Rapid Large-Scale COVID-19 Testing During Shortages

Immunochromatographic enhancement strategy for SARS-CoV-2 detection based on nanotechnology

The global outbreak of coronavirus disease 2019 (COVID-19) has been catastrophic to both human health and social development. Therefore, developing highly reliable and sensitive point-of-care testing (POCT) for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a priority. Among all available POCTs, the lateral flow immunoassay (LFIA, also known as immunochromatography) has proved to be effective due to its accuracy, portability, convenience, and speed. In areas with a scarcity of laboratory resources and medical personnel, the LFIA provides an affordable option for the diagnosis of COVID-19. This review offers a comprehensive overview of methods for improving the sensitivity of SARS-CoV-2 detection using immunochromatography based on nanotechnology, sorted according to the different detection targets (antigens, antibodies, and nucleic acids). It also looks into the performance and properties of the various sensitivity enhancement strategies, before delving into the remaining challenges in COVID-19 diagnosis through LFIA. Ultimately, it seeks to provide helpful guidance in selecting an appropriate strategy for SARS-CoV-2 immunochromatographic detection based on nanotechnology.

Human viral nucleic acids concentrations in wastewater solids from Central and Coastal California USA

We measured concentrations of SARS-CoV-2, influenza A and B virus, respiratory syncytial virus (RSV), mpox virus, human metapneumovirus, norovirus GII, and pepper mild mottle virus nucleic acids in wastewater solids at twelve wastewater treatment plants in Central California, USA. Measurements were made daily for up to two years, depending on the wastewater treatment plant. Measurements were made using digital droplet (reverse-transcription-) polymerase chain reaction (RT-PCR) following best practices for making environmental molecular biology measurements. These data can be used to better understand disease occurrence in communities contributing to the wastewater.

An Elaboration on Sample Size Planning for Performing a One-Sample Sensitivity and Specificity Analysis by Basing on Calculations on a Specified 95% Confidence Interval Width

Sample size calculation based on a specified width of 95% confidence interval will offer researchers the freedom to set the level of accuracy of the statistics that they aim to achieve for a particular study. This paper provides a description of the general conceptual context for performing sensitivity and specificity analysis. Subsequently, sample size tables for sensitivity and specificity analysis based on a specified 95% confidence interval width is then provided. Such recommendations for sample size planning are provided based on two different scenarios: one for a diagnostic purpose and another for a screening purpose. Further discussion on all the other relevant considerations for the determination of a minimum sample size requirement and on how to draft the sample size statement for performing sensitivity and specificity analysis are also provided.

Utilizing student-led contact tracing initiative to alleviate COVID-19 disease burden in central Pennsylvania

PURPOSE

Contact tracing elicits probable contacts from COVID-19 cases. Our student-led contact tracing initiative promoted isolation of both confirmed and probable cases and quarantine of contacts to reduce disease in Central Pennsylvania.

METHODS

Close contacts of COVID-19 cases were contacted by tracers, advised to quarantine, and monitored for 14 days for symptoms. Symptomatic contacts were classified as probable cases and advised to isolate. Data was collected from March 24, 2020 to May 26, 2020. Poisson regression and linear regression were utilized to examine the relationships between case and number of contacts and proportion of symptomatic contacts.

RESULTS

Study sample comprised of 346 confirmed and 157 probable cases. Our results indicate a significant difference in percent of household contacts who became symptomatic between confirmed and probable cases (22% vs. 3%; adjusted P<.01). Similarly, probable cases had significantly fewer non-household contacts compared to confirmed cases (0.87 vs. 0.55; adjusted P<.01).

CONCLUSIONS

Timely notification of exposure to a COVID-19 positive individual by student contact tracers allowed for probable cases to quarantine early in the disease process. Our data suggests that early quarantine and/or isolation may have directly contributed to probable cases having fewer non-household contacts and a smaller proportion of symptomatic household-contacts compared to confirmed cases.

COVID-19 Transmission to Health Care Personnel During Tracheostomy Under a Multidisciplinary Safety Protocol

BACKGROUND

Tracheostomies are highly aerosolizing procedures yet are often indicated in patients with COVID-19 who require prolonged intubation. Robust investigations of the safety of tracheostomy protocols and provider adherence and evaluations are limited.

OBJECTIVES

To determine the rate of COVID-19 infection of health care personnel involved in COVID-19 tracheostomies under a multidisciplinary safety protocol and to investigate health care personnel's attitudes and suggested areas for improvement concerning the protocol.

