COVID-19 has spread globally since its discovery in Hubei province, China in December 2019. A combination of computed tomography imaging, whole genome sequencing, and electron microscopy were initially used to screen and identify SARS-CoV-2, the viral etiology of COVID-19. The aim of this review article is to inform the audience of diagnostic and surveillance technologies for SARS-CoV-2 and their performance characteristics. We describe point-of-care diagnostics that are on the horizon and encourage academics to advance their technologies beyond conception. Developing plug-and-play diagnostics to manage the SARS-CoV-2 outbreak would be useful in preventing future epidemics.
The ability to rapidly diagnose, track, and disseminate information for SARS-CoV-2 is critical to minimize its spread. Here, we engineered a portable smartphone-based quantum barcode serological assay device for real-time surveillance of patients infected with SARS-CoV-2. Our device achieved a clinical sensitivity of 90% and specificity of 100% for SARS-CoV-2, as compared to 34% and 100%, respectively, for lateral flow assays in a head-to-head comparison. The lateral flow assay misdiagnosed ∼2 out of 3 SARS-CoV-2 positive patients. Our quantum dot barcode device has ∼3 times greater clinical sensitivity because it is ∼140 times more analytically sensitive than lateral flow assays. Our device can diagnose SARS-CoV-2 at different sampling dates and infectious severity. We developed a databasing app to provide instantaneous results to inform patients, physicians, and public health agencies. This assay and device enable real-time surveillance of SARS-CoV-2 seroprevalence and potential immunity.
Eastern equine encephalitis (EEE) virus is a highly pathogenic mosquito-borne zoonosis that is responsible for outbreaks of severe disease in humans and equines, resulting in high mortality or severe neurological impairment in most survivors. In the northeastern United States, EEE virus is maintained in an enzootic cycle involving the ornithophilic mosquito, Culiseta melanura (Coquillett) and passerine birds in freshwater swamp habitats. To evaluate the role of Cs. melanura and Culiseta morsitans (Theobald) in recent episodes of EEE virus activity in Massachusetts, we collected blood-fed mosquitoes between June, 2007, and October, 2008, from virus foci in 6 counties, and identified the source of blood meals by PCR amplification of mitochondrial cytochrome b gene and sequencing. Analysis of 529 Cs. melanura and 25 Cs. morsitans revealed that nearly 99% and 96% of mosquitoes, respectively, acquired blood meals solely from avian hosts. American Robin, Turdus migratorius Linnaeus was identified as the most common vertebrate host for Cs. melanura (21.7%, n=115), followed by Tufted Titmouse, Baeolophus bicolor (L.) (8.7%, n=46), Black-capped Chickadee, Poecile atricapillus (L.) (8.5%, n=45), Scarlet Tanager, Piranga olivacea (Gmelin) (6.8%, n=36), Field Sparrow, Spizella pusilla (Wilson) (6.2%, n=33), Northern Cardinal, Cardinalis cardinalis (L.) (5.7%, n=30), and other mostly Passeriformes birds. Mammalian-derived blood meals were identified as white-tailed deer, Odocoileus virginianus Zimmermann, domestic cow, Bos taurus L., and human, Homo sapiens L. There were 4 isolations of EEE virus, West Nile virus, and Highland J virus from Cs. melanura. Our results in conjunction with other lines of evidence, including reservoir competency, prevalence of antibody, and infection in nature, suggest that the American Robin, Tufted Titmouse, Black-capped Chickadee, and a few other passerine birds may play key roles in supporting EEE virus transmission in Massachusetts. Infrequent blood feeding of Cs. melanura on mammalian hosts, including humans, also indicates that this mosquito may occasionally contribute to epidemic/epizootic transmission of EEE virus in this region.
Specific ranges of dissolved oxygen (DO) concentrations must be maintained in a waterbody for it to be hospitable for aquatic animals. DO sensor designs can employ selectively permeable membranes to isolate DO from untargeted compounds or organisms in waterbodies. Hence, the DO concentration can be monitored and the health of the water can be evaluated over time. However, the presence of bacteria in natural waterbodies can lead to the formation of biofilms that can block pores and prevent analyte from permeating the membrane, resulting in inaccurate readings. In this work, we demonstrate the implementation of a fluorosilane-based omniphobic lubricant-infused (OLI) coating on a selectively permeable membrane and investigate the rate of biofilm formation for a commercially available DO sensor. Coated and unmodified membranes were incubated in an environment undergoing accelerated bacterial growth, and the change in sensitivity was evaluated after 40, 100, 250, and 500 h. Our findings show that the OLI membranes attenuate biofouling by 70% and maintain sensitivity after 3 weeks of incubation, further demonstrating that oxygen transfer through the OLI coating is achievable. Meanwhile, unmodified membranes exhibit significant biofouling that results in a 3.35 higher rate of decay in oxygen measurement sensitivity and an over 70% decrease in static contact angle. These results show that the OLI coating can be applied on commercially available membranes to prevent biofouling. Therefore, OLI coatings are a suitable candidate to suppress biofilm formation in the widespread use of selectively permeable membranes for environmental, medical, and fluid separation applications.
Objective: Over the 2018-2019 flu season we conducted a randomized controlled trial examining the efficacy of a Twitter campaign on vaccination rates. Concurrently we investigated potential interactions between digital social network structure and vaccination status. Participants: Undergratuates at a large midwestern public university were randomly assigned to an intervention (n = 353) or control (n = 349) group. Methods: Vaccination data were collected via monthly surveys. Participant Twitter data were collected through the public-facing Twitter API. Intervention impact was assessed with logistic regression. Standard network science tools examined vaccination coverage over online social networks. Results: The campaign had no effect on vaccination outcome. Receiving a flu shot the prior year had a positive impact on participant vaccination. Evidence of an interaction between digital social network structure and vaccination status was detected. Conclusions: Social media campaigns may not be sufficient for increasing vaccination rates. There may be potential for social media campaigns that leverage network structure.
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