Back

An age-structured epidemiological model of the Belgian COVID-19 epidemic

Deforche, K.

2020-04-29 epidemiology
10.1101/2020.04.23.20077115 medRxiv
Show abstract

COVID-19 has prompted many countries to implement extensive social distancing to stop the rapid spread of the virus, in order to prevent over-loading health care systems. Yet, the main epidemic parameters of this virus are not well understood. In the absence of broad testing or serological surveillance, it is hard to evaluate or predict the impact of different strategies to exit implemented lock-down measures. An age-structured epidemiological model was developed, which distinguishes between the younger versus older population (e.g. < 65 and [&ge;] 65). Because the illness severity is markedly different for these two populations, such a separation is necessary when estimating the model based on death and hospitalization incidence data. The model was applied to data of the Belgian epidemic and used to predict how the epidemic would react to a relaxing of social distancing measures.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.