METHODS

All health care personnel involved in tracheostomies in COVID-19-positive patients from April 9 through July 11, 2020, were sent a 22-item electronic survey.

RESULTS

Among 107 health care personnel (80.5%) who responded to the survey, 5 reported a positive COVID-19 test result (n = 2) or symptoms of COVID-19 (n = 3) within 21 days of the tracheostomy. Respondents reported 100% adherence to use of adequate personal protective equipment. Most (91%) were familiar with the tracheostomy protocol and felt safe (92%) while performing tracheostomy. Suggested improvements included creating dedicated tracheostomy teams and increasing provider choices surrounding personal protective equipment.

CONCLUSIONS

Multidisciplinary engagement in the development and implementation of a COVID-19 tracheostomy protocol is associated with acceptable safety for all members of the care team.

Evaluation of the artus® Prep&Amp UM RT-PCR for detection of SARS-CoV-2 from nasopharyngeal swabs without prior nucleic acid eluate extraction

Here we describe a retrospective clinical evaluation of the QIAGEN artus® SARS-CoV-2 Prep&Amp UM RT-PCR assay that detects SARS-CoV-2 RNA without the need for a nucleic acid eluate extraction procedure. Using Roche SARS-CoV-2 RT-PCR on the cobas® 8800 platform as a reference standard, a total of 225 confirmed SARS-CoV-2 positive and 320 negative nasopharyngeal swabs in viral transport media, were used to evaluate the artus® assay. Using the RT-PCR cycle threshold as a semi-quantitative marker of viral load, an assessment of over 370,000 SARS-CoV-2 RT-PCR positive results was used in the design of the reference positive specimen cohort. The viral load of all reference positive specimens used in the evaluation was a unique and accurate representation of the range and levels of SARS-CoV-2 positivity observed over a 13-month period of the COVID-19 pandemic. The artus® RT-PCR detects the presence of SARS-CoV-2 RNA, an internal control, and the human RNase P gene to ensure specimen quality. The diagnostic sensitivity of artus® was 92.89% with a specificity of 100%. To assess the analytical sensitivity, a limit of detection was performed using the 1^st WHO NIBSC SARS-CoV-2 international standard, recording a 95% LOD of 1.1 × 10³ IU/ml. The total invalid rate of specimens was 7.34% due to a lack of detectable RNase P (C_t >35). The artus® SARS-CoV-2 Prep&Amp UM RT-PCR assay is a new rapid RT-PCR assay, which may be considered to produce acceptable levels of diagnostic sensitivity and specificity whilst potentially halving the laboratory processing time.

Maximising the Use of Scarce qPCR Master Mixes

The COVID-19 pandemic resulted in a universal, immediate, and vast demand for comprehensive molecular diagnostic testing, especially real-time quantitative (qPCR)-based methods. This rapidly triggered a global shortage of testing capacity, equipment, and reagents. Even today, supply times for chemicals from date of order to delivery are often much longer than pre-pandemic. Furthermore, many companies have ratcheted up the price for minimum volumes of reaction master mixes essential for qPCR assays, causing additional problems for academic laboratories often operating on a shoestring. We have validated two strategies that stretch reagent supplies and, whilst particularly applicable in case of scarcity, can readily be incorporated into standard qPCR protocols, with appropriate validation. The first strategy demonstrates equivalent performance of a selection of “past expiry date” and newly purchased master mixes. This approach is valid for both standard and fast qPCR protocols. The second validates the use of these master mixes at less than 1x final concentration without loss of qPCR efficiency or sensitivity.

The US Coronavirus Disease 2019 (COVID-19) Surveillance Environment: An Ecological Analysis of the Relationship of Testing Adequacy in the Context of Vaccination

BACKGROUND

Coronavirus disease 2019 (COVID-19) testing is a critical component of public health surveillance and pandemic control, especially among the unvaccinated, as the nation resumes in-person activities. This study examined the relationships between COVID-19 testing rates, testing positivity rates, and vaccination coverage across US counties.

METHODS

Data from the Health and Human Services' Community Profile Report and 2016-2020 American Community Survey 5-Year Estimates were used. A total of 3114 US counties were analyzed from January through September 2021. Associations among the testing metrics and vaccination coverage were estimated using multiple linear regression models with fixed effects for states and adjusted for county demographics. COVID-19 testing rates (polymerase chain reaction [PCR] testing per 1000), testing positivity (percentage of all PCR tests that were positive), and vaccination coverage (percentage of county population that was fully vaccinated) were determined.

