scholarly journals Spatio-temporal distribution of malaria one year after the implementation of additional preventive strategies in Bandiagara, Mali

2020 ◽  
Author(s):  
Drissa Coulibaly ◽  
Boureima Guindo ◽  
Fayçal Maiga ◽  
Salimata Konate ◽  
Astou Diallo ◽  
...  
Keyword(s):  
Time Series ◽  
High Risk ◽  
Clinical Malaria ◽  
Google Earth ◽  
Low Risk ◽  
Geographical Information ◽  
Asymptomatic Malaria ◽  
Entire Study ◽  
North East ◽  
Spatio Temporal

Abstract BackgroundEvaluation of local transmission epidemiology to characterize malaria risk is essential for planning malaria control and elimination programmes. The use of geographical information systems (GIS) has been a major asset to this approach. This study aimed to characterize the local spatio-temporal pattern of malaria infection and clinical disease after implementation of Seasonal Malaria Chemoprevention (SMC) and Indoor Residual Spraying (IRS) in Bandiagara, a Malian town.MethodsFrom October 2017 to December 2018, an active and passive surveillance system was established in a cohort study of three hundred children aged from 6 months to 15 years old. Weekly time-series of clinical malaria and monthly time-series of asymptomatic Plasmodium carriage and rainfall were plotted. Numbers of clinical malaria episodes and asymptomatic parasite carriers were mapped using Quantum Geographic Information System (QGIS). Landscape features of Bandiagara were obtained from Google earth. Clusters of high or low risk were identified under SaTScan® software using a Bernoulli model. ResultsFrom October 2017 to December 2018, 167 clinical malaria cases were recorded, mostly from July to December, while asymptomatic parasite carriage was observed during the entire study period. Three clusters of clinical episodes were found. All were hotspots. They were located in the north-east, south and west. No low risk cluster was identified. Three significant high-risk clusters of asymptomatic parasite carriage were identified in the south, north-east and north. These clusters were located near standing water. ConclusionThis study confirms the seasonality of clinical malaria in Bandiagara. The continued presence of asymptomatic parasite carriers maintains malaria transmission. To advance malaria elimination, control strategies must also target hotspots of asymptomatic parasite carriage. There was a spatial heterogeneity of clinical and asymptomatic malaria. Despite the implementation of additional preventives strategies, the locations of high-risk clusters were stable.

scholarly journals Towards Reliable Velocities of Permanent GNSS Stations

2016 ◽  
Vol 100 (1) ◽  
pp. 17-26
Author(s):  
Janusz Bogusz ◽  
Anna Klos ◽  
Marta Gruszczynska ◽  
Maciej Gruszczynski
Keyword(s):  
Time Series ◽  
Singular Spectrum Analysis ◽  
Principal Component ◽  
North East ◽  
Temporal Correlations ◽  
The North ◽  
Spatio Temporal ◽  
Permanent Station

Abstract In the modern geodesy the role of the permanent station is growing constantly. The proper treatment of the time series from such station lead to the determination of the reliable velocities. In this paper we focused on some pre-analysis as well as analysis issues, which have to be performed upon the time series of the North, East and Up components and showed the best, in our opinion, methods of determination of periodicities (by means of Singular Spectrum Analysis) and spatio-temporal correlations (Principal Component Analysis), that still exist in the time series despite modelling. Finally, the velocities of the selected European permanent stations with the associated errors determined following power-law assumption in the stochastic part is presented.

scholarly journals Social distance and spatial distance are not the same, observations on the use of GIS in leprosy epidemiology

2008 ◽  
Vol 136 (12) ◽  
pp. 1624-1627 ◽  
Author(s):  
T. A. HOEVEN ◽  
E. A. J. FISCHER ◽  
D. PAHAN ◽  
J. H. RICHARDUS
Keyword(s):  
High Risk ◽  
Social Distance ◽  
Geographical Information Systems ◽  
Index Patient ◽  
Low Risk ◽  
Geographical Information ◽  
Spatial Distance ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Leprosy Patients

