Early detection of SARS-CoV-2 variants through dynamic co-mutation network surveillance.

Background: Precise public health and clinical interventions for the COVID-19 pandemic has spurred a global rush on SARS-CoV-2 variant tracking, but current approaches to variant tracking are challenged by the flood of viral genome sequences leading to a loss of timeliness, accuracy, and reliability. Here, we devised a new co-mutation network framework, aiming to tackle these difficulties in variant surveillance. Methods: To avoid simultaneous input and modeling of the whole large-scale data, we dynamically investigate the nucleotide covarying pattern of weekly sequences. The community detection algorithm is applied to a co-occurring genomic alteration network constructed from mutation corpora of weekly collected data. Co-mutation communities are identified, extracted, and characterized as variant markers. They contribute to the creation and weekly updates of a community-based variant dictionary tree representing SARS-CoV-2 evolution, where highly similar ones between weeks have been merged to represent the same variants. Emerging communities imply the presence of novel viral variants or new branches of existing variants. This process was benchmarked with worldwide GISAID data and validated using national level data from six COVID-19 hotspot countries. Results: A total of 235 co-mutation communities were identified after a 120 weeks' investigation of worldwide sequence data, from March 2020 to mid-June 2022. The dictionary tree progressively developed from these communities perfectly recorded the time course of SARS-CoV-2 branching, coinciding with GISAID clades. The time-varying prevalence of these communities in the viral population showed a good match with the emergence and circulation of the variants they represented. All these benchmark results not only exhibited the methodology features but also demonstrated high efficiency in detection of the pandemic variants. When it was applied to regional variant surveillance, our method displayed significantly earlier identification of feature communities of major WHO-named SARS-CoV-2 variants in contrast with Pangolin's monitoring. Conclusion: An efficient genomic surveillance framework built from weekly co-mutation networks and a dynamic community-based variant dictionary tree enables early detection and continuous investigation of SARS-CoV-2 variants overcoming genomic data flood, aiding in the response to the COVID-19 pandemic.

Implementation and evaluation of crowdsourcing in global health education.

BACKGROUND: Current global health course is most set as elective course taught in traditional teacher-taught model with low credit and short term. Innovate teaching models are required. Crowdsourcing characterized by high flexibility and strong application-orientation holds its potential to enhance global health education. We applied crowdsourcing to global health teaching for undergraduates, aiming to develop and evaluate a new teaching model for global health education. METHODS: Crowdsourcing was implemented into traditional course-based teaching via introducing five COVID-19 related global health debates. Undergraduate students majoring in preventative medicine and nursing grouped in teams of 5-8, were asked to resolve these debates in reference to main content of the course and with manner they thought most effective to deliver the messages. Students' experience and teaching effect, were evaluated by questionnaires and teachers' ratings, respectively. McNemar's test was used to compare the difference in students' experience before and after the course, and regression models were used to explore the influencing factors of the teaching effect. RESULTS: A total of 172 undergraduates were included, of which 122 (71%) were females. Students' evaluation of the new teaching model improved after the course, but were polarized. Students' self-reported teaching effect averaged 67.53 ± 16.8 and the teachers' rating score averaged 90.84 ± 4.9. Students majoring in preventive medicine, participated in student union, spent more time on revision, and had positive feedback on the new teaching model tended to perform better. CONCLUSION: We innovatively implemented crowdsourcing into global health teaching, and found this new teaching model was positively received by undergraduate students with improved teaching effects. More studies are needed to optimize the implementation of crowdsourcing alike new methods into global health education, to enrich global health teaching models.

A review on COVID-19 transmission, epidemiological features, prevention and vaccination.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused hundreds of millions of infections and millions of deaths over past two years. Currently, many countries have still not been able to take the pandemic under control. In this review, we systematically summarized what we have done to mitigate the COVID-19 pandemic, from the perspectives of virus transmission, public health control measures, to the development and vaccination of COVID-19 vaccines. As a virus most likely coming from bats, the SARS-CoV-2 may transmit among people via airborne, faecal-oral, vertical or foodborne routes. Our meta-analysis suggested that the R0 of COVID-19 was 2.9 (95% CI: 2.7-3.1), and the estimates in Africa and Europe could be higher. The median Rt could decrease by 23-96% following the nonpharmacological interventions, including lockdown, isolation, social distance, and face mask, etc. Comprehensive intervention and lockdown were the most effective measures to control the pandemic. According to the pooled R0 in our meta-analysis, there should be at least 93.3% (95% CI: 89.9-96.2%) people being vaccinated around the world. Limited amount of vaccines and the inequity issues in vaccine allocation call for more international cooperation to achieve the anti-epidemic goals and vaccination fairness.