RESULTS

Nationally, median daily COVID-19 testing rates were highest in January and September (35.5 and 34.6 tests per capita, respectively) and lowest in July (13.2 tests per capita). Monthly testing positivity was between 0.03 and 0.12 percentage points lower for each percentage points of vaccination coverage, and monthly testing rates were between 0.08 and 0.22 tests per capita higher for each percentage point of vaccination coverage.

CONCLUSIONS

The quantity of COVID-19 testing was associated with vaccination coverage, implying counties having populations with relatively lower protection against the virus are conducting less testing than counties with relatively more protection. Monitoring testing practices in relation to vaccination coverage may be used to monitor the sufficiency of COVID-19 testing based on population susceptibility to the virus.

Clinical evaluation of single-swab sampling for rapid COVID-19 detection in outbreak settings in Dutch nursing homes

PURPOSE

To assess whether one swab can be used to perform both the antigen-detection rapid diagnostic test (Ag-RDT) and reverse transcriptase polymerase chain reaction (RT-PCR) for COVID-19 detection during an outbreak in the nursing home (NH) setting.

METHODS

The single-swab method (SSM), where the Ag-RDT is performed with the transport medium used for RT-PCR, was evaluated in three Dutch NHs and compared to the laboratory setting. We collected Ag-RDT and RT-PCR results, NH resident characteristics and symptomatology. In addition, two focus groups were held with the involved care professionals to gain insight into the feasibility of the SMM in the NH setting.

RESULTS

In the NH setting, the SSM had a sensitivity of 51% and a specificity of 89% compared to RT-PCR. These were lower than in the laboratory setting (69% and 100% respectively). Yet, when stratified for cycle threshold values, the sensitivity became comparable between the settings. Symptoms occurred more frequent in the Ag-RDT+ group than Ag-RDT- group. Resident characteristics did not differ between these groups. Based on the focus groups, the SSM was feasible to perform if certain requirements, such as availability of staff, equipment and proper training, were met. However, the rapid availability of the test results were perceived as a dilemma.

CONCLUSION

The advantages and disadvantages need to be considered before implementation of the SSM can be recommended in the NH setting. For the vulnerable NH residents, it is important to find the right balance between effective testing policy and the burden this imposes.

One-year surveillance of SARS-CoV-2 transmission of the ELISA cohort: A model for population-based monitoring of infection risk

With newly rising coronavirus disease 2019 (COVID-19) cases, important data gaps remain on (i) long-term dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates in fixed cohorts (ii) identification of risk factors, and (iii) establishment of effective surveillance strategies. By polymerase chain reaction and antibody testing of 1% of the local population and >90,000 app-based datasets, the present study surveilled a catchment area of 300,000 inhabitants from March 2020 to February 2021. Cohort (56% female; mean age, 45.6 years) retention was 75 to 98%. Increased risk for seropositivity was detected in several high-exposure groups, especially nurses. Unreported infections dropped from 92 to 29% during the study. "Contact to COVID-19-affected" was the strongest risk factor, whereas public transportation, having children in school, or tourism did not affect infection rates. With the first SARS-CoV-2 cohort study, we provide a transferable model for effective surveillance, enabling monitoring of reinfection rates and increased preparedness for future pandemics.

Scaling of SARS-CoV-2 RNA in Settled Solids from Multiple Wastewater Treatment Plants to Compare Incidence Rates of Laboratory-Confirmed COVID-19 in Their Sewersheds

Published and unpublished reports show that SARS-CoV-2 RNA in publicly owned treatment work (POTW) wastewater influent and solids is associated with new COVID-19 cases or incidence in associated sewersheds, but methods for comparing data collected from diverse POTWs to infer information about the relative incidence of laboratory-confirmed COVID-19 cases, and scaling to allow such comparisons, have not been previously established. Here, we show that SARS-CoV-2 N1 and N2 concentrations in solids normalized by concentrations of PMMoV RNA in solids can be used to compare incidence of laboratory confirmed new COVID-19 cases across POTWs. Using data collected at seven POTWs along the United States West Coast, Midwest, and East Coast serving ∼3% of the U.S. population (9 million people), we show that a 1 log change in N gene/PMMoV is associated with a 0.24 (range 0.19 to 0.29) log10 change in incidence of laboratory confirmed COVID-19. Scaling of N1 and N2 by PMMoV is consistent, conceptually, with a mass balance model relating SARS-CoV-2 RNA to the number of infected individuals shedding virus in their stool. This information should support the application of wastewater-based epidemiology to inform the response to the COVID-19 pandemic and potentially future viral pandemics.

