Displaying publications 1 - 20 of 36 in total

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  1. Hybrid time-space dynamical systems of growth bacteria with applications in segmentation
    Ibrahim RW, Nashine HK, Kamaruddin N
    Math Biosci, 2017 10;292:10-17.
    PMID: 28728968 DOI: 10.1016/j.mbs.2017.07.007
    A biological dynamic system carries engineering properties such as control systems and signal processing (or image processing) addicted to molecular biology at the level of bio-molecular communication networks. Dynamical system features and signal reply functions of cellular signaling pathways are some of the main topics in biological dynamic systems (for example the biological segmentation). In the present paper, we introduce new generalized hybrid time-space dynamical systems of growing bacteria. We impose the approximate analytic solution for the system. The generalization adapted the concepts of the Riemann-Liouville fractional operators for time and the Srivastava-Owa fractional operators for space. Moreover, we introduce a numerical perturbation method of two operators to obtain the approximate solutions. We establish the existence and uniqueness results and impose some applications in the sequel. Moreover, we study the Ulam stability and apply these stable solutions to improve the segmentation of a class of growing bacteria.
    Matched MeSH terms: Spatio-Temporal Analysis
  2. Fulltext Salmon migration patterns revealed the temporal and spatial fluctuations of the radiocesium levels in terrestrial and ocean environments
    Arai T
    PLoS One, 2014;9(6):e100779.
    PMID: 24964195 DOI: 10.1371/journal.pone.0100779
    The disabling of the Fukushima Daiichi Nuclear Power Plant (F1NPP) resulted in the release of radionuclides, including 134Cs and 137Cs, into the air and the ocean. The unpredicted nuclear accident is of global concern for human health and the ecosystem. Although investigations of radionuclides in environments were performed shortly after the accident started, the temporal and spatial impacts and fluctuations on the releasing radionuclides to natural environment remain unclear. I focused on salmon, which migrate from inland to the open ocean globally, to reveal the three-year (May 2011 to February 2014) fluctuations and accumulations of 134Cs and 137Cs from terrestrial to open ocean environments after the F1NPP accident. The 134Cs and 137Cs concentrations in six salmonids exhibited lower temporal variations for three years after the F1NPP accident, suggesting that these radionuclides are widely distributed and these radionuclides remain in the natural environment globally with less convergence. The accumulation patterns were significantly different among the different salmon species. Fluvial (freshwater residence) type salmons exhibited significantly higher accumulation in 134Cs (25.3-40.2 Bq kg(-1) in mean) and 137Cs (41.4-51.7 Bq kg(-1) in mean) than did the anadromous (sea-run) type salmons (0.64-8.03 Bq kg(-1) in mean 134Cs and 0.42-10.2 Bq kg(-1) in mean 137Cs) suggesting widespread contamination in terrestrial environments versus the coastal and open ocean environments. Salmonids are the most highly migratory animals and are characterised by their strong tendency to return home to their natal site for reproduction. Salmonids have a potential to be a good indicator as an effective monitoring animal.
    Matched MeSH terms: Spatio-Temporal Analysis*
  3. Fulltext Coastal proximity of populations in 22 Pacific Island Countries and Territories
    Andrew NL, Bright P, de la Rua L, Teoh SJ, Vickers M
    PLoS One, 2019;14(9):e0223249.
