Comparison of molecular testing strategies for COVID-19 control: a mathematical modelling study

M. Heuvelink G, Wu C, Yang J, Ruktanonchai NW, Qader SH, Ruktanonchai CW, Cleary E, Yao Y, Liu J, Nnanatu CC, Wesolowski A, Cummings DA, Tatem AJ, Lai S. Optimizing the detection of emerging infections using mobility-based spatial sampling

Timely and precise detection of emerging infections is imperative for effective outbreak management and disease control. Human mobility significantly influences the spatial transmission dynamics of infectious diseases. Spatial sampling, integrating the spatial structure of the target, holds promise as an approach for testing allocation in detecting infections, and leveraging information on individuals' movement and contact behavior can enhance targeting precision. This study introduces a spatial sampling framework informed by spatiotemporal analysis of human mobility data, aiming to optimize the allocation of testing resources for detecting emerging infections. Mobility patterns, derived from clustering point-of-interest and travel data, are integrated into four spatial sampling approaches at the community level. We evaluate the proposed mobility-based spatial sampling by analyzing both actual and simulated outbreaks, considering scenarios of transmissibility, intervention timing, and population density in cities. Results indicate that leveraging inter-community movement data and initial case locations, the proposed Case Flow Intensity (CFI) and Case Transmission Intensity (CTI)-informed spatial sampling enhances community-level testing efficiency by reducing the number of individuals screened while maintaining a high accuracy rate in infection identification. Furthermore, the prompt application of CFI and CTI within cities is crucial for effective detection, especially in highly contagious infections within densely populated areas. With the widespread use of human mobility data for infectious disease responses, the proposed theoretical framework extends spatiotemporal data analysis of mobility patterns into spatial sampling, providing a cost-effective solution to optimize testing resource deployment for containing emerging infectious diseases.

SARS-CoV-2 viral titer measurements in Ontario, Canada wastewaters throughout the COVID-19 pandemic

During the COVID-19 pandemic, the Province of Ontario, Canada, launched a wastewater surveillance program to monitor SARS-CoV-2, inspired by the early work and successful forecasts of COVID-19 waves in the city of Ottawa, Ontario. This manuscript presents a dataset from January 1, 2021, to March 31, 2023, with RT-qPCR results for SARS-CoV-2 genes and PMMoV from 107 sites across all 34 public health units in Ontario, covering 72% of the province's and 26.2% of Canada's population. Sampling occurred 2-7 times weekly, including geographical coordinates, serviced populations, physico-chemical water characteristics, and flowrates. In doing so, this manuscript ensures data availability and metadata preservation to support future research and epidemic preparedness through detailed analyses and modeling. The dataset has been crucial for public health in tracking disease locally, especially with the rise of the Omicron variant and the decline in clinical testing, highlighting wastewater-based surveillance's role in estimating disease incidence in Ontario.

Modeling the transmission mitigation impact of testing for infectious diseases

A fundamental question of any program focused on the testing and timely diagnosis of a communicable disease is its effectiveness in reducing transmission. Here, we introduce testing effectiveness (TE)-the fraction by which testing and post-diagnosis isolation reduce transmission at the population scale-and a model that incorporates test specifications and usage, within-host pathogen dynamics, and human behaviors to estimate TE. Using TE to guide recommendations, we show that today's rapid diagnostics should be used immediately upon symptom onset to control influenza A and respiratory syncytial virus but delayed by up to two days to control omicron-era severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, while rapid tests are superior to reverse transcription quantitative polymerase chain reaction (RT-qPCR) to control founder-strain SARS-CoV-2, omicron-era changes in viral kinetics and rapid test sensitivity cause a reversal, with higher TE for RT-qPCR despite longer turnaround times. Last, we illustrate the model's flexibility by quantifying trade-offs in the use of post-diagnosis testing to shorten isolation times.

Non-pharmaceutical interventions to reduce COVID-19 transmission in the UK: a rapid mapping review and interactive evidence gap map

BACKGROUND

Non-pharmaceutical interventions (NPIs) were crucial in the response to the COVID-19 pandemic, although uncertainties about their effectiveness remain. This work aimed to better understand the evidence generated during the pandemic on the effectiveness of NPIs implemented in the UK.

METHODS

We conducted a rapid mapping review (search date: 1 March 2023) to identify primary studies reporting on the effectiveness of NPIs to reduce COVID-19 transmission. Included studies were displayed in an interactive evidence gap map.

RESULTS

After removal of duplicates, 11 752 records were screened. Of these, 151 were included, including 100 modelling studies but only 2 randomized controlled trials and 10 longitudinal observational studies.Most studies reported on NPIs to identify and isolate those who are or may become infectious, and on NPIs to reduce the number of contacts. There was an evidence gap for hand and respiratory hygiene, ventilation and cleaning.

CONCLUSIONS

Our findings show that despite the large number of studies published, there is still a lack of robust evaluations of the NPIs implemented in the UK. There is a need to build evaluation into the design and implementation of public health interventions and policies from the start of any future pandemic or other public health emergency.

Utilization of at-home tests for coronavirus disease 2019 (COVID-19) among healthcare workers in Chicago

Objective

To describe utilization of at-home coronavirus disease 2019 (COVID-19) testing among healthcare workers (HCW).

Design

Serial cross-sectional study.

Setting and participants

HCWs in the Chicago area.

Methods

Serial surveys were conducted from the Northwestern Medicine (NM HCW SARS-CoV-2) Serology Cohort Study. In April 2022, participants reflected on the past 30 days to complete an online survey regarding COVID-19 home testing. Surveys were repeated in June and November 2022. The percentage of completed home tests and ever-positive tests were reported. Multivariable Poisson regression was used to calculate prevalence rate ratios (PRR) and univariate analysis was used for association between participant characteristics with home testing and positivity.

Results

Overall, 2,226 (62.4%) of 3,569 responded to the survey in April. Home testing was reported by 26.6% of respondents and 5.9% reported having at least one positive home test. Testing was highest among those 30-39 years old (35.9%) and nurses (28.3%). A positive test was associated (P < .001) with exposure to people, other than patients with known or suspected COVID-19. Home testing increased in June to 36.4% (positivity 19.9%) and decreased to 25% (positivity 13.5%) by November.

Conclusion

Our cohort findings show the overall increase in both home testing and ever positivity from April to November - a period where changes in variants of concern of SARS-CoV-2 were reported nationwide. Having an exposure to people, other than patients with known or suspected COVID-19 was significantly associated with both, higher home testing frequency and ever-test positivity.

Highly Multiplexed Reverse-Transcription Loop-Mediated Isothermal Amplification and Nanopore Sequencing (LAMPore) for Wastewater-Based Surveillance

Wastewater-based surveillance (WBS) has gained attention as a strategy to monitor and provide an early warning for disease outbreaks. Here, we applied an isothermal gene amplification technique, reverse-transcription loop-mediated isothermal amplification (RT-LAMP), coupled with nanopore sequencing (LAMPore) as a means to detect SARS-CoV-2. Specifically, we combined barcoding using both an RT-LAMP primer and the nanopore rapid barcoding kit to achieve highly multiplexed detection of SARS-CoV-2 in wastewater. RT-LAMP targeting the SARS-CoV-2 N region was conducted on 96 reactions including wastewater RNA extracts and positive and no-target controls. The resulting amplicons were pooled and subjected to nanopore sequencing, followed by demultiplexing based on barcodes that differentiate the source of each SARS-CoV-2 N amplicon derived from the 96 RT-LAMP products. The criteria developed and applied to establish whether SARS-CoV-2 was detected by the LAMPore assay indicated high consistency with polymerase chain reaction-based detection of the SARS-CoV-2 N gene, with a sensitivity of 89% and a specificity of 83%. We further profiled sequence variations on the SARS-CoV-2 N amplicons, revealing a number of mutations on a sample collected after viral variants had emerged. The results demonstrate the potential of the LAMPore assay to facilitate WBS for SARS-CoV-2 and the emergence of viral variants in wastewater.

On the impact of surveillance test strategies: a cost-benefit modelling analysis based upon real-world data from SARS-CoV-2

OBJECTIVES

Active regular surveillance testing of asymptomatic and symptomatic individuals can reduce infection and onward transmission rates, as demonstrated for SARS-CoV-2.

STUDY DESIGN

Cost-benefit analysis based on real-world data.

METHODS

Two different surveillance-testing strategies using nucleic acid amplification tests (NAATs) performed in 14,177 hospital employees were compared for their costs and their effectiveness in preventing secondary infections.

