A remote sensing-based survey of archaeological/heritage sites near Kandahar, Afghanistan through publicly available satellite imagery
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ABSTRACT:
SUBMITTER: Karaucak M
PROVIDER: S-EPMC8562850 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Accurate and comprehensive measurements of economic well-being are fundamental inputs into both research and policy, but such measures are unavailable at a local level in many parts of the world. Here we train deep learning models to predict survey-based estimates of asset wealth across ~ 20,000 African villages from publicly-available multispectral satellite imagery. Models can explain 70% of the variation in ground-measured village wealth in countries where the model was not trained, outperforming previous benchmarks from high-resolution imagery, and comparison with independent wealth measurements from censuses suggests that errors in satellite estimates are comparable to errors in existing ground data. Satellite-based estimates can also explain up to 50% of the variation in district-aggregated changes in wealth over time, with daytime imagery particularly useful in this task. We demonstrate the utility of satellite-based estimates for research and policy, and demonstrate their scalability by creating a wealth map for Africa's most populous country.
| S-EPMC7244551 | biostudies-literature
Project description:Today, the satellite-based monitoring of archaeological sites and site damage is a widespread practice, especially in conflict-affected regions. However, the vast majority of these remote sensing cultural heritage monitoring efforts have been led and conducted by remote researchers, and there remains an urgent need to embed this work within existing, in-country institutions at local and regional levels. Here, we present the archaeological site monitoring approach and results from the project Archaeological Practice and Heritage Protection in the Kurdistan Region of Iraq, a collaborative project between the Sirwan Regional Project and Kurdish Iraqi archaeologists aimed at generating a fully functional and sustainable programme of archaeological site management co-created with, and managed by, Kurdish Iraqi archaeologists and antiquities officials. Between August 2018 and February 2020, 376 archaeological sites in the Sirwan/Upper Diyala River Valley region, located in the Kurdistan Region of Iraq, were assessed for damage by Kurdish Iraqi archaeologists in collaboration with the Sirwan Regional Project. This work represents the first large-scale, systematic dataset of archaeological site conditions and longer-term damage in the Kurdistan Region of Iraq (KRI). Our results show that 86.7% of the assessed archaeological sites and 38.6% of the site surface area in this region were affected by damage between 1951-2018, and demonstrate the great urgency with which action must be taken to develop appropriate safeguarding measures for the KRI's archaeological heritage. On the basis of these results, we outline relevant recommendations for the immediate protection of archaeological sites in Garmian and the greater Kurdistan Region.
| S-EPMC9200297 | biostudies-literature
Project description:BackgroundAcute bacterial meningitis (ABM) is an important cause of morbidity and mortality in children but there are no published data on the treatment outcomes of ABM in Afghanistan.MethodsWe conducted a prospective observational cohort study over one year, February 2020 to January 2021 in a tertiary care hospital in Kandahar, Afghanistan. AMB was diagnosed clinically and on lumbar puncture findings. Binary logistic regression assessed factors for death.ResultsA total of 393 ABM children of mean age 4.8 years were recruited. Most were males [231 (58.8%)], living in rural areas [267 (67.9%)] and in households of >10 inhabitants [294 (74.8%)]. Only 96 (24.4%) had received against both Haemophilus influenzae type b (Hib) or pneumococcal (PCV) vaccines. Children were treated with combination of ceftriaxone and ampicillin and 169/321 (52.6%) received dexamethasone. Of the 321 children with a known outcome, 69 (21.5%) died. Death was significantly associated with: not receiving dexamethasone [adjusted odds ratio (AOR) 4.9 (95% CI 2.6-9.5, p <0.001)], coma on admission [AOR 4.6 (I 2.3-9.5, p <0.001)], no PCV [AOR 2.8 (1.2-6.6, p = 0.019)] or Hib vaccine [AOR 2.8 (1.2-6.6, p = 0.019)], and being male [AOR 2.7 (1.4-5.5, p = 0.005).ConclusionsABM causes significant morbidity and mortality in Afghan children that may be improved by greater use of PCV and Hib vaccines. Adjunct dexamethasone should be evaluated formally in our setting.