    PMID: 31568527 DOI: 10.1371/journal.pone.0223249
    The coastal zones of Small Island States are hotspots of human habitation and economic endeavour. In the Pacific region, as elsewhere, there are large gaps in understandings of the exposure and vulnerability of people in coastal zones. The 22 Pacific Countries and Territories (PICTs) are poorly represented in global analyses of vulnerability to seaward risks. We combine several data sources to estimate populations to zones 1, 5 and 10 km from the coastline in each of the PICTs. Regional patterns in the proximity of Pacific people to the coast are dominated by Papua New Guinea. Overall, ca. half the population of the Pacific resides within 10 km of the coast but this jumps to 97% when Papua New Guinea is excluded. A quarter of Pacific people live within 1 km of the coast, but without PNG this increases to slightly more than half. Excluding PNG, 90% of Pacific Islanders live within 5 km of the coast. All of the population in the coral atoll nations of Tokelau and Tuvalu live within a km of the ocean. Results using two global datasets, the SEDAC-CIESIN Gridded Population of the World v4 (GPWv4) and the Oak Ridge National Laboratory Landscan differed: Landscan under-dispersed population, overestimating numbers in urban centres and underestimating population in rural areas and GPWv4 over-dispersed the population. In addition to errors introduced by the allocation models of the two methods, errors were introduced as artefacts of allocating households to 1 km x 1 km grid cell data (30 arc-seconds) to polygons. The limited utility of LandScan and GPWv4 in advancing this analysis may be overcome with more spatially resolved census data and the inclusion of elevation above sea level as an important dimension of vulnerability.
    Matched MeSH terms: Spatio-Temporal Analysis*
  4. Fulltext Spatial and temporal behavioural responses of wild cattle to tropical forest degradation
    Gardner PC, Goossens B, Goon Ee Wern J, Kretzschmar P, Bohm T, Vaughan IP
    PLoS One, 2018;13(4):e0195444.
    PMID: 29649279 DOI: 10.1371/journal.pone.0195444
    Identifying the consequences of tropical forest degradation is essential to mitigate its effects upon forest fauna. Large forest-dwelling mammals are often highly sensitive to environmental perturbation through processes such as fragmentation, simplification of habitat structure, and abiotic changes including increased temperatures where the canopy is cleared. Whilst previous work has focused upon species richness and rarity in logged forest, few look at spatial and temporal behavioural responses to forest degradation. Using camera traps, we explored the relationships between diel activity, behavioural expression, habitat use and ambient temperature to understand how the wild free-ranging Bornean banteng (Bos javanicus lowi) respond to logging and regeneration. Three secondary forests in Sabah, Malaysian Borneo were studied, varying in the time since last logging (6-23 years). A combination of generalised linear mixed models and generalised linear models were constructed using >36,000 trap-nights. Temperature had no significant effect on activity, however it varied markedly between forests, with the period of intense heat shortening as forest regeneration increased over the years. Bantengs regulated activity, with a reduction during the wet season in the most degraded forest (z = -2.6, Std. Error = 0.13, p = 0.01), and reductions during midday hours in forest with limited regeneration, however after >20 years of regrowth, activity was more consistent throughout the day. Foraging and use of open canopy areas dominated the activity budget when regeneration was limited. As regeneration advanced, this was replaced by greater investment in travelling and using a closed canopy. Forest degradation modifies the ambient temperature, and positively influences flooding and habitat availability during the wet season. Retention of a mosaic of mature forest patches within commercial forests could minimise these effects and also provide refuge, which is key to heat dissipation and the prevention of thermal stress, whilst retention of degraded forest could provide forage.
    Matched MeSH terms: Spatio-Temporal Analysis*
  5. More than motor impairment: A spatiotemporal analysis of cognitive impairment and associated neuropathological changes following cortical photothrombotic stroke
    Sanchez-Bezanilla S, Hood RJ, Collins-Praino LE, Turner RJ, Walker FR, Nilsson M, et al.
    J Cereb Blood Flow Metab, 2021 09;41(9):2439-2455.
