The Detection of Space-Time Interactions

E. G. Knox; M. S. Bartlett

doi:10.2307/2985220

January 1, 1964Journal of the Royal Statistical Society Series C (Applied Statistics)

The Detection of Space-Time Interactions

View at Publisher

Ask AI

Bookmark

Share

Key Points

To resolve the methodological difficulties in defining and detecting epidemicity and space-time clustering when disease occurrences are sparse.
Analyzed the theoretical limitations of using aggregate prevalence and incidence curves to identify epidemics among widely scattered events.
Formulated an alternative mathematical framework modeling the intervals between discrete events, drawing analogies to physics models of low-intensity radiation.
Demonstrated that traditional continuous-variable measures of epidemic waves break down when time units contain few or no observed cases.
Established that sparse disease patterns must be evaluated corpuscularly through temporal and spatial intervals between individual events to establish non-random clustering.

No abstract yet

We only have this paper's title and publication details.

Read it at the source

Ask about this paper

Answers are grounded in this paper and cite their sources.

Implication

Theoretical analysis uncovers limitations in standard epidemic definitions for sparse events, suggesting discrete event-interval modeling improves space-time clustering detection.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Knox et al. (1964) studied this question.

synapsesocial.com/papers/6a13076586514ddae6c10204 https://doi.org/10.2307/2985220

View at Publisher

Ask AI

Bookmark

Share

The Detection of Space-Time Interactions

Key Points

No abstract yet

Ask about this paper

Implication

Discussion

Cite This Study

The Detection of Space-Time Interactions

Key Points

No abstract yet

Ask about this paper

Implication

Discussion

Cite This Study

Keep reading

Keep reading