SARS-CoV-2 viral-load distribution reveals that viral loads increase with age: a retrospective cross-sectional cohort study

Epidemiology and viral loads of respiratory syncytial virus in hospitalized children prior to and during COVID-19 pandemic in Hangzhou, China

Non-pharmaceutical interventions (NPIs) implemented to control SARS-CoV-2 have significantly influenced the activity of respiratory pathogens. This study investigated epidemiological changes among hospitalized patients with respiratory syncytial virus (RSV) before (2017-2019) and during (2020-2022) the COVID-19 pandemic in Hangzhou, China. We also examined viral load distribution across demographic and temporal variables. Nasopharyngeal swabs were collected and RSV loads were quantified using reverse transcriptase polymerase chain reaction (RT-qPCR). RSV epidemic characteristics, seasonal dynamics, and viral load distributions were compared between pre- and pandemic years. General linear models were employed to assess associations between viral loads and age. Among 19 742 cases, 1576 and 2092 tested positive during the pre- and pandemic years, respectively. From February to July 2020, the implementation of NPIs led to the cessation of RSV circulation. However, after these measures were relaxed, RSV cases resurged over two consecutive seasons during the pandemic, notably affecting older children compared to those in the pre-pandemic years (1.00 years, IQR: 0.50-2.00 vs. 0.58 years, IQR: 0.27-1.00, p < 0.001). Specifically, in 2021-2022, an off-season resurgence of RSV began earlier (mid-June), lasted longer (40 weeks), and involved more positive cases (1238 cases) than both 2020-2021 and pre-pandemic years. Viral load distribution demonstrated a clear age-related relationship in both pre- and pandemic years, with younger children consistently showing higher viral loads, independently of gender and season (all p-values for trends <0.001). These findings highlight the impact of NPIs on RSV epidemiology and underscore the need to prioritize RSV infection prevention in younger children from the perspective of viral load.

Impact of COVID-19 and Closed Transmission of SARS-CoV-2 during the First Wave in Toyama Prefecture, Japan, March 30 to May 18, 2020

We studied 226 patients in Toyama Prefecture who were notified of COVID-19 during the first wave between March 30 and May 18, 2020. Of the 226 patients, 22 (9.7%) died, most (95%) of whom were aged ≥65 years. A large cluster comprising 59 patients (41 residents and 18 staff members) was identified in a nursing home on April 17. No deaths occurred among staff members; however, 12 of the 41 residents (29%) died. Although the threshold cycle (Ct) values were significantly lower in the 20-64 and ≥65 years age groups than in the <20 years age group, no correlation was found between the Ct values and severity, fatal outcome, or secondary infection. The haplotype network of 145 SARS-CoV-2 isolates (64%) from 226 patients was analyzed. The viral genomes of the case groups differed by less than five nucleotide bases. These data suggest that the SARS-CoV-2 strains, which were initially introduced into Toyama Prefecture in late March and early April 2020, and their closely related strains, identified as lineage B.1.1, circulated during the first wave. The reduced inter-prefectural mobility of local residents may support the lack of strain diversity in SARS-CoV-2 during the first wave of the state of emergency.

Digital PCR to Measure SARS-CoV-2 RNA, Variants, and Outcomes in Youth

BACKGROUND

The role of SARS-CoV-2 viral load in predicting contagiousness, disease severity, transmissibility, and clinical decision-making continues to be an area of great interest. However, most studies have been in adults and have evaluated SARS-CoV-2 loads using cycle thresholds (Ct) values, which are not standardized preventing consistent interpretation critical to understanding clinical impact and utility. Here, a quantitative SARS-CoV-2 reverse-transcription digital PCR (RT-dPCR) assay normalized to WHO International Units was applied to children at risk of severe disease diagnosed with COVID-19 at St. Jude Children's Research Hospital between March 28, 2020, and January 31, 2022.