    PMID: 33779358 DOI: 10.1177/0271678X211005877
    There is emerging evidence suggesting that a cortical stroke can cause delayed and remote hippocampal dysregulation, leading to cognitive impairment. In this study, we aimed to investigate motor and cognitive outcomes after experimental stroke, and their association with secondary neurodegenerative processes. Specifically, we used a photothrombotic stroke model targeting the motor and somatosensory cortices of mice. Motor function was assessed using the cylinder and grid walk tasks. Changes in cognition were assessed using a mouse touchscreen platform. Neuronal loss, gliosis and amyloid-β accumulation were investigated in the peri-infarct and ipsilateral hippocampal regions at 7, 28 and 84 days post-stroke. Our findings showed persistent impairment in cognitive function post-stroke, whilst there was a modest spontaneous motor recovery over the investigated period of 84 days. In the peri-infarct region, we detected a reduction in neuronal loss and decreased neuroinflammation over time post-stroke, which potentially explains the spontaneous motor recovery. Conversely, we observed persistent neuronal loss together with concomitant increased neuroinflammation and amyloid-β accumulation in the hippocampus, which likely accounts for the persistent cognitive dysfunction. Our findings indicate that cortical stroke induces secondary neurodegenerative processes in the hippocampus, a region remote from the primary infarct, potentially contributing to the progression of post-stroke cognitive impairment.
    Matched MeSH terms: Spatio-Temporal Analysis*
  6. Temporal coexistence mechanisms contribute to the latitudinal gradient in forest diversity
    Usinowicz J, Chang-Yang CH, Chen YY, Clark JS, Fletcher C, Garwood NC, et al.
    Nature, 2017 10 05;550(7674):105-108.
    PMID: 28953870 DOI: 10.1038/nature24038
    The tropical forests of Borneo and Amazonia may each contain more tree species diversity in half a square kilometre than do all the temperate forests of Europe, North America, and Asia combined. Biologists have long been fascinated by this disparity, using it to investigate potential drivers of biodiversity. Latitudinal variation in many of these drivers is expected to create geographic differences in ecological and evolutionary processes, and evidence increasingly shows that tropical ecosystems have higher rates of diversification, clade origination, and clade dispersal. However, there is currently no evidence to link gradients in ecological processes within communities at a local scale directly to the geographic gradient in biodiversity. Here, we show geographic variation in the storage effect, an ecological mechanism that reduces the potential for competitive exclusion more strongly in the tropics than it does in temperate and boreal zones, decreasing the ratio of interspecific-to-intraspecific competition by 0.25% for each degree of latitude that an ecosystem is located closer to the Equator. Additionally, we find evidence that latitudinal variation in climate underpins these differences; longer growing seasons in the tropics reduce constraints on the seasonal timing of reproduction, permitting lower recruitment synchrony between species and thereby enhancing niche partitioning through the storage effect. Our results demonstrate that the strength of the storage effect, and therefore its impact on diversity within communities, varies latitudinally in association with climate. This finding highlights the importance of biotic interactions in shaping geographic diversity patterns, and emphasizes the need to understand the mechanisms underpinning ecological processes in greater detail than has previously been appreciated.
    Matched MeSH terms: Spatio-Temporal Analysis*
  7. Fulltext Spatial and Temporal Patterns of Plasmodium knowlesi Malaria in Sarawak from 2008 to 2017
    Ooi CH, Phang WK, Kent Liew JW, Lau YL
    Am J Trop Med Hyg, 2021 Mar 22;104(5):1814-1819.
    PMID: 33755585 DOI: 10.4269/ajtmh.20-1304
    Zoonotic knowlesi malaria has replaced human malaria as the most prevalent malaria disease in Malaysia. The persistence of knowlesi malaria in high-risk transmission areas or hotspots can be discouraging to existing malaria elimination efforts. In this study, retrospective data of laboratory-confirmed knowlesi malaria cases were obtained from the Sarawak Health Department to investigate the spatiotemporal patterns and clustering of knowlesi malaria in the state of Sarawak from 2008 to 2017. Purely spatial, purely temporal, and spatiotemporal analyses were performed using SaTScan software to define clustering of knowlesi malaria incidence. Purely spatial and spatiotemporal analyses indicated most likely clusters of knowlesi malaria in the northern region of Sarawak, along the Sarawak-Kalimantan border, and the inner central region of Sarawak between 2008 and 2017. Temporal cluster was detected between September 2016 and December 2017. This study provides evidence of the existence of statistically significant Plasmodium knowlesi malaria clusters in Sarawak, Malaysia. The analysis approach applied in this study showed potential in establishing surveillance and risk management system for knowlesi malaria control as Malaysia approaches human malaria elimination.
