Ebola is one of the most deadly viral infections on the planet. Fever and systemic bleeding occur, and three out of four people lose their lives once they are caught. First discovered in the Ebola river in the Democratic Republic of the Congo in 1976, it has become a common endemic disease in Africa.

The spread of Ebola, which has spread in West Africa every year, has been temporarily halted. Ebola, which began in Guinea in March 2014, crossed West Africa into the United States, Britain, Italy and Spain, killing 11,315 people. It was the largest Ebola epidemic in history in the number of deaths and spreading. However, two years later, in 2016, the World Health Organization (WHO) declared a provisional end to the spread of Ebola in three West African countries: Sierra Leone, Guinea and Raibeira.

The ebola epidemic, which has rarely been seen, is a model of infectious disease repair created by prevention experts and mathematicians. Infectious disease repair model is an analysis model that is used to analyze the propagation situation and predict the future development by creating a mathematical formula indicating the state of the infectious disease is spreading. Today, the WHO and the national defense authorities have developed a repair model that is consistent with the reality of most countries and, based on the results, are proposing measures to prevent the disaster.

At the time, the WHO recommended that people in contact with the patient be banned from leaving the country for three weeks. The analysis of the repair model showed that the incubation period of Ebola, three weeks, was actively prevented from moving contacts, resulting in a significant reduction in patient incidence. Experts stress that predicting the spread is very important in the event of infectious diseases.  Lee Hyo-jung, a senior researcher at the National Institute of Mathematical Sciences, who specializes in infectious disease repair models, explained, “There is a significant difference in the number of patients who are additionally encountered under the prevention policy, and the infectious disease repair model helps to set the direction of such a policy.”

In the event of a new coronavirus infection (Corona 19), the infectious disease repair model is being used at the domestic disaster prevention authority meeting. Lee said, “The corona 19 predictions through the infectious disease repair model are being used as a basis for scientific judgment at the Ministry of Science, Technology, Information and Communication, The Central Defense Countermeasures Headquarters, and the Presidential Presiding Office.” In Korea, a number of research teams are developing infectious disease repair models, including professor of cancer management at The Kim Moran National Cancer Center and a team of researchers from the Korea Institute of Science and Technology (KIST) Computational Science and Research Center. According to a repair model developed by Professor Ki’s research team, the corona 19 prevention measures in Korea were found to occur continuously for 25 days after the patient was delayed by one week.

Predict the likelihood of infection and spread through time flow

Researchers from The University of Xi’an-Jiaotong-Liverpool University in China have developed a repair model that predicts future changes using corona-19 daily infected data. And the number of new infections will not increase significantly in the future, and on The 23rd, it will almost never increase to near zero, and it was published on the school’s website (www.xjtlu.edu.cn) on November 11. Courtesy of Xi’an Jiaotong-Liverpool University, China

SEIR is mainly used in repair models used to predict infectious diseases. SEIR is the first letter of the English word for suspectible, exposed, infectious, and removed. Divide the target into four stages of the person who is likely to be infected and predict the patient’s occurrence over time. Depending on the number of people belonging to the four stages of the model can be seen as a time flow of infectious diseases propagation.

However, the model of infectious disease repair is not a pick-up. The proliferation situation flows in the wrong direction with the forecast, or the pattern changes. In fact, many infectious disease repair models have been pouring in in the early days of corona 19, but few have made accurate predictions.

David Paranda, a team of researchers at the French National Center for Scientific Research (CNRS), the London Institute of Mathematics, Imperial College London, and Hokkaido University in Japan analyzed why the predictive accuracy of infectious disease repair models is poor. The results of the analysis using the actual model of infectious disease repair were published in the international journal Chaos on 19 Th of this month.

Repair model, high quality data is difficult to obtain

Worldwide corona19 patient status. Different countries have different aggregation methods and standards. Supplied by Johns Hopkins University.

The researchers found that existing infectious disease repair models depended on only a few families. For example, in the repair model, patients exposed to corona 19 assume that it is transmitted only through humans. In real-world situations, however, they are often infected by viruses that are found on handles and desks, not human beings. In addition, it is assumed that patients or deceased patients who have recovered from corona 19 are forever immune. However, it is not yet known when the immunity of patients with corona 19 persists.

The researchers also pointed out that the quality of the data entering the predictive model also declines. In Italy, for example, patients were not diagnosed and reporting was frequently delayed if symptoms did not appear. China, which was pointed out as the initial origin, has repeatedly put asymptomatic patients in the overall patient statistics, african countries are not counting the exact number of patients. South Korea, on the other hand, is inspecting between 15,000 and 20,000 people every day, including contact vehicles, according to real-time reports. It is pointed out that different criteria and reporting points of data collected by different countries are also limiting the ability to create accurate predictive models. “Even if the number of patients is only 20 percent different, this turns the overall estimate of infected patients from thousands to millions,” the researchers said.

The unpredictability of the epidemiological characteristics of infectious diseases also acts as a factor in reducing the accuracy of the repair model. “During the initial stage of proliferation, they are extremely sensitive to external influences,” the researchers said. For this reason, the research team explains that when deciding on measures such as blockade of cities, it is necessary to make a high-mind decision on the selection of data that enters the infectious disease repair model.

Researcher Kim Chan-so said, “It may be the fate of the model researchers that predicts a wide spread of infectious diseases and signals caution, and if people don’t go outside, the results will eventually be unmatched.”



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