METHODS

Demographic and clinical information from children, adolescents, and young adults treated at St. Jude Children's Research Hospital were abstracted from medical records. Respiratory samples underwent SARS-CoV-2 RNA quantitation by RT-dPCR targeting N1 and N2 genes, with sequencing to determine the genetic lineage of infecting virus.

RESULTS

Four hundred and sixty-two patients aged 0-24 years (median 11 years old) were included during the study period. Most patients were infected by the omicron variant (43.72%), followed by ancestral strain (22.29%), delta (13.20%), and alpha (2.16%). Viral load at presentation ranged from 2.49 to 9.14 log10 IU/mL, and higher viral RNA loads were associated with symptoms (OR 1.32; CI 95% 1.16-1.49) and respiratory disease (OR 1.23; CI 95% 1.07-1.41). Viral load did not differ by SARS-CoV-2 variant, vaccination status, age, or baseline diagnosis.

CONCLUSIONS

SARS-CoV-2 RNA loads predict the presence of symptomatic and respiratory diseases. The use of standardized, quantitative methods is feasible, allows for replication, and comparisons across institutions, and has the potential to facilitate consensus quantitative thresholds for risk stratification and treatment.

Cycle Threshold Values as Indication of Increasing SARS-CoV-2 New Variants, England, 2020-2022

Early detection of increased infections or new variants of SARS-CoV-2 is critical for public health response. To determine whether cycle threshold (Ct) data from PCR tests for SARS-CoV-2 could serve as an early indicator of epidemic growth, we analyzed daily mean Ct values in England, UK, by gene target and used iterative sequential regression to detect break points in mean Ct values (and positive test counts). To monitor the epidemic in England, we continued those analyses in real time. During September 2020-January 2022, a total of 7,611,153 positive SARS-CoV-2 PCR test results with Ct data were reported. Spike (S) gene target (S+/S-)-specific mean Ct values decreased 6-29 days before positive test counts increased, and S-gene Ct values provided early indication of increasing new variants (Delta and Omicron). Our approach was beneficial in the context of the first waves of the COVID-19 pandemic and can be used to support future infectious disease monitoring.

A collaborative approach to improving representation in viral genomic surveillance

The lack of routine viral genomic surveillance delayed the initial detection of SARS-CoV-2, allowing the virus to spread unfettered at the outset of the U.S. epidemic. Over subsequent months, poor surveillance enabled variants to emerge unnoticed. Against this backdrop, long-standing social and racial inequities have contributed to a greater burden of cases and deaths among minority groups. To begin to address these problems, we developed a new variant surveillance model geared toward building 'next generation' genome sequencing capacity at universities in or near rural areas and engaging the participation of their local communities. The resulting genomic surveillance network has generated more than 1,000 SARS-CoV-2 genomes to date, including the first confirmed case in northeast Louisiana of Omicron, and the first and sixth confirmed cases in Georgia of the emergent BA.2.75 and BQ.1.1 variants, respectively. In agreement with other studies, significantly higher viral gene copy numbers were observed in Delta variant samples compared to those from Omicron BA.1 variant infections, and lower copy numbers were seen in asymptomatic infections relative to symptomatic ones. Collectively, the results and outcomes from our collaborative work demonstrate that establishing genomic surveillance capacity at smaller academic institutions in rural areas and fostering relationships between academic teams and local health clinics represent a robust pathway to improve pandemic readiness.

Innate and adaptive immunity to SARS-CoV-2 and predisposing factors

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2), has affected all countries worldwide. Although some symptoms are relatively mild, others are still associated with severe and even fatal clinical outcomes. Innate and adaptive immunity are important for the control of SARS-CoV-2 infections, whereas a comprehensive characterization of the innate and adaptive immune response to COVID-19 is still lacking and the mechanisms underlying immune pathogenesis and host predisposing factors are still a matter of scientific debate. Here, the specific functions and kinetics of innate and adaptive immunity involved in SARS-CoV-2 recognition and resultant pathogenesis are discussed, as well as their immune memory for vaccinations, viral-mediated immune evasion, and the current and future immunotherapeutic agents. We also highlight host factors that contribute to infection, which may deepen the understanding of viral pathogenesis and help identify targeted therapies that attenuate severe disease and infection.

