Geographical patterns of epidemic diffusion in small regional settings

The effects of human spatial organization, infectious disease properties, and population structure on spatial and temporal epidemic patterns in small regional settings were analyzed in this study. Using ideas from previous geographical, epidemiological, and biomathematical works, a simulation model was developed. Spatial and demographic scenarios, used in the simulation model, were recreated from archival research and the literature on settlement patterns. The primary model scenario was an example from a rural preindustrial parish located in western Finland. A descriptive analysis was performed on smallpox and whooping cough epidemics which occurred in this parish during the years 1750-1850. Basic epidemic patterns were discovered in this analysis which were shown to be related to epidemic contact fronts. The diffusion of mortality was also examined. Next, different model spatial settings were devised for use with the simulation model. One of these models was an idealized version of the Finnish parish and the other two models were developed to show the relative effects of settlement patterns on epidemic time series. In addition to these model spatial settings, several contrived disease types with variable length transmission chains were used in the simulations. Factors such as regional population size, susceptible population size, household sizes, and the number of villages were also incorporated into the simulation model. The resulting time series distributions from these simulation runs were reduced to descriptive statistical parameters and other measures. The parameters were then plotted and compared. It was demonstrated that simulated epidemics showed some of the same characteristics of spatial spreading as the natural epidemics occurring in the parish.;However, there was a distinct difference between morbidity and mortality diffusion patterns. Morbidity diffusion among villages tended to be spatially clustered, while mortality diffusion showed a significant alternating spatial pattern. From plots of the duration of epidemics against the percentage of infected individuals, graphical clusters emerged which were associated with disease types and spatial organization. This provided a possible means by which epidemics of unknown or vague etiologies can be identified. The simulation model developed in this study could also be adapted for historical and archaeological research of epidemics in extinct and small modern populations.