PCR combined with serologic testing improves the yield and efficiency of SARS-CoV-2 infection hunting: A study in 40,689 consecutive overseas arrivals

Background The global epidemiological situation of COVID-19 remains serious. The rapid hunting of SARS-CoV-2 infection is the key means for preventing transmission. Methods A total of 40,689 consecutive overseas arrivals were screened for SARS-CoV-2 infection based on PCR and serologic testing. The yield and efficiency of different screening algorithms were evaluated. Result Among the 40,689 consecutive overseas arrivals, 56 (0.14%) subjects were confirmed to have SARS-CoV-2 infection. The asymptomatic rate was 76.8%. When the algorithm based on PCR alone was used, the identification yield of a single round of PCR (PCR1) was only 39.3% (95% CI: 26.1–52.5%). It took at least four rounds of PCR to achieve a yield of 92.9% (95% CI: 85.9–99.8%). Fortunately, an algorithm based on a single round of PCR combined with a single round of serologic testing (PCR1+ Ab1) greatly improved the screening yield to 98.2% (95% CI: 94.6–100.0%) and required 42,299 PCR and 40,689 serologic tests that cost 6,052,855 yuan. By achieving a similar yield, the cost of PCR1+ Ab1 was 39.2% of that of four rounds of PCR. For hunting one case in PCR1+ Ab1, 769 PCR and 740 serologic tests were required, costing 110,052 yuan, which was 63.0% of that of the PCR1 algorithm. Conclusion Comparing an algorithm based on PCR alone, PCR combined with a serologic testing algorithm greatly improved the yield and efficiency of the identification of SARS-CoV-2 infection.

PCR combined with serologic testing improves the yield and efficiency of SARS-CoV-2 infection hunting: A study in 40,689 consecutive overseas arrivals.

Background: The global epidemiological situation of COVID-19 remains serious. The rapid hunting of SARS-CoV-2 infection is the key means for preventing transmission. Methods: A total of 40,689 consecutive overseas arrivals were screened for SARS-CoV-2 infection based on PCR and serologic testing. The yield and efficiency of different screening algorithms were evaluated. Result: Among the 40,689 consecutive overseas arrivals, 56 (0.14%) subjects were confirmed to have SARS-CoV-2 infection. The asymptomatic rate was 76.8%. When the algorithm based on PCR alone was used, the identification yield of a single round of PCR (PCR1) was only 39.3% (95% CI: 26.1-52.5%). It took at least four rounds of PCR to achieve a yield of 92.9% (95% CI: 85.9-99.8%). Fortunately, an algorithm based on a single round of PCR combined with a single round of serologic testing (PCR1+ Ab1) greatly improved the screening yield to 98.2% (95% CI: 94.6-100.0%) and required 42,299 PCR and 40,689 serologic tests that cost 6,052,855 yuan. By achieving a similar yield, the cost of PCR1+ Ab1 was 39.2% of that of four rounds of PCR. For hunting one case in PCR1+ Ab1, 769 PCR and 740 serologic tests were required, costing 110,052 yuan, which was 63.0% of that of the PCR1 algorithm. Conclusion: Comparing an algorithm based on PCR alone, PCR combined with a serologic testing algorithm greatly improved the yield and efficiency of the identification of SARS-CoV-2 infection.

Unspecific reactivity must be excluded in COVID-19 epidemiological analyses or virus tracing based on serologic testing: Analysis of 46,777 post-pandemic samples and 1,114 pre-pandemic samples

