Notes

Depoliticising catastrophe response inside a politically condensed circumstance: the situation from the 2016-2019 exceedingly dry periods inside Zimbabwe.
0%, P = 0.02).

During the COVID-19 pandemic, patients with ocular trauma were more likely to have injuries sustained at home and have additional barriers to care. These changes underscore a need for targeted interventions to optimize emergent eye care during a pandemic.
During the COVID-19 pandemic, patients with ocular trauma were more likely to have injuries sustained at home and have additional barriers to care. These changes underscore a need for targeted interventions to optimize emergent eye care during a pandemic.
Coronavirus disease 2019, caused by novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is highly infectious; however, the different routes of transmission are not well understood. Transmission through tissue transplantation is possible and must be considered. This review will evaluate the current literature regarding routes of transmission, the likelihood of transmission through ocular tissue transplantation, and the guidelines in place to mitigate this risk.

Although respiratory droplets have been the primary route of SARS-CoV-2 transmission, there is evidence that transmission through blood donation and organ or tissue transplantation is possible. This includes corneal transplantation, as SARS-CoV-2 has been detected in conjunctival swabs of infected patients, and the ocular surface may play an important role in viral entry. Several tissue transplantation organizations have guidelines in place regarding the screening of donors and tissue procurement procedures, including clinical and/or PCR screening of donors. The Eye Bank Association of America (EBAA) is currently not recommending asymptomatic PCR screening. However, their antiseptic protocols may play an important role in viral inactivation.

Based on the current literature and guidelines, the risk of SARS-CoV-2 transmission through corneal transplantation is likely low. However, tissue screening guidelines need to be re-evaluated regularly as knowledge regarding the SARS-CoV-2 virus evolves.
Based on the current literature and guidelines, the risk of SARS-CoV-2 transmission through corneal transplantation is likely low. However, tissue screening guidelines need to be re-evaluated regularly as knowledge regarding the SARS-CoV-2 virus evolves.
To highlight the lessons learned from the Ebola outbreak that may inform our approach to the COVID-19 pandemic, particularly related to the widespread disruption of healthcare, ophthalmic disease manifestations, and vision health systems strengthening for future outbreaks.

Coronavirus disease 2019 (COVID-19), first detected in China in December 2019, has become a worldwide health emergency, with significant disruption of all aspects of society, including travel, business, and medical care. Although this pandemic has had unprecedented effects on healthcare delivery in the United States, experiences from recent Ebola virus disease (EVD) outbreaks in Africa provide insight and inform our approach to COVID-19 and outbreak preparedness. Like COVID-19, the rapid emergence of Ebola required new clinical and surgical approaches to understand its associated spectrum of ophthalmic complications and the potential for Ebola viral persistence within the eye and in tear film. Recent reports of ophthalmic findings assoct during this pandemic, providing additional measures of safety while resuming ophthalmic care for all patients. Vision health systems preparedness measures developed during recent EVD outbreaks and the current pandemic provide models for ophthalmic clinical practice, research, and education, as we continue to address COVID-19 and future emerging infectious disease threats.
To compile and report the ocular manifestations of coronavirus disease 2019 (COVID-19) infection and summarize the ocular side effects of investigational treatments of this disease.

Conjunctivitis is by far the most common ocular manifestation of COVID-19 with viral particles being isolated from tears/secretions of infected individuals. Multiple therapeutic options are being explored across a variety of medication classes with diverse ocular side effects.

Eye care professionals must exercise caution, as conjunctivitis may be the presenting or sole finding of an active COVID-19 infection. While no currently studied therapeutic agents have been found to reliably treat COVID-19, early vaccination trials are progressing and show promise. ESI-09 solubility dmso A video abstract is available for a more detailed summary. VIDEO ABSTRACT http//links.lww.com/COOP/A36.
Eye care professionals must exercise caution, as conjunctivitis may be the presenting or sole finding of an active COVID-19 infection. While no currently studied therapeutic agents have been found to reliably treat COVID-19, early vaccination trials are progressing and show promise. A video abstract is available for a more detailed summary. VIDEO ABSTRACT http//links.lww.com/COOP/A36.
As artificial intelligence continues to develop new applications in ophthalmic image recognition, we provide here an introduction for ophthalmologists and a primer on the mechanisms of deep learning systems.

Deep learning has lent itself to the automated interpretation of various retinal imaging modalities, including fundus photography and optical coherence tomography. Convolutional neural networks (CNN) represent the primary class of deep neural networks applied to these image analyses. These have been configured to aid in the detection of diabetes retinopathy, AMD, retinal detachment, glaucoma, and ROP, among other ocular disorders. Predictive models for retinal disease prognosis and treatment are also being validated.

Deep learning systems have begun to demonstrate a reliable level of diagnostic accuracy equal or better to human graders for narrow image recognition tasks. However, challenges regarding the use of deep learning systems in ophthalmology remain. These include trust of unsupervised learning systems and the limited ability to recognize broad ranges of disorders.
Deep learning systems have begun to demonstrate a reliable level of diagnostic accuracy equal or better to human graders for narrow image recognition tasks. However, challenges regarding the use of deep learning systems in ophthalmology remain. These include trust of unsupervised learning systems and the limited ability to recognize broad ranges of disorders.
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