Substantial underestimation of SARS-CoV-2 infection in the United States

Increased generosity under COVID-19 threat

In the face of crises-wars, pandemics, and natural disasters-both increased selfishness and increased generosity may emerge. In this paper, we study the relationship between the presence of COVID-19 threat and generosity using a four-year longitudinal dataset (N = 696,942) capturing real donations made before and during the pandemic, as well as allocations from a 6-month dictator game study (N = 1003 participants) during the early months of the pandemic. Consistent with the notion of "catastrophe compassion" and contrary to some prior research showing a tendency toward self-interested behavior under threat, individuals across both datasets exhibited greater financial generosity when their county experienced COVID-19 threat. While we find that the presence of threat impacted individual giving, behavior was not sensitive to threat level. Our findings have significant societal implications and advance our understanding of economic and psychological theories of social preferences under threat.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

COVID-19 severity: A new approach to quantifying global cases and deaths

As the COVID-19 pandemic has progressed, so too has the recognition that cases and deaths have been underreported, perhaps vastly so. Here, we present an econometric strategy to estimate the true number of COVID-19 cases and deaths for 61 and 56 countries, respectively, from 1 January 2020 to 3 November 2020. Specifically, we estimate a 'structural' model based on the SIR epidemiological model extended to incorporate underreporting. The results indicate significant underreporting by magnitudes that align with existing research and conjectures by public health experts. While our approach requires some strong assumptions, these assumptions are very different from the equally strong assumptions required by other approaches addressing underreporting in the assessment of the extent of the pandemic. Thus, we view our approach as a complement to existing methods.

Associations of Stay-at-Home Order Enforcement With COVID-19 Population Outcomes: An Interstate Statistical Analysis

In the United States, state governors initially enacted coronavirus diseases 2019 (COVID-19)-mitigation policies with limited epidemiologic data. One prevailing legislative approach, from March to May 2020, was the implementation of "stay-at-home" (SAH) executive orders. Although social distancing was encouraged, SAH orders varied between states, and the associations between potential legal prosecution and COVID-19 outcomes are currently unknown. Here, we provide empirical evidence on how executive enforcement of movement restrictions may influence population health during an infectious disease outbreak. A generalized linear model with negative binomial regression family compared COVID-19 outcomes in states with law-enforceable stay-at-home (eSAH) orders versus those with unenforceable or no SAH orders (uSAH), controlling for demographic factors, socioeconomic influences, health comorbidities, and social distancing. COVID-19 incidence was less by 1.22 cases per day per capita in eSAH states compared with uSAH states (coefficient = -1.22, 95% confidence interval (CI): -1.83, -0.61; P < 0.001), and each subsequent day without an eSAH order was associated with a 0.03 incidence increase (coefficient = 0.03, 95% CI: 0.03, 0.04; P < 0.001). Daily mortality was 1.96 less for eSAH states per capita (coefficient = -1.96, 95% CI: -3.25, -0.68; P = 0.004). Our findings suggest allowing the enforcement of public health violations, compared with community education alone, is predictive of improved COVID-19 outcomes.

SARS-CoV-2 infection among educational staff in Berlin, Germany, June to December 2020

BackgroundSARS-CoV-2 infections in preschool and school settings potentially bear occupational risks to educational staff.AimWe aimed to assess the prevalence of SARS-CoV-2 infection in teachers and preschool educators and at identifying factors associated with infection.MethodsWe analysed cross-sectional data derived from 17,448 voluntary, PCR-based screening tests of asymptomatic educational staff in Berlin, Germany, between June and December 2020 using descriptive statistics and a logistic regression model.ResultsParticipants were largely female (73.0%), and median age was 41 years (range: 18-78). Overall, SARS-CoV-2 infection proportion was 1.2% (95% CI: 1.0-1.4). Proportion of positive tests in educational staff largely followed community incidence until the start of the second pandemic wave, when an unsteady plateau was reached. Then, the proportion of positive tests in a (concurrent) population survey was 0.9% (95% CI: 0.6-1.4), 1.2% (95% CI: 0.8-1.8) in teachers and 2.6% (95% CI: 1.6-4.0) in preschool educators. Compared with teachers, increased odds of infection were conferred by being a preschool educator (adjusted odds ratio (aOR): 1.6; 95% CI: 1.3-2.0) and by contact with a SARS-CoV-2 infected individual outside of work (aOR: 3.0; 95% CI: 1.5-5.5). In a step-wise backward selection, the best set of associated factors with SARS-CoV-2 infection involved age, occupation, and calendar week.ConclusionsThese results indicate that preschool educators bear increased odds of SARS-CoV-2 infection compared with teachers. At the same time, the private environment appeared to be a relevant source of SARS-CoV-2 infection for educational staff in 2020.

Post-lockdown changes of age-specific susceptibility and its correlation with adherence to social distancing measures

Social distancing measures are effective in reducing overall community transmission but much remains unknown about how they have impacted finer-scale dynamics. In particular, much is unknown about how changes of contact patterns and other behaviors including adherence to social distancing, induced by these measures, may have impacted finer-scale transmission dynamics among different age groups. In this paper, we build a stochastic age-specific transmission model to systematically characterize the degree and variation of age-specific transmission dynamics, before and after lifting the lockdown in Georgia, USA. We perform Bayesian (missing-)data-augmentation model inference, leveraging reported age-specific case, seroprevalence and mortality data. We estimate that overall population-level transmissibility was reduced to 41.2% with 95% CI [39%, 43.8%] of the pre-lockdown level in about a week of the announcement of the shelter-in-place order. Although it subsequently increased after the lockdown was lifted, it only bounced back to 62% [58%, 67.2%] of the pre-lockdown level after about a month. We also find that during the lockdown susceptibility to infection increases with age. Specifically, relative to the oldest age group (> 65+), susceptibility for the youngest age group (0–17 years) is 0.13 [0.09, 0.18], and it increases to 0.53 [0.49, 0.59] for 18–44 and 0.75 [0.68, 0.82] for 45–64. More importantly, our results reveal clear changes of age-specific susceptibility (defined as average risk of getting infected during an infectious contact incorporating age-dependent behavioral factors) after the lockdown was lifted, with a trend largely consistent with reported age-specific adherence levels to social distancing and preventive measures. Specifically, the older groups (> 45) (with the highest levels of adherence) appear to have the most significant reductions of susceptibility (e.g., post-lockdown susceptibility reduced to 31.6% [29.3%, 34%] of the estimate before lifting the lockdown for the 6+ group). Finally, we find heterogeneity in case reporting among different age groups, with the lowest rate occurring among the 0–17 group (9.7% [6.4%, 19%]). Our results provide a more fundamental understanding of the impacts of stringent lockdown measures, and finer evidence that other social distancing and preventive measures may be effective in reducing SARS-CoV-2 transmission. These results may be exploited to guide more effective implementations of these measures in many current settings (with low vaccination rate globally and emerging variants) and in future potential outbreaks of novel pathogens.

Registered clinical trials investigating treatment of long COVID: a scoping review and recommendations for research

Background

A considerable proportion of individuals report persistent, debilitating and disparate symptoms despite resolution of acute COVID-19 infection (i.e. long COVID). Numerous registered clinical trials investigating treatment of long COVID are expected to be completed in 2021–2022. The aim of this review is to provide a scope of the candidate treatments for long COVID. A synthesis of ongoing long COVID clinical trials can inform methodologic approaches for future studies and identify key research vistas.

Methods

Scoping searches were conducted on multiple national and international clinical trial registries. Interventional trials testing treatments for long COVID were selected. The search timeline was from database inception to 28 July 2021.

Results

This scoping review included 59 clinical trial registration records from 22 countries with a total projected enrolment of 6718. Considerable heterogeneity was exhibited amongst component records with respect to the characterization of long COVID (i.e. name, symptoms- including frequency, intensity, trajectory and duration- mode of ascertainment, and definition of acute phase). In addition, the majority of proposed interventions were non-pharmacological and either targeted multiple long COVID symptoms simultaneously, or focussed on treatment of respiratory/pulmonary sequelae. Multiple interventions targeted inflammation, as well as tissue oxygenation and cellular recovery, and several interventions were repurposed from analogous conditions.

Conclusions

The results of this scoping review investigating ongoing clinical trials testing candidate treatments for long COVID suggest that a greater degree of definitional stringency and homogeneity is needed insofar as the characterization of long COVID and inclusion/exclusion criteria.