COVID-19 Diagnostic Strategies. Part I: Nucleic Acid-Based Technologies

The novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused respiratory infection, resulting in more than two million deaths globally and hospitalizing thousands of people by March 2021. A considerable percentage of the SARS-CoV-2 positive patients are asymptomatic or pre-symptomatic carriers, facilitating the viral spread in the community by their social activities. Hence, it is critical to have access to commercialized diagnostic tests to detect the infection in the earliest stages, monitor the disease, and follow up the patients. Various technologies have been proposed to develop more promising assays and move toward the mass production of fast, reliable, cost-effective, and portable PoC diagnostic tests for COVID-19 detection. Not only COVID-19 but also many other pathogens will be able to spread and attach to human bodies in the future. These technologies enable the fast identification of high-risk individuals during future hazards to support the public in such outbreaks. This paper provides a comprehensive review of current technologies, the progress in the development of molecular diagnostic tests, and the potential strategies to facilitate innovative developments in unprecedented pandemics.

Self-reported symptoms in healthy young adults to predict potential coronavirus disease 2019

OBJECTIVE

To assess the utility of self-reported symptoms in identifying positive coronavirus disease 2019 (COVID-19) cases among predominantly healthy young adults in a military setting.

METHODS

A questionnaire regarding COVID-19 symptoms and exposure history was administered to all individuals contacting the Israeli Defence Forces Corona call-centre, before PCR testing. Surveyed symptoms included cough, fever, sore throat, rhinorrhoea, loss of taste or smell, chest pain and gastrointestinal symptoms. Factors were compared between positive and negative cases based on confirmatory test results, and positive likelihood ratios (LR) were calculated. Results were stratified by sex, body mass index, previous medical history and dates of questioning, and a multivariable analysis for association with positive test was conducted.

RESULTS

Of 24 362 respondents, 59.1% were men with a median age of 20.5 years (interquartile range 19.6-22.4 years). Significant positive LRs were associated with loss of taste or smell (LR 3.38, 95% CI 3.01-3.79), suspected exposure (LR 1.33, 95% CI 1.28-1.39) and fever (LR 1.26, 95% CI 1.17-1.36). Those factors were also associated with positive PCR result in a multivariable analysis (OR 3.51, 95% CI 3.04-4.06; OR 1.86, 95% CI 1.65-2.09; and OR 1.34, 95% CI 1.19-1.51, respectively). Reports of loss of taste or smell increased gradually over time and were significantly more frequent during the late period of the study (63/5231, 1.21%; 156/7941, 1.96%; and 1505/11 190, 13.45%: p < 0.001).

CONCLUSION

Loss of taste or smell, report of a suspicious exposure and fever (>37.5°C) were consistently associated with positive LRs for a positive SARS-CoV-2 PCR test result, in a population of predominantly young and healthy adults.

Machine learning is the key to diagnose COVID-19: a proof-of-concept study

The reverse transcription-polymerase chain reaction (RT-PCR) assay is the accepted standard for coronavirus disease 2019 (COVID-19) diagnosis. As any test, RT-PCR provides false negative results that can be rectified by clinicians by confronting clinical, biological and imaging data. The combination of RT-PCR and chest-CT could improve diagnosis performance, but this would requires considerable resources for its rapid use in all patients with suspected COVID-19. The potential contribution of machine learning in this situation has not been fully evaluated. The objective of this study was to develop and evaluate machine learning models using routine clinical and laboratory data to improve the performance of RT-PCR and chest-CT for COVID-19 diagnosis among post-emergency hospitalized patients. All adults admitted to the ED for suspected COVID-19, and then hospitalized at Rennes academic hospital, France, between March 20, 2020 and May 5, 2020 were included in the study. Three model types were created: logistic regression, random forest, and neural network. Each model was trained to diagnose COVID-19 using different sets of variables. Area under the receiving operator characteristics curve (AUC) was the primary outcome to evaluate model’s performances. 536 patients were included in the study: 106 in the COVID group, 430 in the NOT-COVID group. The AUC values of chest-CT and RT-PCR increased from 0.778 to 0.892 and from 0.852 to 0.930, respectively, with the contribution of machine learning. After generalization, machine learning models will allow increasing chest-CT and RT-PCR performances for COVID-19 diagnosis.

