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  1. Article ; Online: Key risk factors associated with fractal dimension based geographical clustering of COVID-19 data in the Flemish and Brussels region, Belgium

    Yessika Adelwin Natalia / Christel Faes / Thomas Neyens / Naïma Hammami / Geert Molenberghs

    Frontiers in Public Health, Vol

    2023  Volume 11

    Abstract: IntroductionCOVID-19 remains a major concern globally. Therefore, it is important to evaluate COVID-19's rapidly changing trends. The fractal dimension has been proposed as a viable method to characterize COVID-19 curves since epidemic data is often ... ...

    Abstract IntroductionCOVID-19 remains a major concern globally. Therefore, it is important to evaluate COVID-19's rapidly changing trends. The fractal dimension has been proposed as a viable method to characterize COVID-19 curves since epidemic data is often subject to considerable heterogeneity. In this study, we aim to investigate the association between various socio-demographic factors and the complexity of the COVID-19 curve as quantified through its fractal dimension.MethodsWe collected population indicators data (ethnic composition, socioeconomic status, number of inhabitants, population density, the older adult population proportion, vaccination rate, satisfaction, and trust in the government) at the level of the statistical sector in Belgium. We compared these data with fractal dimension indicators of COVID-19 incidence between 1 January – 31 December 2021 using canonical correlation analysis.ResultsOur results showed that these population indicators have a significant association with COVID-19 incidences, with the highest explanatory and predictive power coming from the number of inhabitants, population density, and ethnic composition.ConclusionIt is important to monitor these population indicators during a pandemic, especially when dealing with targeted interventions for a specific population.
    Keywords Belgium ; canonical correlation analysis ; COVID-19 ; fractal dimension ; socio-demographic indicators ; Public aspects of medicine ; RA1-1270
    Language English
    Publishing date 2023-11-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: The COVID-19 wave in Belgium during the Fall of 2020 and its association with higher education.

    Yessika Adelwin Natalia / Christel Faes / Thomas Neyens / Geert Molenberghs

    PLoS ONE, Vol 17, Iss 2, p e

    2022  Volume 0264516

    Abstract: Soon after SARS-CoV-2 emerged in late 2019, Belgium was confronted with a first COVID-19 wave in March-April 2020. SARS-CoV-2 circulation declined in the summer months (late May to early July 2020). Following a successfully trumped late July-August peak, ...

    Abstract Soon after SARS-CoV-2 emerged in late 2019, Belgium was confronted with a first COVID-19 wave in March-April 2020. SARS-CoV-2 circulation declined in the summer months (late May to early July 2020). Following a successfully trumped late July-August peak, COVID-19 incidence fell slightly, to then enter two successive phases of rapid incline: in the first half of September, and then again in October 2020. The first of these coincided with the peak period of returning summer travelers; the second one coincided with the start of higher education's academic year. The largest observed COVID-19 incidence occurred in the period 16-31 October, particularly in the Walloon Region, the southern, French-speaking part of Belgium. We examine the potential association of the higher education population with spatio-temporal spread of COVID-19, using Bayesian spatial Poisson models for confirmed test cases, accounting for socio-demographic heterogeneity in the population. We find a significant association between the number of COVID-19 cases in the age groups 18-29 years and 30-39 years and the size of the higher education student population at the municipality level. These results can be useful towards COVID-19 mitigation strategies, particularly in areas where virus transmission from higher education students into the broader community could exacerbate morbidity and mortality of COVID-19 among populations with prevalent underlying conditions associated with more severe outcomes following infection.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: The COVID-19 wave in Belgium during the Fall of 2020 and its association with higher education

    Yessika Adelwin Natalia / Christel Faes / Thomas Neyens / Geert Molenberghs

    PLoS ONE, Vol 17, Iss

    2022  Volume 2

    Abstract: Soon after SARS-CoV-2 emerged in late 2019, Belgium was confronted with a first COVID-19 wave in March-April 2020. SARS-CoV-2 circulation declined in the summer months (late May to early July 2020). Following a successfully trumped late July-August peak, ...