    Matched MeSH terms: Spatio-Temporal Analysis*
  8. Fulltext Four decades of forest persistence, clearance and logging on Borneo
    Gaveau DL, Sloan S, Molidena E, Yaen H, Sheil D, Abram NK, et al.
    PLoS One, 2014;9(7):e101654.
    PMID: 25029192 DOI: 10.1371/journal.pone.0101654
    The native forests of Borneo have been impacted by selective logging, fire, and conversion to plantations at unprecedented scales since industrial-scale extractive industries began in the early 1970s. There is no island-wide documentation of forest clearance or logging since the 1970s. This creates an information gap for conservation planning, especially with regard to selectively logged forests that maintain high conservation potential. Analysing LANDSAT images, we estimate that 75.7% (558,060 km2) of Borneo's area (737,188 km2) was forested around 1973. Based upon a forest cover map for 2010 derived using ALOS-PALSAR and visually reviewing LANDSAT images, we estimate that the 1973 forest area had declined by 168,493 km2 (30.2%) in 2010. The highest losses were recorded in Sabah and Kalimantan with 39.5% and 30.7% of their total forest area in 1973 becoming non-forest in 2010, and the lowest in Brunei and Sarawak (8.4%, and 23.1%). We estimate that the combined area planted in industrial oil palm and timber plantations in 2010 was 75,480 km2, representing 10% of Borneo. We mapped 271,819 km of primary logging roads that were created between 1973 and 2010. The greatest density of logging roads was found in Sarawak, at 0.89 km km-2, and the lowest density in Brunei, at 0.18 km km-2. Analyzing MODIS-based tree cover maps, we estimate that logging operated within 700 m of primary logging roads. Using this distance, we estimate that 266,257 km2 of 1973 forest cover has been logged. With 389,566 km2 (52.8%) of the island remaining forested, of which 209,649 km2 remains intact. There is still hope for biodiversity conservation in Borneo. Protecting logged forests from fire and conversion to plantations is an urgent priority for reducing rates of deforestation in Borneo.
    Matched MeSH terms: Spatio-Temporal Analysis
  9. Fulltext AI inspired EEG-based spatial feature selection method using multivariate empirical mode decomposition for emotion classification
    Asghar MA, Khan MJ, Rizwan M, Shorfuzzaman M, Mehmood RM
    Multimed Syst, 2021 Apr 21.
    PMID: 33897112 DOI: 10.1007/s00530-021-00782-w
    Classification of human emotions based on electroencephalography (EEG) is a very popular topic nowadays in the provision of human health care and well-being. Fast and effective emotion recognition can play an important role in understanding a patient's emotions and in monitoring stress levels in real-time. Due to the noisy and non-linear nature of the EEG signal, it is still difficult to understand emotions and can generate large feature vectors. In this article, we have proposed an efficient spatial feature extraction and feature selection method with a short processing time. The raw EEG signal is first divided into a smaller set of eigenmode functions called (IMF) using the empirical model-based decomposition proposed in our work, known as intensive multivariate empirical mode decomposition (iMEMD). The Spatio-temporal analysis is performed with Complex Continuous Wavelet Transform (CCWT) to collect all the information in the time and frequency domains. The multiple model extraction method uses three deep neural networks (DNNs) to extract features and dissect them together to have a combined feature vector. To overcome the computational curse, we propose a method of differential entropy and mutual information, which further reduces feature size by selecting high-quality features and pooling the k-means results to produce less dimensional qualitative feature vectors. The system seems complex, but once the network is trained with this model, real-time application testing and validation with good classification performance is fast. The proposed method for selecting attributes for benchmarking is validated with two publicly available data sets, SEED, and DEAP. This method is less expensive to calculate than more modern sentiment recognition methods, provides real-time sentiment analysis, and offers good classification accuracy.
    Matched MeSH terms: Spatio-Temporal Analysis
  10. Monitoring and assessment of urban growth patterns using spatio-temporal built-up area analysis
    Aburas MM, Ho YM, Ramli MF, Ash'aari ZH
    Environ Monit Assess, 2018 Feb 20;190(3):156.