The Influence of Ventilation Measures on the Airborne Risk of Infection in Schools: A Scoping Review

OBJECTIVES

To review the risk of airborne infections in schools and evaluate the effect of intervention measures reported in field studies.

BACKGROUND

Schools are part of a country's critical infrastructure. Good infection prevention measures are essential for reducing the risk of infection in schools as much as possible, since these are places where many individuals spend a great deal of time together every weekday in a small area where airborne pathogens can spread quickly. Appropriate ventilation can reduce the indoor concentration of airborne pathogens and reduce the risk of infection.

METHODS

A systematic search of the literature was conducted in the databases Embase, MEDLINE, and ScienceDirect using keywords such as school, classroom, ventilation, carbon dioxide (CO2) concentration, SARS-CoV-2, and airborne transmission. The primary endpoint of the studies selected was the risk of airborne infection or CO2 concentration as a surrogate parameter. Studies were grouped according to the study type.

RESULTS

We identified 30 studies that met the inclusion criteria, six of them intervention studies. When specific ventilation strategies were lacking in schools being investigated, CO2 concentrations were often above the recommended maximum values. Improving ventilation lowered the CO2 concentration, resulting in a lower risk of airborne infections.

CONCLUSIONS

The ventilation in many schools is not adequate to guarantee good indoor air quality. Ventilation is an important measure for reducing the risk of airborne infections in schools. The most important effect is to reduce the time of residence of pathogens in the classrooms.

Diagnostic accuracy of the Panbio COVID-19 antigen rapid test device for SARS-CoV-2 detection in Kenya, 2021: A field evaluation

BACKGROUND

Accurate and timely diagnosis is essential in limiting the spread of SARS-CoV-2 infection. The reference standard, rRT-PCR, requires specialized laboratories, costly reagents, and a long turnaround time. Antigen RDTs provide a feasible alternative to rRT-PCR since they are quick, relatively inexpensive, and do not require a laboratory. The WHO requires that Ag RDTs have a sensitivity ≥80% and specificity ≥97%.

METHODS

This evaluation was conducted at 11 health facilities in Kenya between March and July 2021. We enrolled persons of any age with respiratory symptoms and asymptomatic contacts of confirmed COVID-19 cases. We collected demographic and clinical information and two nasopharyngeal specimens from each participant for Ag RDT testing and rRT-PCR. We calculated the diagnostic performance of the Panbio™ Ag RDT against the US Centers for Disease Control and Prevention's (CDC) rRT-PCR test.

RESULTS

We evaluated the Ag RDT in 2,245 individuals where 551 (24.5%, 95% CI: 22.8-26.3%) tested positive by rRT-PCR. Overall sensitivity of the Ag RDT was 46.6% (95% CI: 42.4-50.9%), specificity 98.5% (95% CI: 97.8-99.0%), PPV 90.8% (95% CI: 86.8-93.9%) and NPV 85.0% (95% CI: 83.4-86.6%). Among symptomatic individuals, sensitivity was 60.6% (95% CI: 54.3-66.7%) and specificity was 98.1% (95% CI: 96.7-99.0%). Among asymptomatic individuals, sensitivity was 34.7% (95% CI 29.3-40.4%) and specificity was 98.7% (95% CI: 97.8-99.3%). In persons with onset of symptoms <5 days (594/876, 67.8%), sensitivity was 67.1% (95% CI: 59.2-74.3%), and 53.3% (95% CI: 40.0-66.3%) among those with onset of symptoms >7 days (157/876, 17.9%). The highest sensitivity was 87.0% (95% CI: 80.9-91.8%) in symptomatic individuals with cycle threshold (Ct) values ≤30.