Prevalence of current and past COVID-19 in Ohio adults

Purpose To estimate the prevalence of current and past COVID-19 in Ohio adults. Methods We used stratified, probability-proportionate-to-size cluster sampling. During July 2020, we enrolled 727 randomly-sampled adult English- and Spanish-speaking participants through a household survey. Participants provided nasopharyngeal swabs and blood samples to detect current and past COVID-19. We used Bayesian latent class models with multilevel regression and poststratification to calculate the adjusted prevalence of current and past COVID-19. We accounted for the potential effects of non-ignorable non-response bias. Results The estimated statewide prevalence of current COVID-19 was 0.9% (95% credible interval: 0.1%-2.0%), corresponding to ∼85,000 prevalent infections (95% credible interval: 6,300-177,000) in Ohio adults during the study period. The estimated statewide prevalence of past COVID-19 was 1.3% (95% credible interval: 0.2%-2.7%), corresponding to ∼118,000 Ohio adults (95% credible interval: 22,000-240,000). Estimates did not change meaningfully due to non-response bias. Conclusions Total COVID-19 cases in Ohio in July 2020 were approximately 3.5 times as high as diagnosed cases. The lack of broad COVID-19 screening in the United States early in the pandemic resulted in a paucity of population-representative prevalence data, limiting the ability to measure the effects of statewide control efforts.

Targeting lactate metabolism and glycolytic pathways in the tumor microenvironment by natural products: A promising strategy in combating cancer

Anticancer drugs are not purely effective because of their toxicity, side effects, high cost, inaccessibility, and associated resistance. On the other hand, cancer is a complex public health problem that could intelligently adopt different signaling pathways and alter the body's metabolism to escape from the immune system. One of the cancer strategies to metastasize is modifying pH in the tumor microenvironment, ranging between 6.5 and 6.9. As a powerful determiner, lactate is responsible for this acidosis. It is involved in immune stimulation, including innate and adaptive immunity, apoptotic-related factors (Bax/Bcl-2, caspase), and glycolysis pathways (e.g., GLUT-1, PKM2, PFK, HK2, MCT-1, and LDH). Lactate metabolism, in turn, is interconnected with several dysregulated signaling mediators, including PI3K/Akt/mTOR, AMPK, NF-κB, Nrf2, JAK/STAT, and HIF-1α. Because of lactate's emerging and critical role, targeting lactate production and its transporters is important for preventing and managing tumorigenesis. Hence, exploring and developing novel promising anticancer agents to minimize human cancers is urgent. Based on numerous studies, natural secondary metabolites as multi-target alternative compounds with health-promoting properties possess more high effectiveness and low side effects than conventional agents. Besides, the mechanism of multi-targeted natural sources is related to lactate production and cancer-associated cross-talked factors. This review focuses on targeting the lactate metabolism/transporters, and lactate-associated mediators, including glycolytic pathways. Besides, interconnected mediators to lactate metabolism are also targeted by natural products. Accordingly, plant-derived secondary metabolites are introduced as alternative therapies in combating cancer through modulating lactate metabolism and glycolytic pathways.

Fatigue and cognitive impairment in Post-COVID-19 Syndrome: A systematic review and meta-analysis

IMPORTANCE

COVID-19 is associated with clinically significant symptoms despite resolution of the acute infection (i.e., post-COVID-19 syndrome). Fatigue and cognitive impairment are amongst the most common and debilitating symptoms of post-COVID-19 syndrome.

OBJECTIVE

To quantify the proportion of individuals experiencing fatigue and cognitive impairment 12 or more weeks following COVID-19 diagnosis, and to characterize the inflammatory correlates and functional consequences of post-COVID-19 syndrome.

DATA SOURCES

Systematic searches were conducted without language restrictions from database inception to June 8, 2021 on PubMed/MEDLINE, The Cochrane Library, PsycInfo, Embase, Web of Science, Google/Google Scholar, and select reference lists.

STUDY SELECTION

Primary research articles which evaluated individuals at least 12 weeks after confirmed COVID-19 diagnosis and specifically reported on fatigue, cognitive impairment, inflammatory parameters, and/or functional outcomes were selected.

DATA EXTRACTION & SYNTHESIS

Two reviewers independently extracted published summary data and assessed methodological quality and risk of bias. A meta-analysis of proportions was conducted to pool Freeman-Tukey double arcsine transformed proportions using the random-effects restricted maximum-likelihood model.

MAIN OUTCOMES & MEASURES

The co-primary outcomes were the proportions of individuals reporting fatigue and cognitive impairment, respectively, 12 or more weeks following COVID-19 infection. The secondary outcomes were inflammatory correlates and functional consequences associated with post-COVID-19 syndrome.

RESULTS

The literature search yielded 10,979 studies, and 81 studies were selected for inclusion. The fatigue meta-analysis comprised 68 studies, the cognitive impairment meta-analysis comprised 43 studies, and 48 studies were included in the narrative synthesis. Meta-analysis revealed that the proportion of individuals experiencing fatigue 12 or more weeks following COVID-19 diagnosis was 0.32 (95% CI, 0.27, 0.37; p < 0.001; n = 25,268; I2 = 99.1%). The proportion of individuals exhibiting cognitive impairment was 0.22 (95% CI, 0.17, 0.28; p < 0.001; n = 13,232; I2 = 98.0). Moreover, narrative synthesis revealed elevations in proinflammatory markers and considerable functional impairment in a subset of individuals.

CONCLUSIONS & RELEVANCE

A significant proportion of individuals experience persistent fatigue and/or cognitive impairment following resolution of acute COVID-19. The frequency and debilitating nature of the foregoing symptoms provides the impetus to characterize the underlying neurobiological substrates and how to best treat these phenomena.

STUDY REGISTRATION

PROSPERO (CRD42021256965).

Impaired glucose regulation, SARS-CoV-2 infections and adverse COVID-19 outcomes

Impaired glucose regulation (IGR) is common world-wide, and is correlated with Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the virus that causes Coronavirus disease 2019 (COVID-19). However, no systematic reviews are available on the topic, and little is known about the strength of the evidence underlying published associations. The current systematic review identified consistent, reproducible associations but several limitations were observed including: (1) a consistent lack of robust confounder adjustment for risk factors collected prior to infection; (2) lack of data on insulin resistance or glycemia measures [Hemoglobin A1c (HbA1c) or glucose]; (3) few studies considering insulin resistance, glucose or HbA1c values in the clinically normal range as a predictor of SARS-CoV-2 risk; (4) few studies assessed the role of IGR as a risk factor for infection among initially uninfected samples; (5) a paucity of population-based data considering SARS-CoV-2 as a risk factor for the onset of IGR. While diabetes status is a clear predictor of poor prognosis following a SARS-CoV-2 infection, causal conclusions are limited. It is uncertain whether interventions targeting dysglycemia to improve SARS-CoV-2 outcomes have potential to be effective, or if risk assessment should include biomarkers of diabetes risk (ie, insulin and glucose or HbA1c) among diabetes-free individuals. Future studies with robust risk factor data collection, among population-based samples with pre-pandemic assessments will be important to inform these questions.

Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic: a modelling study

BACKGROUND

Numerous countries have imposed strict travel restrictions during the COVID-19 pandemic, contributing to a large socioeconomic burden. The long quarantines that have been applied to contacts of cases may be excessive for travel policy.

METHODS

We developed an approach to evaluate imminent countrywide COVID-19 infections after 0-14-day quarantine and testing. We identified the minimum travel quarantine duration such that the infection rate within the destination country did not increase compared to a travel ban, defining this minimum quarantine as "sufficient."

FINDINGS

We present a generalised analytical framework and a specific case study of the epidemic situation on November 21, 2021, for application to 26 European countries. For most origin-destination country pairs, a three-day or shorter quarantine with RT-PCR or antigen testing on exit suffices. Adaptation to the European Union traffic-light risk stratification provided a simplified policy tool. Our analytical approach provides guidance for travel policy during all phases of pandemic diseases.

INTERPRETATION

For nearly half of origin-destination country pairs analysed, travel can be permitted in the absence of quarantine and testing. For the majority of pairs requiring controls, a short quarantine with testing could be as effective as a complete travel ban. The estimated travel quarantine durations are substantially shorter than those specified for traced contacts.

FUNDING

EasyJet (JPT and APG), the Elihu endowment (JPT), the Burnett and Stender families' endowment (APG), the Notsew Orm Sands Foundation (JPT and APG), the National Institutes of Health (MCF), Canadian Institutes of Health Research (SMM) and Natural Sciences and Engineering Research Council of Canada EIDM-MfPH (SMM).

