On May 19, 2020, data confirmed that coronavirus 2019 disease (COVID-19) had spread worldwide, with more than 4.7 million infected people and more than 316,000 deaths. In this article, we carry out a comparison of the methods to calculate and forecast the growth of the pandemic using two statistical models: the autoregressive integrated moving average (ARIMA) and the Gompertz function growth model. The countries that have been chosen to verify the usefulness of these models are Austria, Switzerland, and Israel, which have a similar number of habitants. The investigation to check the accuracy of the models was carried COVID-19 Growth Patterns Comparison: ARIMA and Gompertz Models Rambam Maimonides Medical Journal 2 July 2020 Volume 11 Issue 3 e0022 out using data on confirmed, non-asymptomatic cases and confirmed deaths from the period February 21-May 19, 2020. We use the root mean squared error (RMSE), the mean absolute percentage error (MAPE), and the regression coefficient index R 2 to check the accuracy of the models. The experimental results provide promising adjustment errors for both models (R 2 >0.99), with the ARIMA model being the best for infections and the Gompertz best for mortality. It has also been verified that countries are affected differently, which may be due to external factors that are difficult to measure quantitatively. These models provide a fast and effective system to check the growth of pandemics that can be useful for health systems and politicians so that appropriate measures are taken and countries' health care systems do not collapse.
We analyze the energy consumption of domestic hot water (DHW) in the hotels of the archipelago of the Canary Islands (Spain). Currently, systems use fossil fuels of propane and gas oil. However, this paper analyzes several alternative systems which focus on renewable and mixed energies, such as biomass, solar thermal and heat pumps systems associated with an electric generation with photovoltaic solar panels for self-consumption. The carbon footprint generated is calculated for each method of generation of DHW. In our analysis, we demonstrate that by using a high-temperature heat pump with an average coefficient of performance (COP) equal to or greater than 4.4 associated with photovoltaic solar panels, a zero-emission domestic hot water system can be achieved, when the installation area of the photovoltaic solar panels is equal to that of the solar thermal system. The importance of DHW’s carbon footprint is proven, as is the efficiency of using high-temperature heat pumps associated with photovoltaic solar panels. As such, such mixed system suggests that the generation of DHW would have zero emissions with maximum annual savings according to hotel occupancy, between 112,417 and 137,644 tons of carbon dioxide (CO2), compared to current boilers based on fossil fuels.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.