Certainty, uncertainty, and the spatiality of disease: a West Nile Virus example

Koch, Tom; Denike, Kenneth

doi:10.1007/s00477-007-0144-z

Cited by 7 publications

(6 citation statements)

References 19 publications

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“…To assume that one can precisely and accurately represent the complex and dynamic world in which we live in a static spatial or spatio‐temporal database is an illusion that we have become experts at propagating (Koch and Denike ). As shown here, conducting analyses based on this assumption without careful thought about its possible consequences can yield misleading results.…”

Section: Discussionmentioning

confidence: 99%

The Effect of Data Inaccuracy on Tests of Space‐Time Interaction

Malizia

2013

Transactions in GIS

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Space-time event data are often subject to deficiencies in: (1) locational accuracy; (2), temporal accuracy; and (3) completeness. This work explores how these failings in the quality of input data may affect the results of global space-time interaction tests. While previous work has partially investigated the impact of locational inaccuracy on the results of these tests, more work remains. The impacts of temporal inaccuracy and incomplete data reporting on the results of these tests remain completely unexplored. This study examines the influence of these problems individually and collectively, using a series of simulations. Findings demonstrate that even in cases of slight inaccuracy or underreporting, the consequences on results are potentially severe. Although the study is couched in terms of data inaccuracy, its relevance to situations where inaccuracy is replaced with uncertainty is self-evident.

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Section: Discussionmentioning

confidence: 99%

The Effect of Data Inaccuracy on Tests of Space‐Time Interaction

Malizia

2013

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“…27–31 In the present study, the nearest-neighbour hierarchical clustering (NHC) model (Appendix 3) was used to identify spatial patterns of SARS distribution. Points were randomly distributed in space and circled in a spatial cluster, if their inter-distance was significantly smaller than the mean distance.…”

Section: Methodsmentioning

confidence: 99%

Data-driven exploration of ‘spatial pattern-time process-driving forces’ associations of SARS epidemic in Beijing, China

Wang

Christakos

Han

et al. 2008

Journal of Public Health

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BackgroundSevere Acute Respiratory Syndrome (SARS) was first reported in November 2002 in China, and spreads to about 30 countries over the next few months. While the characteristics of epidemic transmission are individually assessed, there are also important implicit associations between them.MethodsA novel methodological framework was developed to overcome barriers among separate epidemic statistics and identify distinctive SARS features. Individual statistics were pair-wise linked in terms of their common features, and an integrative epidemic network was formulated.ResultsThe study of associations between important SARS characteristics considerably enhanced the mainstream epidemic analysis and improved the understanding of the relationships between the observed epidemic determinants. The response of SARS transmission to various epidemic control factors was simulated, target areas were detected, critical time and relevant factors were determined.ConclusionIt was shown that by properly accounting for links between different SARS statistics, a data-based analysis can efficiently reveal systematic associations between epidemic determinants. The analysis can predict the temporal trend of the epidemic given its spatial pattern, to estimate spatial exposure given temporal evolution, and to infer the driving forces of SARS transmission given the spatial exposure distribution.

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“…2.1), but similar techniques featured in the Cornwall investigation of 1972, and most of MAFF progress reporting on badger/ bTB. 145 What geographers usefully describe as 'the spatiality of disease' 146 was not just important for epidemiological research: it also guided the underlying logic of implementing 'stamping out' across animal health policy.…”

Section: Research Expansion Policy Tinkeringmentioning

confidence: 99%

Changing Veterinary Knowledge

Cassidy

2019

Vermin, Victims and Disease

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This chapter explores in detail the world and work of the first epistemic community (knowledge network) to engage with bTB—that of animal health, comprising veterinarians, farmers, policymakers and politicians. It will recount the origins of animal health as a core aspect of agricultural governance in the UK since the late nineteenth century, and the role of Mycobacterium bovis in positioning veterinary expertise in government. This chapter will analyse caring practices in animal health, explaining how it must weigh up the best interests of animal populations and human societies against animal suffering and life. It charts the engagement of animal health with the new problem of badger/bTB, including the causes and outcomes of the first ‘independent expert review’ on the topic—delivered to government by Lord Zuckerman in 1980.

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Certainty, uncertainty, and the spatiality of disease: a West Nile Virus example

Cited by 7 publications

References 19 publications

The Effect of Data Inaccuracy on Tests of Space‐Time Interaction

The Effect of Data Inaccuracy on Tests of Space‐Time Interaction

Data-driven exploration of ‘spatial pattern-time process-driving forces’ associations of SARS epidemic in Beijing, China

Changing Veterinary Knowledge

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