Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted more effectively in densely populated areas and omitting this phenomenon from epidemiological models may substantially affect projections of spread and control. Adjusting for deprivation, proportion of ethnic minority population and proportion of key workers among the working population, mortality data from England show good evidence for an increasing trend with population density until a saturating level. Projections from a mathematical model that accounts for this observation deviate markedly from the current status quo for SARS-CoV-2 models which either assume linearity between density and transmission (30% of models) or no relationship at all (70%). Respectively, these standard model structures over- and under-estimate the delay in infection resurgence following the release of lockdown. Models have had a prominent role in SARS-CoV-2 intervention strategy; identifying saturation points for given populations and including transmission terms that account for this feature will improve model utility.

This chapter is focused on the use of maps to summarize the principal epidemiological features behind heterogeneities of dengue virus (DENV) transmission. The nature of the epidemiological data that can be used for mapping is described and how various local and national maps utilize that data is illustrated. Global maps of current and potential future dengue distributions are presented and their use to inform control efforts and epidemiological research is discussed.