CONCLUSION

The overall sensitivity and NPV of the Panbio™ Ag RDT were much lower than expected. The specificity of the Ag RDT was high and satisfactory; therefore, a positive result may not require confirmation by rRT-PCR. The kit may be useful as a rapid screening tool only for symptomatic patients in high-risk settings with limited access to rRT-PCR. A negative result should be interpreted based on clinical and epidemiological information and may require retesting by rRT-PCR.

Association of SARS-CoV-2 viral load distributions with individual demographics and suspected variant type: results from the Liverpool community testing pilot, England, 6 November 2020 to 8 September 2021

BackgroundThe PCR quantification cycle (Cq) is a proxy measure of the viral load of a SARS-CoV-2-infected individual.AimTo investigate if Cq values vary according to different population characteristics, in particular demographic ones, and within the COVID-19 pandemic context, notably the SARS-CoV-2 type/variant individuals get infected with.MethodsWe considered all positive PCR results from Cheshire and Merseyside, England, between 6 November 2020 and 8 September 2021. Cq distributions were inspected with Kernel density estimates. Multivariable quantile regression models assessed associations between people's features and Cq.ResultsWe report Cq values for 188,821 SARS-CoV-2 positive individuals. Median Cqs increased with decreasing age for suspected wild-type virus and Alpha variant infections, but less so, if not, for Delta. For example, compared to 30-39-year-olds (median age group), 5-11-year-olds exhibited 1.8 (95% CI: 1.5 to 2.1), 2.2 (95% CI: 1.8 to 2.6) and 0.8 (95% CI: 0.6 to 0.9) higher median Cqs for suspected wild-type, Alpha and Delta positives, respectively, in multivariable analysis. 12-18-year-olds also had higher Cqs for wild-type and Alpha positives, however, not for Delta. Overall, in univariable analysis, suspected Delta positives reported 2.8 lower median Cqs than wild-type positives (95% CI: 2.7 to 2.8; p < 0.001). Suspected Alpha positives had 1.5 (95% CI: 1.4 to 1.5; p < 0.001) lower median Cqs than wild type.ConclusionsWild-type- or Alpha-infected school-aged children (5-11-year-olds) might transmit less than adults (> 18 years old), but have greater mixing exposures. Smaller differences in viral loads with age occurred in suspected Delta infections. Suspected-Alpha- or Delta-infections involved higher viral loads than wild type, suggesting increased transmission risk. COVID-19 control strategies should consider age and dominant variant.

Diagnostic accuracy of SARS-CoV-2 antigen test in the pediatric population: A systematic review and meta-analysis

BACKGROUND

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused the global coronavirus disease 2019 (COVID-19) pandemic. Rapid identification and isolation of patients infected with SARS-CoV-2 are critical methods for blocking COVID-19 transmission. The advantages of antigen tests, such as their relatively low cost and short turnaround time, can contribute to the prompt identification of infectious individuals. However, the diagnostic accuracy of antigen tests for COVID-19 in children remains inconclusive. This meta-analysis aimed to evaluate the diagnostic performance of antigen tests for SARS-CoV-2 in the pediatric population.

METHODS

We conducted a literature search for relevant studies in the PubMed, Embase, Google Scholar, and Biomed Central databases. Studies evaluating the diagnostic accuracy of antigen tests for SARS-CoV-2 in pediatric patients were included. In addition, we included studies that provided sufficient data to construct a 2 × 2 table on a per-patient basis. The final literature search was performed on October 10, 2021. Days after symptom onset, asymptomatic and symptomatic individuals may have been potential sources of heterogeneity. The overall sensitivity and specificity of the antigen tests were generated using a bivariate random-effects model.