RESULTS

Compared to not testing, NAAT-based testing twice a week accompanied by contact tracing or testing five times a week without tracing of contacts were more effective in preventing infections through early identification of infected individuals. While expansion of the test frequency from two to five times per week increased the initial costs, importantly, a 49.6 % higher inhibitory effect on infection growth with a 11.1-fold reduction of potentially averted infections and resulting workforce loss was observed, demonstrating a substantial cost-benefit of the 5-tests-per-week strategy.

CONCLUSIONS

Adaptation of the test frequency of SARS-CoV-2 and possibly of other pathogens with epidemic potential according to the prevailing incidences and reproduction rates in high-prevalence situations may not only be beneficial in averting potential infections in hospital employees and, subsequently, on a population level but may also represent the most cost-effective method.

The impact of inaccurate assumptions about antibody test accuracy on the parametrisation and results of infectious disease models of epidemics

The parametrisation of infectious disease models is often done based on epidemiological studies that use diagnostic and serology tests to establish disease prevalence or seroprevalence in the population being modelled. During outbreaks of an emerging infectious disease, tests are often used, both for disease control and epidemiological studies, before studies evaluating their accuracy in the population have concluded, with assumptions made about accuracy parameters like sensitivity and specificity. In this simulation study, we simulated such an outbreak, based on the case study of COVID-19, and found that inaccurate parametrisation of infectious disease models due to assumptions about antibody test accuracy in a seroprevalence study can cause modelling results that inform public health decisions to be inaccurate; for example, in our simulation setup, assuming that antibody test specificity was 0.99 instead of 0.90 when it was in fact 0.90 led to an average relative difference of 0.78 in model-projected peak hospitalisations, even when test sensitivity and all other parameters were accurately characterised. We therefore suggest that methods to speed up test evaluation studies are vitally important in the public health response to an emerging outbreak.

In Support of Universal Admission Testing for SARS-CoV-2 During Significant Community Transmission

Many hospitals have stopped or are considering stopping universal admission testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We discuss reasons why admission testing should still be part of a layered system to prevent hospital-acquired SARS-CoV-2 infections during times of significant community transmission. These include the morbidity of SARS-CoV-2 in vulnerable patients, the predominant contribution of presymptomatic and asymptomatic people to transmission, the high rate of transmission between patients in shared rooms, and data suggesting surveillance testing is associated with fewer nosocomial infections. Preferences of diverse patient populations, particularly the hardest-hit communities, should be surveyed and used to inform prevention measures. Hospitals' ethical responsibility to protect patients from serious infections should predominate over concerns about costs, labor, and inconvenience. We call for more rigorous data on the incidence and morbidity of nosocomial SARS-CoV-2 infections and more research to help determine when to start, stop, and restart universal admission testing and other prevention measures.

Epidemiological contemplation for a currently pragmatic COVID-19 health passport: a perspective

The coronavirus disease 2019 (COVID-19) has caused a global pandemic that has wreaked havoc on the lives of millions of people around the world. Confinement measures aim to reduce the epidemic's spread and minimize the burden of morbidity and mortality. In response to the challenges caused by the pandemic, digital health passports have been developed exponentially. We highlight the latent epidemiological barriers to health passports to achieve standardized digital care platforms. This review paper not only highlights the epidemiological barriers but also articulates the possible infrastructure required to make the International Standard for a multi-factor authenticated and validated health passport.

COVID-19 passenger screening to reduce travel risk and translocation of disease

Aviation passenger screening has been used worldwide to mitigate the translocation risk of SARS-CoV-2. We present a model that evaluates factors in screening strategies used in air travel and assess their relative sensitivity and importance in identifying infectious passengers. We use adapted Monte Carlo simulations to produce hypothetical disease timelines for the Omicron variant of SARS-CoV-2 for travelling passengers. Screening strategy factors assessed include having one or two RT-PCR and/or antigen tests prior to departure and/or post-arrival, and quarantine length and compliance upon arrival. One or more post-arrival tests and high quarantine compliance were the most important factors in reducing pathogen translocation. Screening that combines quarantine and post-arrival testing can shorten the length of quarantine for travelers, and variability and mean testing sensitivity in post-arrival RT-PCR and antigen tests decrease and increase with the greater time between the first and second post-arrival test, respectively. This study provides insight into the role various screening strategy factors have in preventing the translocation of infectious diseases and a flexible framework adaptable to other existing or emerging diseases. Such findings may help in public health policy and decision-making in present and future evidence-based practices for passenger screening and pandemic preparedness.

Optimizing the detection of emerging infections using mobility-based spatial sampling

Background

Timely and precise detection of emerging infections is crucial for effective outbreak management and disease control. Human mobility significantly influences infection risks and transmission dynamics, and spatial sampling is a valuable tool for pinpointing potential infections in specific areas. This study explored spatial sampling methods, informed by various mobility patterns, to optimize the allocation of testing resources for detecting emerging infections.

Methods

Mobility patterns, derived from clustering point-of-interest data and travel data, were integrated into four spatial sampling approaches to detect emerging infections at the community level. To evaluate the effectiveness of the proposed mobility-based spatial sampling, we conducted analyses using actual and simulated outbreaks under different scenarios of transmissibility, intervention timing, and population density in cities.

Results

By leveraging inter-community movement data and initial case locations, the proposed case flow intensity (CFI) and case transmission intensity (CTI)-informed sampling approaches could considerably reduce the number of tests required for both actual and simulated outbreaks. Nonetheless, the prompt use of CFI and CTI within communities is imperative for effective detection, particularly for highly contagious infections in densely populated areas.

Conclusions

The mobility-based spatial sampling approach can substantially improve the efficiency of community-level testing for detecting emerging infections. It achieves this by reducing the number of individuals screened while maintaining a high accuracy rate of infection identification. It represents a cost-effective solution to optimize the deployment of testing resources, when necessary, to contain emerging infectious diseases in diverse settings.

Impact on the German asymptomatic screening strategy based on actual user data from SARS-CoV-2 test centers

Since March 2021, Germany has been providing cost-free severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen tests, and many day-to-day activities following the lockdown have required negative test results. Yet it remains unclear how tests have been used and whether there are patterns connected to mitigation measures. We analyzed over 50,000 anonymized records from eight test centers in a typical medium-sized city, with one of them remaining open continuously from March until December 2021. The centers exhibit distinct patterns of visitor types, with the majority tested only once in the investigated period. Individuals who underwent repeated testing tended to favor the same location. A preference for spontaneous testing grew in proportion to the availability of spare tests. Visitors aged 18 to 30 years were distinctly overrepresented compared to the local demographic. A negative binominal model showed that implemented mitigation measures had an impact on the number of tests conducted. Cost-free testing in private facilities was implemented into the German complementary screening strategy, aiming to achieve weekly population-wide testing. This study demonstrates these facilities were rarely used for regular testing but rather for meeting requirements of certified tests. The results should aid authorities in making future decisions regarding infection control.

Use of Community SARS-CoV-2 Case Counts and Instantaneous Reproductive Number to Predict Short-Term COVID-19 Hospital Admission Volumes

The severe acute respiratory syndrome (SARS-CoV-2) pandemic and high hospitalization rates placed a tremendous strain on hospital resources, necessitating the use of models to predict hospital volumes and the associated resource requirements. Complex epidemiologic models have been developed and published, but many require continued adjustment of input parameters. We developed a simplified model for short-term bed need predictions that self-adjusts to changing patterns of disease in the community and admission rates. The model utilizes public health data on community new case counts for SARS-CoV-2 and projects anticipated hospitalization rates. The model was retrospectively evaluated after the second wave of SARS-CoV-2 in New York, New York (October 2020-April 2021) for its accuracy in predicting numbers of coronavirus disease 2019 (COVID-19) admissions 3, 5, 7, and 10 days into the future, comparing predicted admissions with actual admissions for each day at a large integrated health-care delivery network. The mean absolute percent error of the model was found to be low when evaluated across the entire health system, for a single region of the health system or for a single large hospital (6.1%-7.6% for 3-day predictions, 9.2%-10.4% for 5-day predictions, 12.4%-13.2% for 7-day predictions, and 17.1%-17.8% for 10-day predictions).

