Mitigation of breathing contaminants: Exhaust location optimization for indoor space with impinging jet ventilation supply

Densely occupied spaces (e.g., classrooms) are generally over-crowded and pose a high risk of cross-infection during the pandemic of COVID-19. Among various ventilation systems, impinging jet ventilation (IJV) system might be promising for such spaces. However, the exhaust location of the IJV system used for densely occupied classrooms is unclear. This study aims to investigate the effects of exhaust location on the removal of exhaled contaminants in a classroom (15 × 7 × 5 m3) occupied by 50 students. Exhaled contaminants are modeled by a tracer gas released at the top of each manikin. The reference case has three exhausts evenly distributed in the ceiling. The results indicate that: a) a recirculation airflow entraining exhaled contaminants exists above the occupied zone;b) this recirculation air flow entrains contaminants and accumulates them at the upper part of the room near the diffuser;c) locating merely one exhaust on the same side of the supply diffuser leads to the best indoor air quality, i.e., it reduces the mean age of air from 278 s to 243 s, the mass fraction of CO2 from 753 ppm to 726 ppm, and the concentration of tracer gas from 305 ppm to 266 ppm;d) this layout still performs the best when the supply velocity drops to 0.5 m/s. It is worth noting that the proposed layout has fewer exhausts than the reference case but performs better. These results conclude that the exhaust for large spaces is not evenly distributed but depends on the indoor airflow pattern: the key is locating the exhaust near the region with high contaminant concentration. Factors determining the recirculation airflow are suggested to be further studied. Graphical abstract Image 1

Do you trust digital health pass? Understanding tourists' responses toward using health QR codes in pandemic travel. (Special Issue: Tourism recovery under COVID-19: Experiences from China.)

Health information technology has been widely implemented to ensure travel safety in the current normalization stage of COVID-19. However, levels of public trust and acceptance toward health QR codes are low in many countries, impeding tourism recovery after the outbreak. Thus, this study aims to explore the psychological mechanisms underpinning tourist trust, confidence, and behaviors toward traveling with health QR codes. Using a quota sampling, 1089 respondents were collected across mainland China. Results identify that tourists' trust in health QR codes is affected by knowledge, perceived efficacy, privacy risk, and security. People's trust in digital health applications can boost travel confidence and increase acceptance of tracing technology and travel intention after the pandemic. Practical implications for developing policies and strategies to encourage travel are provided.

Efficacy and Safety of Longyizhengqi Granule in Treatment of Mild COVID-19 Patients Caused by SARS-CoV-2 Omicron Variant: A Prospective Study.

Purpose: This study aimed to evaluate the clinical efficacy of Longyizhengqi granule, a traditional Chinese medicine, in patients with mild COVID-19. Patients and Methods: We conducted a prospective study including mild COVID-19 participants conducted at Mobile Cabin Hospital in Shanghai, China. Participants were assigned to receive Longyizhengqi granule or conventional treatment. The primary outcome was the time for nucleic acid to turn negative and the secondary outcomes are hospital stay and changes in cycle threshold (Ct) values for N gene and Orf gene. Multilevel random-intercept model was performed to analyze the effects of treatment. Results: A total of 3243 patients were included in this study (Longyizhengqi granule 667 patients; conventional treatment 2576 patients). Age (43.5 vs 42.1, p<0.01) and vaccination doses (not vaccinated: 15.8% vs 21.7%, 1 dose: 3.5% vs 2.9%, 2 doses: 27.9% vs 25.6%, 3 doses: 52.8% vs 49.8%. p<0.01) show statistical difference between Conventional treatment group and LYZQ granules group. The use of Longyizhengqi granule could significantly reduce the time for nucleic acid to turn negative (14.2 days vs 10.7 days, p<0.01), shorten hospital stay (12.5 days vs 9.9 days, p<0.01), and increase the changes in Ct value for N gene (8.44 vs 10.33, p<0.01) and Orf gene (7.31 vs 8.44, p<0.01) to approximately 1.5. Moreover, the difference in the changes of Ct values on the 4th, 6th, 8th, and 10th days seem to increase between two groups. No serious adverse events were reported. Conclusion: Longyizhengqi granule might be a promising drug for the treatment of mild COVID-19, and it might be beneficial to effectively shorten the negative transition time of nucleic acid, the total days of hospitalization, and increase the changes of Ct values. Long-term randomized controlled trials with follow-up evaluations are required to confirm its long-term efficacy.

