than the cumulative exposure to smoke and these results are consistent with those reported from other studies.6 11

Reasons for evacuation

Despite the expert guidance, an unacceptably high proportion of chemical incidents worldwide result in evacuations. Possible reasons for these include an instinctive response on the behalf of emergency services to evacuate populations in danger, and the preference to “play it safe” by first responders.6 Initial decisions are often taken under very stressful conditions that do not allow time for reflection. Lack of experience has also been proposed as a possible reason since greater frequency of evacuations is reported from areas where chemical incidents are uncommon.17 Another common factor is the delay in getting appropriate public and environmental health advice.

Conclusion

Sheltering may have been a better protective action than evacuation in this chemical incident. Although our study has several limitations, it is based on a real event. These results are consistent with the expert view that favours sheltering as the mode of action in serious chemical air pollution incidents. Evacuations carry their own risks and resource implications. Increased awareness among emergency services may help to reduce unnecessary evacuations in the future.