A new data on the development of the coronavirus infection in the human body was received by the researchers at Trinity College in Dublin. The most important discovery of the scientists is that they have identified a new date for the incubation period of the COVID-19. If earlier the doctors believed that the incubation period lasts from 4 to 7 days, and after it the disease develops in the body, now, a new data have been obtained.
The incubation period can be up to 34 days. This fact can become a serious social turn in decision-making by the governments of many countries of the world. The officials take most of the quarantine measures and restrictions on the basis of the incubation period of the disease of 14 days.
Now, based on a new data, this approach should be revised. The incubation period can be much longer. It means that self-isolation must be extended and provided with various protective measures.
Throughout the pandemic, the scientists have repeatedly encountered a change in the incubation period. In the first stage of the study of the disease, they concluded that the incubation of the virus lasts from 4 to 6 days.
A little later, they found that the incubation period can last for 14 days in the human body. Today these data was updated with a new term, it takes up to 34 days. First of all, according to the researchers, the latent incubation period can be associated with both symptomatic and asymptomatic infections, when it becomes difficult to establish the prevalence and transmission of the disease.
The scientists compiled mathematical simulations of the effective reproductive number R of the epidemic, the spread of the infection, and subsequent planning and mitigation decisions. It all depends entirely on accurate and up-to-date estimates of key modeling parameters.
Taking into account the surveillance situation in different countries of the world, the monitoring data that is carried out in all countries, has provided an updated estimate of the distribution of the incubation period, which, in turn, will improve the modeling of estimates of the effective reproductive number R and, in turn, estimates of the prevalence of asymptomatic cases.