effect on major accidents

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1 An Investigation into a weekend (or bank hoiday) effect on major accidents Nicoa C. Heaey 1 and Andrew G. Rushton 2 1 Heath and Safety Laboratory, Harpur Hi, Buxton, Derbyshire, SK17 9JN 2 Hazardous Instaations Directorate, Heath and Safety Executive, Redgrave Court, Boote, L2 7HS Crown Copyright 28. This artice is pubished with the permission of the controer of HMSO and the Queen s Printer for Scotand A number of recent and high profie accidents in the process industries have occurred on bank hoidays or at weekends. This has ed to the suggestion that there was a potentia for higher numbers of accidents, particuary those cassed as major accidents, to occur on a bank hoiday or a weekend. If this perception shoud represent an actua effect, there coud be serious impications for the work of the safety reguators of major hazard industries and the industries themseves. The Heath and Safety Laboratory (HSL), was commissioned by the Heath and Safety Executive (HSE) to anayse a seection of data on major accidents. The aim of the anaysis was to identify whether there was evidence of a weekend or bank hoiday increase in the numbers of major accidents. Attempts were made to normaise the data to account for the reduced operations and staffing eves sometimes present at process industry sites on weekends or bank hoidays. Unfortunatey, sufficient data coud not be found to normaise the accident data in these respects. Main findings are: Anaysis of the aggregated data and sub-sets consistenty faied to provide evidence for either a weekend or bank hoiday increase in the number of major accidents. Fairy consistent evidence was seen of a mid-week peak and a weekend dip in the number of accidents reported. Chi-Square tests consistenty showed either no significant difference, or significanty more accidents occurring on a weekday in comparison with accidents occurring on a Saturday, Sunday or bank hoiday. In essence, the resuts show either no evidence of an effect, or that the effect is too weak to stand out over other factors within the data avaiabe. INTRODUCTION Unfortunatey, major accidents invoving dangerous substances in the process industries have occurred and continue to occur despite continued efforts aimed at their prevention, contro and mitigation. The contro and reguation of process industry major hazards is informed by anaysis of those accidents (as we as by first principes approaches to hazard management).

2 Severa high profie incidents have occurred at weekends. Exampes incude those at Fixborough, Seveso, Miford Haven and Buncefied (Parker, 1975, Orsini 1977, HSE 1997, Newton 26). The pubication, in 25, of a report into a bank hoiday incident at the Humber Refinery in the UK (HSE 25) was the prompt for the present work. Specuation based on anecdota evidence, has ed to the suggestion that there is a potentia for higher than proportionate numbers of accidents, particuary those cassed as major accidents, to occur on a bank hoiday or a weekend (Saturday or Sunday). Here, this postuated increase of accident incidence on a weekend day or bank hoiday is termed a weekend (or bank hoiday) effect. The term bank hoiday is not used in the strict sense, but is used oosey to refer to the kinds of nationa hoiday days when roes that are normay fied on week days wi not be fied. If this perception shoud represent an actua effect, there coud be serious impications for the work of the reguators regarding major hazard activities and industries. The confirmation of any cear weekend (or bank hoiday) effect might justify further research carifying the causes of the effect and the targeting of resources on reduction of those causes or the introduction of additiona barriers taiored to the identified effect paths. This paper reports the findings of research carried out by the Heath and Safety Laboratory, commissioned by the Heath and Safety Executive. An anaysis of data from a seection of major accident ists and databases was performed, to search for significant differences in the numbers of major accidents occurring on weekdays when compared with weekend days and bank hoidays. Significant differences might provide evidence in support of a weekend or bank hoiday effect on the occurrence of major accidents. More specificay, the objectives of the exercise were: To review five coections (ists or databases) of major accident information (data sources); Identify whether these accidents occurred on a weekday, weekend or bank hoiday; Anayse the data to determine significant (or non-significant) differences in accidents occurring on a weekend or bank hoiday in comparison to non bank hoiday weekdays. Throughout this paper the term accident is used to refer to accidents and incidents recorded across the five sources of data. Fu detais of the anaysis are reported by Heaey 27. This paper provides a summary of the work and some discussion of the context and impications. Previous Work A iterature search found no previous work specificay investigating the presence of a weekend or bank hoiday effect on the occurrence of major accidents. A study of fata accidents at work associated with maintenance (HSE, 1985) found that accidents occurred throughout the working week with a peak observed mid-week. Surprisingy, ony 13% happened during weekend maintenance work, but this may be affected by the recession or reduced production pressures. If accidents were proportionatey 2

