Mass Testing With Contact Tracing Compared to Test and Trace for the Effective Suppression of COVID-19 in the United Kingdom: Systematic Review

Early COVID-19 Pandemic Preparedness: Informing Public Health Interventions and Hospital Capacity Planning Through Participatory Hybrid Simulation Modeling

We engaged with health sector stakeholders and public health professionals within the health system through a participatory modeling approach to support policy-making in the early COVID-19 pandemic in Saskatchewan, Canada. The objective was to use simulation modeling to guide the implementation of public health measures and short-term hospital capacity planning to mitigate the disease burden from March to June 2020. We developed a hybrid simulation model combining System Dynamics (SD), discrete-event simulation (DES), and agent-based modeling (ABM). SD models the population-level transmission of COVID-19, ABM simulates individual-level disease progression and contact tracing intervention, and DES captures COVID-19-related hospital patient flow. We examined the impact of mixed mitigation strategies-physical distancing, testing, conventional and digital contact tracing-on COVID-19 transmission and hospital capacity for a worst-case scenario. Modeling results showed that enhanced contact tracing with mass testing in the early pandemic could significantly reduce transmission, mortality, and the peak census of hospital beds and intensive care beds. Using a participatory modeling approach, we not only directly informed policy-making on contact tracing interventions and hospital surge capacity planning for COVID-19 but also helped validate the effectiveness of the interventions adopted by the provincial government. We conclude with a discussion on lessons learned and the novelty of our hybrid approach.

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

BACKGROUND

Since September 2020, the National Health Service (NHS) COVID-19 contact-tracing app has been used to mitigate the spread of COVID-19 in the United Kingdom. Since its launch, this app has been a part of the discussion regarding the perceived social agency of decision-making algorithms. On the social media website Twitter, a plethora of views about the app have been found but only analyzed for sentiment and topic trajectories thus far, leaving the perceived social agency of the app underexplored.

OBJECTIVE

We aimed to examine the discussion of social agency in social media public discourse regarding algorithm-operated decisions, particularly when the artificial intelligence agency responsible for specific information systems is not openly disclosed in an example such as the COVID-19 contact-tracing app. To do this, we analyzed the presentation of the NHS COVID-19 App on Twitter, focusing on the portrayal of social agency and the impact of its deployment on society. We also aimed to discover what the presentation of social agents communicates about the perceived responsibility of the app.

METHODS

Using corpus linguistics and critical discourse analysis, underpinned by social actor representation, we used the link between grammatical and social agency and analyzed a corpus of 118,316 tweets from September 2020 to July 2021 to see whether the app was portrayed as a social actor.

RESULTS

We found that active presentations of the app-seen mainly through personalization and agency metaphor-dominated the discourse. The app was presented as a social actor in 96% of the cases considered and grew in proportion to passive presentations over time. These active presentations showed the app to be a social actor in 5 main ways: informing, instructing, providing permission, disrupting, and functioning. We found a small number of occasions on which the app was presented passively through backgrounding and exclusion.

CONCLUSIONS

Twitter users presented the NHS COVID-19 App as an active social actor with a clear sense of social agency. The study also revealed that Twitter users perceived the app as responsible for their welfare, particularly when it provided instructions or permission, and this perception remained consistent throughout the discourse, particularly during significant events. Overall, this study contributes to understanding how social agency is discussed in social media discourse related to algorithmic-operated decisions This research offers valuable insights into public perceptions of decision-making digital contact-tracing health care technologies and their perceptions on the web, which, even in a postpandemic world, may shed light on how the public might respond to forthcoming interventions.

Impacts of public health and social measures on COVID-19 in Europe: a review and modified Delphi technique

Introduction

The emergence of the COVID-19 pandemic in early 2020 led countries to implement a set of public health and social measures (PHSMs) attempting to contain the spread of the SARS-CoV-2 virus. This study aims to review the existing literature regarding key results of the PHSMs that were implemented, and to identify the PHSMs considered to have most impacted the epidemiological curve of COVID-19 over the last years during different stages of the pandemic.

