Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa
Fig 2
A summary of previously published papers incorporating human mobility models and infectious disease dynamics.
We reviewed nineteen papers that either simulated (simulated) disease dynamics or used epidemiological data (data). These papers covered a range of infectious diseases (see S1 Table). For each paper we identified the type of mobility model, disease model, location (high, low, or both high and low income country), and the type of movement quantified. Mobility models were classified as a gravity model, radiation model, a spatial transmission kernel, a network, or a risk surface. Disease models included a metapopulation model, metapopulation type model with stochastic fadeouts, time spent at locations with different risks of becoming infected, an individual based model (IBM), and a network. For each paper, the location of either the mobility and/or disease data determined the location of the paper with countries separated as high income or low income. Papers that focused on global disease spread were classified as both high and low income. Mobility was classified as either commuting, regional, or global movement patterns. If the paper did not explicitly state the type of mobility included in the paper the type of mobility was discerned from the spatial resolution of the data. Regional movement includes mobility between political admin units that are larger than a city, in general. If a paper included both global movements, such as airline flights, and localized commuting, then the paper was classified as global. We included papers describing various infectious diseases including cholera, malaria, dengue, measles, pertussis, rubella, influenza, and foot and mouth disease.