Getting Jab or Regular Test: Observations from an Impulsive Epidemic COVID-19 Model

Several safe and effective vaccines are available to prevent individuals from experiencing severe illness or death as a result of COVID-19. Widespread vaccination is widely regarded as a critical tool in the fight against the disease. However, some individuals may choose not to vaccinate due to vaccine hesitancy or other medical conditions. In some sectors, regular compulsory testing is required for such unvaccinated individuals. Interestingly, different sectors require testing at various frequencies, such as weekly or biweekly. As a result, it is essential to determine the optimal testing frequency and identify underlying factors. This study proposes a population-based model that can accommodate different personal decision choices, such as getting vaccinated or undergoing regular tests, as well as vaccine efficacies and uncertainties in epidemic transmission. The model, formulated as impulsive differential equations, uses time instants to represent the reporting date for the test result of an unvaccinated individual. By employing well-accepted indices to measure transmission risk, including the basic reproduction number, the peak time, the final size, and the number of severe infections, the study shows that an optimal testing frequency is highly sensitive to parameters involved in the transmission process, such as vaccine efficacy, disease transmission rate, test accuracy, and existing vaccination coverage. The testing frequency should be appropriately designed with the consideration of all these factors, as well as the control objectives measured by epidemiological quantities of great concern.

Comparing the efficiency of forward and backward contact tracing

Tracing potentially infected contacts of confirmed cases is important when fighting outbreaks of many infectious diseases. The COVID-19 pandemic has motivated researchers to examine how different contact tracing strategies compare in terms of effectiveness (ability to mitigate infections) and cost efficiency (number of prevented infections per isolation). Two important strategies are so-called forward contact tracing (tracing to whom disease spreads) and backward contact tracing (tracing from whom disease spreads). Recently, Kojaku and colleagues reported that backward contact tracing was "profoundly more effective" than forward contact tracing, that contact tracing effectiveness "hinges on reaching the 'source' of infection," and that contact tracing outperformed case isolation in terms of cost efficiency. Here we show that these conclusions are not true in general. They were based in part on simulations that vastly overestimated the effectiveness and efficiency of contact tracing. Our results show that the efficiency of contact tracing strategies is highly contextual; faced with a disease outbreak, the disease dynamics determine whether tracing infection sources or new cases is more impactful. Our results also demonstrate the importance of simulating disease spread and mitigation measures in parallel rather than sequentially.

Viral and antibody dynamics of acute infection with SARS-CoV-2 omicron variant (B.1.1.529): a prospective cohort study from Shenzhen, China

BACKGROUND

Elucidating viral dynamics within the host is important for designing public health measures against SARS-CoV-2, particularly during the early stages of infection when transmission potential rapidly increases. We aimed to analyse the viral and antibody dynamics of the omicron variant in relation to symptom onset or laboratory confirmation and replication dynamics throughout the infection course.

METHODS

In this prospective cohort study, patients with laboratory-confirmed SARS-CoV-2 infection who were admitted to Shenzhen Third People's Hospital (Shenzhen, China) between Jan 11, 2020, and April 24, 2022, were screened for eligibility. We included immunocompetent individuals with acute SARS-CoV-2 infection without antiviral agents targeting SARS-CoV-2. Serial nasopharyngeal swabs and plasma samples were analysed for viral RNAs and specific IgG antibodies of SARS-CoV-2. The comparative viral and antibody kinetics in association with symptom onset or laboratory confirmation and replication dynamics throughout the infection course were calculated by the locally estimated scatterplot smoothing curve fitting polynomial regression. The associations between viral and antibody dynamics and vaccination, age, sex, disease severity, and underlying health conditions were analysed using the Mann-Whitney U test and the Gehan-Breslow-Wilcoxon method.

FINDINGS

15 406 serial nasopharyngeal swabs and 2324 plasma samples were taken from 2043 individuals with acute SARS-CoV-2 infection (n=217 prototype [A.1] and D614G [B.1] variant [wild-type]; n=105 delta variant [B.1.617.2]; n=1721 omicron variant [B.1.1.529]) and were included for the analyses. The mean Ct value of omicron variant on the first day post symptom onset (dpo; defined as the first day post laboratory confirmation in asymptomatic participants) was 22·65 (95% CI 22·05-23·26). Peak viral load was reached with a mean Ct value of 17·63 (17·47-17·79) at a mean of 3·19 dpo (95% CI 3·09-3·28), and viral clearance (Ct values ≥35) was reached at a mean of 13·50 dpo (95% CI 13·32-13·67). Omicron variant showed faster viral replication and clearance than wild-type SARS-CoV-2 and delta variant, and the viral load at the first dpo and the peak viral load was lower than delta variant but higher than wild-type SARS-CoV-2. Age, sex, disease severity, and underlying health conditions were associated with the viral dynamics of omicron variant, with faster viral clearance found in young (aged 0-14 years), male, and asymptomatic participants, and those without underlying health conditions. Replication dynamics thoughout the infection course showed that peak viral load was reached at a mean of 5·06 dpo (4·76-5·36) and viral clearance took a mean of 14·27 days (13·6-14·93) for omicron variant. SARS-CoV-2-specific IgG increased earlier and faster to significantly higher concentrations in breakthrough infection than naive infection with omicron variant, despite long intervals (≥7 months) between the last dose of vaccination and infection.

INTERPRETATION

Our data provide a comprehensive overview of the longitudinal viral and antibody dynamics of omicron variant in people with acute SARS-CoV-2 infection, with important implications for public health strategies, including population screening, antiviral treatment, isolation periods, and vaccination.

FUNDING

National Natural Science Foundation of China and Emergency Key Program of Guangzhou Laboratory.

TRANSLATION

For the Chinese translation of the abstract see Supplementary Materials section.

Molecular Diagnosis of COVID-19; Biosafety and Pre-analytical Recommendations

From the beginning of the COVID-19 epidemic, clinical laboratories around the world have been involved with tests for detection of SARS-CoV-2. At present, RT-PCR (real-time reverse transcription polymerase chain reaction assay) is seen as the gold standard for identifying the virus. Many factors are involved in achieving the highest accuracy in this test, including parameters related to the pre-analysis stage. Having instructions on the type of sample, how to take the sample, and its storage and transportation help control the interfering factors at this stage. Studies have shown that pre-analytical factors might be the cause of the high SARS-CoV-2 test false-negative rates. Also, the safety of personnel in molecular laboratories is of utmost importance, and it requires strict guidelines to ensure the safety of exposed individuals and prevent the virus from spreading. Since the onset of the outbreak, various instructions and guidelines have been developed in this field by the institutions and the Ministry of Health of each country; these guidelines are seriously in need of integration and operation. In this study, we try to collect all the information and research done from the beginning of this pandemic in December 2019 - August 2022 concerning biosafety and protective measures, sample types, sampling methods, container, and storage solutions, sampling equipment, and sample storage and transportation for molecular testing of SARS-CoV-2.

Epidemic Management via Imperfect Testing: A Multi-criterial Perspective

Diagnostic testing may represent a key component in response to an ongoing epidemic, especially if coupled with containment measures, such as mandatory self-isolation, aimed to prevent infectious individuals from furthering onward transmission while allowing non-infected individuals to go about their lives. However, by its own nature as an imperfect binary classifier, testing can produce false negative or false positive results. Both types of misclassification are problematic: while the former may exacerbate the spread of disease, the latter may result in unnecessary isolation mandates and socioeconomic burden. As clearly shown by the COVID-19 pandemic, achieving adequate protection for both people and society is a crucial, yet highly challenging task that needs to be addressed in managing large-scale epidemic transmission. To explore the trade-offs imposed by diagnostic testing and mandatory isolation as tools for epidemic containment, here we present an extension of the classical Susceptible-Infected-Recovered model that accounts for an additional stratification of the population based on the results of diagnostic testing. We show that, under suitable epidemiological conditions, a careful assessment of testing and isolation protocols can contribute to epidemic containment, even in the presence of false negative/positive results. Also, using a multi-criterial framework, we identify simple, yet Pareto-efficient testing and isolation scenarios that can minimize case count, isolation time, or seek a trade-off solution for these often contrasting epidemic management objectives.

