Note: in the actual analysis, the effect of December Tiers was
removed.

CHANGES:

1. Re-introduced Tier lockdown covariates.  National lockdown covariate is set to 0 because
   we cannot identify this from the time-varying baseline force of infection.

2. Added inference on variance parameter for the temporal Gaussian process on beta.

CHANGES:

1. update date and data name in enqueue_pipeline.sh
2. update infection time initialisation in model_spec.py

CHANGES:

1. Implemented log-linear model for weekday effect in I->R hazard;
2. Updated summary.py and within_between.py to match;
3. Implemented linear random walk for new gamma0 parameter.
4. Implemented per-parameter data structure in output HDF5 file.

CHANGES:

1. Updated the model to use the new gemlib library;
2. Removed automatic deletion of results directory by prepare_config.py;
3. Parameterised `gamma` prior parameters and added to template_config.yaml;
4. Updated within_between.py to use global configuration file.

==============================

enqueue_pipeline.sh --> covid_pipeline.sge --> prepare_config.py --> inference.py --> summary.py

enqueue_pipeline.sh identifies the dataset and analysis period, launching 4 SGE jobs [P1, P1+2]\times[specimen_date, report_date]

Each SGE job runs the inference and summary scripts, using information contained in a config.yaml file.

The config.yaml file, together with results outputs, are stored in a results directory specified the config file
and over-ridden in the top-level enqueue_pipeline.sh script.