BACKGROUND: African swine fever (ASF) is a highly contagious and severe haemorrhagic disease of Suidae, with mortalities that approach 100 percent. Several studies suggested the potential implication of non-biting dipterans in the spread of ASFV in pig farms due to the identification of the ASFV DNA. However, to our knowledge, no study has evaluated the viral DNA load in non-biting dipterans collected in outbreak farms and no risk factors have been analysed. In this context, our study aimed to analyse the risk factors associated with the presence of non-biting dipterans collected from ASF outbreaks in relation to the presence and load of viral DNA.
METHODS: Backyard farms (BF), type A farms (TAF), and commercial farms (CF), were targeted for sampling in 2020. In 2021, no BF were sampled. Each farm was sampled only once. The identification of the collected flies to family, genus, or species level was performed based on morphological characteristics using specific keys and descriptions. Pools were made prior to DNA extraction. All extracted DNA was tested for the presence of the ASFV using a real-time PCR protocol. For this study, we considered every sample with a CT value of 40 as positive. The statistical analysis was performed using Epi Info 7 software (CDC, USA).
RESULTS: All collected non-biting flies belonged to five families: Calliphoridae, Sarcophagidae, Fanniidae, Drosophilidae, and Muscidae. Of the 361 pools, 201 were positive for the presence of ASFV DNA. The obtained CT values of the positive samples ranged from 21.54 to 39.63, with a median value of 33.59 and a mean value of 33.56. Significantly lower CT values (corresponding to higher viral DNA load) were obtained in Sarcophagidae, with a mean value of 32.56; a significantly higher number of positive pools were noticed in August, mean value = 33.12.
CONCLUSIONS: Our study brings compelling evidence of the presence of the most common synanthropic flies near domestic pig farms carrying ASFV DNA, highlighting the importance of strengthening the biosecurity measures and protocols for prevention of the insect life cycle and distribution.

In adults, viral load and disease severity can differ by SARS-CoV-2 variant, patterns less understood in children. We evaluated symptomatology, cycle threshold (Ct) values, and SARS-CoV-2 variants among 2,299 pediatric SARS-CoV-2 patients (0-21 years of age) in Colorado, USA, to determine whether children infected with Delta or Omicron had different symptom severity or Ct values than during earlier variants. Children infected during the Delta and Omicron periods had lower Ct values than those infected during pre-Delta, and children <1 year of age had lower Ct values than older children. Hospitalized symptomatic children had lower Ct values than asymptomatic patients. Compared with pre-Delta, more children infected during Delta and Omicron were symptomatic (75.4% pre-Delta, 95.3% Delta, 99.5% Omicron), admitted to intensive care (18.8% pre-Delta, 39.5% Delta, 22.9% Omicron), or received oxygen support (42.0% pre-Delta, 66.3% Delta, 62.3% Omicron). Our data reinforce the need to include children, especially younger children, in pathogen surveillance efforts.

BACKGROUND: Pathogenic infections pose a significant threat to global health, affecting millions of people every year and presenting substantial challenges to healthcare systems worldwide. Efficient and timely testing plays a critical role in disease control and transmission prevention. Group testing is a well-established method for reducing the number of tests needed to screen large populations when the disease prevalence is low. However, it does not fully utilize the quantitative information provided by qPCR methods, nor is it able to accommodate a wide range of pathogen loads.
RESULTS: To address these issues, we introduce a novel adaptive semi-quantitative group testing (SQGT) scheme to efficiently screen populations via two-stage qPCR testing. The SQGT method quantizes cycle threshold (Ct) values into multiple bins, leveraging the information from the first stage of screening to improve the detection sensitivity. Dynamic Ct threshold adjustments mitigate dilution effects and enhance test accuracy. Comparisons with traditional binary outcome GT methods show that SQGT reduces the number of tests by 24% on the only complete real-world qPCR group testing dataset from Israel, while maintaining a negligible false negative rate.
CONCLUSIONS: In conclusion, our adaptive SQGT approach, utilizing qPCR data and dynamic threshold adjustments, offers a promising solution for efficient population screening. With a reduction in the number of tests and minimal false negatives, SQGT holds potential to enhance disease control and testing strategies on a global scale.

