Īnalyses on North and South America have also used similar classical methods, for example model the progression of the outbreak in the United States until the end of 2021 with the simple Susceptible-Infected-Recovered model, and predict epidemic trends in Brazil and Peru using a logistic growth model and machine learning techniques. However, more recent literature has started to cover an increasing number of regions outside of China.įor example, studies covering the wider Asia region include: investigations into the outbreak on board the Diamond Princess cruise ship in Japan, using a Bayesian framework with a Hamiltonian Monte Carlo algorithm estimation of the ascertainment rate in Japan using a Poisson process modelling the evolution of the basic and effective reproduction numbers in South Korea using Susceptible-Infected-Susceptible models and generalised growth models with varying growth rates modelling the basic reproduction number in India with a classical Susceptible-Exposed-Infectious-Recovered-type compartmental model forecasting numbers of cases in Indian states using deep learning-based models. Since the first confirmed cases were reported in China, much of the literature has focused on the outbreak in China including the transmission of the disease, the risk factors of infection, and the biological properties of the virus-see for example key literature such as. ![]() Although the foundations of this disease are very similar to the severe acute respiratory syndrome (SARS) virus that took hold of Asia in 2003, it is shown to spread much more easily and there currently exists no vaccine. At present, over 45 million cases of infected individuals have been confirmed in over 180 countries with in excess of 1 million deaths. After the initial outbreak, COVID-19 continued to spread to all provinces in China and very quickly spread to other countries within and outside of Asia. The novel coronavirus (COVID-19) was widely reported to have first been detected in Wuhan (Hebei province, China) in December 2019. The predictive ability of the log-linear regression model was found to give a better fit and simple estimates of the daily incidence for both countries were computed. Estimates were also computed for the more dynamic effective reproduction number, which showed that since the first cases were confirmed in the respective countries the severity has generally been decreasing. ![]() ![]() Estimates of the basic reproduction number were found to be larger than 1 in both countries, with values being between 2 and 3 for Italy, and 2.5 and 4 for Spain. Using two simple mathematical epidemiological models-the Susceptible-Infectious-Recovered model and the log-linear regression model, we model the daily and cumulative incidence of COVID-19 in the two countries during the early stage of the outbreak, and compute estimates for basic measures of the infectiousness of the disease including the basic reproduction number, growth rate, and doubling time. This paper focuses on the incidence of the disease in Italy and Spain-two of the first and most affected European countries. The novel coronavirus (COVID-19) that was first reported at the end of 2019 has impacted almost every aspect of life as we know it.
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