Post-traumatic stress disorders, anxiety, and depression in college students during the COVID-19 pandemic: a cross-sectional study.

OBJECTIVES: The COVID-19 pandemic has caused an increase in psychiatric disorders in college students, particularly posttraumatic stress disorders (PTSD), depression, and anxiety. While existing studies assess the prevalence of these disorders and their predictors, they overlook potential complications caused by comorbidity between these disorders. To fill this gap, this study examined the prevalence of PTSD, depression, anxiety, and their comorbidity to inform targeted intervention for college students during the COVID-19 pandemic. DESIGN: Self-report questionnaires were used to assess 6,898 college students about six months after the COVID-19 outbreak. RESULTS: The results found that the prevalence of PTSD, depression, and anxiety were 15.5%, 32.2%, and 32.1% respectively, and the prevalence of comorbid PTSD and depression, comorbid PTSD and anxiety, comorbid depression and anxiety, and comorbid PTSD, depression, and anxiety symptoms were 11.5%, 11.6%, 20.4%, and 9.4% respectively. Moreover, left-behind status, lower economic status, previous trauma experiences, exposure to the pandemic, and rumination were risk factors of psychological distress, but self-disclosure was a protective factor for these disorders. CONCLUSION: These results indicate that distinct psychiatric disorders may be comorbid in individuals, and are further influenced by pre-, within-, and post-disaster factors. Furthermore, psychological service targeted at college students should pay attention to comorbid symptoms rather than only symptoms of single disorders.

Transmission mitigation of COVID-19: Exhaled contaminants removal and energy saving in densely occupied space by impinging jet ventilation.

The pandemic of COVID-19 and its transmission ability raise much attention to ventilation design as indoor-transmission outstrips outdoor-transmission. Impinging jet ventilation (IJV) systems might be promising to ventilate densely occupied large spaces due to their high jet momentum. However, their performances in densely occupied spaces have rarely been explored. This study proposes a modified IJV system and evaluates its performance numerically in a densely occupied classroom mockup. A new assessment formula is also proposed to evaluate the nonuniformity of target species CO2. The infector is assumed as the manikin with the lowest tracer gas concentration in the head region. The main results include: a) Indoor air quality (IAQ) in the classroom is improved significantly compared with a mixing ventilation system, i.e., averaged CO2 in the occupied zone (OZ) is reduced from 1287 ppm to 1078 ppm, the OZ-averaged mean age of air is reduced from 439 s to 177 s; b) The mean infection probability is reduced from 0.047% to 0.027% with an infector, and from 0.035% to 0.024% with another infector; c) Cooling coil load is reduced by around 21.0%; d) Overall evaluation indices meet the requirements for comfortable environments, i.e., the temperature difference between head and ankle is within 3 °C and the OZ-averaged predictive mean vote is in the range of -0.5 - 0.5; e) Thermal comfort level and uniformity are decreased, e.g., overcooling near diffuser at ankle level. Summarily, the target system effectively improves IAQ, reduces exhaled-contaminant concentration in head regions, and saves energy as well.

Transmission mitigation of COVID-19: Exhaled contaminants removal and energy saving in densely occupied space by impinging jet ventilation

The pandemic of COVID-19 and its transmission ability raise much attention to ventilation design as indoor-transmission outstrips outdoor-transmission. Impinging jet ventilation (IJV) systems might be promising to ventilate densely occupied large spaces due to their high jet momentum. However, their performances in densely occupied spaces have rarely been explored. This study proposes a modified IJV system and evaluates its performance numerically in a densely occupied classroom mockup. A new assessment formula is also proposed to evaluate the nonuniformity of target species CO2. The infector is assumed as the manikin with the lowest tracer gas concentration in the head region. The main results include: a) Indoor air quality (IAQ) in the classroom is improved significantly compared with a mixing ventilation system, i.e., averaged CO2 in the occupied zone (OZ) is reduced from 1287 ppm to 1078 ppm, the OZ-averaged mean age of air is reduced from 439 s to 177 s;b) The mean infection probability is reduced from 0.047% to 0.027% with an infector, and from 0.035% to 0.024% with another infector;c) Cooling coil load is reduced by around 21.0%;d) Overall evaluation indices meet the requirements for comfortable environments, i.e., the temperature difference between head and ankle is within 3 °C and the OZ-averaged predictive mean vote is in the range of −0.5 - 0.5;e) Thermal comfort level and uniformity are decreased, e.g., overcooling near diffuser at ankle level. Summarily, the target system effectively improves IAQ, reduces exhaled-contaminant concentration in head regions, and saves energy as well. Graphical Image 1

Clinical characteristics of 1139 mild cases of the SARS-CoV-2 Omicron variant infected patients in Shanghai.