    Abstract Soon after SARS-CoV-2 emerged in late 2019, Belgium was confronted with a first COVID-19 wave in March-April 2020. SARS-CoV-2 circulation declined in the summer months (late May to early July 2020). Following a successfully trumped late July-August peak, COVID-19 incidence fell slightly, to then enter two successive phases of rapid incline: in the first half of September, and then again in October 2020. The first of these coincided with the peak period of returning summer travelers; the second one coincided with the start of higher education’s academic year. The largest observed COVID-19 incidence occurred in the period 16–31 October, particularly in the Walloon Region, the southern, French-speaking part of Belgium. We examine the potential association of the higher education population with spatio-temporal spread of COVID-19, using Bayesian spatial Poisson models for confirmed test cases, accounting for socio-demographic heterogeneity in the population. We find a significant association between the number of COVID-19 cases in the age groups 18–29 years and 30–39 years and the size of the higher education student population at the municipality level. These results can be useful towards COVID-19 mitigation strategies, particularly in areas where virus transmission from higher education students into the broader community could exacerbate morbidity and mortality of COVID-19 among populations with prevalent underlying conditions associated with more severe outcomes following infection.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Spatial and temporal analysis of hospitalized dengue patients in Bandung

    Lia Faridah / I. Gede Nyoman Mindra / Ramadhani Eka Putra / Nisa Fauziah / Dwi Agustian / Yessika Adelwin Natalia / Kozo Watanabe

    Tropical Medicine and Health, Vol 49, Iss 1, Pp 1-

    demographics and risk

    2021  Volume 9

    Abstract: Abstract Background Bandung, the fourth largest city in Indonesia and capital of West Java province, has been considered a major endemic area of dengue, and studies show that the incidence in this city could increase and spread rapidly. At the same time, ...

    Abstract Abstract Background Bandung, the fourth largest city in Indonesia and capital of West Java province, has been considered a major endemic area of dengue, and studies show that the incidence in this city could increase and spread rapidly. At the same time, estimation of incidence could be inaccurate due to a lack of reliable surveillance systems. To provide strategic information for the dengue control program in the face of limited capacity, this study used spatial pattern analysis of a possible outbreak of dengue cases, through the Geographic Information System (GIS). To further enhance the information needed for effective policymaking, we also analyzed the demographic pattern of dengue cases. Methods Monthly reports of dengue cases from January 2014 to December 2016 from 16 hospitals in Bandung were collected as the database, which consisted of address, sex, age, and code to anonymize the patients. The address was then transformed into geocoding and used to estimate the relative risk of a particular area’s developing a cluster of dengue cases. We used the kernel density estimation method to analyze the dynamics of change of dengue cases. Results The model showed that the spatial cluster of the relative risk of dengue incidence was relatively unchanged for 3 years. Dengue high-risk areas predominated in the southern and southeastern parts of Bandung, while low-risk areas were found mostly in its western and northeastern regions. The kernel density estimation showed strong cluster groups of dengue cases in the city. Conclusions This study demonstrated a strong pattern of reported cases related to specific demographic groups (males and children). Furthermore, spatial analysis using GIS also visualized the dynamic development of the aggregation of disease incidence (hotspots) for dengue cases in Bandung. These data may provide strategic information for the planning and design of dengue control programs.
    Keywords Bandung ; Dengue infection ; Spatial pattern ; Arctic medicine. Tropical medicine ; RC955-962
    Subject code 910
    Language English
    Publishing date 2021-05-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: TYT CURVE

    Tina Dewi Judistiani / Tetty Yuniaty / Yessika Adelwin Natalia

    International Journal of Integrated Health Sciences, Vol 2, Iss 1, Pp 9-

    PILOT STUDY ON ALTERNATIVES STANDARDS OF REFERENCE TO DETERMINE INTRAUTERINE GROWTH IN LOW RESOURCE SETTING IN INDONESIA

    2014  Volume 14

    Abstract: Objective: To develop a new intrauterine growth curve based on local population for accurate intrauterine growth retardation (IUGR) infant identification. Methods: An observational analytic method was applied to develop Tina-Yessika-Tetty (TYT) curve ... ...