Seroprevalence, Prevalence, and Genomic Surveillance: Monitoring the Initial Phases of the SARS-CoV-2 Pandemic in Betim, Brazil

The COVID-19 pandemic has created an unprecedented need for epidemiological monitoring using diverse strategies. We conducted a project combining prevalence, seroprevalence, and genomic surveillance approaches to describe the initial pandemic stages in Betim City, Brazil. We collected 3239 subjects in a population-based age-, sex- and neighborhood-stratified, household, prospective; cross-sectional study divided into three surveys 21 days apart sampling the same geographical area. In the first survey, overall prevalence (participants positive in serological or molecular tests) reached 0.46% (90% CI 0.12–0.80%), followed by 2.69% (90% CI 1.88–3.49%) in the second survey and 6.67% (90% CI 5.42–7.92%) in the third. The underreporting reached 11, 19.6, and 20.4 times in each survey. We observed increased odds to test positive in females compared to males (OR 1.88 95% CI 1.25–2.82), while the single best predictor for positivity was ageusia/anosmia (OR 8.12, 95% CI 4.72–13.98). Thirty-five SARS-CoV-2 genomes were sequenced, of which 18 were classified as lineage B.1.1.28, while 17 were B.1.1.33. Multiple independent viral introductions were observed. Integration of multiple epidemiological strategies was able to adequately describe COVID-19 dispersion in the city. Presented results have helped local government authorities to guide pandemic management.

Vaccinating Children against COVID-19: Commentary and Mathematical Modeling

With the recent licensure of mRNA vaccines against COVID-19 in the 5- to 11-year-old age group, the public health impact of a childhood immunization campaign is of interest. Using a mathematical epidemiological model, we project that childhood vaccination carries minimal risk and yields modest public health benefits. These include large relative reductions in child morbidity and mortality, although the absolute reduction is small because these events are rare. Furthermore, the model predicts "altruistic" absolute reductions in adult cases, hospitalizations, and mortality. However, vaccinating children to benefit adults should be considered from an ethical as well as a public health perspective. From a global health perspective, an additional ethical consideration is the justice of giving priority to children in high-income settings at low risk of severe disease while vaccines have not been made available to vulnerable adults in low-income settings. IMPORTANCE Countries have recently begun implementation of childhood vaccination against SARS-CoV-2 with the Pfizer/BioNTech mRNA vaccine in children 5 to 11 years of age. Because SARS-CoV-2 disease severity is remarkably age dependent, vaccinating children may have modest public health benefits, relative to the unequivocal benefit of vaccinating vulnerable older adults. Furthermore, vaccinating children to "altruistically" increase herd immunity should be considered from an ethical as well as a public health perspective. An additional question is related to global social justice: should priority be given to vaccinating children in high-income settings while older adult populations in low-resource settings have limited access to vaccine? To address the risks and benefits of childhood vaccination, we provide a balanced commentary, supported by a mathematical epidemiological model, using Australia and Alberta, Canada, as case studies. We give highlights of the modeling findings in the commentary and include details in the supplemental materials for interested readers.

Prevalence of Coronavirus Disease 2019 (COVID-19) in Different Clinical Stages before the National COVID-19 Vaccination Programme in Malaysia: A Systematic Review and Meta-Analysis

More than 1.75 million COVID-19 infections and 16 thousand associated deaths have been reported in Malaysia. A meta-analysis on the prevalence of COVID-19 in different clinical stages before the National COVID-19 Vaccination Program in Malaysia is still lacking. To address this, the disease severity of a total of 215 admitted COVID-19 patients was initially recorded in the early phase of this study, and the data were later pooled into a meta-analysis with the aim of providing insight into the prevalence of COVID-19 in 5 different clinical stages during the outset of the COVID-19 pandemic in Malaysia. We have conducted a systematic literature search using PubMed, Web of Science, Scopus, ScienceDirect, and two preprint databases (bioRxiv and medRxiv) for relevant studies with specified inclusion and exclusion criteria. The quality assessment for the included studies was performed using the Newcastle-Ottawa Scale. The heterogeneity was examined with an I2 index and a Q-test. Funnel plots and Egger's tests were performed to determine publication bias in this meta-analysis. Overall, 5 studies with 6375 patients were included, and the pooled prevalence rates in this meta-analysis were calculated using a random-effect model. The highest prevalence of COVID-19 in Malaysia was observed in Stage 2 cases (32.0%), followed by Stage 1 (27.8%), Stage 3 (17.1%), Stage 4 (7.6%), and Stage 5 (3.4%). About two-thirds of the number of cases have at least one morbidity, with the highest percentage of hypertension (66.7%), obesity (55.5%), or diabetes mellitus (33.3%) in Stage 5 patients. In conclusion, this meta-analysis suggested a high prevalence of COVID-19 occurred in Stage 2. The prevalence rate in Stage 5 appeared to be the lowest among COVID-19 patients before implementing the vaccination program in Malaysia. These meta-analysis data are critically useful for designing screening and vaccination programs and improving disease management in the country.

Antibody Response to SARS-CoV-2 Infection and Vaccination in COVID-19-naïve and Experienced Individuals

Understanding the magnitude of responses to vaccination during the ongoing SARS-CoV-2 pandemic is essential for ultimate mitigation of the disease. Here, we describe a cohort of 102 subjects (70 COVID-19-naïve, 32 COVID-19-experienced) who received two doses of one of the mRNA vaccines (BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna)). We document that a single exposure to antigen via infection or vaccination induces a variable antibody response which is affected by age, gender, race, and co-morbidities. In response to a second antigen dose, both COVID-19-naïve and experienced subjects exhibited elevated levels of anti-spike and SARS-CoV-2 neutralizing activity; however, COVID-19-experienced individuals achieved higher antibody levels and neutralization activity as a group. The COVID-19-experienced subjects exhibited no significant increase in antibody or neutralization titer in response to the second vaccine dose (i.e., third antigen exposure). Finally, we found that COVID-19-naïve individuals who received the Moderna vaccine exhibited a more robust boost response to the second vaccine dose (p = 0.004) as compared to the response to Pfizer-BioNTech. Ongoing studies with this cohort will continue to contribute to our understanding of the range and durability of responses to SARS-CoV-2 mRNA vaccines.

Analytical observational study evaluating global pandemic preparedness and the effectiveness of early COVID-19 responses in Ethiopia, Nigeria, Singapore, South Korea, Sweden, Taiwan, UK and USA

OBJECTIVES

An analysis of early country-specific COVID-19 strategies and the impact of policies, healthcare resources and cultural influences on their effectiveness.

DESIGN

Analytical observational study.

SETTING

USA, UK, Sweden, South Korea, Singapore, Taiwan, Ethiopia and Nigeria.

MAIN OUTCOME MEASURES

OxCGRT indices were used to quantify variations in governments' responses, and effectiveness was measured by the number of deaths as a proportion of the population. Hofstede's cultural dimensions, and the availability of healthcare resources, were analysed for their potential impact on effectiveness.

RESULTS

Effective strategies reflect factors such as speed of governmental intervention, cultural norms, population demographics and available resources. While biases, confounders and lack of data at the beginning of the pandemic make inferences challenging, publicly available data suggest that South Korea, Singapore and Taiwan were most successful through rapid identification and isolation of cases, and effective contact tracing systems.

CONCLUSION

The rapid spread of the highly transmissible SARS-CoV-2 virus took many countries by surprise and the delayed global response contributed to the severity of the COVID-19 pandemic. The speed at which strategies were implemented is highly correlated to the number of deaths. Factors such as cultural norms and healthcare resources impact effectiveness significantly, implying that implementation of a global 'one size fits all' approach is challenging. Global preparedness should focus on effective surveillance and preparedness strategies to enable timely identification and containment of future threats.

SARS-CoV-2 RT-qPCR Test Detection Rates Are Associated with Patient Age, Sex, and Time since Diagnosis

Quantifying the detection rate of the widely used quantitative RT-PCR (RT-qPCR) test for severe acute respiratory syndrome coronavirus 2 and its dependence on patient demographic characteristics and disease progression is key in designing epidemiologic strategies. Analyzing 843,917 test results of 521,696 patients, a "positive period" was defined for each patient between diagnosis of coronavirus disease 2019 and the last positive test result. The fraction of positive test results within this period was then used to estimate detection rate. Regression analyses were used to determine associations of detection with time of sampling after diagnosis, patient demographic characteristics, and viral RNA copy number based on RT-qPCR cycle threshold values of the next positive test result. The overall detection rate in tests performed within 14 days after diagnosis was 83.1%. This rate was higher at days 0 to 5 after diagnosis (89.3%). Furthermore, detection rate was strongly associated with age and sex. Finally, the detection rate with the Allplex 2019-nCoV RT-qPCR kit was associated, at the single-patient level, with viral RNA copy number (P < 10-9). These results show that the reliability of the test result is reduced in later days as well as for women and younger patients, in whom the viral loads are typically lower.