| S-EPMC9000062 | biostudies-literature
Project description:BackgroundLack of accurate data on the distribution of sub-national populations in low- and middle-income countries impairs planning, monitoring, and evaluation of interventions. Novel, low-cost methods to develop unbiased survey sampling frames at sub-national, sub-provincial, and even sub-district levels are urgently needed. This article details our experience using remote satellite imagery to develop a provincial-level representative community survey sampling frame to evaluate the effects of a 7-year health system intervention in Sofala Province, Mozambique.MethodsMozambique's most recent census was conducted in 2007, and no data are readily available to generate enumeration areas for representative health survey sampling frames. To remedy this, we partnered with the Humanitarian OpenStreetMap Team to digitize every building in Sofala and Manica provinces (685,189 Sofala; 925,713 Manica) using up-to-date remote satellite imagery, with final results deposited in the open-source OpenStreetMap database. We then created a probability proportional to size sampling frame by overlaying a grid of 2.106 km resolution (0.02 decimal degrees) across each province, and calculating the number of buildings within each grid square. Squares containing buildings were used as our primary sampling unit with replacement. Study teams navigated to the geographic center of each selected square using geographic positioning system coordinates, and then conducted a standard "random walk" procedure to select 20 households for each time a given square was selected. Based on sample size calculations, we targeted a minimum of 1500 households in each province. We selected 88 grids within each province to reach 1760 households, anticipating ongoing conflict and transport issues could preclude the inclusion of some clusters.ResultsCivil conflict issues forced the exclusion of 8 of 31 subdistricts in Sofala and 15 of 39 subdistricts in Manica. Using Android tablets, Open Data Kit software, and a remote RedCap data capture system, our final sample included 1549 households in Sofala (4669 adults; 4766 children; 33 missing age) and 1538 households in Manica (4422 adults; 4898 children; 33 missing age).ConclusionsOther implementation or evaluation teams may consider employing similar methods to track population distributions for health systems planning or the development of representative sampling frames using remote satellite imagery.
| S-EPMC6206736 | biostudies-literature
Project description:INTRODUCTION:Afghanistan is affected by one of the world's longest protracted armed conflicts, frequent natural disasters, disease outbreaks and large population movements and it suffers from a high burden of tuberculosis (TB), including rifampicin-resistant TB (RR-TB). The study shows Médecins Sans Frontières' experiences with care for patients with RR-TB in Kandahar Province. We describe the uptake of RR-TB treatment, how World Health Organisation criteria for the choice between the short and an individualized regimen were implemented, and treatment outcomes. METHODS:This is a retrospective cohort analysis of routinely collected data from RR-TB patients enrolled in care from 2016 until 2019. Descriptive analysis was performed to present characteristics of patients and treatment outcomes. Multivariable Cox analysis was performed to identify risk factors for having an unfavourable treatment outcome. RESULTS:Out of 146 enrolled RR-TB patients, 112 (76.7%) started treatment: 41 (36.6%) and 71 (63.4%) with the short and individualized treatment regimen, respectively. Of 82 with results for fluoroquinolone susceptibility, 39 (47.6%) had fluoroquinolone-resistant TB. Seven patients with initially fluoroquinolone-resistant TB and three pregnant women started the short regimen and 18 patients eligible for the short regimen started the injectable-free individualized regimen. Overall, six-month smear and culture conversion were 98.7% and 97.1%, respectively; treatment success was 70.1%. Known initial fluoroquinolone resistance (aHR 3.77, 95%CI:1.53-9.27) but not choice of regimen predicted having an unfavourable outcome. CONCLUSION:Even though criteria for the choice of treatment regimen were not applied strictly, we have achieved acceptable outcomes in this cohort. To expand RR-TB care, treatment regimens should fit provision at primary health care level and take patient preferences into account.
| S-EPMC7446914 | biostudies-literature
Project description:BackgroundModern contraceptives are highly effective and reliable methods of preventing unintended pregnancies and reducing maternal deaths. Only 22 percent of currently married women use modern methods of contraceptives in Afghanistan. This study assessed the factors associated with modern contraceptive use among married women attending comprehensive health centers (CHCs) in Kandahar Province.MethodsThis was an institution-based cross-sectional study that included 325 married women who attended randomly selected comprehensive health clinics in Kandahar between September and October 2019. The total sample size was allocated proportionally to selected health clinics based on the recent 3-month average patients load. We used a consecutive sampling method to select study participants. Data were collected in a structured questionnaire, which included information on respondents' demographic, socioeconomic, reproductive, and contraceptive experiences. Data was analyzed using SPSS 21.00 statistical software. We used descriptive statistics such as tables and proportions to present data. Binary and multiple logistic regression analyses were carried out to determine factors associated with modern contraceptive use.ResultsOut of 325 married women, 127 used modern contraceptives with a prevalence of 39.1% (95%CI = 33.7%-44.6%). The results indicated that the area of residence (AOR = 2.61, 95% CI 1.43-4.78) and ever use of contraceptives (AOR = 14.92, 95% CI 6.88-32.34) are associated with modern contraceptive use among married women attending comprehensive health centers in Kandahar.ConclusionThis study found that modern contraceptive use was higher than reported on the national level. The most persistent factors associated with modern contraceptive use in this study were urban residence and ever use of contraceptives. As a policy measure, family planning programs should be prompted to the rural residency in Kandahar Province.