Methods

The PHSM under study were selected from the Oxford COVID-19 Government Response Tracker (OxCGRT), supplemented by topics presented during the Rapid Exchange Forum (REF) meetings in the scope of the Population Health Information Research Infrastructure (PHIRI) project (H2020). The evidence- based review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to identify which reviews have already been published about each PHSMs and their results. In addition, two modified Delphi panel surveys were conducted among subject matter experts from 30 European countries to uphold the results found.

Results

There were 3,212 studies retrieved from PubMed, 162 full texts assessed for eligibility and 35 included in this PHSMs summary. The measures with clearest evidence on their positive impact from the evidence-based review include social distancing, hygiene measures, mask measures and testing policies. From the modified Delphi panel, the PHSMs considered most significant in the four periods analyzed were case isolation at home, face coverings, testing policy, and social distancing, respectively.

Discussion

The evidence found has significant implications for both researchers and policymakers. The study of PHSMs' impact on COVID-19 illustrates lessons learned for future pan- and epidemics, serving as a contribution to the health systems resilience discussion. These lessons, drawn from both the available scientific evidence and the perspectives of relevant subject matter experts, should also be considered in educational and preparedness programs and activities in the public health space.

Critical reflections on three popular computational linguistic approaches to examine Twitter discourses

Although computational linguistic methods-such as topic modelling, sentiment analysis and emotion detection-can provide social media researchers with insights into online public discourses, it is not inherent as to how these methods should be used, with a lack of transparent instructions on how to apply them in a critical way. There is a growing body of work focusing on the strengths and shortcomings of these methods. Through applying best practices for using these methods within the literature, we focus on setting expectations, presenting trajectories, examining with context and critically reflecting on the diachronic Twitter discourse of two case studies: the longitudinal discourse of the NHS Covid-19 digital contact-tracing app and the snapshot discourse of the Ofqual A Level grade calculation algorithm, both related to the UK. We identified difficulties in interpretation and potential application in all three of the approaches. Other shortcomings, such the detection of negation and sarcasm, were also found. We discuss the need for further transparency of these methods for diachronic social media researchers, including the potential for combining these approaches with qualitative ones-such as corpus linguistics and critical discourse analysis-in a more formal framework.

A Metasynthesis and Meta-analysis of the Impact and Diagnostic Safety of COVID-19 Symptom Agnostic Rapid Testing in Low- and Middle-Income Countries: Protocol for a Systematic Review

BACKGROUND

Amid all public health measures to contain COVID-19, the most challenging has been how to break the transmission chain. This has been even more challenging in low- and middle-income countries (LMICs). A public health emergency warrants a public health perspective, which comes down to prevention. Rapid mass testing has been advocated throughout the pandemic as a way to promptly deal with asymptomatic infections, but its usefulness in LMICs is yet to be fully understood.

OBJECTIVE

The study objectives of this paper are to (1) investigate the impact of the different rapid mass testing options for SARS-CoV-2 that have been delivered at point of care in LMICs and (2) evaluate the diagnostic safety (accuracy) of rapid mass testing for SARS-CoV-2 in LMICs.

METHODS

This review will systematically search records in PubMed, EBSCOhost, Cochrane library, Global Index Medicus COVID-19 Register, and Scopus. Records will be managed using Mendeley reference manager and SWIFT-Review. Risk of bias for randomized controlled trials will be assessed using the RoB 2 assessment tool, while nonrandomized interventions will be assessed using the tool developed by the Evidence Project. A narrative approach will be used to synthesize data under the first objective, and either a meta-analysis or synthesis without meta-analysis for the second objective. Tables, figures, and textual descriptions will be used to present findings. The overall body of evidence for the first objective will be assessed using the Grading of Recommendations Assessment, Development, and Evaluation-Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) approach, and for the second objective using GRADE.