In March 2022, the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surged during the Coronavirus Disease 2019 (COVID-19) pandemic in Shanghai, but over 90% of patients were mild. This study included 1139 COVID-19 patients mildly infected with the Omicron variant of SARS-CoV-2 in Shanghai from May 1 to 10, 2022, aiming to clarify the demographic characteristics and clinical symptoms of patients with mild Omicron infection. The clinical phenotypes of Omicron infection were identified by model-based cluster analysis to explore the features of different clusters. The median age of the patients was 41.0 years [IQR: 31.0-52.0 years] and 73.0% were male. The top three clinical manifestations are cough (57.5%), expectoration (48.3%), and nasal congestion and runny nose (43.4%). The prevalence of nasal congestion and runny nose varied significantly across the doses of vaccinations, with 23.1% in the unvaccinated population and 30%, 45.9%, and 44.3% in the 1-dose, 2-dose and 3-dose vaccinated populations, respectively. In addition, there were significant differences for fever (23.1%, 26.0%, 28.6%, 18.4%), head and body heaviness (15.4%, 14.0%, 26.7%, 22.4%), and loss of appetite (25.6%, 30.0%, 33.6%, 27.7%). The unvaccinated population had a lower incidence of symptoms than the vaccinated population. Cluster analysis revealed that all four clusters had multisystemic symptoms and were dominated by both general and respiratory symptoms. The more severe the degree of the symptoms was, the higher the prevalence of multisystemic symptoms will be. The Omicron variant produced a lower incidence of symptoms in mildly infected patients than previous SARS-CoV-2 variants, but the clinical symptoms caused by the Omicron variant are more complex, so that it needs to be differentiated from influenza.

Development of a multi-recombinase polymerase amplification assay for rapid identification of COVID-19, influenza A and B.

The coronavirus disease 2019 (COVID-19) pandemic caused extensive loss of life worldwide. Further, the COVID-19 and influenza mix-infection had caused great distress to the diagnosis of the disease. To control illness progression and limit viral spread within the population, a real-time reverse-transcription PCR (RT-PCR) assay for early diagnosis of COVID-19 was developed, but detection was time-consuming (4-6 h). To improve the diagnosis of COVID-19 and influenza, we herein developed a recombinase polymerase amplification (RPA) method for simple and rapid amplification of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19 and Influenza A (H1N1, H3N2) and B (influenza B). Genes encoding the matrix protein (M) for H1N1, and the hemagglutinin (HA) for H3N2, and the polymerase A (PA) for Influenza B, and the nucleocapsid protein (N), the RNA-dependent-RNA polymerase (RdRP) in the open reading frame 1ab (ORF1ab) region, and the envelope protein (E) for SARS-CoV-2 were selected, and specific primers were designed. We validated our method using SARS-CoV-2, H1N1, H3N2 and influenza B plasmid standards and RNA samples extracted from COVID-19 and Influenza A/B (RT-PCR-verified) positive patients. The method could detect SARS-CoV-2 plasmid standard DNA quantitatively between 102 and 105 copies/ml with a log linearity of 0.99 in 22 min. And this method also be very effective in simultaneous detection of H1N1, H3N2 and influenza B. Clinical validation of 100 cases revealed a sensitivity of 100% for differentiating COVID-19 patients from healthy controls when the specificity was set at 90%. These results demonstrate that this nucleic acid testing method is advantageous compared with traditional PCR and other isothermal nucleic acid amplification methods in terms of time and portability. This method could potentially be used for detection of SARS-CoV-2, H1N1, H3N2 and influenza B, and adapted for point-of-care (POC) detection of a broad range of infectious pathogens in resource-limited settings.

Internet of medical things-enabled CRISPR diagnostics for rapid detection of SARS-CoV-2 variants of concern.