SERS Signature of SARS-CoV-2 in Saliva and Nasopharyngeal Swabs: Towards Perspective COVID-19 Point-of-Care Diagnostics

In this study, the intrinsic surface-enhanced Raman spectroscopy (SERS)-based approach coupled with chemometric analysis was adopted to establish the biochemical fingerprint of SARS-CoV-2 infected human fluids: saliva and nasopharyngeal swabs. The numerical methods, partial least squares discriminant analysis (PLS-DA) and support vector machine classification (SVMC), facilitated the spectroscopic identification of the viral-specific molecules, molecular changes, and distinct physiological signatures of pathetically altered fluids. Next, we developed the reliable classification model for fast identification and differentiation of negative CoV(-) and positive CoV(+) groups. The PLS-DA calibration model was described by a great statistical value-RMSEC and RMSECV below 0.3 and R²_cal at the level of ~0.7 for both type of body fluids. The calculated diagnostic parameters for SVMC and PLS-DA at the stage of preparation of calibration model and classification of external samples simulating real diagnostic conditions evinced high accuracy, sensitivity, and specificity for saliva specimens. Here, we outlined the significant role of neopterin as the biomarker in the prediction of COVID-19 infection from nasopharyngeal swab. We also observed the increased content of nucleic acids of DNA/RNA and proteins such as ferritin as well as specific immunoglobulins. The developed SERS for SARS-CoV-2 approach allows: (i) fast, simple and non-invasive collection of analyzed specimens; (ii) fast response with the time of analysis below 15 min, and (iii) sensitive and reliable SERS-based screening of COVID-19 disease.

DNA amplification tests at universal pre-admission screening with enhanced precaution strategies for asymptomatic patients with COVID-19

Objective

To analyse the effect of hospital pre-admission screening and enhanced precaution strategies on the transmission of severe acute respiratory syndrome coronavirus-2.

Methods

This retrospective cohort study was conducted over 17 months from 11 May 2020 to 30 September 2021 at a large hospital in Tokyo. Universal DNA amplification tests were conducted during pre-admission screening, and enhanced precaution strategies were implemented for all patients with negative admission tests. The primary outcome was the occurrence of symptomatic coronavirus disease 2019 (COVID-19) in patients after admission. The secondary outcomes were time-series analyses of monthly positive admission test numbers, positive rates, clinical features in positive cases, and clinically confirmed nosocomial transmission.

Results

In total, 32,081 patients were screened pre-admission (29,556 asymptomatic patients and 2525 symptomatic patients). Of the asymptomatic patients, 0.11% (n=32) tested positive and were admitted to a designated COVID-19 ward or were not admitted. Among the five inpatients who developed symptomatic COVID-19 during hospitalization, only two cases were related to a single nosocomial transmission.

Conclusion

Pre-admission test screening was effective in identifying asymptomatic cases of COVID-19. This allowed administrators to quarantine patients or delay hospital admission. The combination of testing and enhanced precaution strategies for asymptomatic cases of COVID-19 may minimize nosocomial transmission.

Assessing the spatial distribution of and inequality in 15-minute PCR test site accessibility in Beijing and Guangzhou, China

China has been planning to construct SARS-CoV-2 antigen testing sites within a 15-min walk in most major cities to timely identify asymptomatic cases and stop the transmission of COVID-19. However, little is known about the spatial distribution of 15-min accessibility to PCR test sites. In this study, we analyze the spatial distribution of and inequality in 15-min accessibility to PCR test sites in two major Chinese cities (Beijing and Guangzhou) based on the cumulative-opportunity model. The results indicate that the current distribution of 15-min accessibility to PCR test sites is satisfactory when normal commuting is not disrupted. However, disruptions of normal commuting (e.g., due to work-from-home restrictions) can negatively influence 15-min accessibility to PCR test sites and increase its inequality. Our study provides policymakers with up-to-date knowledge about the spatial distribution of 15-min accessibility to PCR test sites, identifies the disadvantaged neighborhoods in terms of test site accessibility, and highlights the changes in accessibility and inequality because of travel disruptions.

Covid-19 Surveillance Testing and Resident Outcomes in Nursing Homes

BACKGROUND

Despite widespread adoption of surveillance testing for coronavirus disease 2019 (Covid-19) among staff members in skilled nursing facilities, evidence is limited regarding its relationship with outcomes among facility residents.

METHODS

Using data obtained from 2020 to 2022, we performed a retrospective cohort study of testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among staff members in 13,424 skilled nursing facilities during three pandemic periods: before vaccine approval, before the B.1.1.529 (omicron) variant wave, and during the omicron wave. We assessed staff testing volumes during weeks without Covid-19 cases relative to other skilled nursing facilities in the same county, along with Covid-19 cases and deaths among residents during potential outbreaks (defined as the occurrence of a case after 2 weeks with no cases). We reported adjusted differences in outcomes between high-testing facilities (90th percentile of test volume) and low-testing facilities (10th percentile). The two primary outcomes were the weekly cumulative number of Covid-19 cases and related deaths among residents during potential outbreaks.

RESULTS

During the overall study period, 519.7 cases of Covid-19 per 100 potential outbreaks were reported among residents of high-testing facilities as compared with 591.2 cases among residents of low-testing facilities (adjusted difference, -71.5; 95% confidence interval [CI], -91.3 to -51.6). During the same period, 42.7 deaths per 100 potential outbreaks occurred in high-testing facilities as compared with 49.8 deaths in low-testing facilities (adjusted difference, -7.1; 95% CI, -11.0 to -3.2). Before vaccine availability, high- and low-testing facilities had 759.9 cases and 1060.2 cases, respectively, per 100 potential outbreaks (adjusted difference, -300.3; 95% CI, -377.1 to -223.5), along with 125.2 and 166.8 deaths (adjusted difference, -41.6; 95% CI, -57.8 to -25.5). Before the omicron wave, the numbers of cases and deaths were similar in high- and low-testing facilities; during the omicron wave, high-testing facilities had fewer cases among residents, but deaths were similar in the two groups.

CONCLUSIONS

Greater surveillance testing of staff members at skilled nursing facilities was associated with clinically meaningful reductions in Covid-19 cases and deaths among residents, particularly before vaccine availability.

Attitudes towards booster, testing and isolation, and their impact on COVID-19 response in winter 2022/2023 in France, Belgium, and Italy: a cross-sectional survey and modelling study

Background

European countries are focusing on testing, isolation, and boosting strategies to counter the 2022/2023 winter surge due to SARS-CoV-2 Omicron subvariants. However, widespread pandemic fatigue and limited compliance potentially undermine mitigation efforts.

Methods

To establish a baseline for interventions, we ran a multicountry survey to assess respondents’ willingness to receive booster vaccination and comply with testing and isolation mandates. Integrating survey and estimated immunity data in a branching process epidemic spreading model, we evaluated the effectiveness and costs of current protocols in France, Belgium, and Italy to manage the winter wave.

Findings

The vast majority of survey participants (N = 4594) was willing to adhere to testing (>91%) and rapid isolation (>88%) across the three countries. Pronounced differences emerged in the declared senior adherence to booster vaccination (73% in France, 94% in Belgium, 86% in Italy). Epidemic model results estimate that testing and isolation protocols would confer significant benefit in reducing transmission (17–24% reduction, from R = 1.6 to R = 1.3 in France and Belgium, to R = 1.2 in Italy) with declared adherence. Achieving a mitigating level similar to the French protocol, the Belgian protocol would require 35% fewer tests (from 1 test to 0.65 test per infected person) and avoid the long isolation periods of the Italian protocol (average of 6 days vs. 11). A cost barrier to test would significantly decrease adherence in France and Belgium, undermining protocols’ effectiveness.

Interpretation

Simpler mandates for isolation may increase awareness and actual compliance, reducing testing costs, without compromising mitigation. High booster vaccination uptake remains key for the control of the winter wave.

Funding

The 10.13039/501100000780European Commission, ANRS–Maladies Infectieuses Émergentes, the Agence Nationale de la Recherche, the Chaires Blaise Pascal Program of the Île-de-France region.

Potential for Early Noninvasive COVID-19 Detection Using Electronic-Nose Technologies and Disease-Specific VOC Metabolic Biomarkers

The established efficacy of electronic volatile organic compound (VOC) detection technologies as diagnostic tools for noninvasive early detection of COVID-19 and related coronaviruses has been demonstrated from multiple studies using a variety of experimental and commercial electronic devices capable of detecting precise mixtures of VOC emissions in human breath. The activities of numerous global research teams, developing novel electronic-nose (e-nose) devices and diagnostic methods, have generated empirical laboratory and clinical trial test results based on the detection of different types of host VOC-biomarker metabolites from specific chemical classes. COVID-19-specific volatile biomarkers are derived from disease-induced changes in host metabolic pathways by SARS-CoV-2 viral pathogenesis. The unique mechanisms proposed from recent researchers to explain how COVID-19 causes damage to multiple organ systems throughout the body are associated with unique symptom combinations, cytokine storms and physiological cascades that disrupt normal biochemical processes through gene dysregulation to generate disease-specific VOC metabolites targeted for e-nose detection. This paper reviewed recent methods and applications of e-nose and related VOC-detection devices for early, noninvasive diagnosis of SARS-CoV-2 infections. In addition, metabolomic (quantitative) COVID-19 disease-specific chemical biomarkers, consisting of host-derived VOCs identified from exhaled breath of patients, were summarized as possible sources of volatile metabolic biomarkers useful for confirming and supporting e-nose diagnoses.