RESULTS

The screening of records has been finalized. We hope to finalize the synthesis by the end of February 2023 and to prepare the manuscript for publication by April 2023. The study will be reported in accordance with standard guidelines for the reporting of systematic reviews. Review results will be disseminated through conferences and their peer-reviewed publication in a relevant journal.

CONCLUSIONS

This review highlights the role of a preventive approach in infection control using rapid mass testing. It also flags the overriding need to involve users and providers in the evaluation of such tests in the settings for which they are intended. This will be the first review to the best of our knowledge to generate both qualitative and quantitative evidence regarding rapid mass testing specific to LMICs.

TRIAL REGISTRATION

PROSPERO CRD42022283776; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=283776.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/41132.

Waiting Time and Patient Satisfaction in a Subspecialty Eye Hospital Using a Mobile Data Collection Kit: Pre-Post Quality Improvement Intervention

BACKGROUND

Waiting time can considerably increase the cost to both the clinic and the patient and be a major predictor of the satisfaction of eye care users. Efficient management of waiting time remains as a challenge in hospitals. Waiting time management will become even more crucial in the postpandemic era. A key consideration when improving waiting time is the involvement of eye care users. This study aimed at improving patient waiting time and satisfaction through the use of Plan-Do-Study-Act (PDSA) quality improvement cycles.

OBJECTIVE

The objectives of this study were to determine the waiting time and patient satisfaction, measure the association between waiting time and patient satisfaction, and determine the effectiveness of the PDSA model in improving waiting time and satisfaction.

METHODS

This was a pre-post quality improvement study among patients aged 19 to 80 years, who are consulting with the Magrabi International Council of Ophthalmology Cameroon Eye Institute. We used PDSA cycles to conduct improvement audits of waiting time and satisfaction over 6 weeks. A data collection app known as Open Data Kit (Get ODK Inc) was used for real-time tracking of waiting, service, and idling times at each service point. Participants were also asked whether they were satisfied with the waiting time at the point of exit. Data from 51% (25/49) preintervention participants and 49% (24/49) postintervention participants were analyzed using Stata 14 at .05 significance level. An unpaired 2-tailed t test was used to assess the statistical significance of the observed differences in times before and after the intervention. Logistic regression was used to examine the association between satisfaction and waiting time.

RESULTS

In total, 49 participants were recruited with mean age of 49 (SD 15.7) years. The preintervention mean waiting, service, and idling times were 450 (SD 96.6), 112 (SD 47), and 338 (SD 98.1) minutes, respectively. There was no significant association between patient waiting time and satisfaction (odds ratio 1, 95% CI 0.99-1; P=.37; χ23=0.4). The use of PDSA led to 15% (66 minutes/450 minutes) improvement in waiting time (t47=2; P=.05) and nonsignificant increase in patient satisfaction from 32% (8/25) to 33% (8/24; z=0.1; P=.92).

CONCLUSIONS

Use of PDSA led to a borderline statistically significant reduction of 66 minutes in waiting time over 6 weeks and an insignificant improvement in satisfaction, suggesting that quality improvement efforts at the clinic have to be made over a considerable period to be able to produce significant changes. The study provides a good basis for standardizing the cycle (consultation) time at the clinic. We recommend shortening the patient pathway and implementing other measures including a phasic appointment system, automated patient time monitoring, robust ticketing, patient pathway supervision, standard triaging, task shifting, physician consultation planning, patient education, and additional registration staff.

