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1/3 Update of the #covid19 situation in the hospitals of #Belgium. SEIR model is fitted on data over a short period for estimating Re. This plot is for 6-7 days.
2/3 Other plots show results with longer periods. You see a longer plateau and lower values of Re. In fact the estimation is smoother and less reactive to any change, and underfits the hospitalisations (around day30)...
3/3 CONCLUSION : Fitting data is like playing golf : depending on the club you choose, a different force (Re) is applied on the ball over a different contact period. But at the end, similar ball trajectories are obtained (same trend for the fit).

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Nicolas Vandewalle
@vdwnico
A question which is often raised : Was it possible to anticipate the #coronavirus disaster as early as January ? Of course, and I will prove it in this thread... Picture = timeline of #covid19
2/5 In the period January-February, politicians and some experts often compared #covid19 with #influenza, consequently minimizing the problem. My best of citations :
3/5 Let us compare #covid19 (left) vs #influenza (right) with numbers already available by the end of January ! You observe already huge differences. My prefered one : immunity ! Since #covid19 is a new virus, WHO estimated that min 70% of the population will be touched.
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Nicolas Vandewalle
@vdwnico
1/7 [ANALYSIS] Last day before lifting #lockdown in #Belgium. How is the actual situation ? The situation by province seems green everywhere. What to expect the next days ? It is time for a thread about Re and scenarios.
2/7 Looking at numbers, we observe that on May 4th, we have roughly the same number of active cases than March 16th, BUT with 6 times patients in hospitals than the first day of the #lockdown. However, Re decreased by more than a factor 4 !
3/7 Re/R0 is roughly the product of three parameters : Re = T.C.tau where T is the transmissibility of the virus at each contact, C is the average number of contacts per unit of time, and tau is the duration of the disease.
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Nicolas Vandewalle
@vdwnico
1/6 My SEIR model follows the daily data for patients in hospital and ICU. Like ALL other epidemiological models, it is sensitive to many parameters. Nevertheless, it gives trends and the opportunity to test different strategies for leaving the confinement.
2/6 [ACTUAL SCENARIO = CONFINEMENT] Assuming that Re is around 0.8 (as claimed by @sciensano and neglecting the current fluctuation around 1.2) and remains unchanged after May 4, the situation in ICU will improve slowly. Still above 40% of total ICU capacity in June.
3/6 [UNREALISTIC SCENARIO] In an extreme situation : Re takes the value before #lockdown after May 4, the ICU are saturated within 12 days. Not a surprise since it is the average time to develop the disease and to be transferred to hospitals.
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