Guidelines for Infection Control and Burnout Prevention in Healthcare Workers Responding to COVID-19

During the coronavirus disease 2019 (COVID-19) pandemic, frontline healthcare workers (HCWs) suffered more distress from the possibility of contracting the virus, quarantine, social stigma, and prejudice against their families. Many studies have investigated the impact of the pandemic on HCWs; however, studies or guidelines presenting strategies to overcome these challenges are lacking. As part of a 2020 research project supported by the Ministry of Health and Welfare, titled "Health impact assessment of healthcare workers undertaking coronavirus disease 2019 treatment and management in Korea: Identifying problems and researching effective solutions" (HC20C0003), we created guidelines to respond to serious problems posed by infection control. and burnout among HCWs during COVID-19 response measures throughout the extended pandemic period. We formulated the guidelines by means of a systematic review and collated them with the latest literature. The guidelines will highlight the gravity and impact of infection control and burnout among HCWs responding to COVID-19 and include potential prevention strategies, and they can be used as a reference in the event of another emerging infectious disease outbreak in the future.

Comparative effectiveness of contact tracing interventions in the context of the COVID-19 pandemic: a systematic review

Contact tracing is a non-pharmaceutical intervention (NPI) widely used in the control of the COVID-19 pandemic. Its effectiveness may depend on a number of factors including the proportion of contacts traced, delays in tracing, the mode of contact tracing (e.g. forward, backward or bidirectional contact training), the types of contacts who are traced (e.g. contacts of index cases or contacts of contacts of index cases), or the setting where contacts are traced (e.g. the household or the workplace). We performed a systematic review of the evidence regarding the comparative effectiveness of contact tracing interventions. 78 studies were included in the review, 12 observational (ten ecological studies, one retrospective cohort study and one pre-post study with two patient cohorts) and 66 mathematical modelling studies. Based on the results from six of the 12 observational studies, contact tracing can be effective at controlling COVID-19. Two high quality ecological studies showed the incremental effectiveness of adding digital contact tracing to manual contact tracing. One ecological study of intermediate quality showed that increases in contact tracing were associated with a drop in COVID-19 mortality, and a pre-post study of acceptable quality showed that prompt contact tracing of contacts of COVID-19 case clusters / symptomatic individuals led to a reduction in the reproduction number R. Within the seven observational studies exploring the effectiveness of contact tracing in the context of the implementation of other non-pharmaceutical interventions, contact tracing was found to have an effect on COVID-19 epidemic control in two studies and not in the remaining five studies. However, a limitation in many of these studies is the lack of description of the extent of implementation of contact tracing interventions. Based on the results from the mathematical modelling studies, we identified the following highly effective policies: (1) manual contact tracing with high tracing coverage and either medium-term immunity, highly efficacious isolation/quarantine and/ or physical distancing (2) hybrid manual and digital contact tracing with high app adoption with highly effective isolation/ quarantine and social distancing, (3) secondary contact tracing, (4) eliminating contact tracing delays, (5) bidirectional contact tracing, (6) contact tracing with high coverage in reopening educational institutions. We also highlighted the role of social distancing to enhance the effectiveness of some of these interventions in the context of 2020 lockdown reopening. While limited, the evidence from observational studies shows a role for manual and digital contact tracing in controlling the COVID-19 epidemic. More empirical studies accounting for the extent of contact tracing implementation are required.

Modelling the impact of timelines of testing and isolation on disease control

Testing and isolation remain a key component of public health responses to both persistent and emerging infectious diseases. Although the value of these measures have been demonstrated in combating recent outbreaks including the COVID-19 pandemic and monkeypox, their impact depends critically on the timelines of testing and start of isolation during the course of disease. To investigate this impact, we developed a delay differential model and incorporated age-since-symptom-onset as a parameter for delay in testing. We then used the model to compare the outcomes of reverse-transcription polymerase chain reaction (RT-PCR) and rapid antigen (RA) testing methods when isolation starts either at the time of testing or at the time of test result. Parameterizing the model with estimates of SARS-CoV-2 infection and diagnostic sensitivity of the tests, we found that the reduction of disease transmission using the RA test can be comparable to that achieved by applying the RT-PCR test. Given constraints and inevitable delays associated with sample collection and laboratory assays in RT-PCR testing post symptom onset, self-administered RA tests with short turnaround times present a viable alternative for timely isolation of infectious cases.

[Recommendations for action for SARS-CoV-2 testing concepts for asymptomatic healthcare workers]

Background and objective

When implementing SARS-CoV‑2 testing concepts in healthcare facilities, different laws and regulations of equal rank apply. In the light of experienced impediments in translating legal requirements appropriately into legally secure concepts on an operational level, the objective of this paper was to develop corresponding specific recommendations for action.

Methods

On the basis of guiding questions on previously identified fields of action, a focus group consisting of representatives of administration, different medical disciplines, and special interest groups discussed critical aspects of implementation using a holistic approach. The transcribed contents were analyzed through inductive development and deductive application of categories.

Results

All contents of discussion could be matched with the identified categories legal backgrounds, requirements and objectives of testing concepts in healthcare facilities, responsibilities for implementing in operational decision-making chains, and implementing SARS-CoV‑2 testing concepts.

Implications

The correct implementation of the legal requirements into legally compliant SARS-CoV‑2 testing concepts in healthcare facilities previously required the involvement of ministries, representatives of different medical disciplines and professional associations, employer and employee representatives and data privacy experts as well as representatives of possible cost bearers. In addition, an integrative and enforceable composition of laws and regulations is necessary. Defining objectives for testing concepts is significant for the following operational process flows that need to consider aspects of employee data privacy as well as providing additional personnel for fulfilling the tasks. Also, in future one central issue of healthcare facilities concerns the finding of solutions for IT interfaces for information transfer to employees in accordance with data privacy.

Modelling the impact of repeat asymptomatic testing policies for staff on SARS-CoV-2 transmission potential

Repeat asymptomatic testing in order to identify and quarantine infectious individuals has become a widely-used intervention to control SARS-CoV-2 transmission. In some workplaces, and in particular health and social care settings with vulnerable patients, regular asymptomatic testing has been deployed to staff to reduce the likelihood of workplace outbreaks. We have developed a model based on data available in the literature to predict the potential impact of repeat asymptomatic testing on SARS-CoV-2 transmission. The results highlight features that are important to consider when modelling testing interventions, including population heterogeneity of infectiousness and correlation with test-positive probability, as well as adherence behaviours in response to policy. Furthermore, the model based on the reduction in transmission potential presented here can be used to parameterise existing epidemiological models without them having to explicitly simulate the testing process. Overall, we find that even with different model paramterisations, in theory, regular asymptomatic testing is likely to be a highly effective measure to reduce transmission in workplaces, subject to adherence. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

On the optimal presence strategies for workplace during pandemics: A COVID-19 inspired probabilistic model

During pandemics like COVID-19, both the quality and quantity of services offered by businesses and organizations have been severely impacted. They often have applied a hybrid home office setup to overcome this problem, although in some situations, working from home lowers employee productivity. So, increasing the rate of presence in the office is frequently desired from the manager's standpoint. On the other hand, as the virus spreads through interpersonal contact, the risk of infection increases when workplace occupancy rises. Motivated by this trade-off, in this paper, we model this problem as a bi-objective optimization problem and propose a practical approach to find the trade-off solutions. We present a new probabilistic framework to compute the expected number of infected employees for a setting of the influential parameters, such as the incidence level in the neighborhood of the company, transmission rate of the virus, number of employees, rate of vaccination, testing frequency, and rate of contacts among the employees. The results show a wide range of trade-offs between the expected number of infections and productivity, for example, from 1 to 6 weekly infections in 100 employees and a productivity level of 65% to 85%. This depends on the configuration of influential parameters and the occupancy level. We implement the model and the algorithm and perform several experiments with different settings of the parameters. Moreover, we developed an online application based on the result in this paper which can be used as a recommender for the optimal rate of occupancy in companies/workplaces.

