Dataset Information

Spatial dynamics of TB within a highly urbanised Asian metropolis using point patterns.

ABSTRACT: Singapore is a high-income country in a region with a high prevalence of tuberculosis. The Singapore Tuberculosis (TB) Elimination Program (STEP) was set up in 1997, and the better surveillance and clinical management practices initiated under STEP led to a decade-long decline in the incidence levels. However, incidence rates started to rise again since 2008. The reasons for this rise are unclear. This study involved a spatial analysis of the epidemiology of TB among Singapore residents. More than 30 000 cases reported during 1995-2011 and their residential addresses were analysed for spatial risk and spatial clustering, using spatial point pattern methodology. The principal factor responsible for the increasing resident TB incidence in Singapore is the changing age profile of the population. In particular the burgeoning population aged above 65 years accounts for the increase in reported cases. Singapore's population has one of the world's lowest fertility and mortality rates, and the elderly population is projected to grow substantially over the next few decades. Tuberculosis rates may therefore continue to rise even with static or improving case management and surveillance.

SUBMITTER: Das S

PROVIDER: S-EPMC5428374 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatial dynamics of TB within a highly urbanised Asian metropolis using point patterns.

Das Sourav S Cook Alex R AR Wah Win W Win Khin Mar Kyi KM Chee Cynthia Bin Eng CB Wang Yee Tang YT Yang Hsu Li L

Scientific reports 20170224 1

Singapore is a high-income country in a region with a high prevalence of tuberculosis. The Singapore Tuberculosis (TB) Elimination Program (STEP) was set up in 1997, and the better surveillance and clinical management practices initiated under STEP led to a decade-long decline in the incidence levels. However, incidence rates started to rise again since 2008. The reasons for this rise are unclear. This study involved a spatial analysis of the epidemiology of TB among Singapore residents. More th ...[more]

PMID: 28232734

Similar Datasets

Project description:Abstract The Australian backyard mosquito, Aedes notoscriptus, is a highly urbanised pest species that has invaded New Zealand and the USA. Importantly, Ae. notoscriptus has been implicated as a vector of Ross River virus, a common and arthritogenic arbovirus in Australia, and is a laboratory vector of numerous other pathogenic viruses, including West Nile, yellow fever, and Zika viruses. To further explore live viruses harboured by field populations of Ae. notoscriptus and, more specifically, assess the genetic diversity of its virome, we processed 495 pools, comprising a total of 6,674 female Ae. notoscriptus collected across fifteen suburbs in Brisbane, Australia, between January 2018 and May 2019. Nine virus isolates were recovered and characterised by metagenomic sequencing and phylogenetics. The principal viral family represented was Flaviviridae. Known viruses belonging to the genera Flavivirus, Orbivirus, Mesonivirus, and Nelorpivirus were identified together with two novel virus species, including a divergent Thogoto-like orthomyxovirus and an insect-specific flavivirus. Among these, we recovered three Stratford virus (STRV) isolates and an isolate of Wongorr virus (WGRV), which for these viral species is unprecedented for the geographical area of Brisbane. Thus, the documented geographical distribution of STRV and WGRV, both known for their respective medical and veterinary importance, has now been expanded to include this major urban centre. Phylogenies of the remaining five viruses, namely, Casuarina, Ngewotan, the novel Thogoto-like virus, and two new flavivirus species, suggested they are insect-specific viruses. None of these viruses have been previously associated with Ae. notoscriptus or been reported in Brisbane. These findings exemplify the rich genetic diversity and viral abundance within the Ae. notoscriptus virome and further highlight this species as a vector of concern with the potential to transmit viruses impacting human or animal health. Considering it is a common pest and vector in residential areas and is expanding its global distribution, ongoing surveillance, and ecological study of Ae. notoscriptus, together with mapping of its virome and phenotypic characterisation of isolated viruses, is clearly warranted. Immanently, these initiatives are essential for future understanding of both the mosquito virome and the evolution of individual viral species.

Project description:Animal behavior is highly structured. Yet, structured behavioral patterns-or "statistical ethograms"-are not immediately apparent from the full spatiotemporal data that behavioral scientists usually collect. Here, we introduce a framework to quantitatively characterize rodent behavior during spatial (e.g., maze) navigation, in terms of movement building blocks or motor primitives. The hypothesis that we pursue is that rodent behavior is characterized by a small number of motor primitives, which are combined over time to produce open-ended movements. We assume motor primitives to be organized in terms of two sparsity principles: each movement is controlled using a limited subset of motor primitives (sparse superposition) and each primitive is active only for time-limited, time-contiguous portions of movements (sparse activity). We formalize this hypothesis using a sparse dictionary learning method, which we use to extract motor primitives from rodent position and velocity data collected during spatial navigation, and successively to reconstruct past trajectories and predict novel ones. Three main results validate our approach. First, rodent behavioral trajectories are robustly reconstructed from incomplete data, performing better than approaches based on standard dimensionality reduction methods, such as principal component analysis, or single sparsity. Second, the motor primitives extracted during one experimental session generalize and afford the accurate reconstruction of rodent behavior across successive experimental sessions in the same or in modified mazes. Third, in our approach the number of motor primitives associated with each maze correlates with independent measures of maze complexity, hence showing that our formalism is sensitive to essential aspects of task structure. The framework introduced here can be used by behavioral scientists and neuroscientists as an aid for behavioral and neural data analysis. Indeed, the extracted motor primitives enable the quantitative characterization of the complexity and similarity between different mazes and behavioral patterns across multiple trials (i.e., habit formation). We provide example uses of this computational framework, showing how it can be used to identify behavioural effects of maze complexity, analyze stereotyped behavior, classify behavioral choices and predict place and grid cell displacement in novel environments.

Project description:Uncovering the roles of biotic interactions in assembling and maintaining species-rich communities remains a major challenge in ecology. In plant communities, interactions between individuals of different species are expected to generate positive or negative spatial interspecific associations over short distances. Recent studies using individual-based point pattern datasets have concluded that (a) detectable interspecific interactions are generally rare, but (b) are most common in communities with fewer species; and (c) the most abundant species tend to have the highest frequency of interactions. However, it is unclear how the detection of spatial interactions may change with the abundances of each species, or the scale and intensity of interactions. We ask if statistical power is sufficient to explain all three key results.We use a simple two-species model, assuming no habitat associations, and where the abundances, scale and intensity of interactions are controlled to simulate point pattern data. In combination with an approximation to the variance of the spatial summary statistics that we sample, we investigate the power of current spatial point pattern methods to correctly reject the null model of pairwise species independence.We show the power to detect interactions is positively related to both the abundances of the species tested, and the intensity and scale of interactions, but negatively related to imbalance in abundances. Differences in detection power in combination with the abundance distributions found in natural communities are sufficient to explain all the three key empirical results, even if all pairwise interactions are identical. Critically, many hundreds of individuals of both species may be required to detect even intense interactions, implying current abundance thresholds for including species in the analyses are too low. Sy n thesis. The widespread failure to reject the null model of spatial interspecific independence could be due to low power of the tests rather than any key biological process. Since we do not model habitat associations, our results represent a first step in quantifying sample sizes required to make strong statements about the role of biotic interactions in diverse plant communities. However, power should be factored into analyses and considered when designing empirical studies.

Dataset Information

Spatial dynamics of TB within a highly urbanised Asian metropolis using point patterns.

Publications

Spatial dynamics of TB within a highly urbanised Asian metropolis using point patterns.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure