scholarly journals Vulnerabilities Associated with Post-disaster Declines in HIV-testing: Decomposing the Impact of Hurricane Sandy

PLoS Currents ◽  
2018 ◽  
Author(s):  
Erin Thomas
Keyword(s):  
Hiv Testing ◽  
Hurricane Sandy ◽  
The Impact ◽  
Post Disaster

A space time analysis evaluating the impact of hurricane sandy on HIV testing rates

2018 ◽  
Vol 28 ◽  
pp. 839-844 ◽  
Author(s):  
Grete E. Wilt ◽  
Erica Elaine Adams ◽  
Erin Thomas ◽  
Linda Ekperi ◽  
Tanya Telfair LeBlanc ◽  
...  
Keyword(s):  
Hiv Testing ◽  
Hurricane Sandy ◽  
Space Time ◽  
Time Analysis ◽  
The Impact

scholarly journals Building Damage Detection from Post-Event Aerial Imagery Using Single Shot Multibox Detector

2019 ◽  
Vol 9 (6) ◽  
pp. 1128 ◽  
Author(s):  
Yundong Li ◽  
Wei Hu ◽  
Han Dong ◽  
Xueyan Zhang
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Hurricane Sandy ◽  
Training Data ◽  
Aerial Images ◽  
Detection Methods ◽  
Single Shot ◽  
Data Set ◽  
Augmentation Strategies ◽  
Post Disaster

Using aerial cameras, satellite remote sensing or unmanned aerial vehicles (UAV) equipped with cameras can facilitate search and rescue tasks after disasters. The traditional manual interpretation of huge aerial images is inefficient and could be replaced by machine learning-based methods combined with image processing techniques. Given the development of machine learning, researchers find that convolutional neural networks can effectively extract features from images. Some target detection methods based on deep learning, such as the single-shot multibox detector (SSD) algorithm, can achieve better results than traditional methods. However, the impressive performance of machine learning-based methods results from the numerous labeled samples. Given the complexity of post-disaster scenarios, obtaining many samples in the aftermath of disasters is difficult. To address this issue, a damaged building assessment method using SSD with pretraining and data augmentation is proposed in the current study and highlights the following aspects. (1) Objects can be detected and classified into undamaged buildings, damaged buildings, and ruins. (2) A convolution auto-encoder (CAE) that consists of VGG16 is constructed and trained using unlabeled post-disaster images. As a transfer learning strategy, the weights of the SSD model are initialized using the weights of the CAE counterpart. (3) Data augmentation strategies, such as image mirroring, rotation, Gaussian blur, and Gaussian noise processing, are utilized to augment the training data set. As a case study, aerial images of Hurricane Sandy in 2012 were maximized to validate the proposed method’s effectiveness. Experiments show that the pretraining strategy can improve of 10% in terms of overall accuracy compared with the SSD trained from scratch. These experiments also demonstrate that using data augmentation strategies can improve mAP and mF1 by 72% and 20%, respectively. Finally, the experiment is further verified by another dataset of Hurricane Irma, and it is concluded that the paper method is feasible.

scholarly journals A Conceptual Framework Integrating “Building Back Better” and Post-Earthquake Needs for Recovery and Reconstruction

2021 ◽  
Vol 13 (10) ◽  
pp. 5608
Author(s):  
Manjiang Shi ◽  
Qi Cao ◽  
Baisong Ran ◽  
Lanyan Wei
Keyword(s):  
Disaster Recovery ◽  
Social Process ◽  
Principal Component ◽  
Assessment Method ◽  
International Consensus ◽  
Long Term Stability ◽  
The People ◽  
Policy Guidance ◽  
The Impact ◽  
Post Disaster

Global disasters due to earthquakes have become more frequent and intense. Consequently, post-disaster recovery and reconstruction has become the new normal in the social process. Through post-disaster reconstruction, risks can be effectively reduced, resilience can be improved, and long-term stability can be achieved. However, there is a gap between the impact of post-earthquake reconstruction and the needs of the people in the disaster area. Based on the international consensus of “building back better” (BBB) and a post-disaster needs assessment method, this paper proposes a new (N-BBB) conceptual model to empirically analyze recovery after the Changning Ms 6.0 earthquake in Sichuan Province, China. The reliability of the model was verified through factor analysis. The main observations were as follows. People’s needs focus on short-term life and production recovery during post-earthquake recovery and reconstruction. Because of disparities in families, occupations, and communities, differences are observed in the reconstruction time sequence and communities. Through principal component analysis, we found that the N-BBB model constructed in this study could provide strong policy guidance in post-disaster recovery and reconstruction after the Changning Ms 6.0 earthquake, effectively coordinate the “top-down” and “bottom-up” models, and meet the diversified needs of such recovery and reconstruction.