Clinical Evaluation of Roche SD Biosensor Rapid Antigen Test for SARS-CoV-2 in Municipal Health Service Testing Site, the Netherlands

Rapid detection of infection is essential for stopping the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The Roche SD Biosensor rapid antigen test for SARS-CoV-2 was evaluated in a nonhospitalized symptomatic population. We rapid-tested a sample onsite and compared results with those from reverse transcription PCR and virus culture. We analyzed date of onset and symptoms using data from a clinical questionnaire. Overall test sensitivity was 84.9% (95% CI 79.1–89.4) and specificity was 99.5% (95% CI 98.7–99.8). Sensitivity increased to 95.8% (95% CI 90.5–98.2) for persons who sought care within 7 days of symptom onset. Test band intensity and time to result correlated strongly with viral load; thus, strong positive results could be read before the recommended time. Approximately 98% of all viable specimens with cycle threshold <30 were detected. Rapid antigen tests can detect symptomatic SARS-CoV-2 infections in the early phase of disease, thereby identifying the most infectious persons.

Considerations for diagnostic COVID-19 tests

During the early phase of the coronavirus disease 2019 (COVID-19) pandemic, design, development, validation, verification and implementation of diagnostic tests were actively addressed by a large number of diagnostic test manufacturers. Hundreds of molecular tests and immunoassays were rapidly developed, albeit many still await clinical validation and formal approval. In this Review, we summarize the crucial role of diagnostic tests during the first global wave of COVID-19. We explore the technical and implementation problems encountered during this early phase in the pandemic, and try to define future directions for the progressive and better use of (syndromic) diagnostics during a possible resurgence of COVID-19 in future global waves or regional outbreaks. Continuous global improvement in diagnostic test preparedness is essential for more rapid detection of patients, possibly at the point of care, and for optimized prevention and treatment, in both industrialized countries and low-resource settings.

COVID-19 Impact on Diagnostic Innovations: Emerging Trends and Implications

Diagnostic testing remains the backbone of the coronavirus disease 2019 (COVID-19) response, supporting containment efforts to mitigate the outbreak. The severity of this crisis and increasing capacity issues associated with polymerase chain reaction (PCR)-based testing, accelerated the development of diagnostic solutions to meet demands for mass testing. The National Institute for Health Research (NIHR) Innovation Observatory is the national horizon scanning organization in England. Since March, the Innovation Observatory has applied advanced horizon scanning methodologies and tools to compile a diagnostic landscape, based upon data captured for molecular (MDx) and immunological (IDx) based diagnostics (commercialized/in development), for the diagnosis of SARS-CoV-2. In total we identified and tracked 1608 diagnostics, produced by 1045 developers across 54 countries. Our dataset shows the speed and scale in which diagnostics were produced and provides insights into key periods of development and shifts in trends between MDx and IDx solutions as the pandemic progressed. Stakeholders worldwide required timely and detailed intelligence to respond to major challenges, including testing capacity and regulatory issues. Our intelligence assisted UK stakeholders with assessing priorities and mitigation options throughout the pandemic. Here we present the global evolution of diagnostic innovations devised to meet changing needs, their regulation and trends across geographical regions, providing invaluable insights into the complexity of the COVID-19 phenomena.

Domiciliary Hospitalization through Wearable Biomonitoring Patches: Recent Advances, Technical Challenges, and the Relation to Covid-19

This article reviews recent advances and existing challenges for the application of wearable bioelectronics for patient monitoring and domiciliary hospitalization. More specifically, we focus on technical challenges and solutions for the implementation of wearable and conformal bioelectronics for long-term patient biomonitoring and discuss their application on the Internet of medical things (IoMT). We first discuss the general architecture of IoMT systems for domiciliary hospitalization and the three layers of the system, including the sensing, communication, and application layers. In regard to the sensing layer, we focus on current trends, recent advances, and challenges in the implementation of stretchable patches. This includes fabrication strategies and solutions for energy storage and energy harvesting, such as printed batteries and supercapacitors. As a case study, we discuss the application of IoMT for domiciliary hospitalization of COVID 19 patients. This can be used as a strategy to reduce the pressure on the healthcare system, as it allows continuous patient monitoring and reduced physical presence in the hospital, and at the same time enables the collection of large data for posterior analysis. Finally, based on the previous works in the field, we recommend a conceptual IoMT design for wearable monitoring of COVID 19 patients.