DATA AVAILABILITY STATEMENT : The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary material.INTRODUCTION : Physical and non-physical processes that occur in nature may
influence biological processes, such as dissemination of infectious diseases.
However, such processes may be hard to detect when they are complex systems.
Because complexity is a dynamic and non-linear interaction among numerous
elements and structural levels in which specific effects are not necessarily linked
to any one specific element, cause-effect connections are rarely or poorly
observed.
METHODS : To test this hypothesis, the complex and dynamic properties of
geo-biological data were explored with high-resolution 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
epidemiologic data display complex properties? and (ii) can such properties
facilitate or prevent disease dissemination?
RESULTS : 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.
DISCUSSION : Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis
of geo-referenced complexity may support anticipatory epidemiological policies.https://www.frontiersin.org/journals/veterinary-science#am2024Veterinary Tropical DiseasesSDG-03:Good heatlh and well-bein