scholarly journals Building Damage Detection Using U-Net with Attention Mechanism from Pre- and Post-Disaster Remote Sensing Datasets

2021 ◽  
Vol 13 (5) ◽  
pp. 905
Author(s):  
Chuyi Wu ◽  
Feng Zhang ◽  
Junshi Xia ◽  
Yichen Xu ◽  
Guoqing Li ◽  
...  
Keyword(s):  
Damage Assessment ◽  
Large Scale ◽  
Binary Classification ◽  
Open Data ◽  
Building Damage ◽  
Attention Mechanism ◽  
Large Scale Dataset ◽  
Data Program ◽  
The Impact ◽  
Post Disaster

The building damage status is vital to plan rescue and reconstruction after a disaster and is also hard to detect and judge its level. Most existing studies focus on binary classification, and the attention of the model is distracted. In this study, we proposed a Siamese neural network that can localize and classify damaged buildings at one time. The main parts of this network are a variety of attention U-Nets using different backbones. The attention mechanism enables the network to pay more attention to the effective features and channels, so as to reduce the impact of useless features. We train them using the xBD dataset, which is a large-scale dataset for the advancement of building damage assessment, and compare their result balanced F (F1) scores. The score demonstrates that the performance of SEresNeXt with an attention mechanism gives the best performance, with the F1 score reaching 0.787. To improve the accuracy, we fused the results and got the best overall F1 score of 0.792. To verify the transferability and robustness of the model, we selected the dataset on the Maxar Open Data Program of two recent disasters to investigate the performance. By visual comparison, the results show that our model is robust and transferable.

scholarly journals Planning prompts to promote uptake of HIV services among men: a randomised trial in rural Uganda

2020 ◽  
Vol 5 (11) ◽  
pp. e003390
Author(s):  
Nolan M Kavanagh ◽  
Elisabeth M Schaffer ◽  
Alex Ndyabakira ◽  
Kara Marson ◽  
Diane V Havlir ◽  
...  
Keyword(s):  
Hiv Testing ◽  
Community Health ◽  
Control Group ◽  
Health Campaign ◽  
Percentage Point Increase ◽  
Percentage Points ◽  
Point Increase ◽  
Cost Planning ◽  
Testing Uptake ◽  
The Impact

IntroductionInterventions informed by behavioural economics, such as planning prompts, have the potential to increase HIV testing at minimal or no cost. Planning prompts have not been previously evaluated for HIV testing uptake. We conducted a randomised clinical trial to evaluate the effectiveness of low-cost planning prompts to promote HIV testing among men.MethodsWe randomised adult men in rural Ugandan parishes to receive a calendar planning prompt that gave them the opportunity to make a plan to get tested for HIV at health campaigns held in their communities. Participants received either a calendar showing the dates when the community health campaign would be held (control group) or a calendar showing the dates and prompting them to select a date and time when they planned to attend (planning prompt group). Participants were not required to select a date and time or to share their selection with study staff. The primary outcome was HIV testing uptake at the community health campaign.ResultsAmong 2362 participants, 1796 (76%) participants tested for HIV. Men who received a planning prompt were 2.2 percentage points more likely to test than the control group, although the difference was not statistically significant (77.1% vs 74.9%; 95% CI –1.2 to 5.7 percentage points, p=0.20). The planning prompt was more effective among men enrolled ≤40 days before the campaigns (3.6 percentage-point increase in testing; 95% CI –2.9 to 10.1, p=0.27) than among men enrolled >40 days before the campaigns (1.8 percentage-point increase; 95% CI –2.3 to 5.8, p=0.39), although the effects within the subgroups were not significant.ConclusionThese findings suggest that planning prompts may be an effective behavioural intervention to promote HIV testing at minimal or no cost. Large-scale studies should further assess the impact and cost-effectiveness of such interventions.

scholarly journals When rebuilding no longer means recovery: the stress of staying put after Hurricane Sandy

