Pedro Saavedra1, Angelo Santana2, Luis Bello3, José-Miguel Pacheco1, Esther Sanjuán4. 1. Department of Mathematics, University of Las Palmas de Gran Canaria, Las Palmas, Spain. 2. Department of Mathematics, University of Las Palmas de Gran Canaria, Las Palmas, Spain. angelo.santana@ulpgc.es. 3. Department of Physical Education and Biomedical and Health Research Universitary Institute, University of Las Palmas de Gran Canaria, Las Palmas, Spain. 4. Department of Animal Pathology and Production, Bromatology and Food Technology, University of Las Palmas de Gran Canaria, Las Palmas, Spain.
Abstract
BACKGROUND: The number of deaths attributable to COVID-19 in Spain has been highly controversial since it is problematic to tell apart deaths having COVID as the main cause from those provoked by the aggravation by the viral infection of other underlying health problems. In addition, overburdening of health system led to an increase in mortality due to the scarcity of adequate medical care, at the same time confinement measures could have contributed to the decrease in mortality from certain causes. Our aim is to compare the number of deaths observed in 2020 with the projection for the same period obtained from a sequence of previous years. Thus, this computed mortality excess could be considered as the real impact of the COVID-19 on the mortality rates. METHODS: The population was split into four age groups, namely: (< 50; 50-64; 65-74; 75 and over). For each one, a projection of the death numbers for the year 2020, based on the interval 2008-2020, was estimated using a Bayesian spatio-temporal model. In each one, spatial, sex, and year effects were included. In addition, a specific effect of the year 2020 was added ("outbreak"). Finally, the excess deaths in year 2020 were estimated as the count of observed deaths minus those projected. RESULTS: The projected death number for 2020 was 426,970 people, the actual count being 499,104; thus, the total excess of deaths was 72,134. However, this increase was very unequally distributed over the Spanish regions. CONCLUSION: Bayesian spatio-temporal models have proved to be a useful tool for estimating the impact of COVID-19 on mortality in Spain in 2020, making it possible to assess how the disease has affected different age groups accounting for effects of sex, spatial variation between regions and time trend over the last few years.
BACKGROUND: The number of deaths attributable to COVID-19 in Spain has been highly controversial since it is problematic to tell apart deaths having COVID as the main cause from those provoked by the aggravation by the viral infection of other underlying health problems. In addition, overburdening of health system led to an increase in mortality due to the scarcity of adequate medical care, at the same time confinement measures could have contributed to the decrease in mortality from certain causes. Our aim is to compare the number of deaths observed in 2020 with the projection for the same period obtained from a sequence of previous years. Thus, this computed mortality excess could be considered as the real impact of the COVID-19 on the mortality rates. METHODS: The population was split into four age groups, namely: (< 50; 50-64; 65-74; 75 and over). For each one, a projection of the death numbers for the year 2020, based on the interval 2008-2020, was estimated using a Bayesian spatio-temporal model. In each one, spatial, sex, and year effects were included. In addition, a specific effect of the year 2020 was added ("outbreak"). Finally, the excess deaths in year 2020 were estimated as the count of observed deaths minus those projected. RESULTS: The projected death number for 2020 was 426,970 people, the actual count being 499,104; thus, the total excess of deaths was 72,134. However, this increase was very unequally distributed over the Spanish regions. CONCLUSION: Bayesian spatio-temporal models have proved to be a useful tool for estimating the impact of COVID-19 on mortality in Spain in 2020, making it possible to assess how the disease has affected different age groups accounting for effects of sex, spatial variation between regions and time trend over the last few years.
Authors: Camila Alves Dos Santos Siqueira; Yan Nogueira Leite de Freitas; Marianna de Camargo Cancela; Monica Carvalho; Albert Oliveras-Fabregas; Dyego Leandro Bezerra de Souza Journal: PLoS One Date: 2020-07-29 Impact factor: 3.240
Authors: Thomas Beaney; Jonathan M Clarke; Vageesh Jain; Amelia Kataria Golestaneh; Gemma Lyons; David Salman; Azeem Majeed Journal: J R Soc Med Date: 2020-09 Impact factor: 5.344