    Abstract Objective: To develop a new intrauterine growth curve based on local population for accurate intrauterine growth retardation (IUGR) infant identification. Methods: An observational analytic method was applied to develop Tina-Yessika-Tetty (TYT) curve derived from 13,405 neonatal anthropometric measurements taken from the medical record database of Dr. Hasan Sadikin General Hospital, Bandung, Indonesia. The infants included in this study were born during the period of January 1st, 2005 to December 31st, 2009. The new curve was then compared to the Lubchenco and Alisjahbana curves. Only 6,814 data met the inclusion and exclusion criteria. Results: The mean birth weight in this study was lower compared to that of the Lubchenco and Alisjahbana studies. Comparison of the three curves showed that there was a significant difference among the three curves (R=0.998, R2=0.996, p<0.001), which indicates a probability for a new newborn classification. Conclusions: TYT curve may be used as an alternative to identify IUGR immediately after birth, especially when detection during pregnancy is not available in low resource setting. A prospective study with a larger population is needed; However, this study has provided an evidence to support the need for timely evaluation for such growth chart as they change over time.
    Keywords Alisjahbana curve ; intrauterine growth ; Lubchenco curve ; TYT curve ; Medicine ; R
    Subject code 339
    Language English
    Publishing date 2014-06-01T00:00:00Z
    Publisher Universitas Padjadjaran
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Pitch and Flat Roof Factors’ Association with Spatiotemporal Patterns of Dengue Disease Analysed Using Pan-Sharpened Worldview 2 Imagery

    Fedri Ruluwedrata Rinawan / Ryutaro Tateishi / Ardini Saptaningsih Raksanagara / Dwi Agustian / Bayan Alsaaideh / Yessika Adelwin Natalia / Ahyani Raksanagara

    ISPRS International Journal of Geo-Information, Vol 4, Iss 4, Pp 2586-

    2015  Volume 2603

    Abstract: Dengue disease incidence is related with the construction of a house roof, which is an Aedes mosquito habitat. This study was conducted to classify pitch roof (PR) and flat roof (FR) surfaces using pan-sharpened Worldview 2 to identify dengue disease ... ...

    Abstract Dengue disease incidence is related with the construction of a house roof, which is an Aedes mosquito habitat. This study was conducted to classify pitch roof (PR) and flat roof (FR) surfaces using pan-sharpened Worldview 2 to identify dengue disease patterns (DDPs) and their association with DDP. A Supervised Minimum Distance classifier was applied to 653 training data from image object segmentations: PR (81 polygons), FR (50), and non-roof (NR) class (522). Ground validation of 272 pixels (52 for PR, 51 for FR, and 169 for NR) was done using a global positioning system (GPS) tool. Getis-Ord score pattern analysis was applied to 1154 dengue disease incidence with address-approach-based data with weighted temporal value of 28 days within a 1194 m spatial radius. We used ordinary least squares (OLS) and geographically weighted regression (GWR) to assess spatial association. Our findings showed 70.59% overall accuracy with a 0.51 Kappa coefficient of the roof classification images. Results show that DDPs were found in hotspot, random, and dispersed patterns. Smaller PR size and larger FR size showed some association with increasing DDP into more clusters (OLS: PR value = −0.27; FR = 0.04; R2 = 0.076; GWR: R2 = 0.76). The associations in hotspot patterns are stronger than in other patterns (GWR: R2 in hotspot = 0.39, random = 0.37, dispersed = 0.23).
    Keywords dengue disease incidence ; address-approach-based data ; Getis-Ord score ; segmentation ; Supervised Minimum Distance ; ordinary least squares (OLS) ; geographically weighted regression (GWR) ; Geography (General) ; G1-922
    Subject code 006
    Language English
    Publishing date 2015-11-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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