Tracing app technology: an ethical review in the COVID-19 era and directions for post-COVID-19

We conducted a systematic literature review on the ethical considerations of the use of contact tracing app technology, which was extensively implemented during the COVID-19 pandemic. The rapid and extensive use of this technology during the COVID-19 pandemic, while benefiting the public well-being by providing information about people's mobility and movements to control the spread of the virus, raised several ethical concerns for the post-COVID-19 era. To investigate these concerns for the post-pandemic situation and provide direction for future events, we analyzed the current ethical frameworks, research, and case studies about the ethical usage of tracing app technology. The results suggest there are seven essential ethical considerations-privacy, security, acceptability, government surveillance, transparency, justice, and voluntariness-in the ethical use of contact tracing technology. In this paper, we explain and discuss these considerations and how they are needed for the ethical usage of this technology. The findings also highlight the importance of developing integrated guidelines and frameworks for implementation of such technology in the post- COVID-19 world.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10676-022-09659-6.

Progression of LAMP as a Result of the COVID-19 Pandemic: Is PCR Finally Rivaled?

Reflecting on the past three years and the coronavirus disease 19 (COVID-19) pandemic, varying global tactics offer insights into the most effective public-health responses. In the US, specifically, rapid and widespread testing was quickly prioritized to lower restrictions sooner. Essentially, only two types of COVID-19 diagnostic tests were publicly employed during the peak pandemic: the rapid antigen test and reverse transcription polymerase chain reaction (RT-PCR). However, neither test ideally suited the situation, as rapid antigen tests are far too inaccurate, and RT-PCR tests require skilled personnel and sophisticated equipment, leading to long wait times. Loop-mediated isothermal amplification (LAMP) is another exceptionally accurate nucleic acid amplification test (NAAT) that offers far quicker time to results. However, RT-LAMP COVID-19 tests have not been embraced as extensively as rapid antigen tests or RT-PCR. This review will investigate the performance of current RT-LAMP-based COVID-19 tests and summarize the reasons behind the hesitancy to embrace RT-LAMP instead of RT-PCR. We will also look at other LAMP platforms to explore possible improvements in the accuracy and portability of LAMP, which could be applied to COVID-19 diagnostics and future public-health outbreaks.

Assessment of COVID-19 Molecular Testing Capacity in Jordan: A Cross-Sectional Study at the Country Level

Coronavirus disease 2019 (COVID-19) pandemic control measures rely on the accurate and timely diagnosis of infected individuals. Real-time polymerase chain reaction (qPCR) remains the gold-standard method for laboratory diagnosis of the disease. Delayed diagnosis due to challenges that face laboratories performing COVID-19 testing can hinder public health control measures. Such challenges may be related to shortages in staff, equipment or materials, improper inventory management, flawed workflow, or long turnaround time (TAT). The aim of the current study was to assess the overall COVID-19 molecular testing capacity in Jordan as of April 2021. In addition, the study’s objectives included the identification of potential defects that could comprise the utility of the COVID-19 molecular testing capacity in the country. All laboratories certified by the Ministry of Health (MoH) in Jordan to conduct molecular testing for SARS-CoV-2 were invited to participate in this study. Data were obtained from the participating laboratories (those which agreed to participate) by either telephone interviews or a self-reported written questionnaire with items assessing the key aspects of COVID-19 molecular testing. The full molecular testing capacity in each laboratory was self-reported considering 24 working hours. The total number of participating laboratories was 51 out of 77 (66.2%), with the majority being affiliated with MoH (n = 17) and private laboratories (n = 20). The total molecular COVID-19 testing capacity among the participating laboratories was estimated at 574,441 tests per week, while the actual highest number of tests performed over a single week was 310,047 (54.0%, reported in March 2021). Laboratories affiliated with the MoH were operating at a level closer to their maximum capacity (87.2% of their estimated full capacity for COVID-19 testing) compared to private hospital laboratories (41.3%, p = 0.004), private laboratories (20.8%, p < 0.001), and academic/research laboratories (14.7%, p < 0.001, ANOVA). The national average daily COVID-19 molecular testing was 349.2 tests per 100,000 people in April 2021. The average TAT over the first week of April 2021 for COVID-19 testing was 932 min among the participating laboratories, with the longest TAT among MoH laboratories (mean: 1959 min) compared to private laboratories (mean: 333 min, p < 0.001). Molecular COVID-19 testing potential in Jordan has not been fully utilized, particularly for private laboratories and those belonging to academic/research centers. Supply-chain challenges and shortages in staff were identified as potential obstacles hindering the exploitation of full molecular testing capacity for COVID-19 in the country.