UNASSIGNED: Since there are currently no specific SARS-CoV-2 prognostic viral biomarkers for predicting disease severity, there has been interest in using SARS-CoV-2 polymerase chain reaction (PCR) cycle-threshold (Ct) values to predict disease progression.
UNASSIGNED: This study assessed the association between in-hospital mortality of hospitalized COVID-19 cases and Ct-values of gene targets specific to SARS-CoV-2.
UNASSIGNED: Clinical data of hospitalized COVID-19 cases from Gauteng Province from April 2020-July 2022 were obtained from a national surveillance system and linked to laboratory data. The study period was divided into pandemic waves: Asp614Gly/wave1 (7 June-22 Aug 2020); beta/wave2 (15 Nov 2020-6 Feb 2021); delta/wave3 (9 May-18 Sept 2021) and omicron/wave4 (21 Nov 2021-22 Jan 2022). Ct-value data of genes specific to SARS-CoV-2 according to testing platforms (Roche-ORF gene; GeneXpert-N2 gene; Abbott-RdRp gene) were categorized as low (Ct < 20), mid (Ct20-30) or high (Ct > 30).
UNASSIGNED: There were 1205 recorded cases: 836(69.4%; wave1), 122(10.1%;wave2) 21(1.7%; wave3) and 11(0.9%;in wave4). The cases\' mean age(±SD) was 49 years(±18), and 662(54.9%) were female. There were 296(24.6%) deaths recorded: 241(81.4%;wave1), 27 (9.1%;wave2), 6 (2%;wave3), and 2 (0.7%;wave4) (p < 0.001). Sample distribution by testing platforms was: Roche 1,033 (85.7%), GeneXpert 169 (14%) and Abbott 3 (0.3%). The median (IQR) Ct-values according to testing platform were: Roche 26 (22-30), GeneXpert 38 (36-40) and Abbott 21 (16-24). After adjusting for sex, age and presence of a comorbidity, the odds of COVID-19 associated death were high amongst patients with Ct values 20-30[adjusted Odds Ratio (aOR) 2.25; 95% CI: 1.60-3.18] and highest amongst cases with Ct-values <20 (aOR 3.18; 95% CI: 1.92-5.27), compared to cases with Ct-values >30.
UNASSIGNED: Although odds of COVID19-related death were high amongst cases with Ct-values <30, Ct values were not comparable across different testing platforms, thus precluding the comparison of SARS-CoV-2 Ct-value results.

OBJECTIVE: The aim of the study was to determine and evaluate the clinical usefulness of pathogen specific semi-quantitative cut-offs in stool samples with multiple pathogen detections.
METHODS: The PCR (Seegene Allplex Gastrointestinal Virus Assay) data from 4527 positive samples received over 16 months were retrospectively analyzed to investigate the distribution of the Ct values of each individual viral pathogen. By using interquartile ranges for each viral pathogen, pathogen specific semi-quantitative cut-offs were determined.
RESULTS: After a thorough analysis of the Ct values, a well-founded decision to exclude all results with a Ct value higher than 35 was made. This approach made it possible to generate a more nuanced report and to facilitate clinical interpretation in case of mixed infections by linking a lower Ct value of a pathogen to a greater likelihood of being a relevant causative pathogen. Moreover, not reporting viral pathogens with a Ct value higher than 35 led to a significant reduction (p < 0.0001) of reported mixed infections compared to oversimplified qualitative or qualitative reporting.
CONCLUSIONS: By omitting very high Ct values and reporting semi-quantitatively, value was added to the syndromic reports, leading to an easier to read lab report, especially in mixed infections.

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.

The concept of viral load was introduced in the 1980s to measure the amount of viral genetic material in a person\'s blood, primarily for human immunodeficiency virus (HIV). It has since become crucial for monitoring HIV infection progression and assessing the efficacy of antiretroviral therapy. However, during the coronavirus disease 2019 pandemic, the term \"viral load\" became widely popularized, not only for the scientific community but for the general population. Viral load plays a critical role in both clinical patient management and research, providing valuable insights for antiviral treatment strategies, vaccination efforts, and epidemiological control measures. As measuring viral load is so important, why don\'t researchers discuss the best way to do it? Is it simply acceptable to use raw Ct values? Relying solely on Ct values for viral load estimation can be problematic due to several reasons. First, Ct values can vary between different quantitative polymerase chain reaction assays, platforms, and laboratories, making it difficult to compare data across studies. Second, Ct values do not directly measure the quantity of viral particles in a sample and they can be influenced by various factors such as initial viral load, sample quality, and assay sensitivity. Moreover, variations in viral RNA extraction and reverse-transcription steps can further impact the accuracy of viral load estimation, emphasizing the need for careful interpretation of Ct values in viral load assessment. Interestingly, we did not observe scientific articles addressing different strategies to quantify viral load. The absence of standardized and validated methods impedes the implementation of viral load monitoring in clinical management. The variability in cell quantities within samples and the variation in viral particle numbers within infected cells further challenge accurate viral load measurement and interpretation. To advance the field and improve patient outcomes, there is an urgent need for the development and validation of tailored, standardized methods for precise viral load quantification.