Results from Canton Grisons of Switzerland suggest repetitive testing reduces SARS-CoV-2 incidence (February-March 2021)

In February 2021, in response to emergence of more transmissible SARS-CoV-2 virus variants, the Canton Grisons launched a unique RNA mass testing program targeting the labour force in local businesses. Employees were offered weekly tests free of charge and on a voluntary basis. If tested positive, they were required to self-isolate for ten days and their contacts were subjected to daily testing at work. Thereby, the quarantine of contact persons could be waved.Here, we evaluate the effects of the testing program on the tested cohorts. We examined 121,364 test results from 27,514 participants during February-March 2021. By distinguishing different cohorts of employees, we observe a noticeable decrease in the test positivity rate and a statistically significant reduction in the associated incidence rate over the considered period. The reduction in the latter ranges between 18 and 50%. The variability is partly explained by different exposures to exogenous infection sources (e.g., contacts with visiting tourists or cross-border commuters). Our analysis provides the first empirical evidence that applying repetitive mass testing to a real population over an extended period of time can prevent spread of COVID-19 pandemic. However, to overcome logistic, uptake, and adherence challenges it is important that the program is carefully designed and that disease incursion from the population outside of the program is considered and controlled.

Prioritizing interventions for preventing COVID-19 outbreaks in military basic training

Like other congregate living settings, military basic training has been subject to outbreaks of COVID-19. We sought to identify improved strategies for preventing outbreaks in this setting using an agent-based model of a hypothetical cohort of trainees on a U.S. Army post. Our analysis revealed unique aspects of basic training that require customized approaches to outbreak prevention, which draws attention to the possibility that customized approaches may be necessary in other settings, too. In particular, we showed that introductions by trainers and support staff may be a major vulnerability, given that those individuals remain at risk of community exposure throughout the training period. We also found that increased testing of trainees upon arrival could actually increase the risk of outbreaks, given the potential for false-positive test results to lead to susceptible individuals becoming infected in group isolation and seeding outbreaks in training units upon release. Until an effective transmission-blocking vaccine is adopted at high coverage by individuals involved with basic training, need will persist for non-pharmaceutical interventions to prevent outbreaks in military basic training. Ongoing uncertainties about virus variants and breakthrough infections necessitate continued vigilance in this setting, even as vaccination coverage increases.

Invited Commentary: Mechanistic and Biologically Based Models in Epidemiology-A Powerful Underutilized Tool

Mechanistic and biologically based mathematical models of chronic and behavioral disease processes aim to capture the main mechanistic or biological features of the disease development and to connect these with epidemiologic outcomes. These approaches have a long history in epidemiologic research and are complementary to traditional epidemiologic or statistical approaches to investigate the role of risk factor exposures on disease risk. Simonetto et al. (Am J Epidemiol. 2022;191(10):1766-1775) present a mechanistic, process-oriented model to investigate the role of smoking, hypertension, and dyslipidemia in the development of atherosclerotic lesions and their progression to myocardial infarction. Their approach builds on and brings to cardiovascular disease the ideas and perspectives of earlier mechanistic and biologically based models for the epidemiology of cancer and other chronic diseases, providing important insights into the mechanisms and epidemiology of smoking related myocardial infarction. We argue that although mechanistic modeling approaches have demonstrated their value and place in epidemiology, they are highly underutilized. We call for efforts to grow mechanistic and biologically based modeling research, expertise, and awareness in epidemiology, including the development of training and collaboration opportunities to attract more students and researchers from science, technology, engineering, and medical field into the epidemiology field.

The unmitigated profile of COVID-19 infectiousness

Quantifying the temporal dynamics of infectiousness of individuals infected with SARS-CoV-2 is crucial for understanding the spread of COVID-19 and for evaluating the effectiveness of mitigation strategies. Many studies have estimated the infectiousness profile using observed serial intervals. However, statistical and epidemiological biases could lead to underestimation of the duration of infectiousness. We correct for these biases by curating data from the initial outbreak of the pandemic in China (when mitigation was minimal), and find that the infectiousness profile of the original strain is longer than previously thought. Sensitivity analysis shows our results are robust to model structure, assumed growth rate and potential observational biases. Although unmitigated transmission data is lacking for variants of concern (VOCs), previous analyses suggest that the alpha and delta variants have faster within-host kinetics, which we extrapolate to crude estimates of variant-specific unmitigated generation intervals. Knowing the unmitigated infectiousness profile of infected individuals can inform estimates of the effectiveness of isolation and quarantine measures. The framework presented here can help design better quarantine policies in early stages of future epidemics.

Testing and isolation to prevent overloaded healthcare facilities and reduce death rates in the SARS-CoV-2 pandemic in Italy

Background

During the first wave of COVID-19, hospital and intensive care unit beds got overwhelmed in Italy leading to an increased death burden. Based on data from Italian regions, we disentangled the impact of various factors contributing to the bottleneck situation of healthcare facilities, not well addressed in classical SEIR-like models. A particular emphasis was set on the undetected fraction (dark figure), on the dynamically changing hospital capacity, and on different testing, contact tracing, quarantine strategies.

Methods

We first estimated the dark figure for different Italian regions. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread, the model was optimized to fit data (infected, hospitalized, ICU, dead) published by the Italian Civil Protection.

Results

We show that testing influenced the infection dynamics by isolation of newly detected cases and subsequent interruption of infection chains. The time-varying reproduction number (R t) in high testing regions decreased to <1 earlier compared to the low testing regions. While an early test and isolate (TI) scenario resulted in up to ~31% peak reduction of hospital occupancy, the late TI scenario resulted in an overwhelmed healthcare system.

Conclusions

An early TI strategy would have decreased the overall hospital usage drastically and, hence, death toll (∼34% reduction in Lombardia) and could have mitigated the lack of healthcare facilities in the course of the pandemic, but it would not have kept the hospitalization amount within the pre-pandemic hospital limit.

One Health response to SARS-CoV-2-associated risk from mink farming in British Columbia, Canada, October 2020 to October 2021

Background

Mink farms are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks and carry an associated risk of novel SARS-CoV-2 variant emergence and non-human reservoir creation. In Denmark, control measures were insufficient to prevent onward transmission of a mink-associated variant, contributing to the nation-wide culling of farmed mink. To date, British Columbia (BC) is the only Canadian province to report mink farm SARS-CoV-2 outbreaks. The objective of this study is to describe BC's One Health response to SARS-CoV-2-associated risk from mink farming, its outcomes, and insights from implementation.

Methods

The detection of two mink farm outbreaks in December 2020 catalyzed BC's risk mitigation response for both infected and uninfected farms, including the following: farm inspections and quarantines; Public Health Orders mandating mink mortality surveillance, enhanced personal protective equipment, biosafety measures and worker coronavirus disease 2019 vaccination, at-a-minimum weekly worker viral testing, and wildlife surveillance.

Results

A One Health approach enabled a timely, evidence-informed and coordinated response as the situation evolved, including the use of various legislative powers, consistent messaging and combined human and mink phylogenetic analysis. Ongoing mink and worker surveillance detected asymptomatic/subclinical infections and facilitated rapid isolation/quarantine to minimize onward transmission. Voluntary testing and mandatory vaccination for workers were acceptable to industry; enhanced personal protective equipment requirements were challenging. Regular farm inspections helped to assess and improve compliance.

Conclusion

British Columbia's One Health response reduced the risk of additional outbreaks, viral evolution and reservoir development; however, a third outbreak was detected in May 2021 despite implemented measures, and long-term sustainability of interventions proved challenging for both industry and governmental agencies involved.

Understanding COVID-19 Situation in Nepal and Implications for SARS-CoV-2 Transmission and Management

Background

The pandemic of Coronavirus Disease 2019 (COVID-19), one of the most infectious diseases in the modern history, is caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) and has had a profound health and economic toll, globally. This paper identifies the overall health status associated with COVID-19 pandemic in all 7 provinces of Nepal, a developing country in South Asia, analyzing data from January 2020 to February 2022. It focuses on the SARS-CoV-2 prevalence, transmission through wastewater and other routes, diagnostics, treatment options, and alternative medicines, thereby offering key perspectives for its management.

Materials and Methods

Studies regarding coronavirus spanning the 2017 to 2022 period were searched on the web, Nepalese database, and Web of Science. Refined criteria included SARS-CoV-2 in wastewater of Nepal or worldwide. Demographic data (sex, age-group, and geographic location) were also obtained from websites and relevant reports of the Ministry of Health and Population (MOHP) of Nepal, ranging from January 2020 to February 2022. Moreover, trends concerning lockdown, business, and border activities in Nepal between February 2020 and October 2020 were evaluated. The viral dissemination pathways, diagnosis, and available treatment options, including the Ayurvedic medicine, were also examined.