Equitable access to COVID-19 vaccines makes a life-saving difference to all countries

Despite broad agreement on the negative consequences of vaccine inequity, the distribution of COVID-19 vaccines is imbalanced. Access to vaccines in high-income countries (HICs) is far greater than in low- and middle-income countries (LMICs). As a result, there continue to be high rates of COVID-19 infections and deaths in LMICs. In addition, recent mutant COVID-19 outbreaks may counteract advances in epidemic control and economic recovery in HICs. To explore the consequences of vaccine (in)equity in the face of evolving COVID-19 strains, we examine vaccine allocation strategies using a multistrain metapopulation model. Our results show that vaccine inequity provides only limited and short-term benefits to HICs. Sharper disparities in vaccine allocation between HICs and LMICs lead to earlier and larger outbreaks of new waves. Equitable vaccine allocation strategies, in contrast, substantially curb the spread of new strains. For HICs, making immediate and generous vaccine donations to LMICs is a practical pathway to protect everyone.

Three waves changes, new variant strains, and vaccination effect against COVID-19 pandemic

It has been more than one year since the first case of the coronaviruses was infected by COVID-19 in China. The world witnessed three waves of the corona virus till now, and more upcoming is expected, whereas several challenges are presented. Empirical data displayed that the features of the virus effects do vary between the three periods. The severity of the disease, differences in symptoms, attitudes of the people have been reported, although the comparative characteristics of the three waves still keep essentially indefinite. In contrast, the sense of danger toward the cries gradually decreases in most countries. This may be due to some factors, including the approved vaccines, introducing alternative plans from politicians to control and deal with the epidemic, and decreasing the mortality rates. However, the alarm voice started to rise again with the appearance of new variant strains with several mutations in the virus. Several more questions began to be asked without sufficient answers. Mutations in COVID-19 have introduced an extreme challenge in preventing and treating SARS-COV-2. The essential feature for mutations is producing new variants known by high tensmibility, disturbing the viral fitness, and enhancing the virus replication. One of the variants that has emerged recently is the Delta variant (B.1.617.2), which was firstly detected in India. In November 2021, a more ferocious mutant appeared in South Africa, also called omicron (B.1.1.529). These mutants grabbed world attention because of their higher transmissibility than the progenitor variants and spread rapidly. Several information about the virus are still confusing and remains secret. There are eight approved vaccines in the market; however, the investigation race about their effect against reinfection and their role against the new variants is still under investigation. Furthermore, this is the first time vaccinating against COVID-19, so the question remains: Will we need an annual dose of the corona vaccines, and the side effects don't been observed till now?

Practical Indicators for Risk of Airborne Transmission in Shared Indoor Environments and Their Application to COVID-19 Outbreaks

Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (H_r) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission.

Practical Indicators for Risk of Airborne Transmission in Shared Indoor Environments and Their Application to COVID-19 Outbreaks

Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (H_r) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission.

Spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level

In recent history, Coronavirus Disease 2019 (COVID-19) is one of the worst infectious disease outbreaks affecting humanity. The World Health Organization has defined the outbreak of COVID-19 as a pandemic, and the massive growth of the number of infected cases in a short time has caused enormous pressure on medical systems. Mexico surpassed 3.7 million confirmed infections and 285,000 deaths on October 23, 2021. We analysed the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We computed weekly Moran’s I index to assess spatial autocorrelation over time and identify clusters of the disease using the “flexibly shaped spatial scan” approach. Finally, we compared Euclidean, cost, resistance distances and gravitational model to select the best-suited approach to predict inter-municipality contagion. We found that COVID-19 pandemic in Mexico is characterised by clusters evolving in space and time as parallel epidemics. The gravitational distance was the best model to predict newly infected municipalities though the predictive power was relatively low and varied over time. This study helps us understand the spread of the epidemic over the Mexican territory and gives insights to model and predict the epidemic behaviour.

On some fundamental challenges in monitoring epidemics

Epidemic models often reflect characteristic features of infectious spreading processes by coupled nonlinear differential equations considering different states of health (such as susceptible, infectious or recovered). This compartmental modelling approach, however, delivers an incomplete picture of the dynamics of epidemics, as it neglects stochastic and network effects, and the role of the measurement process, on which the estimation of epidemiological parameters and incidence values relies. In order to study the related issues, we combine established epidemiological spreading models with a measurement model of the testing process, considering the problems of false positives and false negatives as well as biased sampling. Studying a model-generated ground truth in conjunction with simulated observation processes (virtual measurements) allows one to gain insights into the fundamental limitations of purely data-driven methods when assessing the epidemic situation. We conclude that epidemic monitoring, simulation, and forecasting are wicked problems, as applying a conventional data-driven approach to a complex system with nonlinear dynamics, network effects and uncertainty can be misleading. Nevertheless, some of the errors can be corrected for, using scientific knowledge of the spreading dynamics and the measurement process. We conclude that such corrections should generally be part of epidemic monitoring, modelling and forecasting efforts. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.

A statistical model of COVID-19 testing in populations: effects of sampling bias andtesting errors

We develop a statistical model for the testing of disease prevalence in a population. The model assumes a binary test result, positive or negative, but allows for biases in sample selection and both type I (false positive) and type II (false negative) testing errors. Our model also incorporates multiple test types and is able to distinguish between retesting and exclusion after testing. Our quantitative framework allows us to directly interpret testing results as a function of errors and biases. By applying our testing model to COVID-19 testing data and actual case data from specific jurisdictions, we are able to estimate and provide uncertainty quantification of indices that are crucial in a pandemic, such as disease prevalence and fatality ratios. This article is part of the theme issue 'Data science approach to infectious disease surveillance'.

Framework for enhancing the estimation of model parameters for data with a high level of uncertainty

Reliable data are essential to obtain adequate simulations for forecasting the dynamics of epidemics. In this context, several political, economic, and social factors may cause inconsistencies in the reported data, which reflect the capacity for realistic simulations and predictions. In the case of COVID-19, for example, such uncertainties are mainly motivated by large-scale underreporting of cases due to reduced testing capacity in some locations. In order to mitigate the effects of noise in the data used to estimate parameters of models, we propose strategies capable of improving the ability to predict the spread of the diseases. Using a compartmental model in a COVID-19 study case, we show that the regularization of data by means of Gaussian process regression can reduce the variability of successive forecasts, improving predictive ability. We also present the advantages of adopting parameters of compartmental models that vary over time, in detriment to the usual approach with constant values.

Estimating pediatric cases of COVID-19 over time in the United States: Filling in a gap in public use data

Background

COVID-19 continues to disturb nearly all aspects of life, leaving us striving to reach herd immunity. Currently, only weekly standardized incidence rate data per age group are publicly available, limiting assessment of herd immunity. Here, we estimate the time-series case counts of COVID-19 among age groups currently ineligible for vaccination in the USA.

Methods

This was a secondary analysis of publicly available data. COVID-19 case counts by age groups were computed using incidence rate data from the CDC and population estimates from the US Census Bureau. We also created a web-based application to allow on demand analysis.

Results

A total of 78 weeks of data were incorporated in the analysis, suggesting the highest peak in cases within the 5–11-year age group on week ending 2021-01-09 (n = 61,095) followed by the 12-15-year age group (n = 58,093). As of July 24, 2021, case counts in the 5-11-year age group have expanded beyond other groups rapidly.

Discussion

This study suggests it is possible to estimate pediatric case counts of COVID-19. National agencies should report COVID-19 time series case counts for pediatric age cohorts. These data will enhance our ability to estimate the population at risk and tailor interventions accordingly.