A New Way to Trace SARS-CoV-2 Variants Through Weighted Network Analysis of Frequency Trajectories of Mutations.

Early detection of SARS-CoV-2 variants enables timely tracking of clinically important strains in order to inform the public health response. Current subtype-based variant surveillance depending on prior subtype assignment according to lag features and their continuous risk assessment may delay this process. We proposed a weighted network framework to model the frequency trajectories of mutations (FTMs) for SARS-CoV-2 variant tracing, without requiring prior subtype assignment. This framework modularizes the FTMs and conglomerates synchronous FTMs together to represent the variants. It also generates module clusters to unveil the epidemic stages and their contemporaneous variants. Eventually, the module-based variants are assessed by phylogenetic tree through sub-sampling to facilitate communication and control of the epidemic. This process was benchmarked using worldwide GISAID data, which not only demonstrated all the methodology features but also showed the module-based variant identification had highly specific and sensitive mapping with the global phylogenetic tree. When applying this process to regional data like India and South Africa for SARS-CoV-2 variant surveillance, the approach clearly elucidated the national dispersal history of the viral variants and their co-circulation pattern, and provided much earlier warning of Beta (B.1.351), Delta (B.1.617.2), and Omicron (B.1.1.529). In summary, our work showed that the weighted network modeling of FTMs enables us to rapidly and easily track down SARS-CoV-2 variants overcoming prior viral subtyping with lag features, accelerating the understanding and surveillance of COVID-19.

Research capacity of global health institutions in China: a gap analysis focusing on their collaboration with other low-income and middle-income countries.

INTRODUCTION: This paper presented qualitative and quantitative data collected on the research capacity of global health institutions in China and aimed to provide a landscaping review of the development of global health as a new discipline in the largest emerging economy of the world. METHODS: Mixed methods were used and they included a bibliometric analysis, a standardised survey and indepth interviews with top officials of 11 selected global health research and educational institutions in mainland China. RESULTS: The bibliometric analysis revealed that each institution had its own focus areas, some with a balanced focus among chronic illness, infectious disease and health systems, while others only focused on one of these areas. Interviews of key staff from each institution showed common themes: recognition that the current research capacity in global health is relatively weak, optimism towards the future, as well as an emphasis on mutual beneficial networking with other countries. Specific obstacles raised and the solutions applied by each institution were listed and discussed. CONCLUSION: Global health institutions in China are going through a transition from learning and following established protocols to taking a more leading role in setting up China's own footprint in this area. Gaps still remain, both in comparison with international institutions, as well as between the leading Chinese institutions and those that have just started. More investment needs to be made, from both public and private domains, to improve the overall capacity as well as the mutual learning and communication within the academic community in China.

Evaluation of China's Hubei control strategy for COVID-19 epidemic: an observational study.

BACKGROUND: To fight against COVID-19, many policymakers are wavering on stricter public health interventions. Examining the different strategies both in and out of China's Hubei province, which contained the epidemic in late February 2020, could yield valuable guidance for the management of future pandemics. This study assessed the response process and estimated the time-varying effects of the Hubei control strategy. Analysis of these strategies provides insights for the design and implementation of future policy interventions. METHODS: We retrospectively compared the spread and control of COVID-19 between China's Hubei (excluding Wuhan) and non-Hubei areas using data that includes case reports, human mobility, and public health interventions from 1 January to 29 February 2020. Static and dynamic risk assessment models were developed to statistically investigate the effects of the Hubei control strategy on the virus case growth after adjusting importation risk and policy response timing with the non-Hubei strategy as a control. RESULTS: The analysis detected much higher but differential importation risk in Hubei. The response timing largely coincided with the importation risk in non-Hubei areas, but Hubei areas showed an opposite pattern. Rather than a specific intervention assessment, a comprehensive comparison showed that the Hubei control strategy implemented severe interventions characterized by unprecedentedly strict and 'monitored' self-quarantine at home, while the non-Hubei strategy included physical distancing measures to reduce contact among individuals within or between populations. In contrast with the non-Hubei control strategy, the Hubei strategy showed a much higher, non-linear and gradually diminishing protective effect with at least 3 times fewer cases. CONCLUSIONS: A risk-based control strategy was crucial to the design of an effective response to the COVID-19 outbreak. Our study demonstrates that the stricter Hubei strategy achieves a stronger controlling effect compared to other strategies. These findings highlight the health benefits and policy impacts of precise and differentiated strategies informed by constant monitoring of outbreak risk.