Previous studies have highlighted CRISPR-based nucleic acid detection as rapid and sensitive diagnostic methods for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we reported an optimized CRISPR-Cas12a diagnostic platform for the safe and rapid detection of SARS-CoV-2 variants of concern (VOCs). This platform, which was referred to as CALIBURN-v2, could complete the diagnosis on extracted RNA samples within 25 min in a closed-lid reaction mode and had 100-fold increase in detection sensitivity in comparison with previous platforms. Most importantly, by integrating a portable device and smartphone user interface, CALIBURN-v2 allowed for cloud server-based data collection and management, thus transforming the point-of-care testing (POCT) platform to internet of medical things (IoMT) applications. It was found that IoMT-enabled CALIBURN-v2 could achieve 95.56% (172 out of 180) sensitivity for SARS-CoV-2 wild type and 94.38% (84 out of 89) overall sensitivity for SARS-CoV-2 variants including Delta and Omicron strains. Therefore, our study provides a feasible approach for IoMT-enabled CRISPR diagnostics for the detection of SARS-CoV-2 VOCs.

A new PEDV strain CH/HLJJS/2022 can challenge current detection methods and vaccines.

BACKGROUND: Porcine epidemic diarrhea virus (PEDV) variant strains cause great economic losses to the global swine industry. However, vaccines do not provide sufficient protection against currently circulating strains due to viral mutations. This study traced the molecular characteristics of the most recent isolates in China and aimed to provide a basis for the prevention and treatment of PEDV. METHODS: We obtained samples from a Chinese diarrheal swine farm in 2022. Reverse transcription polymerase chain reaction and immunofluorescence were used to determine the etiology, and the full-length PEDV genome was sequenced. Nucleotide similarity was calculated using MEGA to construct a phylogenetic tree and DNASTAR. Mutant amino acids were aligned using DNAMAN and modeled by SWISS-MODEL, Phyre2 and FirstGlance in JMOL for protein tertiary structure simulation. Additionally, TMHMM was used for protein function prediction. RESULTS: A PEDV virulent strain CH/HLJJS/2022 was successfully isolated in China. A genome-wide based phylogenetic analysis suggests that it belongs to the GII subtype, and 96.1-98.9% homology existed in the whole genomes of other strains. For the first time, simultaneous mutations of four amino acids were found in the highly conserved membrane (M) and nucleocapsid (N) proteins, as well as eight amino acid mutations that differed from the vast majority of strains in the spike (S) protein. Three of the mutations alter the S-protein spatial structure. In addition, typing markers exist during strain evolution, but isolates are using the fusion of specific amino acids from multiple variant strains to add additional features, as also demonstrated by protein alignments and 3D models of numerous subtype strains. CONCLUSION: The newly isolated prevalent strain CH/HLJJS/2022 belonged to the GII subtype, and thirteen mutations different from other strains were found, including mutations in the highly conserved m and N proteins, and in the S1° and COE neutralizing epitopes of the S protein. PEDV is breaking through original cognitions and moving on a more complex path. Surveillance for PEDV now and in the future and improvements derived from mutant strain vaccines are highly warranted.

Internet of medical things-enabled CRISPR diagnostics for rapid detection of SARS-CoV-2 variants of concern

Previous studies have highlighted CRISPR-based nucleic acid detection as rapid and sensitive diagnostic methods for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we reported an optimized CRISPR-Cas12a diagnostic platform for the safe and rapid detection of SARS-CoV-2 variants of concern (VOCs). This platform, which was referred to as CALIBURN-v2, could complete the diagnosis on extracted RNA samples within 25 min in a closed-lid reaction mode and had 100-fold increase in detection sensitivity in comparison with previous platforms. Most importantly, by integrating a portable device and smartphone user interface, CALIBURN-v2 allowed for cloud server-based data collection and management, thus transforming the point-of-care testing (POCT) platform to internet of medical things (IoMT) applications. It was found that IoMT-enabled CALIBURN-v2 could achieve 95.56% (172 out of 180) sensitivity for SARS-CoV-2 wild type and 94.38% (84 out of 89) overall sensitivity for SARS-CoV-2 variants including Delta and Omicron strains. Therefore, our study provides a feasible approach for IoMT-enabled CRISPR diagnostics for the detection of SARS-CoV-2 VOCs.

Meaning in life and health behavior habits during the COVID-19 pandemic: Mediating role of health values and moderating role of conscientiousness.