3 spread over the entire week (that is, if there were no reduction in activity or numbers of peope at risk and accidents were eveny distributed) then of course about 3% of accidents woud occur at weekends (2/7 ~.3). Data Sources and Anaysis A seection of five data sources, with appropriate incusion criteria, were identified and utiised throughout this work. Appendix A gives an outine description of the sources, an indication of the criteria for incusion of data in each source and, where appropriate, additiona criteria appied in the data seected for this study. The data sources covered a varying range of the process industries, and varied in their incusion criteria. Each of the five data sources was interrogated and information extracted. Journa artices and websites (see references) were used to suppement the date and country information from the accident data sources to identify the day of the week an accident occurred on. Using this information most accidents coud be tagged according to whether they occurred on weekdays, weekends or bank hoidays. There was apparent repication of some accident reports both within and between the various data sources. In some cases the repication was cear, whist in other cases it was not so cear. Where possibe, repicated accident reports were removed to reduce the ikeihood of dupication in the anayses. HSL reied on its subjective judgement to remove this repicated information. Attempted Normaisation of the Data There are potentiay numerous and varied factors which might infuence the occurrence of accidents on weekdays, weekends or bank hoidays. One obvious factor is the extent to which operations may (or may not) differ: some sites wi operate in simiar mode regardess of the day of the week, others may operate very differenty (perhaps not at a) on a bank hoiday. Another factor is the presence of popuation (both on and around the major hazard site). The effects of these factors may be simpe (e.g. fewer operations eading to fewer opportunities for accidents) or compex (e.g. fewer peope on site may resut in fewer casuaties in the event of an accident, or, a greater number of peope on site, by virtue of their appropriate actions, may inhibit the escaation from an initiating event to a reportabe accident). A fair comparison of the incidence of accidents (and their consequences) woud take account of other factors which raise or ower the potentia for such accidents at weekends or bank hoidays. To some extent the occurrence of accidents may be inhibited at weekends or bank hoidays if operations are reduced or consequences may be inhibited if fewer peope are present. So, for exampe, a fair comparison woud take account of reduced operations (or exposure to consequences) outside weekdays. In the discussion above, a simpe definition of weekend (i.e. a Saturday and Sunday) has been used. However if there is a weekend effect it may not be reevant to 3

4 distinguish between midnight on Sunday and resumption of norma office hours on Monday. A weekend effect may aso be somehow reated to (or, at best, confounded with) diurna effects (which have been studied separatey, Fortson 24). It was, therefore, desirabe to expore whether the anaysis was sensitive to scaing of the data to factors such as degree of weekend working and popuation present. So it was envisaged that aternative anayses woud be undertaken with the data normaised in respect of these factors. Literature and abstract searches were carried out in order to identify a method (i.e. a reevant data source) for normaising the major accident data, in ine with differences in the productivity eves and work patterns typicay observed in the different industries reporting accidents. An appropriate source for this information was not identified. Furthermore, the accident information hed in the data sources was not detaied enough to identify information such as staff shift patterns or patterns in productivity eves, and normaisation of the accident data was not possibe (neither for these factors nor for other factors). Anaysis Anaysis was performed on the aggregated data from a sources, on data from each source separatey (or a seection of that singe-source data) and on subdivisions of the aggregated data (for exampe, the aggregated set of accidents with reported consequences incuding ten or more fataities). The Chi-square test was appied to the accident information coected from the five data sources to assess the significance (or non-significance) of differences between the proportions of major accidents occurring on weekdays, weekends and bank hoidays. A variety of t-test was used to determine the statistica significance of differences in the reative proportions of weekend to weekday accidents in subsets of the data, when compared with the same proportions in the overa aggregated data. RESULTS An overview anaysis was performed on the aggregated data from a sources. The raw aggregated dataset consisted of information reating to 4333 accidents, coected across the five data sources. Repicated accident reports (numbering 487) were removed from the dataset before the overview anaysis. The remaining sampe of 3846 accidents were cassified according to the day of the week on which they occurred. Figure shows the breakdown of the accidents, by day of the week. Information was not avaiabe (N/A) for some accidents. The chart shows a mid-week peak and a decrease in accidents reported as occurring at the weekend (Saturday and Sunday). Tabe 1 shows the breakdown of the sampe, by bank hoiday accidents. To determine a bank hoiday both the country, and exact date were required. This additiona data was not aways avaiabe eading to a higher number of accidents cassed as N/A. 4

