2014.ISDS.Abstracts.Final.pdf


ISDS Annual Conference Proceedings 2014. This is an Open Access article distributed under the terms of the Creative Commons Attribution-
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ISDS 2014 Conference Abstracts

Spatial Analysis when the Location of Infection is 
Uncertain: An Innovative Approach Using an Animal-
Herd-Level Weighted Analysis
Céline Dupuy*1, 2, Claire Morlot3, Pierre Demont4, Marie-Pierre Callait-Cardinal4, Christian 
Ducrot2, Didier Calavas1 and Emilie Gay1

1ANSES, Lyon, France; 2INRA, Saint Genès Champanelle, France; 3Direction générale de l’Alimentation, Paris, France; 4VetAgroSup, 
Marcy l’Etoile, France

Objective
Spatial analysis of infectious diseases enables identification of 

areas at high risk for infection, a useful tool for implementation of 
risk-based surveillance. For chronic diseases, the period between 
infection and detection can be long and when animal movements are 
important, identifying the place of infection is difficult. The objective 
of this study is to propose an innovative approach for spatial analysis 
that takes into account uncertainty regarding the location where 
animals were infected. An animal-herd-level weighted analysis was 
used and applied to bovine cysticercosis in France.

Introduction
Bovine cysticercosis is a zoonotic foodborne disease caused by 

Taenia saginata involving cattle as the intermediate host and humans 
as the final host. Humans are infected by eating raw or undercooked 
meat of infected cattle. Cattle are infected after grazing on pasture 
infected by human feces. Disease detection in cattle is performed 
during post-mortem meat inspection at the slaughterhouse through 
the identification of cysts in muscle tissue. Cysts develop from a 
viable stage to a degenerated stage in one to nine months, both stages 
being visible and distinguishable in cattle muscle. Due to the slow 
development of cysts and the complexity of cattle movements (up to 
ten different herds from birth to slaughter in France), there is a strong 
bias to consider the last farm location before slaughter as the location 
of infection.

Methods
A spatial analysis was performed using a spatial scan statistic 

[2]. The background population was defined as the number of cattle 
slaughtered in each commune (French administrative area). The 
case population was defined as the number of animal-herd weights 
aggregated by commune. Animal-herd weight was defined as the 
probability that the animal was infected in a given herd. For instance, 
an animal that spent time in three different herds from birth to 
slaughter was assigned three probabilities to have been infected in one 
of these herds: P1, P2 and P3 (P1+P2+P3=1). Based on the chronology 
of cyst development, rules to attribute these probabilities have been 
defined. The model was adjusted for age and sex, since these variables 
are associated with bovine cysticercosis [1].

Results
The data used came from a national survey conducted in France 

in 2010 on all the cattle slaughterhouses and from the national 
cattle database for cattle movements. After removal of missing 
data, information regarding 4,557,593 cattle slaughtered in 181 
slaughterhouses was used (91.1% of cattle slaughtered in France 
in 2010). Among these, post mortem inspection allowed the 
identification of 6,431 cattle harboring at least one cyst (i.e. regardless 
of its stage of development) and 603 harboring at least one viable 
cyst. Three significant clusters for cattle with all types of cysts were 

detected (Figure A). Only one significant cluster was detected in 
eastern France when cattle with viable cysts only were taken into 
account (Figure B).

Conclusions
Formerly, only cattle with viable cysts, i.e. acute lesions, would 

have been considered for spatial analysis so as to limit bias regarding 
the location of infection. The difference in location of the clusters 
detected, when considering only cattle harboring viable cysts or 
cattle harboring all types of cysts, proved the relevancy of this novel 
approach. Animal-herd-level analysis could be useful for other 
chronic diseases, such as bovine tuberculosis, for which the period 
between infection and detection can be long and variable. Dedicated 
rules to attribute probabilities taking into account the evolution of the 
disease would then have to be defined.

Apparent prevalence (%) of bovine cysticercosis (A: with viable or degenerated 
cysts; B: with viable cysts only) and significant clusters of cattle harboring 
viable or degenerated cysts (A) and viable cysts only (B). RR= relative risk.

Keywords
Animal health surveillance; Public Health; Spatial analysis; zoonosis

References

1.Dupuy, C., et al. (2014). Construction of standardized surveillance
indicators for bovine cysticercosis. Prev Vet Med, 115, 208-292.

2.Kulldorff, M. (1997). A spatial scan statistic. Theory and Methods,
26(6), 1481-1496.

*Céline Dupuy
E-mail: celine.dupuy@agriculture.gouv.fr    

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 7(1):e21, 2015