RESULTS

Five studies with 4400 participants were included. The meta-analysis of antigen tests generated a pooled sensitivity of 65.9% (95% CI: 52.8%-77.0%) and pooled specificity of 99.9% (95% CI: 98.9%-100.0%). A subgroup analysis of studies reporting antigen test data for symptomatic patients showed a pooled sensitivity of 64.5% and a pooled specificity of 99.7%. The subgroup analysis of studies that included 881 asymptomatic participants generated a pooled sensitivity of 48.4% and a pooled specificity of 99.5%.

CONCLUSION

Antigen tests exhibit moderate sensitivity and high specificity for detecting SARS-CoV-2 in children. Antigen tests might have moderate sensitivity for detecting SARS-CoV-2 in symptomatic children, and serial testing might effectively prevent further SARS-CoV-2 transmission.

A collaborative approach to improve representation in viral genomic surveillance

The lack of routine viral genomic surveillance delayed the initial detection of SARS-CoV-2, allowing the virus to spread unfettered at the outset of the U.S. epidemic. Over subsequent months, poor surveillance enabled variants to emerge unnoticed. Against this backdrop, long-standing social and racial inequities have contributed to a greater burden of cases and deaths among minority groups. To begin to address these problems, we developed a new variant surveillance model geared toward building microbial genome sequencing capacity at universities in or near rural areas and engaging the participation of their local communities. The resulting genomic surveillance network has generated more than 1,000 SARS-CoV-2 genomes to date, including the first confirmed case in northeast Louisiana of Omicron, and the first and sixth confirmed cases in Georgia of the emergent BA.2.75 and BQ.1.1 variants, respectively. In agreement with other studies, significantly higher viral gene copy numbers were observed in Delta variant samples compared to those from Omicron BA.1 variant infections, and lower copy numbers were seen in asymptomatic infections relative to symptomatic ones. Collectively, the results and outcomes from our collaborative work demonstrate that establishing genomic surveillance capacity at smaller academic institutions in rural areas and fostering relationships between academic teams and local health clinics represent a robust pathway to improve pandemic readiness.

Author summary

Genomic surveillance involves decoding a pathogen’s genetic code to track its spread and evolution. During the pandemic, genomic surveillance programs around the world provided valuable data to scientists, doctors, and public health officials. Knowing the complete SARS-CoV-2 genome has helped detect the emergence of new variants, including ones that are more transmissible or cause more severe disease, and has supported the development of diagnostics, vaccines, and therapeutics. The impact of genomic surveillance on public health depends on representative sampling that accurately reflects the diversity and distribution of populations, as well as rapid turnaround time from sampling to data sharing. After a slow start, SARS-CoV-2 genomic surveillance in the United States grew exponentially. Despite this, many rural regions and ethnic minorities remain poorly represented, leaving significant gaps in the data that informs public health responses. To address this problem, we formed a network of universities and clinics in Louisiana, Georgia, and Mississippi with the goal of increasing SARS-CoV-2 sequencing volume, representation, and equity. Our results demonstrate the advantages of rapidly sequencing pathogens in the same communities where the cases occur and present a model that leverages existing academic and clinical infrastructure for a powerful decentralized genomic surveillance system.

High Prevalence of Undocumented SARS-CoV-2 Infections in the Pediatric Population of the Tyrolean District of Schwaz

Complementing the adult seroprevalence data collected at the time of the rapid SARS-CoV-2 mass vaccination in the district of Schwaz in 2021, we set out to establish the seroprevalence of SARS-CoV-2 among the pediatric population of the district. A total of 369 children, mean age 9.9 (SD 3.4), participated in the study, answering a structured questionnaire on the history of SARS-CoV-2 infection, household contacts, symptoms and history of vaccination. We determined binding and neutralizing antibody levels using plasma samples provided. We estimated the overall prevalence of SARS-CoV-2 infection in the general pediatric population at the time of the study using the census data from Statistik Austria and daily reports of officially confirmed cases. Excluding study participants who reported a history of PCR-confirmed infection, the age-standardized seroprevalence of previously unknown SARS-CoV-2 infection among the general pediatric population of the district was 27% (95% CI: 26.1–27.8). Adding this to the officially documented cases, the true overall prevalence was 32.8% (95% CI: 31.9–33.6) in contrast to the officially documented 8.0% (95% CI: 7.5–8.5) by June 2021. This translated into a proportion of 75.7% (95% CI: 74.4–77.0) of cases being officially undocumented, suggesting a high extent of silent SARS-CoV-2 infections in the pediatric population and possibly silent transmission.

