The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world's most vulnerable populations at risk. Epidemiological modelling is vital to guiding evidence-informed or data-driven decision making. In forced displacement contexts, and in particular refugee and internally displaced people (IDP) settlements, it meets several challenges including data availability and quality, the applicability of existing models to those contexts, the accurate modelling of cultural differences or specificities of those operational settings, the communication of results and uncertainties, as well as the alignment of strategic goals between diverse partners in complex situations. In this paper, we systematically review the limited epidemiological modelling work applied to refugee and IDP settlements so far, and discuss challenges and identify lessons learnt from the process. With the likelihood of disease outbreaks expected to increase in the future as more people are displaced due to conflict and climate change, we call for the development of more approaches and models specifically designed to include the unique features and populations of refugee and IDP settlements. To strengthen collaboration between the modelling and the humanitarian public health communities, we propose a roadmap to encourage the development of systems and frameworks to share needs, build tools and coordinate responses in an efficient and scalable manner, both for this pandemic and for future outbreaks.

This study demonstrates how a large-scale satellite-derived dataset can be used to investigate statistically robust trends in shoreline position over a 31-year period from 1987 to 2017, at a regional scale. Regional patterns of shoreline behaviour are important for resolving consistent or, alternatively, dissimilar patterns of past shoreline change. Such patterns are best explored using temporally frequent and spatially extensive datasets. Here we analyse satellite-derived shorelines to identify spatial patterns of hotspots of coastline change on the wave-exposed coast of Victoria in south-east Australia where rates of change exceed 0.5 m yr⁻¹. Analysis of shoreline position changes at a 50 m alongshore interval along 900 km of the 1230 km coastline reveals a number of distinct behaviours related to coastal type (rock vs sand coast), landform, shoreline orientation and/or anthropogenic drivers of change. Overall the results show that statistically significant change in shoreline position has affected only a relatively small proportion of the study region over the last 31 years; that the proportion and rate of progradational and recessional change is similar; and that change is localised but dispersed widely along the Victorian coast. Coasts located at the entrances to large tidal inlets have shown the greatest change. The association of hotspots with embayed sandy beaches and adjacent to headlands points to the importance of geological control on shoreline behaviour. Consistent with other regional scale studies of shoreline change, this study found little regional coherence in shoreline behaviour. Instead change is predominately attributed to local factors such as the geological framework of the coast, localised hydrodynamic conditions and anthropogenic influences. Collectively, these results indicate that there is strong geologic control on shoreline erosion in Victoria due to the high diversity of landforms along the coastline; and that further analysis is required to tease out the seasonal to interannual sensitivities to changes in the historical wave climate and the secondary interaction of sediment supply for headlands and hydrodynamics for tidal inlets.