    PMID: 29464400 DOI: 10.1007/s10661-018-6522-9
    The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns.
    Matched MeSH terms: Spatio-Temporal Analysis
  11. Spatiotemporal analysis of ground and satellite-based aerosol for air quality assessment in the Southeast Asia region
    Nguyen TTN, Pham HV, Lasko K, Bui MT, Laffly D, Jourdan A, et al.
    Environ Pollut, 2019 Dec;255(Pt 1):113106.
    PMID: 31541826 DOI: 10.1016/j.envpol.2019.113106
    Satellite observations for regional air quality assessment rely on comprehensive spatial coverage, and daily monitoring with reliable, cloud-free data quality. We investigated spatiotemporal variation and data quality of two global satellite Aerosol Optical Depth (AOD) products derived from MODIS and VIIRS imagery. AOD is considered an essential atmospheric parameter strongly related to ground Particulate Matter (PM) in Southeast Asia (SEA). We analyze seasonal variation, urban/rural area influence, and biomass burning effects on atmospheric pollution. Validation indicated a strong relationship between AERONET ground AOD and both MODIS AOD (R2 = 0.81) and VIIRS AOD (R2 = 0.68). The monthly variation of satellite AOD and AERONET AOD reflects two seasonal trends of air quality separately for mainland countries including Myanmar, Laos, Cambodia, Thailand, Vietnam, and Taiwan, Hong Kong, and for maritime countries consisting of Indonesia, Philippines, Malaysia, Brunei, Singapore, and Timor Leste. The mainland SEA has a pattern of monthly AOD variation in which AODs peak in March/April, decreasing during wet season from May-September, and increasing to the second peak in October. However, in maritime SEA, AOD concentration peaks in October. The three countries with the highest annual satellite AODs are Singapore, Hong Kong, and Vietnam. High urban population proportions in Singapore (40.7%) and Hong Kong (21.6%) were associated with high AOD concentrations as expected. AOD values in SEA urban areas were a factor of 1.4 higher than in rural areas, with respective averages of 0.477 and 0.336. The AOD values varied proportionately to the frequency of biomass burning in which both active fires and AOD peak in March/April and September/October. Peak AOD in September/October in some countries could be related to pollutant transport of Indonesia forest fires. This study analyzed satellite aerosol product quality in relation to AERONET in SEA countries and highlighted framework of air quality assessment over a large, complicated region.
    Matched MeSH terms: Spatio-Temporal Analysis*
  12. Spatiotemporal variation of groundwater quality using integrated multivariate statistical and geostatistical approaches in Amol-Babol Plain, Iran
    Sheikhy Narany T, Ramli MF, Aris AZ, Sulaiman WN, Fakharian K
    Environ Monit Assess, 2014 Sep;186(9):5797-815.
    PMID: 24891071 DOI: 10.1007/s10661-014-3820-8
    In recent years, groundwater quality has become a global concern due to its effect on human life and natural ecosystems. To assess the groundwater quality in the Amol-Babol Plain, a total of 308 water samples were collected during wet and dry seasons in 2009. The samples were analysed for their physico-chemical and biological constituents. Multivariate statistical analysis and geostatistical techniques were applied to assess the spatial and temporal variabilities of groundwater quality and to identify the main factors and sources of contamination. Principal component analysis (PCA) revealed that seven factors explained around 75% of the total variance, which highlighted salinity, hardness and biological pollution as the dominant factors affecting the groundwater quality in the Plain. Two-way analysis of variance (ANOVA) was conducted on the dataset to evaluate the spatio-temporal variation. The results showed that there were no significant temporal variations between the two seasons, which explained the similarity between six component factors in dry and wet seasons based on the PCA results. There are also significant spatial differences (p > 0.05) of the parameters under study, including salinity, potassium, sulphate and dissolved oxygen in the plain. The least significant difference (LSD) test revealed that groundwater salinity in the eastern region is significantly different to the central and western side of the study area. Finally, multivariate analysis and geostatistical techniques were combined as an effective method for demonstrating the spatial structure of multivariate spatial data. It was concluded that multiple natural processes and anthropogenic activities were the main sources of groundwater salinization, hardness and microbiological contamination of the study area.