SUMMARYContacts of leprosy patients have a higher risk of developing clinical leprosy. Being a contact is defined socially, but with the introduction of geographical information systems (GIS) in infectious disease epidemiology, it is necessary to relate spatial distance to social distance. We measured the distances between patients and their socially defined contacts in northwest Bangladesh. Contact categories differ in mean distance to the index patients. Sixty-seven per cent of the high-risk contacts lived within 10 metres (m), while all low-risk contacts lived >10 m from the index patient. Classification based on intervals of spatial distance creates categories that contain contacts of different socially defined categories, illustrated by a category of people living between 10 m and 20 m consisting of 47% of high-risk contacts and 52% low-risk contacts. Classification of contacts based on the spatial distance, as performed with GIS techniques, produces other groups than with social definitions.

scholarly journals PO 8419 SPATIO-TEMPORAL MAPPING OF ASYMPTOMATIC AND CLINICAL MALARIA INFECTIONS REVEALS FOCI OF MALARIA TRANSMISSION FOR TARGETED CONTROL INTERVENTIONS

2019 ◽  
Vol 4 (Suppl 3) ◽  
pp. A35.2-A35
Author(s):  
Makhtar Niang ◽  
Cheikh Talla ◽  
Nafissatou Diagne ◽  
Fatoutama Diene-Sarr ◽  
Cheikh Sokhna
Keyword(s):  
Malaria Transmission ◽  
Malaria Incidence ◽  
Clinical Malaria ◽  
Asymptomatic Malaria ◽  
Design Strategies ◽  
Cross Sectional ◽  
Asymptomatic Infections ◽  
Spatio Temporal ◽  
Malaria Episodes

BackgroundThe global decline of malaria incidence over the past decade has led to the thought that elimination could be achieved. This has resulted in an increased interest to design strategies to target the hidden reservoir of asymptomatic infections among populations and interrupt on-going residual local malaria transmission. This study explored the reservoir of asymptomatic Plasmodium infections and its relationship with subsequent clinical malaria infections in low-transmission areas in Senegal.MethodsCross-sectional surveys were carried out in 2013, 2014, 2015, and 2016 and combined with longitudinal follow-up to determine and geolocalise both asymptomatic and clinical malaria episodes in Dielmo and Ndiop, Senegal. The prevalence of asymptomatic Plasmodium carriage in the community was investigated by real-time PCR while clinical malaria attacks were identified at health facilities during the transmission season. All households were georeferenced to spatially map asymptomatic and clinical infections.ResultsThe study revealed substantial asymptomatic infections with average parasite carriage of 8.11% and 7% in Dielmo and Ndiop, respectively. P. falciparum accounted for most asymptomatic infections (more than 90%). In Dielmo, 95% of asymptomatic infections clustered within the same geographical areas while infections were disparate in Ndiop. Preliminary fine-scale mapping of asymptomatic and clinical malaria infections identified clusters of higher malaria incidence interpreted as foci of transmission across the four-year study period with 95%–98% of clinical infections occurring in households where an asymptomatic malaria infection existed.ConclusionThis study revealed substantial asymptomatic Plasmodium infections in both settings throughout the four-year study period and spatial clusters of malaria infections at the microepidemiological level. Together, these findings could offer a feasible approach for a rational targeting of malaria control interventions to achieve elimination.

scholarly journals Temporal Monitoring and Predicting of the Abundance of Malaria Vectors Using Time Series Analysis of Remote Sensing Data through Google Earth Engine

2021 ◽  
Author(s):  
Fahimeh Youssefi ◽  
Mohmmad Javad Valadan Zoej ◽  
Ahmad Ali Hanafi-Bojd ◽  
Alireza Borhani Darian ◽  
Mehdi Khaki ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
High Risk ◽  
Environmental Factors ◽  
Remote Sensing Data ◽  
Google Earth ◽  
Landsat 8 ◽  
Sensing Data ◽  
Temporal Prediction ◽  
Daily Precipitation Data