Adherence to Social-Distancing and Personal Hygiene Behavior Guidelines and Risk of COVID-19 Diagnosis: Evidence From the Understanding America Study

Objectives. To assess the association between individual-level adherence to social-distancing and personal hygiene behaviors recommended by public health experts and subsequent risk of COVID-19 diagnosis in the United States. Methods. Data are from waves 7 through 26 (June 10, 2020-April 26, 2021) of the Understanding America Study COVID-19 survey. We used Cox models to assess the relationship between engaging in behaviors considered high risk and risk of COVID-19 diagnosis. Results. Individuals engaging in behaviors indicating lack of adherence to social-distancing guidelines, especially those related to large gatherings or public interactions, had a significantly higher risk of COVID-19 diagnosis than did those who did not engage in these behaviors. Each additional risk behavior was associated with a 9% higher risk of COVID-19 diagnosis (hazard ratio [HR] = 1.09; 95% confidence interval [CI] = 1.05, 1.13). Results were similar after adjustment for sociodemographic characteristics and local infection rates. Conclusions. Personal mitigation behaviors appear to influence the risk of COVID-19, even in the presence of social factors related to infection risk. Public Health Implications. Our findings emphasize the importance of individual behaviors for preventing COVID-19, which may be relevant in contexts with low vaccination. (Am J Public Health. 2022;112(1):169-178. https://doi.org/10.2105/AJPH.2021.306565).

[Personality traits as risk factors for the development of cognitive impairment and affective symptoms in patients with COVID-19]

OBJECTIVE

To identify possible associations between premorbid personality traits and cognitive impairment and affective symptoms in patients who have recovered from COVID-19.

MATERIAL AND METHODS

The study included 30 people with the so-called post-COVID syndrome. The diagnosis of COVID-19 was previously confirmed by laboratory tests in each patient. The control group included 15 healthy individuals. The Hospital Anxiety and Depression Scale was used to assess depression and anxiety. Cognitive function was assessed using the Verbal Fluency Test (VF), the Montreal Cognitive Scale (MOCA), and the Wisconsin Card Sorting Test (WCST). The Munich Personality Test (MRT) and the Toronto Alexithymia Scale (TAS-26) were used to assess premorbid personality characteristics. Multiple stepwise regression analysis was used as the main statistical method to identify the relationship between premorbid personality constructs and cognitive test results and affective and anxiety symptoms.

RESULTS

The presence of frustration tolerance in the personality structure reduced the number of incorrect answers (beta coefficient -0.811) in WCST and decreased the delay in responses with positive reinforcement (-0.630), and also reduced the level of depression (-0.465). Extraversion decreased the MOCA test score (-0.675) and increased the percentage of perseverative incorrect answers on the WCST test (0.573). The constructs of adherence to social norms and propensity to isolate lowered the final MOCA score (beta coefficients are -0.725 and -0.527, respectively). The esoteric tendencies construct decreased the latency of positive and negative reinforcement responses in WCST (-0.441 and -0.528, respectively). The severity of alexithymia was positively correlated with depression (beta 0.577), while neuroticism was positively correlated with anxiety (0.737).

CONCLUSION

Low levels of frustration tolerance and esoteric tendencies have negative effects on cognition in COVID-19 survivors, while high levels of these constructs are protective against cognitive decline and depression.

Public health impact of the Pfizer-BioNTech COVID-19 vaccine (BNT162b2) in the first year of rollout in the United States

BACKGROUND

As the body of evidence on COVID-19 and post-vaccination outcomes continues to expand, this analysis sought to evaluate the public health impact of the Pfizer-BioNTech COVID-19 Vaccine, BNT162b2, during the first year of its rollout in the US.

METHODS

A combined Markov decision tree model compared clinical and economic outcomes of the Pfizer-BioNTech COVID-19 Vaccine (BNT162b2) versus no vaccination in individuals aged ≥12 years. Age-stratified epidemiological, clinical, economic, and humanistic parameters were derived from existing data and published literature. Scenario analysis explored the impact of using lower and upper bounds of parameters on the results. The health benefits were estimated as the number of COVID-19 symptomatic cases, hospitalizations and deaths averted, and Quality Adjusted Life Years (QALYs) saved. The economic benefits were estimated as the amount of healthcare and societal cost savings associated with the vaccine-preventable health outcomes.

RESULTS

It was estimated that, in 2021, the Pfizer-BioNTech COVID-19 Vaccine (BNT162b2) contributed to averting almost 9 million symptomatic cases, close to 700,000 hospitalizations, and over 110,000 deaths, resulting in an estimated $30.4 billion direct healthcare cost savings, $43.7 billion indirect cost savings related to productivity loss, as well as discounted gains of 1.1 million QALYs. Scenario analyses showed that these results were robust; the use of alternative plausible ranges of parameters did not change the interpretation of the findings.

CONCLUSIONS

The Pfizer-BioNTech COVID-19 Vaccine (BNT162b2) contributed to generate substantial public health impact and vaccine-preventable cost savings in the first year of its rollout in the US. The vaccine was estimated to prevent millions of COVID-19 symptomatic cases and thousands of hospitalizations and deaths, and these averted outcomes translated into cost-savings in the billions of US dollars and thousands of QALYs saved. As only direct impacts of vaccination were considered, these estimates may be conservative.

Modeling the Transmission of COVID-19: Impact of Mitigation Strategies in Prekindergarten-Grade 12 Public Schools, United States, 2021

BACKGROUND

Schools are an integral part of the community; however, congregate settings facilitate transmission of SARS-CoV-2, presenting a challenge to school administrators to provide a safe, in-school environment for students and staff.

METHODS

We adapted the Centers for Disease Control and Prevention's COVIDTracer Advanced tool to model the transmission of SARS-CoV-2 in a school of 596 individuals. We estimate possible reductions in cases and hospitalizations among this population using a scenario-based analysis that accounts for (a) the risk of importation of infection from the community; (b) adherence to key Centers for Disease Control and Prevention-recommended mitigation strategies: mask wearing, cleaning and disinfection, hand hygiene, and social distancing; and (c) the effectiveness of contact tracing interventions at limiting onward transmission.

RESULTS

Low impact and effectiveness of mitigation strategies (net effectiveness: 27%) result in approximately 40% of exposed staff and students becoming COVID-19 cases. When the net effectiveness of mitigation strategies was 69% or greater, in-school transmission was mostly prevented, yet importation of cases from the surrounding community could result in nearly 20% of the school's population becoming infected within 180 days. The combined effects of mitigation strategies and contact tracing were able to prevent most onward transmission. Hospitalizations were low among children and adults (<0.5% of the school population) across all scenarios examined.

CONCLUSIONS

Based on our model, layering mitigation strategies and contact tracing can limit the number of cases that may occur from transmission in schools. Schools in communities with substantial levels of community spread will need to be more vigilant to ensure adherence of mitigation strategies to minimize transmission. Our results show that for school administrators, teachers, and parents to provide the safest environment, it is important to utilize multiple mitigation strategies and contract tracing that reduce SARS CoV-2 transmission by at least 69%. This will require training, reinforcement, and vigilance to ensure that the highest level of adherence is maintained over the entire school term.

Changing trends in mortality among solid organ transplant recipients hospitalized for COVID-19 during the course of the pandemic

Mortality among patients hospitalized for COVID-19 has declined over the course of the pandemic. Mortality trends specifically in solid organ transplant recipients (SOTR) are unknown. Using data from a multicenter registry of SOTR hospitalized for COVID-19, we compared 28-day mortality between early 2020 (March 1, 2020-June 19, 2020) and late 2020 (June 20, 2020-December 31, 2020). Multivariable logistic regression was used to assess comorbidity-adjusted mortality. Time period of diagnosis was available for 1435/1616 (88.8%) SOTR and 971/1435 (67.7%) were hospitalized: 571/753 (75.8%) in early 2020 and 402/682 (58.9%) in late 2020 (p < .001). Crude 28-day mortality decreased between the early and late periods (112/571 [19.6%] vs. 55/402 [13.7%]) and remained lower in the late period even after adjusting for baseline comorbidities (aOR 0.67, 95% CI 0.46-0.98, p = .016). Between the early and late periods, the use of corticosteroids (≥6 mg dexamethasone/day) and remdesivir increased (62/571 [10.9%] vs. 243/402 [61.5%], p < .001 and 50/571 [8.8%] vs. 213/402 [52.2%], p < .001, respectively), and the use of hydroxychloroquine and IL-6/IL-6 receptor inhibitor decreased (329/571 [60.0%] vs. 4/492 [1.0%], p < .001 and 73/571 [12.8%] vs. 5/402 [1.2%], p < .001, respectively). Mortality among SOTR hospitalized for COVID-19 declined between early and late 2020, consistent with trends reported in the general population. The mechanism(s) underlying improved survival require further study.