    Matched MeSH terms: Spatio-Temporal Analysis
  13. Temporal and spatial mapping of hand, foot and mouth disease in Sarawak, Malaysia
    Sham NM, Krishnarajah I, Ibrahim NA, Lye MS
    Geospat Health, 2014 May;8(2):503-7.
    PMID: 24893027
    Hand, foot and mouth disease (HFMD) is endemic in Sarawak, Malaysia. In this study, a geographical information system (GIS) was used to investigate the relationship between the reported HFMD cases and the spatial patterns in 11 districts of Sarawak from 2006 to 2012. Within this 7-years period, the highest number of reported HFMD cases occurred in 2006, followed by 2012, 2008, 2009, 2007, 2010 and 2011, in descending order. However, while there was no significant distribution pattern or clustering in the first part of the study period (2006 to 2011) based on Moran's I statistic, spatial autocorrelation (P = 0.068) was observed in 2012.
    Matched MeSH terms: Spatio-Temporal Analysis
  14. Temporal variation of phytoplankton growth and grazing loss in the west coast of Peninsular Malaysia
    Lim JH, Lee CW, Kudo I
    Environ Monit Assess, 2015 May;187(5):246.
    PMID: 25864082 DOI: 10.1007/s10661-015-4487-5
    Phytoplankton growth (μ) and grazing loss (g) rates were measured monthly by the Landry-Hassett dilution method over a 2-year period at both estuarine (Klang) and coastal water (Port Dickson) systems along the Straits of Malacca. Chlorophyll a (Chl a) concentration ranged from 0.20 to 4.47 μg L(-1) at Klang except on two occasions when Chl a spiked above 10 μg L(-1). In contrast, Chl a concentrations were relatively stable at Port Dickson (0.14 to 2.76 μg L(-1)). From the rate measurements, μ was higher (t = 2.01, df = 43, p  0.80). g ranged from 0.30 to 1.50 and 0.21 to 1.51 day(-1) at Klang and Port Dickson, respectively. In this study, grazing loss was coupled to phytoplankton growth, and the ratio of g/μ or grazing pressure which estimates the proportion of primary production grazed was 50% at Klang and lower than at Port Dickson (68%; t = 2.213, df = 36, p 
    Matched MeSH terms: Spatio-Temporal Analysis
  15. Fulltext Coral mass spawning predicted by rapid seasonal rise in ocean temperature
    Keith SA, Maynard JA, Edwards AJ, Guest JR, Bauman AG, van Hooidonk R, et al.
    Proc Biol Sci, 2016 05 11;283(1830).
    PMID: 27170709 DOI: 10.1098/rspb.2016.0011
    Coral spawning times have been linked to multiple environmental factors; however, to what extent these factors act as generalized cues across multiple species and large spatial scales is unknown. We used a unique dataset of coral spawning from 34 reefs in the Indian and Pacific Oceans to test if month of spawning and peak spawning month in assemblages of Acropora spp. can be predicted by sea surface temperature (SST), photosynthetically available radiation, wind speed, current speed, rainfall or sunset time. Contrary to the classic view that high mean SST initiates coral spawning, we found rapid increases in SST to be the best predictor in both cases (month of spawning: R(2) = 0.73, peak: R(2) = 0.62). Our findings suggest that a rapid increase in SST provides the dominant proximate cue for coral mass spawning over large geographical scales. We hypothesize that coral spawning is ultimately timed to ensure optimal fertilization success.
    Matched MeSH terms: Spatio-Temporal Analysis
  16. Autochthonous spread of DENV-3 genotype III in Malaysia mitigated by pre-existing homotypic and heterotypic immunity
    Tan KK, Nellis S, Zulkifle NI, Sulaiman S, AbuBakar S
    Epidemiol Infect, 2018 10;146(13):1635-1641.