5 Tota No Breakdown of accident information by day of week Mon Tues Wed Thurs Fri Sat Sun N/A Day of Week Figure 1. Breakdown of accident information by day of week (n = 3846) Resuts of Chi-square cacuations showed there were significanty more accidents on a weekday (Monday Friday) than on a Saturday, Sunday, weekend (Saturday and Sunday) or bank hoiday in this overa sampe. A itte over 2% of accidents occurred on a weekend (compared with ~3% for a fat distribution). Significanty more accidents occurred on a Saturday, in comparison to a Sunday. Anaysis: by Data Source and by Consequence (numbers of fataities) Further anayses of the accident data were aso performed to expore the sensitivity of features in the data to the data source and to a measure of accident consequence (number of fataities). The data from each data source in isoation was anaysed. The resuts for each data source, comparabe with Figure 1 for the aggregated data, are presented in Appendix A. The aggregated data was subdivided by ranges of numbers of fataities (a crude indication of accident severity). The resuts are detaied in Heaey 27. In most cases, for either individua data sources or for subsets of the aggregated data based on bands of consequence (ranges of numbers of fataities), the features of the overview anaysis were confirmed. Tabe 1. Breakdown of bank hoiday accident information (n = 3846) Bank hoiday Tota no. accidents Yes 46 No 238 N/A 1492 Tota

6 Tota No Breakdown of Lees accident information by day of week Mon Tues Wed Thurs Fri Sat Sun N/A Day of Week Figure 2. Breakdown of Lees accident information by day of week (n = 551) There were some apparent distinctions between features of the overview anaysis and the anaysis of individua data sources or sub-sets of the aggregated data. For exampe, a reativey high proportion of weekend to weekday accidents was seen in both the Lees data (Figure 2, Appendix A) and a ten or more fataity accidents subset of the aggregated data, when compared to the overa aggregated data. A Chi-square test showed no significant difference between accidents on weekdays and weekends for these two cases, where the overa, aggregated data had shown significanty more accidents on weekdays. Further statistica anaysis was necessary to estabish whether this change was significant or merey a consequence of the smaer amount of data in a singe source or sub-set of the aggregated data. A form of t-test was used to determine the statistica significance of differences in the reative proportions of weekend to weekday accidents in individua data sources or sub-sets of the aggregated data, in comparison with the overa, aggregated sampe. A statisticay significant higher proportion of weekend to weekday accidents was observed in both the Lees data and a ten or more fataity accidents subset of the aggregated data, when compared to the overa aggregated data. Therefore, the dip in weekend accidents noted earier (HSE 1985) and here in the overview anaysis is significanty ess pronounced in some subsets of the data. Athough these findings do not show evidence in support of a weekend or bank hoiday effect, the resuts of the t-test suggest that some subsets of the data (in particuar the Lees data, and a ten or more fataity accidents subset of the aggregated data) are different in nature to the overa, aggregated data. It is possibe this is evidence of a weak, reative association of arger/more severe accidents with weekends. In no case was there evidence of an excess in the incidence of accidents on weekends (or bank hoidays). The fu resuts are reported by Heaey 27. DISCUSSION The aggregated data studied here is principay distinguished from the data reviewed earier by HSE (HSE 1985) by its focus on the process industries (i.e. excuding construction etc). 6

