Vietnam needs to pay attention to promoting the process of building system data systems, science, which can think of using efficient translation forecast models of 9: 00/6: 26 namcho domain Now, in the context of disease is still raging, there are many researchers and experts suggesting anti-epidemic solutions. In particular, there are forecast models given to present the perspectives, scripts and response solutions. However, there are no models that really persuade. Change with Ho Chi Minh City Law, Prof. Nguyen Van Tuan, Director of Epidemiological and Osteoporosis Programs under Garvan Medical Research Institute ( Australia) COMMENTS: The construction of a prognostic model is very difficult and takes a lot of time
. In Covid-19 translation, it can be said that most models are wrong. The game of the forecast model. Reporters: In his experience, what is the role of pandemic prognostic models? Prof
Nguyen Van Tuan: There are many types of models for Covid-19 translation. The first is a clinical application model, identifies people at high risk, making it possible to identify and prioritize patients for treatment. The second is the prognosis of the scale and movement of translation in the community, making policy planning better. The third is a forecast model that only aims to predict the number of incomes in the future. All of these models have an important role because they are based on the government. For example, as a model of Professor Neil Ferguson, an expert on his famous epidemic. He was the one who built models predict the disease for the British government right from the early days of the epidemic. Professor Neil Ferguson predicted that the number of deaths was too high, so the British government immediately blocked the country. In Australia, the government also relies on the model of the Doherty Institute to go to the vaccination and city blockade policy. Neil Ferguson, expert on his famous epidemic
Photo: The Guardian / J-Idea. Related prognosis of Covid-19 translation, which are important steps? Building and deploying a model that usually has to go through 4 steps. The first is to choose the possible model. In fact, many models can be considered (such as traditional epidemiological models, statistical models, interactive models). However, only a few models can be suitable for the local and data situation, so this is an important step. Then we must collect data and parameters. This is the quality decision step of the model. Normally, the epidemiological model requires a lot of detailed data, such as the distribution of the age group population, distributing hospital stay time, ICU time distribution, the probability of turning mild to heavy ... If we don't have these data, it is difficult to build a complete model to be able to predict the most effectively. Next, we need to write a computer program to estimate the parameters. This is a technical step, from the mathematical epidemic model to calculate using computer languages. Just a wrong code line can lead to the entire model error. So the role of computer program writers can be said to be as important as the data collection step. Finally, we will test the model. After a model, it is necessary to check the model to see if the results are reasonable or not. Normally, people use high-power computers to simulate a population of several million people to see how "behavior" of the model. Only when the model has passed the inspection, it is only available in reality. Not easy. In fact, how to build and operate difficult prognosis models? Any prognostic models also rely on some assumptions. The epidemiological prognosis model is very complicated, as it prognizes the situation of a population going from exposure to infection, from infection to hospitalization, from hospitalization to death. Meanwhile, each individual has its own risk factors that can affect that development. For example, the elderly has rapidly and higher than young people. All such factors are called parameters, and a model can have dozens of such parameters. For example, the Seir model we used to use about 25 parameters. In general, building a prognostic model very much and takes a lot of time .. His self-owned or witnessed failures in the prognostic model in medicine? What is the lesson after that defeat? In short, no model is perfect, but there are some useful models. In osteoporosis specialties, the models that we research and deployment need 20 years to have data, and after announcing, it takes 5 years to be clinically deployed. The reason is because the model affects the decision to treat patients, must be appraised by the new medical and legal associations to ensure scientific and legal properties. In translation of Covid-19, maybe Saying that most models until now are wrong. More than a year ago, San British Medical Journal passed through hundreds of models for Diagnostic Covid-19 and the author concluded that tissue h . Dịch vụ:
Thiết kế website,
quảng cáo google,
đăng ký website bộ công thương uy tín
