A space-time conditional intensity model for invasive meningococcal disease occurrence
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Abstract (arXiv)
A novel point process model continuous in space-time is proposed for quantifying the transmission dynamics of the two most common meningococcal antigenic sequence types observed in Germany 2002-2008. Modelling is based on the conditional intensity function (CIF) which is described by a superposition of additive and multiplicative components. As an epidemiological interesting finding, spread behaviour was shown to depend on type in addition to age: basic reproduction numbers were 0.25 (95% CI 0.19-0.34) and 0.11 (95% CI 0.07-0.17) for types B:P1.7-2,4:F1-5 and C:P1.5,2:F3-3, respectively. Altogether, the proposed methodology represents a comprehensive and universal regression framework for the modelling, simulation and inference of self-exciting spatio-temporal point processes based on the CIF. Usability of the modelling in biometric practice is promoted by an implementation in the R package surveillance.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Aug 2015.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 2; 2024: 0; 2025: 2; 2026: 2.
9 papers.
- 2021Neural Flows: Efficient Alternative to Neural ODEscited by 101
- 2023Spatio-temporal Diffusion Point Processescited by 52
- 2023Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processescited by 8
- 2025A Spatio-Temporal Point Process for Fine-Grained Modeling of Reading Behaviorcited by 3
- 2022Beyond Hawkes: Neural Multi-event Forecasting on Spatio-temporal Point Processescited by 1
- 2025Deep spatio-temporal point processes: Advances and new directionscited by 1
- 2021Statistical learning and cross-validation for point processescited by 0
- 2026Long-range Modeling and Processing of Multimodal Event Sequencescited by 0
- 2026On Observation Time for Recovering Latent Hawkes Networkscited by 0
- 2026On Observation Time for Recovering Latent Hawkes Networks8 May 2026
- 2026Long-range Modeling and Processing of Multimodal Event Sequences1 Feb 2026
- 2025A Spatio-Temporal Point Process for Fine-Grained Modeling of Reading Behavior24 Jun 2025
- 2025Deep spatio-temporal point processes: Advances and new directions8 Apr 2025
- 2023Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes9 Oct 2023
- 2023Spatio-temporal Diffusion Point Processes21 May 2023
- 2022Beyond Hawkes: Neural Multi-event Forecasting on Spatio-temporal Point Processes5 Nov 2022
- 2021Neural Flows: Efficient Alternative to Neural ODEs25 Oct 2021
- 2021Statistical learning and cross-validation for point processes1 Mar 2021