Causal, Bayesian, & non-parametric modeling of the SARS-CoV-2 viral load distribution vs. patient's age

The viral load of patients infected with SARS-CoV-2 varies on logarithmic scales and possibly with age. Controversial claims have been made in the literature regarding whether the viral load distribution actually depends on the age of the patients. Such a dependence would have implications for the COVID-19 spreading mechanism, the age-dependent immune system reaction, and thus for policymaking. We hereby develop a method to analyze viral-load distribution data as a function of the patients' age within a flexible, non-parametric, hierarchical, Bayesian, and causal model. The causal nature of the developed reconstruction additionally allows to test for bias in the data. This could be due to, e.g., bias in patient-testing and data collection or systematic errors in the measurement of the viral load. We perform these tests by calculating the Bayesian evidence for each implied possible causal direction. The possibility of testing for bias in data collection and identifying causal directions can be very useful in other contexts as well. For this reason we make our model freely available. When applied to publicly available age and SARS-CoV-2 viral load data, we find a statistically significant increase in the viral load with age, but only for one of the two analyzed datasets. If we consider this dataset, and based on the current understanding of viral load's impact on patients' infectivity, we expect a non-negligible difference in the infectivity of different age groups. This difference is nonetheless too small to justify considering any age group as noninfectious.

Shedding of infectious SARS-CoV-2 despite vaccination

The SARS-CoV-2 Delta Variant of Concern is highly transmissible and contains mutations that confer partial immune escape. The emergence of Delta in North America caused the first surge in COVID-19 cases after SARS-CoV-2 vaccines became widely available. To determine whether individuals infected despite vaccination might be capable of transmitting SARS-CoV-2, we compared RT-PCR cycle threshold (Ct) data from 20,431 test-positive anterior nasal swab specimens from fully vaccinated (n = 9,347) or unvaccinated (n = 11,084) individuals tested at a single commercial laboratory during the interval 28 June- 1 December 2021 when Delta variants were predominant. We observed no significant effect of vaccine status alone on Ct value, nor when controlling for vaccine product or sex. Testing a subset of low-Ct (<25) samples, we detected infectious virus at similar rates, and at similar titers, in specimens from vaccinated and unvaccinated individuals. These data indicate that vaccinated individuals infected with Delta variants are capable of shedding infectious SARS-CoV-2 and could play a role in spreading COVID-19.

Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data

Background

Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored.

Methods

This study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients.

Results

This analysis identified 13 genes significantly upregulated in COVID-19 patients’ leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included OAS1, OAS2, OAS3, OASL, HERC6, SERPING1, IFI6, IFI44, IFI44L, CMPK2, RSAD2, EPSTI1, and CXCL10, all of which are involved in antiviral immune regulation. We found that these genes’ downregulation was associated with worse clinical outcomes in COVID-19 patients, such as intensive care unit (ICU) admission, mechanical ventilatory support (MVS) requirement, elevated D-dimer levels, and increased viral loads. Furthermore, this analysis identified two COVID-19 clusters based on the expression profiles of the 13 genes, termed COV-C1 and COV-C2. Compared with COV-C1, COV-C2 more highly expressed the 13 genes, had stronger antiviral immune responses, were younger, and displayed more favorable clinical outcomes.

Conclusions

A strong antiviral immune response is essential in reducing severity of COVID-19.

