MAPS Forecast through the end of the year

MAPS Forecast through the end of the year

September 10, 2022

This is NOT a normal forecast, it is an uncalibrated training run "straight out of the box". In this run a 50% new booster compliance is assumed with a normalized rollout delivery rate. Recent wastewater data has indicated an upcoming surge. The model captures this likely mini surge. It is too early for the new booster to have a significant impact but over the course of the next few months it is likely having an effect.

A few of caveats, this is a training run for the model ensemble, does not include "spreader" events, and does not have BA.4.6 or BA.2.75 variants. As indicated in the article below, the BA.4/5 subvariants exhibit nearly a 2 fold increase in evading immunity. First, the training will be completed with these variants and spreader events, and then sensitivity simulations with/without the new booster added.These will all be posted sometime tomorrow/Monday with state forecasts and animations.This MAPS version has a new reinfection algorithm that is much more realistic. At least it suggests we can get off this "plateau" we are currently. Remember the high possibility of a new variant could put us in familiar territory again. Global wide vaccination is a must!

For the love of humanity get the new booster/mask/distance!

Other news of interest: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.biorxiv.org/content/10.1101/2022.08.09.503384v1.full.pdf

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MAPS Model Description

Multiple Algorithm Pandemic Software MAPS is a valuable tool for forecasts or research that simulates pandemics or epidemics. It is written so that for a given virus the use can choose what type of differential equation solver that is most appropriate. The level of sophistication allows the simulation of the common flu to more complicated viral pathways. It is written in modular FORTRAN and can be run in serial (one processor) or parallel (unlimited processors). This provides a platform that can model a single point all the way up to global scales. If run in parallel the domain is decomposed to accommodate the number of processors specified. In this mode the domain is specified by latitude and longitude bounds and a desired grid spacing to produce a mesh, where the differential equations are solved for each square contained in the mesh. The individual points and MPI decomposed sub-domains are not independent. They communicate through ground and air transportation. The model has several solver algorithms, from a simple SI compartment model (flu) to the most sophisticated SEIRDCV (Susceptible Exposed Infected Recovering Death reCovered Vaccinated) compartment model. Variants are all subject to their own characteristic settings, from varying transmission to death rates. They also have settings for hospitalization rates. Hospitalization has its own algorithm that can mimic capacity effects like stress, triage mode, transport to adjacent hospitals, and ICU vs normal beds. Each variant also has its own mask/Shelter In Place settings reflecting country/state/local. mitigation policies including vaccination/booster rates. Output can range from global, country, state, local average files with the S E I R C D V fields or optional spatial output (GrADS, EWB, netCDF, ascii). The model also can be run in a "normal" or "forecast" modes. Post-processing can be run as a simple statistical analysis or a more involved training mode for the forecast system. The assimilation system can ingest observations at multiple scales with a multitude of methodologies. Seperate files are created depending on the number of processors deployed.