AUTHOR=Hoogesteyn A. L. , Rivas A. L. , Smith S. D. , Fasina F. O. , Fair J. M. , Kosoy M. 

TITLE=Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination

JOURNAL=Frontiers in Veterinary Science

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2023.1149460

DOI=10.3389/fvets.2023.1149460

ISSN=2297-1769

ABSTRACT=Geo-referenced physical and non-physical processes in nature may influence biological processes, such as within infectious disease outbreaks. To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced data display complex properties? and (ii) can such properties facilitate or prevent disease dispersal? Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties ‒including data circularity‒ were demonstrated. The emergent patterns helped identify 11 counties as ‘disseminators’ or ‘facilitators’ (F) and 264 counties as ‘barriers’ (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. If further corroborated, it is suggested that the analysis of geo-referenced complexity may support anticipatory epidemiological policies.