An increasing number of studies have explored health behavior changes since the COVID-19 outbreak, however, the potential mechanism leading to the acquisition of COVID-19-related health behavior habits remains largely underexplored. The current study aimed to investigate how meaning in life contributed to the Chinese general public's acquisition of COVID-19-related health behavior habits, and whether health values would play a mediating role and conscientiousness would play a further moderating role in this relation. A total of 1024 Chinese participants (age range = 17-63 years; 67.29% females) were recruited by posting flyers on an open-access web forum. All participants voluntarily completed a series of online anonymous questionnaires assessing conscientiousness, meaning in life, health values and health behavior habits. Results showed that (1) the majority of the respondents reported the acquisition of COVID-19-related health behavior habits, and meaning in life positively predicted COVID-19-related health behavior habits; (2) health values mediated the link between meaning in life and health behavior habits; and (3) conscientiousness moderated the indirect effect, such that the indirect effect was stronger among individuals with low conscientiousness. These findings have important implications for revealing the reconstruction of the Chinese public's health behavior habits and its potential mechanism that meaning in life influences health behavior habits through health values during the COVID-19 pandemic, particularly for individuals with low conscientiousness.

Clinical predictors and RT-PCR profile of prolonged viral shedding in patients with SARS-CoV-2 Omicron variant in Shanghai: A retrospective observational study

Objective To evaluate determinants of prolonged viral RNA shedding in hospitalized patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant infection. Materials and methods Hospitalized patients tested SARS-CoV-2 positive by nasopharyngeal real-time reverse transcriptase-polymerase chain reaction (RT-PCR) were included in the single-center, retrospective study. Patients were divided into 2 groups according to the timing of viral clearance (≤ 8 days, “early clearance” and ≥15 days, “late clearance”). Results 4,084 patients were included in the study (1,023 late clearance, 3,061 early clearance), with median age of 50 years and a higher proportion (61.4%) of male. Univariate analyses showed that comorbidities (including hypertension, diabetes, and coronary heart disease), receiving vaccine, the number of vaccinations, cycle threshold (Ct) open reading frame 1ab (ORF 1ab), and nucleocapsid protein (N) gene values on admission were associated with late viral clearance. In the multivariable analysis, the number of vaccinations (P = 0.010) and Ct ORF 1ab gene (P < 0.001) values on admission were significantly associated with late viral clearance. Generalized Estimating Equations (GEE) analysis showed that the Ct value of ORF 1ab gene and N gene remained unchanged within 3 days, and showed progressively higher values with increasing days during late viral RNA clearance. Conclusion The number of vaccinations and Ct values of ORF 1ab gene were independently associated with a prolonged SARS-CoV-2 RNA shedding.

Successful Intervention with Traditional Chinese Medicine for Severe Coronavirus Disease 2019: A Case Report

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2, is a major public health threat worldwide. However, there are no clinically approved antiviral drugs for COVID-19. Traditional Chinese medicine (TCM) is an important part of complementary and alternative medicine. Based on the TCM principles of pathogenesis, our team proposed “San Tong strategies” (san tong liao fa) and the “Truncation and Reversion strategy” (jie duanniu zhuan ce lve) and developed a Chinese herbal medicine formula to dispel external pathogens, clear heat, drain fire, and detoxify. A 50-year-old man with severe COVID-19 was admitted and received our oral Chinese herbal formula, acupoint plaster application, and moxibustion for 14 days. The computed tomography manifestations of COVID-19 showed marked improvements, and the patient achieved complete remission of fever, cough, fatigue, dizziness, nasal congestion, and rhinorrhea. This case provides a specific TCM treatment plan and effective reference for the treatment of COVID-19.

Optimizing the Systematic Characteristics of Online Learning Systems to Enhance the Continuance Intention of Chinese College Students

Different from systems that directly provide online shared courses such as MOOC, online learning systems such as Tencent Classroom simulate a real classroom environment for students and teachers to realize online face-to-face teaching, utilized during the COVID-19 pandemic. Nevertheless, due to the limitation of physical distance, the intelligent design of online learning systems is necessary to provide students with a good learning experience. This study notes that an unexpected optimization effect is the impact of system characteristics on the flow experience of online learning systems, which has not been studied, but plays a vital role in the effectiveness of online learning systems. In the study, a questionnaire was created and multi-stage sampling was used to investigate 623 college students. Based on the DeLone and McLean model of IS success and flow theory, a model for optimizing system characteristics and flow experience was constructed and its effectiveness was tested. The results reveal that system characteristics have a positive impact on continuance intention and flow experience. Additionally, flow experience and learning effect have a positive impact on continuance intention. Furthermore, flow experience has a positive impact on the learning effect. This study emphasizes the flow experience of online learning systems and reveals the optimization direction of online virtual face-to-face classrooms to provide references for the Ministry of Education, schools, and enterprises providing education systems.

Bibliometric analysis of the top-50 cited articles on COVID-19 and physical activity.

