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In this study, we couple compartment models for indoor air quality and disease transmission to develop a novel SEIR-e model for disease transmission and pathogen exposure. In doing so, we gain insight into the contribution of people–people and people–pathogen interactions to the spread of transmissible diseases. A general modelling framework is used to assess the risk of infection in indoor environments due to people–pathogen interactions via inhalation of viral airborne aerosols, and contact with contaminated surfaces. We couple the indoor environment model with a standard disease transmission model to investigate how both people–people and people–pathogen interactions result in disease transmission. The coupled model is referred to as the SEIR-e model. To demonstrate the applicability of the SEIR-e model and the novel insights it can provide into different exposure pathways, parameter values which describe exposure due to people–people and people–pathogen interactions are inferred using Bayesian techniques and case data relating to the 2020 outbreak of COVID-19 in Victoria (Australia).

At the centers of previously glaciated regions such as Hudson Bay in Canada and the Gulf of Bothnia in Fennoscandia, it has been observed that the sea level history follows an exponential form and that the associated decay time is relatively insensitive to uncertainty in the ice loading history. We revisit the issue of decay time sensitivity by computing relative sea level histories for Richmond Gulf and James Bay in Hudson Bay and Ångerman River in Sweden for a suite of reconstructions of the North American and Fennoscandian Ice Sheets and Earth viscosity profiles. We find that while some Earth viscosity models do indeed show insensitivity in computed decay times to the ice history, this is not true in all cases. Moreover, we find that the location of the study site relative to the geometry of the ice sheet is an important factor in determining ice sensitivity, and based on our set of ice sheet reconstructions, conclude that the location of James Bay is not well-suited to a decay time analysis. We describe novel corrections to the RSL data to remove the effects associated with the spatial distribution of sea level indicators as well as for other signals unrelated to regional ice loading (ocean loading, rotation and global mean sea-level changes) and demonstrate that they can significantly affect the inference of viscosity structure. We performed a forward modelling analysis based on a commonly adopted 2-layer, sub-lithosphere viscosity structure to determine how the solution space of viscosity models changes with the input ice history at the three study sites. While the solution spaces depend on ice history, for both Richmond Gulf and Ångerman River there are regions of parameter space where solutions are common across all or most ice histories, indicating low ice load sensitivity for these mantle viscosity parameters. For example, in Richmond Gulf, upper mantle viscosity values of (0.3–0.5)x1021 Pa s and lower mantle viscosity values of (5–50)x1021 Pa s tend to satisfy the data constraint consistently for most ice histories considered in this study. Similarly, the Ångerman River solution spaces contain a solution with an upper mantle viscosity of 0.3 × 1021 Pa s and lower mantle viscosity values of (5–50)x1021 Pa s common to 9 of the 10 ice histories considered there. However, the dependence of the viscosity solution space on ice history suggests that joint estimation of ice and Earth parameters is the optimal approach.

We present a sensitivity analysis aimed at testing whether observables related to glacial isostatic adjustment can support or refute the occurrence of a low viscosity melt-rich layer (MRL) above the mantle transition zone, as required by the 'transition-zone water-filter' model (Bercovici & Karato 2003). In total, 1600 model runs were performed sampling a range of MRL thicknesses (1, 10 and 20 km) and viscosities (10 15 -10 19 Pa·s), plausible viscosity values in the upper and lower mantle regions and four distinct ice histories. To determine decay time constraints, we consider relative sea level (RSL) data from two sites [Angerman River (AR), Sweden and Richmond Gulf (RG), Canada] and use a new method of observational sea level data correction. Comparing model output of postglacial decay times and J 2 to observational constraints, we find numerous possible solutions, largely as a result of parameter trade-off. The investigated observables are sensitive to the existence of an MRL and reasonable variations in its thickness and viscosity. The magnitude and nature of this sensitivity varies between the two data types as well as the adopted background viscosity structure. Decay time results from either considered location do not strictly support or exclude MRL existence. However, both locations offer MRL viscosity requirements for given thicknesses, with AR being more restrictive. RG constraints allow MRL viscosities as low as 10 16 Pa·s (10 km) and 10 17 Pa·s (20 km). AR results narrow these permitted viscosity ranges to 10 18 Pa·s or greater for both 10 and 20 km MRL thicknesses. In the case of a 1 km thick MRL, AR constraints permit the viscosity to be as low as 10 17 Pa·s, whereas those of RG permit any MRL viscosity. The decay time observations are satisfied by only a small subset of 'background' mantle viscosities (regardless of the MRL properties), none of which support a spherically symmetric solution of Earth viscosity. Finally, comparing model output to the observed J 2 value did not provide any constraints on MRL properties. However, our results show that this observable has a strong preference for viscosity values in the lower mantle that are equal to or greater than 10 22 Pa·s.