Abstract Background: In many studies in the field of malaria, environmental factors have been acquired in single-time, multi-time or a short time series using remote sensing and meteorological data. Selecting the best periods of the year to monitor the habitats of Anopheles larvae can be effective in better and faster control of malaria outbreak.Methods: In this article, high-risk times for three regions in Iran, including Qaleh-Ganj, Sarbaz and Bashagard counties with history of malaria prevalence had been estimated. For this purpose, a series of environmental factors affecting the growth and survival of Anopheles had been used over a seven-year period through the GEE. Environmental factors used in this study include NDVI and LST extracted from Landsat-8 satellite images, daily precipitation data from PERSIANN-CDR, soil moisture data from NASA-USDA Enhanced SMAP, ET data from MODIS sensor, and vegetation health indices included TCI and VCI extracted from MODIS sensors. All these parameters were extracted on a monthly average for seven years and, their results were fused at the decision level using majority voting method to estimate high-risk time in a year.Results: The results of this study indicated that there were two high-risk times for all three study areas in a year to increase the abundance of Anopheles mosquitoes. The first peak occurred from late winter to late spring and the second peak from late summer to mid-autumn. If there is a malaria patient in the area, after the end of the Anopheles larvae growth period, the disease will spread throughout the region. Further evaluation of the results against the entomological data available in previous studies showed that the high-risk times predicted in this study were consistent with the increase in the abundance of Anopheles mosquitoes in the study areas. Conclusions: The proposed method is very useful for temporal prediction of the increase of the abundance of Anopheles mosquitoes and also the use of optimal data with the aim of monitoring the exact location of Anopheles habitats. This study extracted high-risk time based on the analysis of the time series of remote sensing data.

scholarly journals Assessment of Coastal Aquaculture for India from Sentinel-1 SAR Time Series

2019 ◽  
Vol 11 (3) ◽  
pp. 357 ◽  
Author(s):  
Kumar Prasad ◽  
Marco Ottinger ◽  
Chunzhu Wei ◽  
Patrick Leinenkugel
Keyword(s):  
Time Series ◽  
Coastal Zone ◽  
Accuracy Assessment ◽  
Economic Value ◽  
Global Scale ◽  
Google Earth ◽  
Shape Information ◽  
Shuttle Radar Topographic Mission ◽  
Sar Data ◽  
Spatio Temporal

Aquaculture is one of the fastest growing primary food production sectors in India and ranks second behind China. Due to its growing economic value and global demand, India’s aquaculture industry experienced exponential growth for more than one decade. In this study, we extract land-based aquaculture at the pond level for the entire coastal zone of India using large-volume time series Sentinel-1 synthetic-aperture radar (SAR) data at 10-m spatial resolution. Elevation and slope from Shuttle Radar Topographic Mission digital elevation model (SRTM DEM) data were used for masking inappropriate areas, whereas a coastline dataset was used to create a land/ocean mask. The pixel-wise temporal median was calculated from all available Sentinel-1 data to significantly reduce the amount of noise in the SAR data and to reduce confusions with temporary inundated rice fields. More than 3000 aquaculture pond vector samples were collected from high-resolution Google Earth imagery and used in an object-based image classification approach to exploit the characteristic shape information of aquaculture ponds. An open-source connected component segmentation algorithm was used for the extraction of the ponds based on the difference in backscatter intensity of inundated surfaces and shape metrics calculated from aquaculture samples as input parameters. This study, for the first time, provides spatial explicit information on aquaculture distribution at the pond level for the entire coastal zone of India. Quantitative spatial analyses were performed to identify the provincial dominance in aquaculture production, such as that revealed in Andhra Pradesh and Gujarat provinces. For accuracy assessment, 2000 random samples were generated based on a stratified random sampling method. The study demonstrates, with an overall accuracy of 0.89, the spatio-temporal transferability of the methodological framework and the high potential for a global-scale application.

scholarly journals TimeSpec4LULC: A Global Deep Learning-driven Dataset of MODIS Terra-Aqua Multi-Spectral Time Series for LULC Mapping and Change Detection

2021 ◽  
Author(s):  
Rohaifa Khaldi ◽  
Domingo Alcaraz-Segura ◽  
Emilio Guirado ◽  
Yassir Benhammou ◽  
Abdellatif El Afia ◽  
...  
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Change Detection ◽  
Google Earth ◽  
Data Availability ◽  
Temporal Consistency ◽  
Learning Networks ◽  
Spatio Temporal ◽  
Combined Time Series ◽  
Earth’S System