Background: Since the 2019 novel coronavirus (COVID-19) pneumonia outbreak in late 2019, an endless stream of research has emerged surrounding physical activity. This study analyzes the 50 most influential articles on COVID-19 and physical activity over the past 2 years to describe the research landscape and hotspots from bibliometric citation analysis. Methods: The top-50 cited articles were extracted from the Web of Science Core Collection database, and bibliometric citation analysis was performed by Excel 2019 and VOSviewer software. Results: The top-50 articles were cited 160.48 ± 106.90 (range: 70-587). Most of the articles were from the United States (14), followed by Italy (11) and England (9). The International Journal of Environmental Research and Public Health (n = 10) is the journal with the top-50 cited articles. The collaboration between authors was mainly among three teams, including Smith L, Musumeci G, and Napoli C. The hotspot of research around COVID-19 and physical activity focused on lifestyle change (sedentary behavior, sitting time), mental health (depressive, anxiety, loneliness), the credibility of physical activity assessment tools (reliability, validity), and physical activity of different populations (gender, youth, children). Conclusions: Based on a bibliometric analysis of high-impact articles on COVID-19 and physical activity highlights physical activity as an essential lifestyle change and developments and hotspots in this field. These data will provide insights for future researchers regarding the direction of physical activity research in the COVID-19 pandemic.

Simulating inter-individual contact in the inter-station passenger transfer system connecting multiple metro stations based on space–time path data

Determining passengers’ inter-individual contact in the metro station area (MSA) is an important issue to simulate and mitigate the spread of the Coronavirus disease 2019 (COVID-19) pandemic. Taking the inter-station passenger transfer system (IPTS) as an example, this study aimed to verify the passenger flows’ influence on the inter-individual contact around the MSA. Based on actual observed data, the passengers’ space–time paths (STP) in the network were obtained through an agent-based simulation. In this study, the direct contact model and the mediate contact model were used to describe the inter-individual contact in view of the passengers’ STP. The contact count and the exposure duration were defined as indicators to measure the contact degree of individual and the system. The results show that the time-varying trip distribution of the metro passengers significantly affected the inter-individual contact degree and the spatial distribution of contact risk region in the MSA. The intersection of passenger flow in different directions and the concentrated movement of passenger flow in the same direction increased the inter-individual contact and prolonged exposure in the morning. Through simulation experiments, the study verified the effects of controlling the flow direction and equalizing passenger flow generation measures aiming to reduce inter-individual contact and cumulative exposure duration.

A university-clustered tuberculosis outbreak during the COVID-19 pandemic in eastern China.

During the COVID-19 pandemic in 2020, a tuberculosis outbreak occurred in a university in eastern China, with 4,488 students and 421 staff on the campus. A 19-year-old student was diagnosed in August 2019. Later, the first round of screening was initiated among close contacts, but no active cases were found. Till September 2020, four rounds of screening were performed. Four rounds of screening were conducted on September 9, November 8, November 22-25 in 2019 and September 2020, with 0, 5, 0 and 43 cases identified, respectively. A total of 66 active tuberculosis were found in the same university, including 4 sputum culture-positive and 7 sputum smear-positive. The total attack rate of active tuberculosis was 1.34% (66/4909). The whole-genome sequencing showed that the isolates belonged to the same L2 sub-specie and were sensitive to all tested antituberculosis drugs. Delay detection, diagnosis and report of cases were the major cause of this university tuberculosis epidemic. More attention should be paid to the asymptomatic students in the index class. After the occurrence of tuberculosis cases in schools, multiple rounds of screening should be carried out, and preventive therapy should be applied in a timely manner.

Movie Box Office Prediction Based on IFOA-GRNN

Predicting movie box office has received extensive attention from academia and industry. At present, the main method of forecasting movie box office is subjective prediction, which is not widely accepted due to its accuracy and applicability. This study improves the fruit fly algorithm to optimize the generalized regression neural network (IFOA-GRNN) model to predict whether a movie can become a high-grossing movie. By using the actual box office data and performing virtual simulation calculations, the root means square error of the IFOA-GRNN model predicting the movie box office is 0.3412, and the classification accuracy is about 90%. By comparing this model with FOA-GRNN, KNN, GRNN, Random Forest, Naive Bayes, Ensembles for Boosting, Discriminant Analysis Classifier, and SVM, it is found that the prediction effect of the IFOA-GRNN model is significantly better than the above eight models. The contribution of this article is to propose a generalized regression neural network model based on an improved fruit fly optimization algorithm, which can greatly improve the accuracy of movie box office prediction.