The Importance of Groundwater in Critical Zone Science

The critical zone (CZ)-from treetops to groundwater-is an increasingly studied part of the earth system, where scientists study interactions between water, air, rock, soil, and life. Groundwater is both a boundary and an essential store in this integrated system, but is often not well considered in part because of the difficulty in accessing it and its slow movement relative to other parts of the system. Here, we describe some fundamental areas where groundwater hydrology is of fundamental importance to CZ science, including sustaining streamflow and vegetation, reacting with minerals to produce dissolved solutes and regolith, and influencing energy fluxes across the land-atmosphere interface. As the timing and type of precipitation change with climate, groundwater may play an even more important role in CZ processes as a sustainable water source for plants and streamflow. Many open questions also exist about the role of CZ processes on groundwater. Many data streams are needed and important to quantifying the integrated response of the CZ to groundwater and vice versa, but long-term data records are often incomplete or discontinued due to limited funding. We argue that the long timescales of processes that involve groundwater necessitate data collection efforts beyond typical federal funding timespans. Sustaining monitoring networks and developing new ones aimed at testing hypotheses related to slow-moving, groundwater-controlled CZ processes should be a scientific priority, and here we outline some open questions that we hope will motivate groundwater scientists to get involved in CZ science.

Characterization of IgG Antibody Response against SARS-CoV-2 (COVID-19) in the Cypriot Population

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has hit its second year and continues to damage lives and livelihoods across the globe. There continues to be a global effort to present serological data on SARS-CoV-2 antibodies in different individuals. As such, this study aimed to characterize the seroprevalence of SARS-CoV-2 antibodies in the Cypriot population for the first time since the pandemic started. Our results show that a majority of people infected with SARS-CoV-2 developed IgG antibodies against the virus, whether anti-NP, anti-S1RBD, or both, at least 20 days after their infection. Additionally, the percentage of people with at least one antibody against SARS-CoV-2 in the group of volunteers deemed SARS-CoV-2 negative via RT-PCR or who remain untested/undetermined (14.43%) is comparable to other reported percentages worldwide, ranging anywhere from 0.2% to 24%. We postulate that these percentages reflect the underreporting of true infections in the population, and also show the steady increase of herd immunity. Additionally, we showed a significantly marked decrease in anti-NP IgG antibodies in contrast to relatively stable levels of anti-S1RBD IgG antibodies in previously infected individuals across time.

Patterns of SARS-CoV-2 Testing Preferences in a National Cohort in the United States: Latent Class Analysis of a Discrete Choice Experiment

BACKGROUND

Inadequate screening and diagnostic testing in the United States throughout the first several months of the COVID-19 pandemic led to undetected cases transmitting disease in the community and an underestimation of cases. Though testing supply has increased, maintaining testing uptake remains a public health priority in the efforts to control community transmission considering the availability of vaccinations and threats from variants.

OBJECTIVE

This study aimed to identify patterns of preferences for SARS-CoV-2 screening and diagnostic testing prior to widespread vaccine availability and uptake.

METHODS

We conducted a discrete choice experiment (DCE) among participants in the national, prospective CHASING COVID (Communities, Households, and SARS-CoV-2 Epidemiology) Cohort Study from July 30 to September 8, 2020. The DCE elicited preferences for SARS-CoV-2 test type, specimen type, testing venue, and result turnaround time. We used latent class multinomial logit to identify distinct patterns of preferences related to testing as measured by attribute-level part-worth utilities and conducted a simulation based on the utility estimates to predict testing uptake if additional testing scenarios were offered.

RESULTS

Of the 5098 invited cohort participants, 4793 (94.0%) completed the DCE. Five distinct patterns of SARS-CoV-2 testing emerged. Noninvasive home testers (n=920, 19.2% of participants) were most influenced by specimen type and favored less invasive specimen collection methods, with saliva being most preferred; this group was the least likely to opt out of testing. Fast-track testers (n=1235, 25.8%) were most influenced by result turnaround time and favored immediate and same-day turnaround time. Among dual testers (n=889, 18.5%), test type was the most important attribute, and preference was given to both antibody and viral tests. Noninvasive dual testers (n=1578, 32.9%) were most strongly influenced by specimen type and test type, preferring saliva and cheek swab specimens and both antibody and viral tests. Among hesitant home testers (n=171, 3.6%), the venue was the most important attribute; notably, this group was the most likely to opt out of testing. In addition to variability in preferences for testing features, heterogeneity was observed in the distribution of certain demographic characteristics (age, race/ethnicity, education, and employment), history of SARS-CoV-2 testing, COVID-19 diagnosis, and concern about the pandemic. Simulation models predicted that testing uptake would increase from 81.6% (with a status quo scenario of polymerase chain reaction by nasal swab in a provider's office and a turnaround time of several days) to 98.1% by offering additional scenarios using less invasive specimens, both viral and antibody tests from a single specimen, faster turnaround time, and at-home testing.

CONCLUSIONS

We identified substantial differences in preferences for SARS-CoV-2 testing and found that offering additional testing options would likely increase testing uptake in line with public health goals. Additional studies may be warranted to understand if preferences for testing have changed since the availability and widespread uptake of vaccines.

The age structure of cases as the key of COVID-19 severity: Longitudinal population-based analysis of European countries during 150 days

AIMS

Over a million confirmed cases of the coronavirus disease (COVID-19) across 16 European countries were observed during the first wave of the pandemic. Epidemiological measures like the case fatality rate (CFR) are generally used to determine the severity of the illness. The aim is to investigate the impact of the age structure of reported cases on the reported CFR and possibilities of its demographic adjustment for a better cross-country comparison (age-standardized CFRs, time delay between cases detection and death).

METHODS

This longitudinal study uses prospective, population-based data covering 150 days, starting on the day of confirmation of the 100th case in each country. COVerAGE-DB and the Human Mortality Database were used in this regard. The age-standardized CFRs were calculated with and without the time delay of the number of deaths after the confirmation of the cases.

RESULTS

The observed decline in the CFRs at the end of the first wave is partly given by the changes in the age structure of confirmed cases. Using the adjusted (age-standardized) CFRs with time delay, the risk of death among confirmed cases is much more stable in comparison to crude (observed) CFRs.

CONCLUSIONS

Preventing the spread of COVID-19 among the elderly is an important way to positively influence the overall fatality rate, decrease the number of deaths, and not overload the health systems. The crude CFRs (still often presented) are not sufficient for a proper evaluation of the development across populations nor as a means of identifying the influencing factors.

Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic: a modelling study

BACKGROUND

Numerous countries imposed strict travel restrictions, contributing to the large socioeconomic burden during the COVID-19 pandemic. The long quarantines that apply to contacts of cases may be excessive for travel policy.

METHODS

We developed an approach to evaluate imminent countrywide COVID-19 infections after 0-14-day quarantine and testing. We identified the minimum travel quarantine duration such that the infection rate within the destination country did not increase compared to a travel ban, defining this minimum quarantine as "sufficient."

FINDINGS

We present a generalised analytical framework and a specific case study of the epidemic situation on November 21, 2021, for application to 26 European countries. For most origin-destination country pairs, a three-day or shorter quarantine with RT-PCR or antigen testing on exit suffices. Adaptation to the European Union traffic-light risk stratification provided a simplified policy tool. Our analytical approach provides guidance for travel policy during all phases of pandemic diseases.

INTERPRETATION

For nearly half of origin-destination country pairs analysed, travel can be permitted in the absence of quarantine and testing. For the majority of pairs requiring controls, a short quarantine with testing could be as effective as a complete travel ban. The estimated travel quarantine durations are substantially shorter than those specified for traced contacts.

FUNDING

EasyJet (JPT and APG), the Elihu endowment (JPT), the Burnett and Stender families' endowment (APG), the Notsew Orm Sands Foundation (JPT and APG), the National Institutes of Health (MCF), Canadian Institutes of Health Research (SMM) and Natural Sciences and Engineering Research Council of Canada EIDM-MfPH (SMM).

The Multi-Compartment SI(RD) Model with Regime Switching: An Application to COVID-19 Pandemic

We study—with existence and unicity results—a variant of the SIR model for an infectious disease incorporating both the possibility of a death outcome—in a short period of time—and a regime switch that can account for the mitigation measures used to control the spreading of the infections, such as a total lockdown. This model is parametrised by three parameters: the basic reproduction number, the mortality rate of the infected, and the duration of the disease. We discuss a particular example of application to Portuguese COVID-19 data in two short periods just after the start of the epidemic in 4 March 2020, with the first two cases dated that day. We propose a simple and effective method for the estimation of the main parameters of the disease, namely, the basic reproduction number and the mortality rate of the infected. We correct these estimated values to take into account the asymptomatic non-diagnosed members of the population. We compare the outcome of the model in the cases of the existence, or not, of a regime switch, and under three different scenarios, with a remarkable agreement between model and data deaths in the case of our basis scenario. In a final short remark, we deal with the existence of symmetries for the proposed model.