7 The aggregated data (particuary because it incudes the arge IChemE dataset) incudes a wide range of consequences, incuding but not imited to major accidents. From the distribution of accidents by day of the week (Figure 1) and statistica anaysis, it is cear that there is no absoute and disproportionate increase in the incidence of accidents on weekends (or bank hoidays). In no case were accidents occurring on weekends or on bank hoidays in excess of those expected in a fat distribution (where accident frequency is statisticay independent of the day). In the aggregated data, there is a reative increase in weekend accidents when compared to the broader-based study (from ~13% in HSE 1985 to ~2 % in the aggregated data here). There were significanty more accidents on a weekday (Monday Friday) than on a Saturday, Sunday, weekend (Saturday and Sunday) or bank hoiday in this overa sampe. A itte over 2% of accidents occurred on a weekend (compared with ~3% for a fat distribution). Significanty more accidents occurred on a Saturday, in comparison to a Sunday. Anaysis of the individua data sources which are more ceary restricted to major accidents (for exampe Lees), or subsets of the data more restricted to arge scae consequences (for exampe accidents associated with ten or more fataities) showed a weak reative increase in the incidence of accidents on weekends. But these increases were of itte or no statistica significance, or ese were confounded by the reduced amount of data. These anayses produced no genera evidence of a disproportionate increase in accident numbers on weekends or bank hoidays and no concusive evidence that more consequentia, infuentia or spectacuar accidents correate positivey with weekends or bank hoidays. There were some indications that more consequentia, infuentia or spectacuar accidents are reativey (but not absoutey) more ikey at weekends, though this may merey be due to a confounding factor (i.e. industries capabe of more consequentia, infuentia or spectacuar accidents may be more ikey to be operating on weekends and bank hoidays). When viewing the data cassified by consequence (simpy represented by number of fataities), there may be a confounding effect in that weekend (or bank hoiday) incidents may be ess consequentia than corresponding weekday events. For exampe, had the Fixborough disaster occurred during a norma working day (and been in other respects unchanged) the fataities in that incident might have been ten times greater (Rushton, 1998). There are, undoubtedy, some safety professionas who beieve there is a weekend (or bank hoiday) effect. Perhaps this beief is mistaken, or perhaps it is based on sound (if unsubstantiated) intuition. It is easy to conjecture how a weekend effect might arise. There may be fewer staff to detect incipient causes (accident initiators or barrier faiures), supervise interventions, respond to incipient causes or diagnose eading indicators. For exampe there may be more situations put on hod awaiting the attention of weekday staff or contractors. It is 7

8 easy to specuate on other features of bank hoiday and weekend working which might weaken or remove barriers to the initiation of or escaation to an event. It is possibe there is a weekend effect, that is too weak to stand out over other factors within the data avaiabe. Where common sense and/or engineering judgment indicates a greater propensity for initiation or escaation of events in some particuar circumstances (incuding but not imited to weekends or bank hoidays), then that propensity shoud of course be given proportionate attention in the management of hazards. CONCLUSIONS There are some safety professionas who beieve there is a disproportionate incidence of accidents (particuary major accidents) on weekend days or bank hoidays (a weekend (or bank hoiday) effect ). Study of the day of occurrence of a arge number of accidents in the process industries shows no statistica evidence of a weekend or bank hoiday increase in the numbers of major accidents. The main findings were: Anaysis of the aggregated accident data from five sources and sub sets of that data consistenty faied to provide convincing evidence for either a weekend or bank hoiday increase in the number of major accidents. Fairy consistent evidence was seen of a mid-week peak and a weekend dip in the number of accidents reported. Chi-Square tests consistenty showed either no significant difference, or significanty more accidents occurring on a weekday in comparison with accidents occurring on a Saturday, Sunday or bank hoiday. There is some weak evidence of a reative increase in incidence of accidents on weekends in the process industries compared to industry in genera. There is weak evidence of a reative increase in incidence of major accidents on weekends in the process industries compared to accidents in the process industries in genera. In essence, the work has shown either no evidence of an effect, or that the effect is too weak to stand out over other factors within the data avaiabe. Athough evidence was not found in support of a weekend or bank hoiday effect, at this juncture, such an effect has not been disproved. It is possibe that a weekend or bank hoiday effect may exist, but was not reveaed in this study due to the masking effect of other factors. A comprehensive understanding of the organisationa factors underying major accidents is vita in order to inform reguators and major hazard industries, regarding reguation and the prevention of major accidents. Where common sense and/or engineering judgment indicates a greater propensity for initiation or escaation of events in any particuar circumstances, then that propensity shoud be given proportionate attention. 8