Abstract. Land Use and Land Cover (LULCs) mapping and change detection are of paramount importance to understand the distribution and effectively monitor the dynamics of the Earth’s system. An unexplored way to create global LULC maps is by building good quality LULC-models based on state-of-the-art deep learning networks. Building such models requires large global good quality time series LULC datasets, which are not available yet. This paper presents TimeSpec4LULC (Khaldi et al., 2021), a smart open-source global dataset of multi-Spectral Time series for 29 LULC classes. TimeSpec4LULC was built based on the 7 spectral bands of MODIS sensor at 500 m resolution from 2002 to 2021, and was annotated using a spatial agreement across the 15 global LULC products available in Google Earth Engine. The 19-year monthly time series of the seven bands were created globally by: (1) applying different spatio-temporal quality assessment filters on MODIS Terra and Aqua satellites, (2) aggregating their original 8-day temporal granularity into monthly composites, (3) merging their data into a Terra+Aqua combined time series, and (4) extracting, at the pixel level, 11.85 million time series for the 7 bands along with a set of metadata about geographic coordinates, country and departmental divisions, spatio-temporal consistency across LULC products, temporal data availability, and the global human modification index. To assess the annotation quality of the dataset, a sample of 100 pixels, evenly distributed around the world, from each LULC class, was selected and validated by experts using very high resolution images from both Google Earth and Bing Maps imagery. This smartly, pre-processed, and annotated dataset is targeted towards scientific users interested in developing and evaluating various machine learning models, including deep learning networks, to perform global LULC mapping and change detection.

Papillary Thyroid Carcinoma: How Radical Lymphadenectomy Should be Performed?

Swiss Surgery ◽  
2003 ◽  
Vol 9 (2) ◽  
pp. 63-68
Author(s):  
Schweizer ◽  
Seifert ◽  
Gemsenjäger
Keyword(s):  
High Risk ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Low Risk ◽  
Papillary Thyroid ◽  
Sentinel Nodes ◽  
Fand Sich ◽  
Radical Lymphadenectomy ◽  
N Status

Fragestellung: Die Bedeutung von Lymphknotenbefall bei papillärem Schilddrüsenkarzinom und die optimale Lymphknotenchirurgie werden kontrovers beurteilt. Methodik: Retrospektive Langzeitstudie eines Operateurs (n = 159), prospektive Dokumentation, Nachkontrolle 1-27 (x = 8) Jahre, Untersuchung mit Bezug auf Lymphknotenbefall. Resultate: Staging. Bei 42 Patienten wurde wegen makroskopischem Lymphknotenbefall (cN1) eine therapeutische Lymphadenektomie durchgeführt, mit pN1 Status bei 41 (98%) Patienten. Unter 117 Patienten ohne Anhalt für Lymphknotenbefall (cN0) fand sich okkulter Befall bei 5/29 (17%) Patienten mit elektiver (prophylaktischer) Lymphadenektomie, und bei 2/88 (2.3%) Patienten ohne Lymphadenektomie (metachroner Befall) (p < 0.005). Lymphknotenrezidive traten (1-5 Jahre nach kurativer Primärtherapie) bei 5/42 (12%) pN1 und bei 3/114 (2.6%) cN0, pN0 Tumoren auf (p = 0009). Das 20-Jahres-Überleben war bei TNM I + II (low risk) Patienten 100%, d.h. unabhängig vom N Status; pN1 vs. pN0, cN0 beeinflusste das Überleben ungünstig bei high risk (>= 45-jährige) Patienten (50% vs. 86%; p = 0.03). Diskussion: Der makroskopische intraoperative Lymphknotenbefund (cN) hat Bedeutung: - Befall ist meistens richtig positiv (pN1) und erfordert eine ausreichend radikale, d.h. systematische, kompartiment-orientierte Lymphadenektomie (Mikrodissektion) zur Verhütung von - kurablem oder gefährlichem - Rezidiv. - Okkulter Befall bei unauffälligen Lymphknoten führt selten zum klinischen Rezidiv und beeinflusst das Überleben nicht. Wir empfehlen eine weniger radikale (sampling), nur zentrale prophylaktische Lymphadenektomie, ohne Risiko von chirurgischer Morbidität. Ein empfindlicherer Nachweis von okkultem Befund (Immunhistochemie, Schnellschnitt von sampling Gewebe oder sentinel nodes) erscheint nicht rational. Bei pN0, cN0 Befund kommen Verzicht auf 131I Prophylaxe und eine weniger intensive Nachsorge in Frage.

Individuals at high risk for suicide are categorically distinct from those at low risk.

2017 ◽  
Vol 29 (4) ◽  
pp. 382-393 ◽  
Author(s):  
Tracy K. Witte ◽  
Jill M. Holm-Denoma ◽  
Kelly L. Zuromski ◽  
Jami M. Gauthier ◽  
John Ruscio
Keyword(s):  
High Risk ◽  
Low Risk
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