Parna Mandal (University of Leeds) – How Human Mobility and Urban Structure Shape Cholera Transmission

Urbanization shapes infectious disease dynamics through mobility, infrastructure, and spatial structure. Prior work shows how density and network connectivity influence epidemic spread [1,2], particularly for directly transmitted diseases such as COVID-19 and influenza [1,2,3]. However, many models assume pairwise transmission or use static mobility representations, which are less suitable for waterborne diseases like cholera, where risk depends on overlap between movement and shared infrastructure. While spatial cholera dynamics have been studied [4], few models combine mechanistic disease progression, behaviourally realistic mobility, and spatially explicit infrastructure. Common mobility models (e.g., gravity or radiation [2], commuting data [3]) also fail to capture repeated, preferential use of specific locations.

We develop a spatially explicit agent-based model combining a SEIRS process with a density-augmented Exploration and Preferential Return (d-EPR) mobility framework. Agents move between households and shared infrastructure, repeatedly visiting familiar locations while occasionally exploring new ones. Contamination accumulates at infrastructure sites and infection occurs through repeated exposure. The model is implemented on GIS-based urban layouts to examine how spatial structure, movement, and infrastructure jointly shape epidemic dynamics.

Results show that infection concentrates around shared infrastructure, particularly in main activity hubs. In baseline settings, mobility clusters agents into high-use areas, producing localised growth before outward spread. Mobility reduction limits spatial spread and lowers incidence but increases localised exposure. Decentralisation redistributes activity, reducing pressure on individual sites and lowering transmission by limiting repeated exposure. Across scenarios, concentrated movement leads to a small number of high-burden transmission points and faster outbreaks, while reduced or distributed movement spreads load, lowering peak exposure and flattening incidence. These findings highlight the central role of mobility, infrastructure interactions and suggest that targeted, structure-specific interventions are more effective than uniform approaches.

[1]Aguilar, J., Bassolas, A., Ghoshal, G., Hazarie, S., Kirkley, A., Mazzoli, M., ... & Sadilek, A. (2022). Impact of urban structure on infectious disease spreading. Scientific reports, 12(1), 3816.

[2] Wen, T. H., Hsu, C. S., & Hu, M. C. (2018). Evaluating neighborhood structures for modeling intercity diffusion of large-scale dengue epidemics. International journal of health geographics, 17, 1-15.

[3] Moss, R., Naghizade, E., Tomko, M., & Geard, N. (2019). What can urban mobility data reveal about the spatial distribution of infection in a single city?. BMC public health, 19, 1-16.

[4] Phelps, M. D., Azman, A. S., Lewnard, J. A., Antill´on, M., Simonsen, L., Andreasen, V., & Pitzer, V. E. (2017). The importance of thinking beyond the water-supply in cholera epidemics: A historical urban case-study. PLoS neglected tropical diseases, 11(11), e0006103.