| S-EPMC8046549 | biostudies-literature
Project description:High-throughput genomic and molecular profiling of tumors is emerging as an important clinical approach. Molecular profiling is increasingly being used to guide cancer patient care, especially in advanced and incurable cancers. However, navigating the scientific literature to make evidence-based clinical decisions based on molecular profiling results is overwhelming for many oncology clinicians and researchers. The Personalized Cancer Therapy website (www.personalizedcancertherapy.org) was created to provide an online resource for clinicians and researchers to facilitate navigation of available data. Specifically, this resource can be used to help identify potential therapy options for patients harboring oncogenic genomic alterations. Herein, we describe how content on www.personalizedcancertherapy.org is generated and maintained. We end with case scenarios to illustrate the clinical utility of the website. The goal of this publicly available resource is to provide easily accessible information to a broad oncology audience, as this may help ease the information retrieval burden facing participants in the precision oncology field. Cancer Res; 77(21); e123-6. ©2017 AACR.
| S-EPMC5774617 | biostudies-other
Project description:BackgroundWildland fire (wildfire; bushfire) pollution contributes to poor air quality, a risk factor for premature death. The frequency and intensity of wildfires are expected to increase; improved tools for estimating exposure to fire smoke are vital. New-generation satellite-based sensors produce high-resolution spectral images, providing real-time information of surface features during wildfire episodes. Because of the vast size of such data, new automated methods for processing information are required.ObjectiveWe present a deep fully convolutional neural network (FCN) for predicting fire smoke in satellite imagery in near-real time (NRT).MethodsThe FCN identifies fire smoke using output from operational smoke identification methods as training data, leveraging validated smoke products in a framework that can be operationalized in NRT. We demonstrate this for a fire episode in Australia; the algorithm is applicable to any geographic region.ResultsThe algorithm has high classification accuracy (99.5% of pixels correctly classified on average) and precision (average intersection over union = 57.6%).SignificanceThe FCN algorithm has high potential as an exposure-assessment tool, capable of providing critical information to fire managers, health and environmental agencies, and the general public to prevent the health risks associated with exposure to hazardous smoke from wildland fires in NRT.
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Project description:Differential gene expression analysis is widely used to study changes in gene expression profiles between two or more groups of samples (e.g., physiological versus pathological conditions, pre-treatment versus post-treatment, and infected versus non-infected tissues). This protocol aims to identify gene expression changes in a pre-selected set of genes associated with severe acute respiratory syndrome coronavirus 2 viral infection and host cell antiviral response, as well as subsequent gene expression association with phenotypic features using samples deposited in public repositories. For complete details on the use and outcome of this informatics analysis, please refer to Bizzotto et al. (2020).
| S-EPMC8061314 | biostudies-literature
Project description:Electrocardiography (ECG) is a key non-invasive diagnostic tool for cardiovascular diseases which is increasingly supported by algorithms based on machine learning. Major obstacles for the development of automatic ECG interpretation algorithms are both the lack of public datasets and well-defined benchmarking procedures to allow comparison s of different algorithms. To address these issues, we put forward PTB-XL, the to-date largest freely accessible clinical 12-lead ECG-waveform dataset comprising 21837 records from 18885 patients of 10 seconds length. The ECG-waveform data was annotated by up to two cardiologists as a multi-label dataset, where diagnostic labels were further aggregated into super and subclasses. The dataset covers a broad range of diagnostic classes including, in particular, a large fraction of healthy records. The combination with additional metadata on demographics, additional diagnostic statements, diagnosis likelihoods, manually annotated signal properties as well as suggested folds for splitting training and test sets turns the dataset into a rich resource for the development and the evaluation of automatic ECG interpretation algorithms.
| S-EPMC7248071 | biostudies-literature