Three-Month Pulmonary Function and Radiological Outcomes in COVID-19 Survivors: A Longitudinal Patient Cohort Study.

BACKGROUND: This study aimed to investigate pulmonary function and radiological outcomes in a group of coronavirus disease 2019 (COVID-19) survivors. METHODS: One hundred seventy-two COVID-19 survivors in a follow-up clinic in a referral hospital underwent high-resolution computed tomography (CT) of the thorax and pulmonary function at 3 months after hospital discharge. RESULTS: The median duration from hospital discharge to radiological and pulmonary function test (interquartile range) was 90 (88-95) days. Abnormal pulmonary function was found in 11 (6.40%) patients, and abnormal small airway function (FEF25-75%) in 12 (6.98%). Six (3.49%) patients had obstructive ventilation impairment, and 6 (3.49%) had restrictive ventilatory impairment. No significant differences in lung function parameters were observed between the nonsevere and severe groups. Of 142 COVID-19 patients who underwent CT scan, 122 (85.91%) showed residual CT abnormalities and 52 (36.62%) showed chronic and fibrotic changes. The ground-glass opacities absorption in the lungs of severe cases was less satisfactory than that of nonsevere patients. The severe patients had higher CT scores than the nonsevere cases (2.00 vs 0.00; P < .001). CONCLUSIONS: Of the COVID-19 survivors in our study, 6.40% still presented pulmonary function abnormality 3 months after discharge, which did not vary by disease severity during hospitalization; 85.91% of patients had abnormalities on chest CT, with fibrous stripes and ground-glass opacities being the most common patterns.

Impact of the gate-keeping policies of China's primary healthcare model on the future burden of tuberculosis in China: a protocol for a mathematical modelling study.

INTRODUCTION: In the past three decades, China has made great strides in the prevention and treatment of tuberculosis (TB). However, the TB burden remains high. In 2019, China accounted for 8.4% of global incident cases of TB, the third highest in the world, with a higher prevalence in rural areas. The Healthy China 2030 highlights the gate-keeping role of primary healthcare (PHC). However, the impact of PHC reforms on the future TB burden is unclear. We propose to use mathematical models to project and evaluate the impacts of different gate-keeping policies. METHODS AND ANALYSIS: We will develop a deterministic, population-level, compartmental model to capture the dynamics of TB transmission within adult rural population. The model will incorporate seven main TB statuses, and each compartment will be subdivided by service providers. The parameters involving preference for healthcare seeking will be collected using discrete choice experiment (DCE) method. We will solve the deterministic model numerically over a 20-year (2021-2040) timeframe and predict the TB prevalence, incidence and cumulative new infections under the status quo or various policy scenarios. We will also conduct an analysis following standard protocols to calculate the average cost-effectiveness for each policy scenario relative to the status quo. A numerical calibration analysis against the available published TB prevalence data will be performed using a Bayesian approach. ETHICS AND DISSEMINATION: Most of the data or parameters in the model will be obtained based on secondary data (eg, published literature and an open-access data set). The DCE survey has been reviewed and approved by the Ethics Committee of the School of Public Health, Sun Yat-sen University. The approval number is SYSU [2019]140. Results of the study will be disseminated through peer-reviewed journals, media and conference presentations.

Difficulties encountered by public health workers in COVID-19 outbreak: a cross-sectional study based on five provinces.