Results

Aerosols generated during the hospital, industrial, recreational, and household activities were found to contribute to the propagation of SARS-CoV-2 into environmental wastewater, thereby putting the surrounding communities at risk of infection. When lockdown ended and businesses opened in October 2020, the number of active cases of COVID-19 increased exponentially. Bagmati Province had the highest number of cases (53.84%), while the remaining 6 provinces tallied 46.16%. Kathmandu district had the highest number of COVID-19 cases (138, 319 cases), while Manang district had the smallest number of infections (81 cases). The male population was found to be predominantly infected (58.7%). The most affected age groups were the 31 to 40 years old males (25.92%) and the 21 to 30 years old females (26.85%).

Conclusion

The pandemic impacted the public health and economic growth in our study duration. SARS-CoV-2 was prevalent in the wastewater of Nepal. The Terai districts and the megacities were mostly affected by SARS-CoV-2 infections. Working-age groups and males were identified as the highest risk groups. More investigations on the therapeutic and alternative cures are recommended. These findings may guide the researchers and professionals with handling the COVID-19 challenges in developing countries such as Nepal and better prepare for future pandemics.

Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections

Across the world, the COVID-19 pandemic has disproportionately affected economically disadvantaged groups. This differential impact has numerous possible explanations, each with significantly different policy implications. We examine, for the first time in a low- or middle-income country, which mechanisms best explain the disproportionate impact of the virus on the poor. Combining an epidemiological model with rich data from Bogotá, Colombia, we show that total infections and inequalities in infections are largely driven by inequalities in the ability to work remotely and in within-home secondary attack rates. Inequalities in isolation behavior are less important but non-negligible, while access to testing and contract-tracing plays practically no role because it is too slow to contain the virus. Interventions that mitigate transmission are often more effective when targeted on socioeconomically disadvantaged groups.

Testing and Isolation Efficacy: Insights from a Simple Epidemic Model

Testing individuals for pathogens can affect the spread of epidemics. Understanding how individual-level processes of sampling and reporting test results can affect community- or population-level spread is a dynamical modeling question. The effect of testing processes on epidemic dynamics depends on factors underlying implementation, particularly testing intensity and on whom testing is focused. Here, we use a simple model to explore how the individual-level effects of testing might directly impact population-level spread. Our model development was motivated by the COVID-19 epidemic, but has generic epidemiological and testing structures. To the classic SIR framework we have added a per capita testing intensity, and compartment-specific testing weights, which can be adjusted to reflect different testing emphases-surveillance, diagnosis, or control. We derive an analytic expression for the relative reduction in the basic reproductive number due to testing, test-reporting and related isolation behaviours. Intensive testing and fast test reporting are expected to be beneficial at the community level because they can provide a rapid assessment of the situation, identify hot spots, and may enable rapid contact-tracing. Direct effects of fast testing at the individual level are less clear, and may depend on how individuals' behaviour is affected by testing information. Our simple model shows that under some circumstances both increased testing intensity and faster test reporting can reduce the effectiveness of control, and allows us to explore the conditions under which this occurs. Conversely, we find that focusing testing on infected individuals always acts to increase effectiveness of control.

Free PoC Testing for SARS-CoV-2 in Germany: Factors Expanding Access to Various Communities in a Medium-Sized City

During the third wave of the COVID-19 (coronavirus disease 2019) pandemic in Germany, free SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) point-of-care (PoC) antigen tests were offered to citizens at least once a week to prevent spreading by asymptomatic infected individuals. This study investigated user groups, timing, frequency, and test center locations in a typical medium-sized European city. We analyzed 27,369 pseudonymized datasets from eight centers over 12 weeks. Those were evaluated according to age, residence, appointment, and potential repeated test occurrence. The centers were visited by different groups; some centers were preferred by a predominantly younger demographic, whereas a mobile option attracted an older age group by reaching districts with few other testing possibilities. Elderly individuals were tested more spontaneously than younger individuals, and a test center at a ‘park and ride’ had more spontaneous visitors from outside of the city compared to other test locations. Only a small proportion of less than 4% came for testing more than five times. To preferably address many people for voluntary antigen testing, it is crucial to offer different test opportunities accounting for individual behavioral patterns, despite this requiring more complex and costly design than conventional forms.

Why Controlling the Asymptomatic Infection Is Important: A Modelling Study with Stability and Sensitivity Analysis

The large proportion of asymptomatic patients is the major cause leading to the COVID-19 pandemic which is still a significant threat to the whole world. A six-dimensional ODE system (SEIAQR epidemical model) is established to study the dynamics of COVID-19 spreading considering infection by exposed, infected, and asymptomatic cases. The basic reproduction number derived from the model is more comprehensive including the contribution from the exposed, infected, and asymptomatic patients. For this more complex six-dimensional ODE system, we investigate the global and local stability of disease-free equilibrium, as well as the endemic equilibrium, whereas most studies overlooked asymptomatic infection or some other virus transmission features. In the sensitivity analysis, the parameters related to the asymptomatic play a significant role not only in the basic reproduction number R0. It is also found that the asymptomatic infection greatly affected the endemic equilibrium. Either in completely eradicating the disease or achieving a more realistic goal to reduce the COVID-19 cases in an endemic equilibrium, the importance of controlling the asymptomatic infection should be emphasized. The three-dimensional phase diagrams demonstrate the convergence point of the COVID-19 spreading under different initial conditions. In particular, massive infections will occur as shown in the phase diagram quantitatively in the case R0>1. Moreover, two four-dimensional contour maps of Rt are given varying with different parameters, which can offer better intuitive instructions on the control of the pandemic by adjusting policy-related parameters.

Assessment of the fatality rate and transmissibility taking account of undetected cases during an unprecedented COVID-19 surge in Taiwan

Background

During the COVID-19 outbreak in Taiwan between May 11 and June 20, 2021, the observed fatality rate (FR) was 5.3%, higher than the global average at 2.1%. The high number of reported deaths suggests that many patients were not treated promptly or effectively. However, many unexplained deaths were subsequently identified as cases, indicating a few undetected cases, resulting in a higher estimate of FR. Whether the true FR is exceedingly high and what factors determine the detection of cases remain unknown. Estimating the true number of total infected cases (i.e. including undetected cases) can allow an accurate estimation of FR and effective reproduction number (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{t}$$\end{document}Rt).

Methods

We aimed at quantifying the time-varying FR and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{t}$$\end{document}Rt using the estimated true numbers of cases; and, exploring the relationship between the true case number and test and trace data. After adjusting for reporting delays, we developed a model to estimate the number of undetected cases using reported deaths that were and were not previously detected. The daily FR and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{t}$$\end{document}Rt were calculated using the true number of cases. Afterwards, a logistic regression model was used to assess the impact of daily testing and tracing data on the detection ratio of deaths.

Results

The estimated true daily case number at the peak of the outbreak on May 22 was 897, which was 24.3% higher than the reported number, but the difference became less than 4% on June 9 and afterwards. After taking account of undetected cases, our estimated mean FR (4.7%) was still high but the daily rate showed a large decrease from 6.5% on May 19 to 2.8% on June 6. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{t}$$\end{document}Rt reached a maximum value of 6.4 on May 11, compared to 6.0 estimated using the reported case number. The decreasing proportion of undetected cases was found to be associated with the increases in the ratio of the number of tests conducted to reported cases, and the proportion of cases that are contact traced before symptom onset.

Conclusions

Increasing testing capacity and contact tracing coverage without delays not only improve parameter estimation by reducing hidden cases but may also reduce fatality rates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07190-z.

On an optimal testing strategy for workplace settings operating during the COVID-19 pandemic

High quality daily testing for the presence of the SARS-CoV-2 in workplace settings has become part of the standard and mandatory protection measures implemented widely in response to the current pandemic. Such tests are often limited to a small fraction of the attending personnel due to cost considerations, limited availability and processing capabilities and the often cumbersome requirements of the test itself. A maximally efficient use of such an important and frequently scarce resource is clearly required. We here present an optimal testing strategy which minimises the presence of pre-symptomatic and asymptomatic infected members of the population in a workplace setting, derived under a series of simplifying statistical assumptions. These assumptions however, retain many of the generalities of the problem and yield robust results, as verified through a number of numerical simulations. We show that reduction in overall infected-person-days, IPD, by significant percentages can be achieved, for fixed numbers of tests per day of 5% and 10% of the population, of 30% and 50% in the IPD numbers, respectively.

