Spatial Effects of Livestock Farming on Human Infections With Shiga Toxin‐Producing Escherichia coli O157 in Small but Densely Populated Regions: The Case of the Netherlands. (23rd November 2020)

• Record Type: Journal Article
• Authors: Mulder, A. C.; van de Kassteele, J.; Heederik, D.; Pijnacker, R.; Mughini‐Gras, L.; Franz, E.
• Is Part Of: GeoHealth. Volume 4:Number 11(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-11-23
• Subjects: STEC O157 -- livestock -- small ruminants -- population‐weighted number of animals -- environmental transmission; Environmental health -- Periodicals; Electronic journals; Periodicals; 616.98
• DOI: 10.1029/2020GH000276
• Languages: English
• ISSNs: 2471-1403

Abstract

Abstract: The role of environmental transmission of typically foodborne pathogens like Shiga toxin‐producing Escherichia coli (STEC) O157 is increasingly recognized. To gain more insights into spatially restricted risk factors that play a role in this transmission, we assessed the spatial association between sporadic STEC O157 human infections and the exposure to livestock (i.e. small ruminants, cattle, poultry, and pigs) in a densely populated country: the Netherlands. This was done for the years 2007–2016, using a state‐of‐the‐art spatial analysis method in which hexagonal areas with different sizes (90, 50, 25 and 10 km 2 ) were used in combination with a novel probability of exposure metric: the population‐weighted number of animals per hexagon. To identify risk factors for STEC O157 infections and their population attributable fraction (PAF), a spatial regression model was fitted using integrated nested Laplace approximation (INLA). Living in hexagonal areas of 25, 50 and 90 km 2 with twice as much population‐weighted small ruminants was associated with an increase of the incidence rate of human STEC O157 infections in summer (RR of 1.09 [95%CI;1.01–1.17], RR of 1.17 [95%CI;1.07–1.28] and RR of 1.13 [95%CI;1.01–1.26]), with a PAF of 49% (95%CI;8–72%). Results suggest exposure to small ruminants to be a risk factor, although no evidence on the mode of transmission is provided. Therefore, the underlying mechanisms warrant further investigation and could offer new targets for control. The newly proposed exposure metric has potential to improve existing spatial modeling studies on infectious diseases related to livestock exposure, especially in densely populated countries like the Netherlands. Plain Language Summary: Contaminated food is often the source of infections transmissible between animals and humans. This is typically caused by foodborne pathogens like Shiga toxin‐producing Escherichia coli (STEC) O157. However, it is increasingly recognized that not all STEC O157 infections are foodborne, as they can also occur via environment‐mediated transmission routes. To gain more insights in what can influence the risk for people to acquire a STEC O157 infection, we assessed the spatial association between sporadic STEC O157 human infections and the exposure to livestock (i.e. small ruminants, cattle, poultry, and pigs) in the Netherlands. This was done for the years 2007–2016, with a novel probability of exposure metric: the population‐weighted number of animals per hexagon. To identify which livestock exposures increase STEC O157 infection risk and how large the contributions of these exposures are (population attributable fraction (PAF)), a spatial regression analysis was performed. Results suggest that exposure to small ruminants is a spatially restricted risk factor, but no evidence on the mode of transmission is provided. Therefore, the underlying mechanisms warrant further investigation and could offer new targets for control. The newly proposed exposure metric has potential to improve existing spatial modeling studies on infectious diseases related to livestock exposure. Key Points: Results indicate that human exposure to small ruminants, and not cattle, is a spatially restricted risk factor for STEC O157 infections However, the underlying mechanisms warrant further investigation and corresponding results could offer new targets for control The newly proposed exposure metric has potential to improve similar spatial modeling studies, especially in densely populated countries