Saliva for COVID-19 Testing: Simple but Useless or an Undervalued Resource?

During the COVID-19 pandemic, countries with robust population-based asymptomatic testing were generally successful in controlling virus spread, hence reducing hospitalizations and deaths. This effectiveness inspired widespread asymptomatic surveillance for COVID-19/SARS-CoV-2 globally. Polarized vaccination programs, coupled with the relatively short-lived immunity vaccines provide, mean that reciprocal cross-border exchanges of each new variant are likely, as evidenced by Delta and Gamma, and asymptomatic testing will be required for the foreseeable future. Reliance on nasopharyngeal swabs contributes to “testing fatigue” arising due to difficulties in standardizing administration, unpleasantness, and inappropriateness of use in younger people or individuals with special needs. There has also been erosion in confidence of testing due to variable and/or poor accuracy of lateral flow devices to detect COVID-19. Here, we question why saliva-based PCR assays are not being used more widely, given that standardization is easy and this non-invasive test is suitable for everyone, providing high sensitivity and accuracy. We reflect on our experience with the University of Nottingham COVID-19 Asymptomatic Testing, where (as of October 2021) 96,317 samples have been processed by RT-qPCR from 23,740 repeat saliva donors, yielding 465 positive cases. We challenge myths that saliva is difficult to process, concluding that it is an undervalued resource for both asymptomatic and symptomatic detection of SARS-CoV-2 genomes to an accuracy of &gt;99% and a sensitivity of 1–10 viral copies/μl. In July 2021, our data enabled Nottingham to become the first UK University to gain accreditation and the first UK institute to gain this accolade for saliva.

Development of a reproducible method for monitoring SARS-CoV-2 in wastewater

Monitoring the genetic signal of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through RNA titers in wastewater has emerged as a promising strategy for tracking community-scale prevalence of coronavirus disease 2019 (COVID-19). Although many studies of SARS-CoV-2 in wastewater have been conducted around the world, a uniform procedure for concentrating the virus in wastewater is lacking. The goal of this study was to comprehensively evaluate how different methods for concentrating the suspended solids in wastewater affect the associated SARS-CoV-2 RNA signal and the time required for processing samples for wastewater-based epidemiology efforts. We additionally consider the effects of sampling location in the wastewater treatment train (i.e., following preliminary or primary treatment), pasteurization, and RNA extraction method. Comparison of the liquid phase to suspended solids obtained via centrifugation or vacuum filtration suggests that the RNA signal of SARS-CoV-2 preferentially occurs in the solids. Therefore, we assert that the recovery of SARS-CoV-2 from wastewater should focus on suspended solids. Our data indicate that the measured SARS-CoV-2 signal is higher among samples taken from the primary clarifier effluent, as opposed to those taken after preliminary treatment. Additionally, we provide evidence that sample pasteurization at 60 °C for 90 min reduces the SARS-CoV-2 signal by approximately 50-55%. Finally, the results indicate that a magnetic bead approach to RNA extraction leads to a higher SARS-CoV-2 signal than does a silica membrane approach.

A single dose of SARS-CoV-2 FINLAY-FR-1A vaccine enhances neutralization response in COVID-19 convalescents, with a very good safety profile: An open-label phase 1 clinical trial

BACKGROUND

As a first step towards a vaccine protecting COVID-19 convalescents from reinfection, we evaluated FINLAY-FR-1A vaccine in a clinical trial.

METHODS

Thirty COVID-19 convalescents aged 22-57 years were studied: convalescents of mild COVID-19, asymptomatic convalescents, both with PCR-positive at the moment of diagnosis; and individuals with subclinical infection detected by viral-specific IgG. They received a single intramuscular injection of the FINLAY-FR-1A vaccine (50 µg of the recombinant dimeric receptor binding domain). The primary outcomes were safety and reactogenicity, assessed over 28 days after vaccination. The secondary outcome was vaccine immunogenicity. Humoral response at baseline and following vaccination was evaluated by ELISA and live-virus neutralization test. The effector T cellular response was also assessed. Cuban Public Registry of Clinical Trials, WHO-ICTRP: https://rpcec.sld.cu/en/trials/RPCEC00000349-En.

FINDINGS

No serious adverse events were reported. Minor adverse events were found, the most common, local pain: 3 (10%) and redness: 2 (6·7%). The vaccine elicited a >21 fold increase in IgG anti-RBD antibodies 28 days after vaccination. The median of inhibitory antibody titres (94·0%) was three times greater than that of the COVID-19 convalescent panel. Virus neutralization titres higher than 1:160 were found in 24 (80%) participants. There was also an increase in RBD-specific T cells producing IFN-γ and TNF-α.

INTERPRETATION

A single dose of the FINLAY-FR-1A vaccine against SARS-CoV-2 was an efficient booster of pre-existing natural immunity, with excellent safety profile.

FUNDING

Partial funding for this study was received from the Project-2020-20, Fondo de Ciencia e Innovación (FONCI), Ministry of Science, Technology and the Environment, Cuba.   RESUMEN.

ANTECEDENTES

Como un primer paso hacia una vacuna que proteja a los convalecientes de COVID-19 de la reinfección, evaluamos la vacuna FINLAY-FR-1A en un ensayo clínico.

MÉTODOS

Se estudiaron treinta convalecientes de COVID-19 de 22 a 57 años: convalecientes de COVID-19 leve y convalecientes asintomáticos, ambos con prueba PCR positiva al momento del diagnóstico; e individuos con infección subclínica detectada por IgG específica viral. Los participantes recibieron una dosis única por vía intramuscular de la vacuna FINLAY-FR-1A (50 µg del dominio de unión al receptor recombinante dimérico del SARS CoV-2). Las variables de medida primarias fueron la seguridad y la reactogenicidad, evaluadas durante 28 días después de la vacunación. La variable secundaria, la inmunogenicidad. La respuesta humoral, al inicio del estudio y después de la vacunación, se evaluó por ELISA y mediante la prueba de neutralización del virus vivo. También se evaluó la respuesta de células T efectoras. Registro Público Cubano de Ensayos Clínicos, WHO-ICTRP: https://rpcec.sld.cu/en/trials/RPCEC00000349-En.

RESULTADOS

No se reportaron eventos adversos graves. Se encontraron eventos adversos leves, los más comunes, dolor local: 3 (10%) y enrojecimiento: 2 (6·7%). La vacuna estimuló un incremento >21 veces de los anticuerpos IgG anti-RBD 28 días después de la vacunación. La mediana de los títulos de anticuerpos inhibidores (94·0%) fue aproximadamente tres veces mayor que la del panel de convalecientes de COVID-19. Se encontraron títulos de neutralización viral superiores a 1:160 en 24 (80%) de los participantes. También hubo un aumento en las células T específicas de RBD que producen IFN-γ y TNF-α.

INTERPRETACIÓN

Una sola dosis de la vacuna FINLAY-FR-1A contra el SARS-CoV-2 reforzó eficazmente la inmunidad natural preexistente, con un excelente perfil de seguridad.

FINANCIAMIENTO

Se recibió un financiamiento parcial del Proyecto-2020-20, Fondo de Ciencia e Innovación (FONCI), Ministerio de Ciencia, Tecnología y Medio Ambiente, Cuba.

The Epidemiology of COVID-19 in Malaysia

BACKGROUND

COVID-19 has rapidly spread across the globe. Critical to the control of COVID-19 is the characterisation of its epidemiology. Despite this, there has been a paucity of evidence from many parts of the world, including Malaysia. We aim to describe the epidemiology of COVID-19 in Malaysia to inform prevention and control policies better.

METHODS

Malaysian COVID-19 data was extracted from 16 March 2020 up to 31 May 2021. We estimated the following epidemiological indicators: 7-day incidence rates, 7-day mortality rates, case fatality rates, test positive ratios, testing rates and the time-varying reproduction number (Rt).

FINDINGS

Between 16 March 2020 and 31 May 2021, Malaysia has reported 571,901 cases and 2,796 deaths. Malaysia's average 7-day incidence rate was 26•6 reported infections per 100,000 population (95% CI: 17•8, 38•1). The average test positive ratio and testing rate were 4•3% (95% CI: 1•6, 10•2) and 0•8 tests per 1,000 population (95% CI: <0•1, 3•7), respectively. The case fatality rates (CFR) was 0•6% (95% CI: <0•1, 3•7). Among the 2,796 cases who died, 87•3% were ≥ 50 years.