A message of the majority with scientific evidence encourages young people to show their prosocial nature in COVID-19 vaccination

The most promising way to prevent the explosive spread of COVID-19 infection is to achieve herd immunity through vaccination. It is therefore important to motivate those who are less willing to be vaccinated. To address this issue, we conducted an online survey of 6232 Japanese people to investigate age- and gender-dependent differences in attitudes towards COVID-19 vaccination and the underlying psychological processes. We asked participants to read one of nine different messages about COVID-19 vaccination and rate their willingness to be vaccinated. We also collected their 17 social personality trait scores and demographic information. We found that males 10-20 years old were least willing to be vaccinated. We also found that prosocial traits are the driving force for young people, but the motivation in older people also depends on risk aversion and self-interest. Furthermore, an analysis of 9 different messages demonstrated that for young people (particularly males), the message emphasizing the majority's intention to vaccinate and scientific evidence for the safety of the vaccination had the strongest positive effect on the willingness to be vaccinated, suggesting that the "majority + scientific evidence" message nudges young people to show their prosocial nature in action.

Epidemiological evaluation of mass testing in a small municipality in the Netherlands during the SARS-CoV-2 epidemic

During 6 weeks in February-March 2021, the Dutch municipal health service Utrecht studied the epidemiological effects on test incidence and the detection of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mass testing (MT). During MT, inhabitants of Bunschoten could repeatedly test regardless of symptoms and as often as desired at the close-by test facilities in the municipality. Data from the regular COVID-19 registration was used for analysis. In Bunschoten, MT caused a significant increase in test incidence and an immediate increase in the number of detected active infections, in contrast to a stabilisation in the rest of the province of Utrecht. Age distribution of test incidence shifted to the older population in Bunschoten during MT. During MT, there was a 6.8 percentage point increase in detected asymptomatic cases, a 0.4 percentage point increase in pre-symptomatic cases and a decrease of 0.5 days between onset of symptoms and test date. This study has shown that MT increases test incidence and helps to obtain a more complete view of the presence of SARS-CoV-2 in a community, which can be useful in specific situations with a defined target group or goal. However, the question remains open whether the use of MT is proportionate to the overall gain.

Systematic review of empirical studies comparing the effectiveness of non-pharmaceutical interventions against COVID-19

OBJECTIVES

To evaluate which non-pharmaceutical interventions (NPIs) have been more and less effective in controlling the COVID-19 pandemic.

METHODS

We performed a systematic review of published and unpublished empirical studies, either observational or interventional, analysing the comparative effectiveness of NPIs against the COVID-19 pandemic. We searched Embase/Medline and medRxiv to identify the relevant literature.

RESULTS

We identified 34 studies. During the first wave of the COVID-19 pandemic, school closing was the most effective NPI, followed by workplace closing, business and venue closing and public event bans. Public information campaigns and mask wearing requirements were also effective in controlling the pandemic while being less disruptive for the population than other NPIs. There was no evidence on the effectiveness of public transport closure, testing and contact tracing strategies and quarantining or isolation of individuals. Early implementation was associated with a higher effectiveness in reducing COVID-19 cases and deaths, while general stringency of the NPIs was not.

CONCLUSIONS

In this systematic review, we found that school closing, followed by workplace closing, business and venue closing and public event bans were the most effective NPIs in controlling the spread of COVID-19. An early response and a combination of specific social distancing measures are effective at reducing COVID-19 cases and deaths. Continuous monitoring of NPIs effectiveness is needed in order to adapt decision making.