Role of population and test characteristics in antigen-based SARS-CoV-2 diagnosis, Czechia, August to November 2021

BackgroundAnalyses of diagnostic performance of SARS-CoV-2 antigen rapid diagnostic tests (AG-RDTs) based on long-term data, population subgroups and many AG-RDT types are scarce.AimWe aimed to analyse sensitivity and specificity of AG-RDTs for subgroups based on age, incidence, sample type, reason for test, symptoms, vaccination status and the AG-RDT's presence on approved lists.MethodsWe included AG-RDT results registered in Czechia's Information System for Infectious Diseases between August and November 2021. Subpopulations were analysed based on 346,000 test results for which a confirmatory PCR test was recorded ≤ 3 days after the AG-RDT; 38 AG-RDTs with more than 100 PCR-positive and 300 PCR-negative samples were individually evaluated.ResultsAverage sensitivity and specificity were 72.4% and 96.7%, respectively. We recorded lower sensitivity for age groups 0-12 (65.5%) and 13-18 years (65.3%). The sensitivity level rose with increasing SARS-CoV-2 incidence from 66.0% to 76.7%. Nasopharyngeal samples had the highest sensitivity and saliva the lowest. Sensitivity for preventive reasons was 63.6% vs 86.1% when testing for suspected infection. Sensitivity was 84.8% when one or more symptoms were reported compared with 57.1% for no symptoms. Vaccination was associated with a 4.2% higher sensitivity. Significantly higher sensitivity levels pertained to AG-RDTs on the World Health Organization Emergency Use List (WHO EUL), European Union Common List and the list of the United Kingdom's Department of Health and Social Care.ConclusionAG-RDTs from approved lists should be considered, especially in situations associated with lower viral load. Results are limited to SARS-CoV-2 delta variant.

Sensitivity of Reverse Transcription Polymerase Chain Reaction Tests for Severe Acute Respiratory Syndrome Coronavirus 2 Through Time

BACKGROUND

Reverse transcription polymerase chain reaction (RT-PCR) tests are the gold standard for detecting recent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Reverse transcription PCR sensitivity varies over the course of an individual's infection, related to changes in viral load. Differences in testing methods, and individual-level variables such as age, may also affect sensitivity.

METHODS

Using data from New Zealand, we estimate the time-varying sensitivity of SARS-CoV-2 RT-PCR under varying temporal, biological, and demographic factors.

RESULTS

Sensitivity peaks 4-5 days postinfection at 92.7% (91.4%-94.0%) and remains over 88% between 5 and 14 days postinfection. After the peak, sensitivity declined more rapidly in vaccinated cases compared with unvaccinated, females compared with males, those aged under 40 compared with over 40s, and Pacific peoples compared with other ethnicities.

CONCLUSIONS

Reverse transcription PCR remains a sensitive technique and has been an effective tool in New Zealand's border and postborder measures to control coronavirus disease 2019. Our results inform model parameters and decisions concerning routine testing frequency.

Antibody Response to SARS-CoV-2 in the First Batch of COVID-19 Patients in China by a Self-Developed Rapid IgM-IgG Test

It has been over two years since the COVID-19 pandemic began and it is still an unprecedented global challenge. Here, we aim to characterize the antibody profile from a large batch of early COVID-19 cases in China, from January – March 2020. More than 1,000 serum samples from participants in Hubei and Zhejiang province were collected. A series of serum samples were also collected along the disease course from 70 patients in Shanghai and Chongqing for longitudinal analysis. The serologic assay (ALLtest) we developed was confirmed to have high sensitivity (92.58% - 97.55%) and high specificity (92.14% - 96.28%) for the detection of SARS-CoV-2 nucleocapsid-specific antibodies. Confirmed cases found in the Hubei Provincial Center for Disease Control and Prevention (HBCDC), showed a significantly (p = 0.0018) higher positive rate from the ALLtest than RNA test. Then, we further identified the disease course, age, sex, and symptoms that were correlating factors with our ALLtest results. In summary, we confirmed the high reliability of our ALLtest and its important role in COVID-19 diagnosis. The correlating factors we identified will require special attention during future clinical application.