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). Serologic testing is complementary to nucleic acid screening to identify SARS-CoV-2. This study aimed to evaluate unspecific reactivity in SARS-CoV-2 serologic tests. Materials and methods Total anti-SARS-CoV-2 antibodies from 46,777 subjects who were screened for SARS-CoV-2 were retrospectively studied to evaluate the incidence and characteristics of the unspecific reactivity. A total of 1,114 pre-pandemic samples were also analysed to compare unspecific reactivity. Results The incidence of unspecific reactivity in anti-SARS-CoV-2 total antibody testing was 0.361% in 46,777 post-pandemic samples, similar to the incidence of 0.359% (4/1,114) in 1,114 pre-pandemic samples (p = 0.990). Subjects ≥ 19 years old had a 2.753-fold [95% confidence interval (CI), 1.130–6.706] higher probability of unspecific reactivity than subjects < 19 years old (p = 0.026). There was no significant difference between the sexes. The unspecific reactivity was associated with 14 categories within the disease spectrum, with three tops being the skin and subcutaneous tissue diseases (0.93%), respiratory system diseases (0.78%) and neoplasms diseases (0.76%). The percentage of patients with a titer ≥ 13.87 cut-off index (COI) in the unspecific reactivity was 7.69%. Conclusion Our results suggest a unspecific reactivity incidence rate of 0.361% involving 14 categories on the disease spectrum. Unspecific reactivity needs to be excluded when performing serologic antibody testing in COVID-19 epidemiological analyses or virus tracing.

Fractional SEIR model and data-driven predictions of COVID-19 dynamics of Omicron variant.

We study the dynamic evolution of COVID-19 caused by the Omicron variant via a fractional susceptible-exposed-infected-removed (SEIR) model. Preliminary data suggest that the symptoms of Omicron infection are not prominent and the transmission is, therefore, more concealed, which causes a relatively slow increase in the detected cases of the newly infected at the beginning of the pandemic. To characterize the specific dynamics, the Caputo-Hadamard fractional derivative is adopted to refine the classical SEIR model. Based on the reported data, we infer the fractional order and time-dependent parameters as well as unobserved dynamics of the fractional SEIR model via fractional physics-informed neural networks. Then, we make short-time predictions using the learned fractional SEIR model.

Ambient BTEX Concentrations during the COVID-19 Lockdown in a Peri-Urban Environment (Orléans, France)

During the period from 17 March to 10 May 2020, France saw dramatic shifts in domestic, industrial and transport activities as a national lockdown was introduced. So far, studies have generally focused on urban settings, by contrast, this work reports data for a peri-urban location. Air samples were collected and analyzed using a fully automated GC-MS-FID system in an air quality monitoring station situated in the suburbs of Orléans, France. Average concentrations of BTEX (benzene, toluene, ethylbenzene, and xylenes) before, during, and after lockdown, were 402 ± 143, 800 ± 378 and 851 ± 445 pptv, respectively. Diurnal variation in BTEX and correlations between each of its components were analyzed to determine its various sources. The toluene/benzene (T/B) and m,p-xylene/ethylbenzene (MP/E) ratios, photochemical ages were used to explore whether the BTEX were from local or more distant sources. Together with a host of complementary measurements including NOx, O3, black carbon, meteorological parameters, and anthropogenic activities, we were able to make some inferences on the sources of BTEX. The results suggest that although anomalous local anthropogenic activity can lead to significant changes in BTEX concentrations, pollution levels in Orléans are mostly dependent on meteorological conditions, specifically whether the winds are coming from the Paris region. It appears, based on these measurements, that the pollution in the Orléans area is very much tied to the nearby megacity of Paris, this may be true for other peri-urban sites with implications for city planning and pollution mitigation strategies.

Influence of COVID-19 on Manufacturing Industry and Corresponding Countermeasures from Supply Chain Perspective.

It is critical for the recovery of manufacturing industry against COVID-19 by analyzing its impact from supply chain perspective and exploring corresponding countermeasures. Firstly, this paper studies the initial impact caused by worldwide spread of the coronavirus, such as production disruption of raw material and spare parts, unsatisfied market demand due to setbacks in logistics, increasing bankruptcy risk for small and mediumsized enterprises (SMEs), and demand fluctuation enlargement. Secondly, the aftershock of COVID-19 is analyzed. With the trend of regionalization and digitalization, two-step countermeasures are proposed to help the recovery of manufacturing industry within the pandemic and better prepare for the post-COVID-19 world from supply chain perspective.