CONTRIBUTIONS OF SPATIAL EPIDEMIOLOGY TO THE MONITORING AND CONTROL OF Q FEVER: SYSTEMATIC REVIEW
Abstract
Q fever is a worldwide zoonosis caused by Coxiella burnetii with many hosts, being domestic ruminants the most important infection source for humans, mainly after inhalation of contaminated aerosols or because the proximity to areas with infected livestock. Geographic information systems (GIS) is becoming increasingly accurate providing spatial databases of infectious disease trends. We followed the PRISMA method and searched for literature in three databases: PubMed®, Scopus® and Web of Science. Initially we obtained 1584 records, of which a total of 86 articles were finally included, published from 31 different countries between 1964 and 2021. We extracted quantitative information that we coded and included in an Excel table and summarized the main contributions. Since the epidemic in the Netherlands between 2007-2010, more and more articles have been published on this topic, with the Netherlands being the country with the highest number of extracted references. Map visualization was present in 60% of the cases, while the remaining 20% used spatial tools to perform scans or modelling to predict and monitor the incidence of Q fever. Most of the maps depicted are symbol or coropletic graphic maps, isopletic appear to a lesser extent or combined with the other two. ArcGis and to a smaller degree QGIS are mostly used for the realization of these maps. This GIS software provide tools for mapping and spatial analysis. Other software such as SPSS and R were used for the analysis of spatial data and spatio-temporal models applied to GIS, such as the Kernel density model or Bayesian models. GIS are more used in animal health than in public health and GIS stated the important role of wind in the spread of the infection or detect the risk of infection for people in relation to proximity to infected dairy goat herds.
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