9 In recognition of the imitations associated with this research, it is recommended that these findings be considered as a foundation for further work, with a focus on addressing some of the imitations encountered in this research. DISCLAIMER The views expressed in this paper are those of the authors aone and are not a statement of HSE poicy. REFERENCES EC, 1997, Counci Directive 96/82/EC of 9 December 1996 on the contro of majoraccident hazards invoving dangerous substances, Officia Journa of the European Communities, Luxembourg (aso known as the Seveso II directive ), as amended by Directive 23/15/EC. Fortson, K., 24, The Diurna pattern of on-the-job injuries, Monthy Labor Review, September Heaey, N., 27, An investigation into a weekend or bank hoiday effect on major accidents. HSL report. RSU/RM/7/4. HSE, 1985, Deady Maintenance A Study of Fata Accidents at Work, ISBN HMSO. HSE 1997, The exposion and fires at the Texaco Refinery, Miford Haven, 24 Juy 1994, ISBN HSE, 25, Pubic report of the fire and exposion at the Conoco Phiips Humber Refinery on 16 Apri 21 at Kirchsteiger, C., 21, MARS 4. An Eectronic Documentation & Anaysis System for Industria Accidents Data, European Commission, DG JRC, EUR EN, Ispra. Newton, Lord, 26, Buncefied: Initia Report to the Heath and Safety Commission and the Environment Agency of the investigation into the exposions and fires at the Buncefied oi storage and transfer depot, Heme Hempstead, on 11 December 25 at Orsini, B.,Pariamentary Commission of Inquiry on the Escape of Toxic Substances on 1 Juy 1976 at the ICMESA Estabishment and the Consequent Potentia Dangers to Heath and the Environment due to Industria Activity, Rome (Engish transation, HSE, 198) Parker, R.J., 1975, The Fixborough Disaster: Report of the Court of Inquiry, HMSO, ISBN Rushton, A.G., 1998, Lessons Learned from Past Accidents, in Risk assessment and management in the context of the Seveso II directive (Kirchsteiger C, Christou MD and Papadakis GA Eds.), Industria Safety Series Voume 6, Esevier. Data sources Institution of Chemica Engineers Accident database. A CD of Chemica and Processindustry accidents, created and maintained by IChemE. 9

10 Lees, F Loss Prevention in the Process Industries: hazard identification, assessment and contro. Voume 3 Appendices. 2nd Edition. Large Property Damage Losses in the Hydrocarbon-Chemica Industries: A Thirty-Year Review. 13th Edition, 199. Large Property Damage Losses in the Hydrocarbon-Chemica Industries A Thirty-Year Review. 19th Edition, 21. Major Accident Reporting System, accessed September 26 at: MHIDAS (Major Hazard Incident Data Service) database. Enquiries directed to the Heath and Safety Executive, Hazardous Instaations Directorate, Business Assurance and Operations Anaysis Team, Boote. Suppementary information Day of the week information accessed October 26 at: com/utiity/dayofweek.htm Day of the week and Bank hoiday information accessed October 26 at: timeanddate.com/caendar/ Bank hoiday information accessed October 26 at: Word Commercia hoidays, Business America, Dec 95, Vo. 116 Issue 12, p21 Appendix A: Sampe of data sources and appropriate reevance criteria Loss Prevention in the Process Industries. Lees. This is a persona seection/coection by the author (F.P. Lees) of major accidents reported by the process industry. The coection is in the form of a ist. So, the incusion criterion was the subjective discretion of Lees. A accidents in the ist were effectivey cassified as major by the author due to their incusion in the seection, and were a considered in this anaysis. The sampe of 551 accidents recorded in the Lees database were organised according to the day of the week they occurred on. Figure 2 shows the breakdown of the Lees accidents, by day of the week, N/A was used where information was not avaiabe. Large Property Damage Losses in the Hydrocarbon-Chemica Industries: A Thirty- Year Review. Marsh McLennan. This is a ist reviewing 1 arge property damage or osses occurring in the hydrocarbon processing and chemica industries over a thirty-year period. (Information reating to an additiona 15 accidents, taken from the atest version of the review was aso incuded). A accidents were incuded in this anaysis. The incusion criterion was economic oss (in the quaifying period and imited by number). The sampe of 115 accidents recorded in the Marsh McLennan database were organised according to the day of the week they occurred on. 1