Evaluation of the Panbio™ COVID-19 ag rapid test at an emergency room in a hospital in São Paulo, Brazil

BACKGROUND

The performance characteristics of the Panbio™ COVID-19 Ag test was evaluated at an emergency room setting against RT-PCR, considered the gold-standard for the detection of SARS-CoV-2, in São Paulo, Brazil. The study aimed to determine the sensitivity, specificity, Positive Percent Agreement (PPA), and Negative Percent Agreement (NPA) as compared to RT-PCR.

METHODS

Specimens from 127 suspected patients were tested by both the Panbio™ COVID-19 Ag test and by RT-PCR.

RESULTS

In relation to RT-PCR using Ct values ≤ 40 as the upper limit for positivity, the Panbio™ COVID-19 Ag test showed an overall sensitivity of 84.3% (95% CI 75‒93.8%) and 98.2% (95% CI 96‒98.8%) overall specificity. For Ct values ≤ 25 (n = 37), the Panbio™ COVID-19 Ag test showed 97% sensitivity.

DISCUSSION

The concordance between the Panbio™ COVID-19 Ag test and RT-PCR was 97% at Ct values below 25 but decreased at higher Ct values. For disease control, it is very important to identify infected individuals who present COVID-19 symptoms and also those who are suspected of infection due to contact with infected individuals.

CONCLUSION

The Panbio™ COVID-19 Ag test is suitable for use as a diagnostic test for rapid screening of patients presenting COVID-19 symptoms, or those suspected of being infected, prior to being admitted to hospital.

Surveillance-to-Diagnostic Testing Program for Asymptomatic SARS-CoV-2 Infections on a Large, Urban Campus in Fall 2020

BACKGROUND

Six months into the COVID-19 pandemic, college campuses faced uncertainty regarding the likely prevalence and spread of disease, necessitating large-scale testing to help guide policy following re-entry.

METHODS

A SARS-CoV-2 testing program combining pooled saliva sample surveillance leading to diagnosis and intervention surveyed over 112,000 samples from 18,029 students, staff and faculty, as part of integrative efforts to mitigate transmission at the Georgia Institute of Technology in Fall 2020.

RESULTS

Cumulatively, we confirmed 1,508 individuals diagnostically, 62% of these through the surveillance program and the remainder through diagnostic tests of symptomatic individuals administered on or off campus. The total strategy, including intensification of testing given case clusters early in the semester, was associated with reduced transmission following rapid case increases upon entry in Fall semester in August 2020, again in early November 2020, and upon re-entry for Spring semester in January 2021. During the Fall semester daily asymptomatic test positivity initially peaked at 4.1% but fell below 0.5% by mid-semester, averaging 0.84% across the Fall semester, with similar levels of control in Spring 2021.

CONCLUSIONS

Owing to broad adoption by the campus community, we estimate that the program protected higher risk staff and faculty while allowing some normalization of education and research activities.

The impact of multiple non-pharmaceutical interventions on controlling COVID-19 outbreak without lockdown in Hong Kong: A modelling study

BACKGROUND

The 'third wave' of COVID-19 in Hong Kong, China was suppressed by non-pharmaceutical interventions (NPIs). Although social distancing regulations were quickly strengthened, the outbreak continued to grow, causing increasing delays in tracing and testing. Further regulations were introduced, plus 'targeted testing' services for at-risk groups. Estimating the impact of individual NPIs could provide lessons about how outbreaks can be controlled without radical lockdown. However, the changing delays in confirmation time challenge current modelling methods. We used a novel approach aimed at disentangling and quantifying the effects of individual interventions.

METHODS

We incorporated the causes of delays in tracing and testing (i.e. load-efficiency relationship) and the consequences from such delays (i.e. the proportion of un-traced cases and the proportion of traced-cases with confirmation delay) into a deterministic transmission model, which was fitted to the daily number of cases with and without an epi‑link (an indication of being contact-traced). The effect of each NPI was then calculated.

FINDINGS

The model estimated that after earlier relaxation of regulations, Re rose from 0.7 to 3.2. Restoration of social distancing to the previous state only reduced Re to 1.3, because of increased delay in confirmation caused by load on the contact-tracing system. However, Re decreased by 20.3% after the introduction of targeted testing and by 17.5% after extension of face-mask rules, reducing Re to 0.9 and suppressing the outbreak. The output of the model without incorporation of delay failed to capture important features of transmission and Re.

INTERPRETATION

Changing delay in confirmation has a significant impact on disease transmission and estimation of transmissibility. This leads to a clear recommendation that delay should be monitored and mitigated during outbreaks, and that delay dynamics should be incorporated into models to assess the effects of NPIs.

FUNDING

City University of Hong Kong and Health and Medical Research Fund.

Cost-effectiveness of anti-SARS-CoV-2 antibody diagnostic tests in Brazil

BACKGROUND

Although serologic tests for COVID-19 diagnosis are rarely indicated nowadays, they remain commercially available and widely used in Brazil. The objective of this study was to evaluate the cost-effectiveness of anti-SARS-CoV-2antibody diagnostic tests for COVID-19 in Brazil.

METHODS

Eleven commercially available diagnostic tests, comprising five lateral-flow immunochromatographic assays (LFAs) and six immunoenzymatic assays (ELISA) were analyzed from the perspective of the Brazilian Unified Health System.

RESULTS

The direct costs of LFAs ranged from US$ 11.42 to US$ 17.41and of ELISAs, from US$ 6.59 to US$ 10.31. Considering an estimated disease prevalence between 5% and 10%, the anti-SARS-CoV-2 ELISA (IgG) was the most cost-effective test, followed by the rapid One Step COVID-19 Test, at an incremental cost-effectiveness ratio of US$ 2.52 and US$ 1.26 per properly diagnosed case, respectively. Considering only the LFAs, at the same prevalence estimates, two tests, the COVID-19 IgG/IgM and the One Step COVID-19 Test, showed high effectiveness at similar costs. For situations where the estimated probability of disease is 50%, the LFAs are more costly and less effective alternatives.

CONCLUSIONS

Nowadays there are few indications for the use of serologic tests in the diagnosis of COVID-19 and numerous commercially available tests, with marked differences are observed among them. In general, LFA tests are more cost-effective for estimated low-COVID-19-prevalences, while ELISAs are more cost-effective for high-pretest-probability scenarios.

Performance of Three Tests for SARS-CoV-2 on a University Campus Estimated Jointly with Bayesian Latent Class Modeling

Accurate tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been critical in efforts to control its spread. The accuracy of tests for SARS-CoV-2 has been assessed numerous times, usually in reference to a gold standard diagnosis. One major disadvantage of that approach is the possibility of error due to inaccuracy of the gold standard, which is especially problematic for evaluating testing in a real-world surveillance context. We used an alternative approach known as Bayesian latent class modeling (BLCM), which circumvents the need to designate a gold standard by simultaneously estimating the accuracy of multiple tests. We applied this technique to a collection of 1,716 tests of three types applied to 853 individuals on a university campus during a 1-week period in October 2020. We found that reverse transcriptase PCR (RT-PCR) testing of saliva samples performed at a campus facility had higher sensitivity (median, 92.3%; 95% credible interval [CrI], 73.2 to 99.6%) than RT-PCR testing of nasal samples performed at a commercial facility (median, 85.9%; 95% CrI, 54.7 to 99.4%). The reverse was true for specificity, although the specificity of saliva testing was still very high (median, 99.3%; 95% CrI, 98.3 to 99.9%). An antigen test was less sensitive and specific than both of the RT-PCR tests, although the sample sizes with this test were small and the statistical uncertainty was high. These results suggest that RT-PCR testing of saliva samples at a campus facility can be an effective basis for surveillance screening to prevent SARS-CoV-2 transmission in a university setting. IMPORTANCE Testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been vitally important during the COVID-19 pandemic. There are a variety of methods for testing for this virus, and it is important to understand their accuracy in choosing which one might be best suited for a given application. To estimate the accuracy of three different testing methods, we used a data set collected at a university that involved testing the same samples with multiple tests. Unlike most other estimates of test accuracy, we did not assume that one test was perfect but instead allowed for some degree of inaccuracy in all testing methods. We found that molecular tests performed on saliva samples at a university facility were similarly accurate as molecular tests performed on nasal samples at a commercial facility. An antigen test appeared somewhat less accurate than the molecular tests, but there was high uncertainty about that.