UNASSIGNED: With the popularity of computed tomography (CT) of the thorax, the rate of diagnosis for patients with early-stage lung cancer has increased. However, distinguishing high-risk pulmonary nodules (HRPNs) from low-risk pulmonary nodules (LRPNs) before surgery remains challenging.
UNASSIGNED: A retrospective analysis was performed on 1064 patients with pulmonary nodules (PNs) admitted to the Qilu Hospital of Shandong University from April to December 2021. Randomization of all eligible patients to either the training or validation cohort was performed in a 3:1 ratio. Eighty-three PNs patients who visited Qianfoshan Hospital in the Shandong Province from January through April of 2022 were included as an external validation. Univariable and multivariable logistic regression (forward stepwise regression) were used to identify independent risk factors, and a predictive model and dynamic web nomogram were constructed by integrating these risk factors.
UNASSIGNED: A total of 895 patients were included, with an incidence of HRPNs of 47.3% (423/895). Logistic regression analysis identified four independent risk factors: the size, consolidation tumor ratio, CT value of PNs, and carcinoembryonic antigen levels in blood. The area under the ROC curves was 0.895, 0.936, and 0.812 for the training, internal validation, and external validation cohorts, respectively. The Hosmer-Lemeshow test demonstrated excellent calibration capability, and the fit of the calibration curve was good. DCA has shown the nomogram to be clinically useful.
UNASSIGNED: The nomogram performed well in predicting the likelihood of HRPNs. In addition, it identified HRPNs in patients with PNs, achieved accurate treatment with HRPNs, and is expected to promote their rapid recovery.

UNASSIGNED: Comparison of clinical value of RT-qPCR-based SARS-CoV-2 tests performed on saliva samples (SSs) and nasopharyngeal swab samples (NPSs) for prediction of the COVID-19 disease severity.
UNASSIGNED: Three paired SSs and NPSs collected every 3 days from 100 hospitalised COVID-19 patients during 2020 Jul-2021 Jan were tested by RT-qPCR for the original SARS-CoV-2 virus and compared to 150 healthy controls. Cases were divided into mild+moderate (Cohort I, N = 47) and severe disease (Cohort II, N = 53) cohorts and compared.
UNASSIGNED: SARS-CoV-2 was detected in 65% (91/140) vs. 53% (82/156) of NPSs and 49% (68/139) vs. 48% (75/157) of SSs collected from Cohort I and II, respectively, resulting in the total respective detection rates of 58% (173/296) vs. 48% (143/296) (P = 0.017). Ct values of SSs were lower than those of NPSs (mean Ct = 28.01 vs. 30.07, P = 0.002). Although Ct values of the first SSs were significantly lower in Cohort I than in Cohort II (P = 0.04), it became negative earlier (mean 11.7 vs. 14.8 days, P = 0.005). Multivariate Cox proportional hazards regression analysis showed that Ct value ≤30 from SSs was the independent predictor for severe COVID-19 (HR = 10.06, 95% CI: 1.84-55.14, P = 0.008).
UNASSIGNED: Salivary RT-qPCR testing is suitable for SARS-CoV-2 infection control, while simple measurement of Ct values can assist in prediction of COVID-19 severity.

To investigate the associations between the overall burden of comorbidity, inflammatory indicators in plasma and Ct values among the elderly with COVID-19.
We conducted a retrospective observational study. The results of each nucleic acid test of during hospitalization were obtained. Linear regression models assessed the associations between the overall burden of comorbidity, inflammatory indicators in plasma and Ct values among the elderly. A causal mediation analysis was performed to assess the mediation effects of inflammatory indicators on the association between the overall burden of comorbidity and Ct values.
A total of 767 COVID-19 patients aged ≥ 60 years were included between April 2022 and May 2022. Patients with a high burden of comorbidity had significantly lower Ct values of the ORF gene than subjects with a low burden of comorbidity (median, 24.81 VS 26.58, P < 0.05). Linear regression models showed that a high burden of comorbidity was significantly associated with higher inflammatory responses, including white blood cell count, neutrophil count and C-reactive protein. Also, white blood cell count, neutrophil count, C-reactive protein and the overall burden of comorbidity assessed by age-adjusted Charlson comorbidity index were independent risk factors for the Ct values. A mediation analysis detected the mediation effect of white blood cells on the association between the burden of comorbidity and Ct values, with the indirect effect estimates of 0.381 (95% CI: 0.166, 0.632, P < 0.001). Similarly, the indirect effect of C-reactive protein was -0.307 (95% CI: -0.645, -0.064, P = 0.034). White blood cells and C-reactive protein significantly mediated the relationship between the burden of comorbidity and Ct values by 29.56% and 18.13% of the total effect size, respectively.
Inflammation mediated the association between the overall burden of comorbidity and Ct values among elderly with COVID-19, which suggests that combined immunomodulatory therapies could reduce the Ct values for such patients with a high burden of comorbidity.