Update Round5-MODUS_Covid-Episim-Abstract.md

updated abstract w/ more descriptions

model-abstracts/2023-08-01/Round5-MODUS_Covid-Episim-Abstract.md

@@ -8,14 +8,14 @@ _Usage: Please copy this file and save in your team's `data-processed` folder, r
 
 ## Summary comments on results
 **Difference between vaccination campaigns:**
-No matter which vaccination campaign we assume, we observe an infection wave in October 2023 and a smaller infection wave in March 2024. The differences in heights of peaks and valleys between the different campaigns are negligible small. We believe that we hardly see a difference in infection numbers when considering the different campaigns, as the vaccine's effect is outsized for progression to a more severe disease state, especially for the elderly (60+) population.
+No matter which vaccination campaign we assume, we observe an infection wave in October 2023 and a smaller infection wave in March 2024. The differences in heights of peaks and valleys between the different campaigns are negligible. We believe that we hardly see a difference in infection numbers when considering the different campaigns, as the vaccine's effect is outsized for progression to a more severe disease state, especially for the elderly (60+) population.
 
 **Difference between optimistic and pessimistic waning:**
-For both optimistic and pessimistic waning we observe the above-mentioned waves in October 2023 and March 2024. The heights of the peaks and valleys are lower when assuming optimistic waning. We believe that the difference in waning speed is too small to have any significant effect on the structure of the infection curve in our model. 
+For both optimistic and pessimistic waning we observe the above-mentioned waves in Fall 2023 and Spring 2024; with the optimistic scenarios, the waves occur several weeks later than in the pessimistic scenarios. The valley between the Fall & Spring waves, as well as the Spring peak have lower infections in the optimistic scenario than in the pessimistic scenario. 
 
 ## Comments on observed dynamics given model assumptions
 
-For future virus variants, we assume that they are introduced every 30 days, with a constant immune escape speed.  Earlier simulations have shown that without seasonal effects this leads, within a small number of years, to a dying out of the waves and in consequence to a constant incidence.  Once we include seasonal effects, this leads to a self-selection of a wave length that fits into the annual cycle, e.g. one or two or three waves per year.   With currently plausible parameters, these wave lengths are much longer than the above 30 days, meaning that only _some_ of the new virus variants trigger a new wave.
+For future virus variants, we assume that they are introduced every 30 days, with a constant and relatively small immune escape speed (no "game-changer" variants).  Earlier simulations have shown that without seasonal effects this leads, within a small number of years, to a dying out of the waves and in consequence to a constant incidence.  Once we include seasonal effects, this leads to a self-selection of a wave length that fits into the annual cycle, e.g. one or two or three waves per year. With currently plausible parameters, these wave lengths are much longer than the above 30 days, meaning that only _some_ of the new virus variants trigger a new wave.
 
 The wave length is determined by the waning speed of the immunity <mark>multiplied with</mark> the escape speed of the virus variants -- the slower the waning speed and the slower the escape speed, the longer the wave length.  It is to be expected that both get slower, and indeed the data from 2023 implies that the overall dynamics has made considerable progress in this direction.  
 
@@ -28,18 +28,18 @@ Our model predicts (still) two waves per year for both the "optimistic" and the
 ### Waning of protection against infection
 In our model we assume that receiving the monovalent booster XBB1.5 or being infected with the XBB1.5 strain results in a protection against infection of 98%. We hereby assume the the novel monovalent XBB1.5. booster protects as well against the XBB1.5. variant as the initial mRNA vaccine protected against the wild type. 
 
-We model protection against infection ...  <mark>bitte erklären.</mark>
+Our ABM explicitly models effective antibody levels of each agent in response to immunisation events (infections and vaccinations). Higher levels of antibodies lead to higher protection against infection. For more details on this mechanism, see [Müller et al.](https://doi.org/10.1016%2Fj.isci.2023.107554)
 
 We assume the same waning speed for all agents.
 
 #### Optimistic waning of protection against infection 
-Within 6 months the protection wanes to 70% of the initial immunty, resulting in a VE against infection of <mark>69%</mark>.
+Based on the Round 5 guidlines, the protection wanes to 70% of the initial immunty (VE = 98%) within 6 months, resulting in a VE against infection of <mark>69%</mark>.
 
 #### Pessimistic waning of protection against infection
-Within 6 months the protection wanes to 40% of the initial immunty, resulting in a VE against infection of <mark>39%</mark>.
+Within 6 months the protection wanes to 40% of the initial immunty (VE = 98%), resulting in a VE against infection of <mark>39%</mark>.
 
 #### Any variation from the scenarios as specified
-FILL (if applicable)
+None. 
 
 ### Vaccination
 
@@ -65,7 +65,7 @@ We do not consider immune classes, rather every agent has their own unique immun
 In our model, whenever an agent recovers, they are automatically considered susceptible again. They never reach full immunity. Hence, every agent is (to a certain extent) susceptible.
 
 ##### Proportion of people that are naïve at start of projection (not vaccinated or infected)
-Less than XX% of our agents are naive at the start of the projection (meaning that they have neither been vaccinated nor been infected with ANY virus strain).
+Around 5% of our agents are naive at the start of the projection (meaning that they have neither been vaccinated nor been infected with ANY virus strain). Note: in our Round 2 submission, <2% of agents were naive at the start of the study time frame. We have updated our model parameters since then, leading to this discrepancy. 
 
 #### Population ageing 
 Not implemented.