2021 ◽  
Vol 165 (3-4) ◽  
Author(s):  
Liz Koslov ◽  
Alexis Merdjanoff ◽  
Elana Sulakshana ◽  
Eric Klinenberg
Keyword(s):  
Climate Change ◽  
Mental Health ◽  
Health Outcomes ◽  
Social Economic ◽  
Hurricane Sandy ◽  
Flood Insurance ◽  
Health Consequences ◽  
The Usa ◽  
Policy Shifts ◽  
Post Disaster

AbstractAfter a disaster, it is common to equate repopulation and rebuilding with recovery. Numerous studies link post-disaster relocation to adverse social, economic, and health outcomes. However, there is a need to reconsider these relationships in light of accelerating climate change and associated social and policy shifts in the USA, including the rising cost of flood insurance, the challenge of obtaining aid to rebuild, and growing interest in “managed retreat” from places at greatest risk. This article presents data from a survey of individuals who opted either to rebuild in place or relocate with the help of a voluntary home buyout after Hurricane Sandy. Findings show those who lived in buyout-eligible areas and relocated were significantly less likely to report worsened stress than those who rebuilt in place. This suggests access to a government-supported voluntary relocation option may, under certain circumstances, lessen the negative mental health consequences associated with disaster-related housing damage.

scholarly journals Return Migration after Natural Disasters

2017 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
Mikiyasu Nakayama ◽  
Nicholas Nicholas Bryner ◽  
Satoru Mimura
Keyword(s):  
United States ◽  
Natural Disasters ◽  
Hurricane Katrina ◽  
Case Studies ◽  
Return Migration ◽  
The United States ◽  
Hurricane Sandy ◽  
Indian Ocean Tsunami ◽  
Special Issue ◽  
Post Disaster

This special issue features policy priorities, public perceptions, and policy options for addressing post-disaster return migration in the United States, Japan, and a couple of Asian countries. It includes a series of case studies in these countries, which are based on a sustained dialogue among scholars and policymakers about whether and how to incentivize the return of displaced persons, considering social, economic, and environmental concerns. The research team, composed of researchers from Indonesia, Japan, Sri Lanka, and the United States, undertook a collaborative and interdisciplinary research process to improve understanding about how to respond to the needs of those displaced by natural disasters and to develop policy approaches for addressing post-disaster return. The research focused on the following three key issues: objectives of return migration (whether to return, in what configuration, etc.), priorities and perceptions that influence evacuees’ decision-making regarding return, and policies and practices that are used to pursue return objectives. This special issue includes ten articles on the following disaster cases: the Great East Japan Earthquake in 2011, Hurricane Katrina in 2005 and Hurricane Sandy in 2012, the Great Indian Ocean Tsunami in 2004, and the Great Sumatra Island Earthquake in 2009. Important lessons for the future were secured out of these case studies, covering the entire phase of return, namely planning, implementation, and monitoring.

scholarly journals Housing Transitions and Recovery of Older Adults Following Hurricane Sandy

2018 ◽  
Vol 74 (6) ◽  
pp. 1041-1052 ◽  
Author(s):  
Alexis A Merdjanoff ◽  
Rachael Piltch-Loeb ◽  
Sarah Friedman ◽  
David M Abramson
Keyword(s):  
Older Adults ◽  
Age Groups ◽  
Family Health ◽  
Hurricane Sandy ◽  
Younger Adults ◽  
Younger Age ◽  
Observational Cohort ◽  
Emergency Housing ◽  
Young Old ◽  
Post Disaster

Abstract Objectives This study explores the effects of social and environmental disruption on emergency housing transitions among older adults following Hurricane Sandy. It is based upon the Sandy Child and Family Health (S-CAFH) Study, an observational cohort of 1,000 randomly sampled New Jersey residents living in the nine counties most affected by Sandy. Methods This analysis examines the post-Sandy housing transitions and recovery of the young-old (55–64), mid-old (65–74), and old-old (75+) compared with younger adults (19–54). We consider length of displacement, number of places stayed after Sandy, the housing host (i.e., family only, friends only, or multi-host), and self-reported recovery. Results Among all age groups, the old-old (75+) reported the highest rates of housing damage and were more likely to stay in one place besides their home, as well as stay with family rather than by themselves after the storm. Despite this disruption, the old-old were most likely to have recovered from Hurricane Sandy. Discussion Findings suggest that the old-old were more resilient to Hurricane Sandy than younger age groups. Understanding the unique post-disaster housing needs of older adults can help identify critical points of intervention for their post-disaster recovery.

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