    PMID: 29860959 DOI: 10.1017/S0950268818001425
    Dengue virus type 3 genotype III (DENV-3/III) is widely distributed in most dengue-endemic regions. It emerged in Malaysia in 2008 and autochthonously spread in the midst of endemic DENV-3/I circulation. The spread, however, was limited and the virus did not cause any major outbreak. Spatiotemporal distribution study of DENV-3 over the period between 2005 and 2011 revealed that dengue cases involving DENV-3/III occurred mostly in areas without pre-existing circulating DENV-3. Neutralisation assays performed using sera of patients with the respective infection showed that the DENV-3/III viruses can be effectively neutralised by sera of patients with DENV-3 infection (50% foci reduction neutralisation titres (FRNT50) > 1300). Sera of patients with DENV-1 infection (FRNT50 ⩾ 190), but not sera of patients with DENV-2 infection (FRNT50 ⩽ 50), were also able to neutralise the virus. These findings highlight the possibility that the pre-existing homotypic DENV-3 and the cross-reacting heterotypic DENV-1 antibody responses could play a role in mitigating a major outbreak involving DENV-3/III in the Klang Valley, Malaysia.
    Matched MeSH terms: Spatio-Temporal Analysis
  17. Fulltext A spatio-temporal agent-based approach for modeling the spread of zoonotic cutaneous leishmaniasis in northeast Iran
    Tabasi M, Alesheikh AA, Sofizadeh A, Saeidian B, Pradhan B, AlAmri A
    Parasit Vectors, 2020 Nov 11;13(1):572.
    PMID: 33176858 DOI: 10.1186/s13071-020-04447-x
    BACKGROUND: Zoonotic cutaneous leishmaniasis (ZCL) is a neglected tropical disease worldwide, especially the Middle East. Although previous works attempt to model the ZCL spread using various environmental factors, the interactions between vectors (Phlebotomus papatasi), reservoir hosts, humans, and the environment can affect its spread. Considering all of these aspects is not a trivial task.

    METHODS: An agent-based model (ABM) is a relatively new approach that provides a framework for analyzing the heterogeneity of the interactions, along with biological and environmental factors in such complex systems. The objective of this research is to design and develop an ABM that uses Geospatial Information System (GIS) capabilities, biological behaviors of vectors and reservoir hosts, and an improved Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model to explore the spread of ZCL. Various scenarios were implemented to analyze the future ZCL spreads in different parts of Maraveh Tappeh County, in the northeast region of Golestan Province in northeastern Iran, with alternative socio-ecological conditions.

    RESULTS: The results confirmed that the spread of the disease arises principally in the desert, low altitude areas, and riverside population centers. The outcomes also showed that the restricting movement of humans reduces the severity of the transmission. Moreover, the spread of ZCL has a particular temporal pattern, since the most prevalent cases occurred in the fall. The evaluation test also showed the similarity between the results and the reported spatiotemporal trends.

    CONCLUSIONS: This study demonstrates the capability and efficiency of ABM to model and predict the spread of ZCL. The results of the presented approach can be considered as a guide for public health management and controlling the vector population .

    Matched MeSH terms: Spatio-Temporal Analysis*
  18. Spatio-temporal patterns of dengue in Malaysia: combining address and sub-district level
    Ling CY, Gruebner O, Krämer A, Lakes T
    Geospat Health, 2014 Nov;9(1):131-40.
