ArticleStatistical methods in medical research2016
Spatial Bayesian surveillance for small area case event data.
Article in Statistical methods in medical research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- A scalable variational method for estimating the latent infection-rate field of an outbreak.PloS one · 2026Article
- Detecting outbreaks using a spatial latent field.PloS one · 2025Article
- Evaluation and comparison of spatial cluster detection methods for improved decision making of disease surveillance: a case study of national dengue surveillance in Thailand.BMC medical research methodology · 2024Article
- Two-step spatiotemporal anomaly detection corrected for lag reporting time with application to real-time dengue surveillance in Thailand.BMC medical research methodology · 2024Article
- Integration of animal health and public health surveillance sources to exhaustively inform the risk of zoonosis: An application to echinococcosis in Rio Negro, Argentina.PLoS neglected tropical diseases · 2020Article
- Revisiting area risk classification of visceral leishmaniasis in Brazil.BMC infectious diseases · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
There has been little development of surveillance procedures for epidemiological data with fine spatial resolution such as case events at residential address locations. This is often due to difficulties of access when confidentiality of medical records is an issue. However, when such data are available, it is important to be able to affect an appropriate analysis strategy. We propose a model for point events in the context of prospective surveillance based on conditional logistic modeling. A weighted conditional autoregressive model is developed for irregular lattices to account for distance effects, and a Dirichlet tessellation is adopted to define the neighborhood structure. Localized clustering diagnostics are compared including the proposed local Kullback-Leibler information criterion. A simulation study is conducted to examine the surveillance and detection methods, and a data example is provided of non-Hodgkin's lymphoma data in South Carolina.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.