INTERPRETATION

The public health response was successful in the suppression of COVID-19 transmission or the first half of 2020. However, a state election and outbreaks in institutionalised populations have been the catalyst for more significant community propagation. This rising community transmission has continued in 2021, leading to increased incidence and strained healthcare systems. Calibrating NPI based on epidemiological indicators remain critical for us to live with the virus. (243 words).

FUNDING

This study is part of the COVID-19 Epidemiological Analysis and Strategies (CEASe) Project with funding from the Ministry of Science, Technology and Innovation (UM.0000245/HGA.GV).

A statistical model for the dynamics of COVID-19 infections and their case detection ratio in 2020

The case detection ratio of coronavirus disease 2019 (COVID-19) infections varies over time due to changing testing capacities, different testing strategies, and the evolving underlying number of infections itself. This note shows a way of quantifying these dynamics by jointly modeling the reported number of detected COVID-19 infections with nonfatal and fatal outcomes. The proposed methodology also allows to explore the temporal development of the actual number of infections, both detected and undetected, thereby shedding light on the infection dynamics. We exemplify our approach by analyzing German data from 2020, making only use of data available since the beginning of the pandemic. Our modeling approach can be used to quantify the effect of different testing strategies, visualize the dynamics in the case detection ratio over time, and obtain information about the underlying true infection numbers, thus enabling us to get a clearer picture of the course of the COVID-19 pandemic in 2020.

COVID-19 wastewater epidemiology: a model to estimate infected populations

BACKGROUND

Wastewater-based epidemiology provides an opportunity for near real-time, cost-effective monitoring of community-level transmission of SARS-CoV-2. Detection of SARS-CoV-2 RNA in wastewater can identify the presence of COVID-19 in the community, but methods for estimating the numbers of infected individuals on the basis of wastewater RNA concentrations are inadequate.

METHODS

This is a wastewater-based epidemiology study using wastewater samples that were collected weekly or twice a week from three sewersheds in South Carolina, USA, between either May 27 or June 16, 2020, and Aug 25, 2020, and tested for SARS-CoV-2 RNA. We developed a susceptible-exposed-infectious-recovered (SEIR) model based on the mass rate of SARS-CoV-2 RNA in the wastewater to predict the number of infected individuals, and have also provided a simplified equation to predict this. Model predictions were compared with the number of confirmed cases identified by the Department of Health and Environmental Control, South Carolina, USA, for the same time period and geographical area.

FINDINGS

We plotted the model predictions for the relationship between mass rate of virus release and numbers of infected individuals, and we validated this prediction on the basis of estimated prevalence from individual testing. A simplified equation to estimate the number of infected individuals fell within the 95% confidence limits of the model. The rate of unreported COVID-19 cases, as estimated by the model, was approximately 11 times that of confirmed cases (ie, ratio of estimated infections for every confirmed case of 10·9, 95% CI 4·2-17·5). This rate aligned well with an independent estimate of 15 infections for every confirmed case in the US state of South Carolina.

INTERPRETATION

The SEIR model provides a robust method to estimate the total number of infected individuals in a sewershed on the basis of the mass rate of RNA copies released per day. This approach overcomes some of the limitations associated with individual testing campaigns and thereby provides an additional tool that can be used to inform policy decisions.

FUNDING

Clemson University, USA.

COVID-19 wastewater epidemiology: a model to estimate infected populations

BACKGROUND

Wastewater-based epidemiology provides an opportunity for near real-time, cost-effective monitoring of community-level transmission of SARS-CoV-2. Detection of SARS-CoV-2 RNA in wastewater can identify the presence of COVID-19 in the community, but methods for estimating the numbers of infected individuals on the basis of wastewater RNA concentrations are inadequate.

METHODS

This is a wastewater-based epidemiology study using wastewater samples that were collected weekly or twice a week from three sewersheds in South Carolina, USA, between either May 27 or June 16, 2020, and Aug 25, 2020, and tested for SARS-CoV-2 RNA. We developed a susceptible-exposed-infectious-recovered (SEIR) model based on the mass rate of SARS-CoV-2 RNA in the wastewater to predict the number of infected individuals, and have also provided a simplified equation to predict this. Model predictions were compared with the number of confirmed cases identified by the Department of Health and Environmental Control, South Carolina, USA, for the same time period and geographical area.

FINDINGS

We plotted the model predictions for the relationship between mass rate of virus release and numbers of infected individuals, and we validated this prediction on the basis of estimated prevalence from individual testing. A simplified equation to estimate the number of infected individuals fell within the 95% confidence limits of the model. The rate of unreported COVID-19 cases, as estimated by the model, was approximately 11 times that of confirmed cases (ie, ratio of estimated infections for every confirmed case of 10·9, 95% CI 4·2-17·5). This rate aligned well with an independent estimate of 15 infections for every confirmed case in the US state of South Carolina.

INTERPRETATION

The SEIR model provides a robust method to estimate the total number of infected individuals in a sewershed on the basis of the mass rate of RNA copies released per day. This approach overcomes some of the limitations associated with individual testing campaigns and thereby provides an additional tool that can be used to inform policy decisions.

FUNDING

Clemson University, USA.

Implications derived from S-protein variants of SARS-CoV-2 from six continents

The spike (S) protein is a critical determinant of the infectivity and antigenicity of SARS-CoV-2. Several mutations in the S protein of SARS-CoV-2 have already been detected, and their effect in immune system evasion and enhanced transmission as a cause of increased morbidity and mortality are being investigated. From pathogenic and epidemiological perspectives, S proteins are of prime interest to researchers. This study focused on the unique variants of S proteins from six continents: Asia, Africa, Europe, Oceania, South America, and North America. In comparison to the other five continents, Africa had the highest percentage of unique S proteins (29.1%). The phylogenetic relationship implies that unique S proteins from North America are significantly different from those of the other five continents. They are most likely to spread to the other geographic locations through international travel or naturally by emerging mutations. It is suggested that restriction of international travel should be considered, and massive vaccination as an utmost measure to combat the spread of the COVID-19 pandemic. It is also further suggested that the efficacy of existing vaccines and future vaccine development must be reviewed with careful scrutiny, and if needed, further re-engineered based on requirements dictated by new emerging S protein variants.

Confirmed circulation of SARS-CoV-2 in Irish blood donors prior to first national notification of infection

Introduction

Blood donor studies offer a unique opportunity to screen healthy populations for the presence of antibodies to emerging infections. We describe the use of blood donor specimens to track the ‘first-wave’ of the COVID-19 pandemic in Ireland.

Methodology

A random selection of donor samples received by the Irish Blood Transfusion Service (IBTS) between February and September 2020 (n = 8,509) were screened by multiple commercial SARs-CoV-2 antibody assays. The antibody detection rate was adjusted to the population to determine the SARS-CoV-2 seroprevalence in Ireland.

Results

SARS-CoV-2 antibody detection rose significantly during the first peak of COVID-19 infection, increasing from 0.3% in March, to 2.9% in April (p < 0.0001, The first SARS-CoV-2 antibody positive donor samples were collected on the 17th February 2020, 2 weeks prior to the first official notification. This is the earliest serological evidence of SARS-CoV-2 circulating in the Irish population. Our results also show a significantly higher antibody prevalence in the Capital city and in donors less than 40 years of age.

Conclusions

The present study demonstrates evidence of SARS-CoV-2 antibody reactivity across all age groups and counties. The critical value of blood donor seroprevalence studies is apparent in this report which identified the earliest serological evidence of SARS-CoV-2 infection in Ireland, as well as documenting the evolution of COVID-19 pandemic in Ireland over time.

Spatial and Temporal Trends of SARS-CoV-2 RNA from Wastewater Treatment Plants over 6 Weeks in Cape Town, South Africa

Recent scientific trends have revealed that the collection and analysis of data on the occurrence and fate of SARS-CoV-2 in wastewater may serve as an early warning system for COVID-19. In South Africa, the first COVID-19 epicenter emerged in the Western Cape Province. The City of Cape Town, located in the Western Cape Province, has approximately 4 million inhabitants. This study reports on the monitoring of SARS-CoV-2 RNA in the wastewater of the City of Cape Town's wastewater treatment plants (WWTPs) during the peak of the epidemic. During this period, the highest overall median viral RNA signal was observed in week 1 (9200 RNA copies/mL) and declined to 127 copies/mL in week 6. The overall decrease in the amount of detected viral SARS-CoV-2 RNA over the 6-week study period was associated with a declining number of newly identified COVID-19 cases in the city. The SARS-CoV-2 early warning system has now been established to detect future waves of COVID-19.