11 Tota No Breakdown of M-M accident information by day of week Mon Tues Wed Thurs Fri Sat Sun N/A Day of Week Figure 3. Breakdown of Marsh McLennan accident information by day of week (n = 115) Figure 3 shows the breakdown of the Marsh McLennan accidents, by day of the week. MHIDAS. The Major Hazard Incidents Data Service. This is a coection of wordwide accidents recorded using information taken from the pubic domain. The coection is in the form of a database. The incusion criterion is incidents invoving hazardous materias that had an off-site impact, or had the potentia to have an off-site impact. Such impacts incude human casuaties or damage to pant, property or the natura environment. A accidents in the database are effectivey cassified as major due to the offsite impact (or potentia for offsite impact). The most recent 86 accidents recorded excuding those occurring in ong standing members of the European Union, i.e. Begium, France, (West) Germany, Itay, Luxembourg, Netherands, Denmark, Ireand, United Kingdom, Greece, Portuga, Spain were considered for this anaysis. This reduced set was used in order to minimise the number of accidents ikey to be incuded within the remit of the other data sources, therefore minimising repicated incidents in the anaysis. (The current work was imited to the incusion of 86 accidents due to project resources.) Figure 4 shows the breakdown of the MHIDAS accidents, by day of the week, N/A was used where information was not avaiabe. The graph shows a mid-week peak and a decrease in accidents reported as occurring at the weekend (Saturday and Sunday). EU MARS. The Major Accident Reporting System. This is a distributed information network compiing information from 15 databases in each member state of the European Union. A accidents in the compied database are effectivey cassified as major accidents, as the reporting process reies on the major accident definitions in the Seveso directives (EC 1997). A accidents in the database were incuded in this anaysis. The sampe of 63 accidents recorded in the EU MARS database were organised according to the day of the week they occurred on. 11

12 Tota No Breakdown of MHIDAS accident information by day of week Day of Week Mon Tues Wed Thurs Fri Sat Sun N/A 2 Figure 4. Breakdown of MHIDAS accident information by day of week (n = 86) Tota No Breakdown of EU MARS accident information by day of week Mon Tues Wed Thurs Fri Sat Sun N/A 1 Day of Week Figure 5. Breakdown of EU MARS accident information by day of week (n = 63) Tota No Breakdown of IChemE accident information by day of week Mon Tues Wed Thurs Fri Sat Sun N/A Day of Week Figure 6. Breakdown of IChemE accident information by day of week (n = 224) 12

13 Figure 5 shows the breakdown of the EU MARS accidents, by day of the week. The graph shows peaks on Monday and Thursday and a decrease in accidents reported as occurring at the weekend (Saturday and Sunday). IChemE Accident Database. This is an accident database used wordwide by chemica and process industries. The database was created and maintained by the Institution of Chemica Engineers and detais the cause and effect of accidents and incidents. The incusion criterion is broad, incuding any accident report in the process industry. The consequences of the accidents are many and varied and so it is uncear that a the accidents woud meet a definition of major (such as in the Seveso Directives). A accidents in the database were incuding in this anaysis. The sampe of 224 accidents recorded in the IChemE database were organised according to the day of the week they occurred on. Figure 6 shows the breakdown of the IChemE accidents, by day of the week, N/A was used where information was not avaiabe. The graph shows a mid-week peak and a decrease in accidents reported as occurring at the weekend (Saturday and Sunday). 13