Determinants of SARS-CoV-2 Contagiousness in Household Contacts of Symptomatic Adult Index Cases

Background

Identifying determinants of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) transmission in settings of contagion is fundamental to inform containment strategies. We assessed SARS-CoV-2 cycle threshold value (Ct) from the first diagnostic nasal-pharyngeal swab of symptomatic index cases and which demographic or clinical characteristics among cases and contacts are associated with transmission risk within households.

Methods

This is a retrospective prevalence study on secondary SARS-CoV-2 cases (SC) among the household contacts of symptomatic adult index cases randomly sampled from all the SARS-CoV-2-positive diagnostic nasopharyngeal swabs analyzed at our regional referral hospital (Amedeo di Savoia Hospital, Turin, Italy) in March, 2020. Index cases underwent a telephone survey to collect their demographic and clinical data and all their household contacts. The Ct value of RdRp gene from the first diagnostic swab of index cases was recorded and index cases were grouped according to Ct tertiles (A < first tertile, first ≤ B ≤ second tertile, C ≥ second tertile). Post hoc analysis was performed in SC as well as contacts that did not undergo SARS-CoV-2 testing but developed compatible signs and symptoms. Non-parametric tests and generalized linear models were run.

Results

Index (n = 72) and contact (n = 164) median age was 54 (48-63) and 32 (20-56) years, respectively. A total of 60, 50, and 54 subjects were contacts of group A, B, and C index cases, respectively; 35.9% of contacts were SC. Twenty-four further subjects (14.6%) met the criteria for symptom-based likely positive SC. The secondary attack rate was 36.0% (28.6-43.4), assuming a mean incubation period of 5 days and a maximum infectious period of 20 days. SC prevalence differed between Ct groups (53.3% A, 32.0% B, 20.4% C; p < 0.001). No difference in SC was found according to sex, presence of signs/symptoms, and COVID-19 severity of index cases, or according to contacts' sex and number per household. The age of both index cases [aOR 4.52 (1.2-17.0) for 60 vs. ≤45 years old] and contacts [aOR 3.66 (1.3-10.6) for 60 vs. ≤45years old] and the Ct of the index [aOR 0.17 (0.07-0.4) for Ct ≥ 31.8 vs. Ct < 24.4] independently associated with SC risk. Sensitivity analysis including symptoms-based likely positive SC supported all the previous results.

Conclusion

In confined transmission settings such as households, PCR Ct values may inform on the contagiousness of infected subjects and age may modulate transmission/contagion risk.

SARS-CoV-2 Transmission Risk Model in an Urban Area of Mexico, Based on GIS Analysis and Viral Load

The COVID-19 pandemic highlighted health systems vulnerabilities, as well as thoughtlessness by governments and society. Due to the nature of this contingency, the use of geographic information systems (GIS) is essential to understand the SARS-CoV-2 distribution dynamics within a defined geographic area. This work was performed in Tepic, a medium-sized city in Mexico. The residence of 834 COVID-19 infected individuals was georeferenced and categorized by viral load (Ct). The analysis took place during the maximum contagion of the first four waves of COVID-19 in Mexico, analyzing 158, 254, 143, and 279 cases in each wave respectively. Then heatmaps were built and categorized into five areas ranging from very low to very high risk of contagion, finding that the second wave exhibited a greater number of cases with a high viral load. Additionally, a spatial analysis was performed to measure urban areas with a higher risk of contagion, during this wave this area had 19,203.08 km² (36.11% of the city). Therefore, a kernel density spatial model integrated by meaningful variables such as the number of infected subjects, viral load, and place of residence in cities, to establish geographic zones with different degrees of infection risk, could be useful for decision-making in future epidemic events.