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Spatio-temporal cluster analysis of the incidence of Campylobacter cases and patients with general diarrhea in a Danish county, 1995-2004.

Jepsen MR, Simonsen J, Ethelberg S - Int J Health Geogr (2009)

Bottom Line: We used a modified form of local Moran's I to test if features with similar incidence rates occurred next to each other in space and time, and compared the observed clusters with simulated clusters.The results showed a significant persisting clustering of Campylobacter incidence rates in the Western part of Funen.Results were visualized using the Netlogo software.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of policy analysis, National Environmental Research Institute, University of Aarhus, Roskilde, Denmark. mrj@dmu.dk

ABSTRACT
Campylobacter infections are the main cause of bacterial gastroenteritis in Denmark. While primarily foodborne, Campylobacter infections are also to some degree acquired through other sources which may include contact with animals or the environment, locally contaminated drinking water and more. We analyzed Campylobacter cases for clustering in space and time for the large Danish island of Funen in the period 1995-2003, under the assumption that infections caused by 'environmental' factors may show persistent clustering while foodborne infections will occur randomly in space. Input data were geo-coded datasets of the addresses of laboratory-confirmed Campylobacter cases and of the background population of Funen County. The dataset had a spatial extent of 4.900 km2. Data were aggregated into units of analysis (so-called features) of 5 km by 5 km times 1 year, and the Campylobacter incidence calculated. We used a modified form of local Moran's I to test if features with similar incidence rates occurred next to each other in space and time, and compared the observed clusters with simulated clusters. Because clusters may be caused by a high tendency among local GPs to submit stool samples, we also analyzed a dataset of all submitted stool samples for comparison. The results showed a significant persisting clustering of Campylobacter incidence rates in the Western part of Funen. Results were visualized using the Netlogo software. The underlying causes of the observed clustering are not known and will require further examination, but may be partially explained by an increased rate of stool samples submissions by physicians in the area. We hope, by this approach, to have developed a tool which will allow for analyses of geographical clusters which may in turn form a basis for further epidemiological examinations to cast light on the sources of infection.

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A nine year stack of data highlighting the province capital Odense.
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Figure 2: A nine year stack of data highlighting the province capital Odense.

Mentions: Combining the 25 km2 cells with a one year temporal resolution of the nine year period covered (1995–2003) resulted in a three-dimensional data frame, where the unit of analysis is a space-time cell with the dimensions 25 km2 * 1 year, henceforth referred to as a feature. In total, the data frame was composed of 1,881 features (209 * 9). The space-time continuum was thus divided into discrete units where the third spatial dimension, elevation, was substituted for time. In the following, we will refer to all features within a given year as a 'layer' and to all features from the same geographical location as a 'stack'. Figure 2 shows the data frame with the study area (corresponding to a layer) demarked in green and a nine year 'stack' of data for the 25 km2 area covering Odense, the major city on Funen.


Spatio-temporal cluster analysis of the incidence of Campylobacter cases and patients with general diarrhea in a Danish county, 1995-2004.

Jepsen MR, Simonsen J, Ethelberg S - Int J Health Geogr (2009)

A nine year stack of data highlighting the province capital Odense.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2654880&req=5

Figure 2: A nine year stack of data highlighting the province capital Odense.
Mentions: Combining the 25 km2 cells with a one year temporal resolution of the nine year period covered (1995–2003) resulted in a three-dimensional data frame, where the unit of analysis is a space-time cell with the dimensions 25 km2 * 1 year, henceforth referred to as a feature. In total, the data frame was composed of 1,881 features (209 * 9). The space-time continuum was thus divided into discrete units where the third spatial dimension, elevation, was substituted for time. In the following, we will refer to all features within a given year as a 'layer' and to all features from the same geographical location as a 'stack'. Figure 2 shows the data frame with the study area (corresponding to a layer) demarked in green and a nine year 'stack' of data for the 25 km2 area covering Odense, the major city on Funen.

Bottom Line: We used a modified form of local Moran's I to test if features with similar incidence rates occurred next to each other in space and time, and compared the observed clusters with simulated clusters.The results showed a significant persisting clustering of Campylobacter incidence rates in the Western part of Funen.Results were visualized using the Netlogo software.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of policy analysis, National Environmental Research Institute, University of Aarhus, Roskilde, Denmark. mrj@dmu.dk

ABSTRACT
Campylobacter infections are the main cause of bacterial gastroenteritis in Denmark. While primarily foodborne, Campylobacter infections are also to some degree acquired through other sources which may include contact with animals or the environment, locally contaminated drinking water and more. We analyzed Campylobacter cases for clustering in space and time for the large Danish island of Funen in the period 1995-2003, under the assumption that infections caused by 'environmental' factors may show persistent clustering while foodborne infections will occur randomly in space. Input data were geo-coded datasets of the addresses of laboratory-confirmed Campylobacter cases and of the background population of Funen County. The dataset had a spatial extent of 4.900 km2. Data were aggregated into units of analysis (so-called features) of 5 km by 5 km times 1 year, and the Campylobacter incidence calculated. We used a modified form of local Moran's I to test if features with similar incidence rates occurred next to each other in space and time, and compared the observed clusters with simulated clusters. Because clusters may be caused by a high tendency among local GPs to submit stool samples, we also analyzed a dataset of all submitted stool samples for comparison. The results showed a significant persisting clustering of Campylobacter incidence rates in the Western part of Funen. Results were visualized using the Netlogo software. The underlying causes of the observed clustering are not known and will require further examination, but may be partially explained by an increased rate of stool samples submissions by physicians in the area. We hope, by this approach, to have developed a tool which will allow for analyses of geographical clusters which may in turn form a basis for further epidemiological examinations to cast light on the sources of infection.

Show MeSH
Related in: MedlinePlus