Article

The influence of the full moon on the number of accessions to an animal emergency centre

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Abstract

To test the hypothesis that the number of animal emergency centre accessions is associated with the time of the full moon. Retrospective study. A comparison was made of the number of accessions to the University of Melbourne Animal Emergency Centre in the period February 2003 to January 2006 on full moon and non-full moon days, adjusted for day of the week and public holiday. A three day period with the day of the full moon as the middle day was taken to be a full moon period. A total of 12,102 animals were presented to the Centre in this time. An adjusted count ratio of 1.048 (95% CI 0.97 to 1.14; P = 0.26) for accessions on full moon days compared with those on non-full moon days indicated that there was no significant association between the full moon and the number of accessions per day. There was no significant difference between the number of animals presented to the University of Melbourne Animal Emergency Centre on full moon days and non-full moon days.

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... In veterinary medicine, there is a paucity of studies and publications that address the epidemiology of emergency care, thus leaving a gap in the preparation, surveillance, and recognition of critical cases that require rapid interventions. There are studies that have evaluated variations in emergency admissions with moon cycles or holidays (WELLS et al., 2007;MCALEES;ANDERON, 2007;DROBATZ et al., 2009), emergency oncology review in small animal clinics (TUMIELEWICZ et al., 2019), the epidemiological aspects and main pathologies of feline patients (SÃO GERMANO et al., 2011), epidemiology of trauma in small animals (ROHDE et al., 2014), and another study addressing emergencies in the general context (GUTERRES et al., 2013). In translational medicine, there is evidence of the benefits of emergency epidemiological studies at the interface and collaboration for all species (FÉLIX; GOMMEREN; BOYSEN, 2019). ...
... At the international level, there are only three studies that have evaluated the epidemiological aspects of emergencies (MCALEES; ANDERSON, 2007;WELLS et al., 2007;DROBATZ et al., 2009), In these studies, the focus of the authors was not to evaluate the cause of emergencies, nor the epidemiological data of the occurrences; only the period of admissions and/or the possibility of associations between certain types of emergencies and the cycles of the moon, holidays, or times of the year were studied. Thus, the present work stands out with regard to the study of the epidemiological aspects of different causes of emergencies in dogs and cats. ...
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The purpose of this study was to investigate an ancient hypothesis; the moon effect might increase incidence of injuries and hence admission of patients with trauma to Emergency Rooms (ERs) on full moon days. During thirteen months, 58000 trauma patients admitted in three hospitals that had the highest load of trauma patients in Tehran were studied. Due to lack of complete data, 3543 patients (6.1%) were excluded from the study, leaving 54457 cases for further analysis. We selected lunar calendar for our study, so dates of patients' admissions were converted to lunar months and three day- periods with 15th as middle day were defined as full moon days. In our study the number of trauma patients was not increased during the full moon days against other days of lunar month. Statistical analyses of data didn't exhibit a positive relation between full moon days and increasing of trauma patient admission to ERs. An association between assault and attempted suicide was not observed around the full moon days either. The results did not show significant reduction of GCS score of patients on full moon days and there was not any increase in severity of traumatic injury sustained during full moon days. It seems necessary to conduct studies regarding the probability of moon effect through on different database, geographic areas and for appropriate periods in order to reach a conclusive result.
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This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.
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