    PMID: 25545931
    Spatio-temporal patterns of dengue risk in Malaysia were studied both at the address and the sub-district level in the province of Selangor and the Federal Territory of Kuala Lumpur. We geocoded laboratory-confirmed dengue cases from the years 2008 to 2010 at the address level and further aggregated the cases in proportion to the population at risk at the sub-district level. Kulldorff's spatial scan statistic was applied for the investigation that identified changing spatial patterns of dengue cases at both levels. At the address level, spatio-temporal clusters of dengue cases were concentrated at the central and south-eastern part of the study area in the early part of the years studied. Analyses at the sub-district level revealed a consistent spatial clustering of a high number of cases proportional to the population at risk. Linking both levels assisted in the identification of differences and confirmed the presence of areas at high risk for dengue infection. Our results suggest that the observed dengue cases had both a spatial and a temporal epidemiological component, which needs to be acknowledged and addressed to develop efficient control measures, including spatially explicit vector control. Our findings highlight the importance of detailed geographical analysis of disease cases in heterogeneous environments with a focus on clustered populations at different spatial and temporal scales. We conclude that bringing together information on the spatio-temporal distribution of dengue cases with a deeper insight of linkages between dengue risk, climate factors and land use constitutes an important step towards the development of an effective risk management strategy.
    Matched MeSH terms: Spatio-Temporal Analysis
  19. Fulltext Spatio-temporal analysis on enterovirus cases through integrated surveillance in Taiwan
    Chan TC, Hwang JS, Chen RH, King CC, Chiang PH
    BMC Public Health, 2014 Jan 08;14:11.
    PMID: 24400725 DOI: 10.1186/1471-2458-14-11
    BACKGROUND: Severe epidemics of enterovirus have occurred frequently in Malaysia, Singapore, Taiwan, Cambodia, and China, involving cases of pulmonary edema, hemorrhage and encephalitis, and an effective vaccine has not been available. The specific aim of this study was to understand the epidemiological characteristics of mild and severe enterovirus cases through integrated surveillance data.

    METHODS: All enterovirus cases in Taiwan over almost ten years from three main databases, including national notifiable diseases surveillance, sentinel physician surveillance and laboratory surveillance programs from July 1, 1999 to December 31, 2008 were analyzed. The Pearson's correlation coefficient was applied for measuring the consistency of the trends in the cases between different surveillance systems. Cross correlation analysis in a time series model was applied for examining the capability to predict severe enterovirus infections. Poisson temporal, spatial and space-time scan statistics were used for identifying the most likely clusters of severe enterovirus outbreaks. The directional distribution method with two standard deviations of ellipse was applied to measure the size and the movement of the epidemic.

    RESULTS: The secular trend showed that the number of severe EV cases peaked in 2008, and the number of mild EV cases was significantly correlated with that of severe ones occurring in the same week [r = 0.553, p spatio-temporal clusters in June 2008, the mild cases had begun to rise since May 2008, and the outbreak spread from south to north.

    CONCLUSIONS: Local public health professionals can monitor the temporal and spatial trends plus spatio-temporal clusters and isolation rate of EV-71 in mild and severe EV cases in a community when virus transmission is high, to provide early warning signals and to prevent subsequent severe epidemics.

    Matched MeSH terms: Spatio-Temporal Analysis
  20. Temporal variability and climatology of hydrodynamic, water property and water quality parameters in the West Johor Strait of Singapore
    Behera MR, Chun C, Palani S, Tkalich P
    Mar Pollut Bull, 2013 Dec 15;77(1-2):380-95.
    PMID: 24139643 DOI: 10.1016/j.marpolbul.2013.09.043
    The study presents a baseline variability and climatology study of measured hydrodynamic, water properties and some water quality parameters of West Johor Strait, Singapore at hourly-to-seasonal scales to uncover their dependency and correlation to one or more drivers. The considered parameters include, but not limited by sea surface elevation, current magnitude and direction, solar radiation and air temperature, water temperature, salinity, chlorophyll-a and turbidity. FFT (Fast Fourier Transform) analysis is carried out for the parameters to delineate relative effect of tidal and weather drivers. The group and individual correlations between the parameters are obtained by principal component analysis (PCA) and cross-correlation (CC) technique, respectively. The CC technique also identifies the dependency and time lag between driving natural forces and dependent water property and water quality parameters. The temporal variability and climatology of the driving forces and the dependent parameters are established at the hourly, daily, fortnightly and seasonal scales.
    Matched MeSH terms: Spatio-Temporal Analysis
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