OBJECTIVES: The aim of this study is to address the difficulties encountered by public health workers in the early and middle stages of their efforts to combat COVID-19, compare the gaps among different types of institutions, and identify shortcomings in epidemic control. METHODS: Using multi-stage sampling, a survey of public health workers involved in the prevention and control of COVID-19 was conducted from 18 February to 1 March 2020 through a self-administered questionnaire. These public health workers were from the primary health care center (defined as "primary-urban" and "primary-rural" for those in urban and rural areas, respectively) and the center for disease control and prevention (defined as "non-primary") in five provinces including Hubei, Guangdong, Sichuan, Jiangsu and Gansu, China. RESULTS: A total of 9,475 public health workers were surveyed, of which 40.0 %, 27.0 % and 33.0 % were from the primary-rural, primary-urban and non-primary, respectively. The resources shortage were reported by 27.9 % participants, with the primary-rural being the worst affected (OR = 1.201, 95 %CI: 1.073-1.345). The difficulties in data processing were reported by 31.5 % participants, with no significant differences among institutions. The difficulties in communication and coordination were reported by 29.8 % participants, with the non-primary being the most serious (primary-rural: OR = 0.520, 95 %CI: 0.446-0.606; primary-urban: OR = 0.533, 95 %CI: 0.454-0.625). The difficulties with target audiences were reported by 20.2 % participants, with the primary-urban being the worst (OR = 1.368, 95 %CI: 1.199-1.560). The psychological distress were reported by 48.8 % participants, with no significant differences among institutions. CONCLUSIONS: Psychological distress is the most serious problem in the prevention and control of COVID-19. Resources shortage in primary-rural, difficulties in communication and coordination in non-primary, and difficulties with target audiences in the primary-urban deserve attention. This study will provide scientific evidences for improving the national public health emergency management system, especially for reducing the urban-rural differences in emergency response capacity.

Mental Health Help-Seeking and Associated Factors Among Public Health Workers During the COVID-19 Outbreak in China.

Background: The COVID-19 outbreak in China has created multiple stressors that threaten individuals' mental health, especially among public health workers (PHW) who are devoted to COVID-19 control and prevention work. This study aimed to investigate the prevalence of mental help-seeking and associated factors among PHW using Andersen's Behavioral Model of Health Services Use (BMHSU). Methods: A cross-sectional survey was conducted among 9,475 PHW in five provinces across China between February 18 and March 1, 2020. The subsample data of those who reported probable mental health problems were analyzed for this report (n = 3,417). Logistic and hierarchical regression analyses were conducted to examine the associations of predisposing, enabling, need, and COVID-19 contextual factors with mental health help-seeking. Results: Only 12.7% of PHW reported professional mental help-seeking during the COVID-19 outbreak. PHW who were older, had more days of overnight work, received psychological training, perceived a higher level of support from the society, had depression and anxiety were more likely to report mental help-seeking (ORm range: 1.02-1.73, all p < 0.05) while those worked in Centers for Disease Control and Prevention were less likely to seek help (ORm = 0.57, p < 0.01). The belief that mental health issues were not the priority (64.4%), lack of time (56.4%), and shortage of psychologists (32.7%) were the most frequently endorsed reasons for not seeking help. Conclusions: The application of BMHSU confirmed associations between some factors and PHW's mental health help-seeking. Effective interventions are warranted to promote mental health help-seeking of PHW to ameliorate the negative impact of mental illness and facilitate personal recovery and routine work.

Prevalence of mental health problems and associated factors among front-line public health workers during the COVID-19 pandemic in China: an effort-reward imbalance model-informed study.

BACKGROUND: Poor mental health status and associated risk factors of public health workers have been overlooked during the COVID-19 pandemic. This study used the effort-reward imbalance model to investigate the association between work-stress characteristics (effort, over-commitment, reward) and mental health problems (anxiety and depression) among front-line public health workers during the COVID-19 pandemic in China. METHODS: A total of 4850 valid online questionnaires were collected through a self- constructed sociodemographic questionnaire, the adapted ERI questionnaire, the 9-item Patient Health Questionnaire (PHQ-9) and the 7-item General Anxiety Disorder Scale (GAD-7). Hierarchical logistic regression analysis was conducted to investigate the association between ERI factors and mental health problems (i.e., depression and anxiety), with reward treated as a potential moderator in such associations. RESULTS: The data showed that effort and over-commitment were positively associated with depression and anxiety, while reward was negatively associated with depression and anxiety. Development and job acceptance were the two dimensions of reward buffered the harmful effect of effort/over-commitment on depression and anxiety, whereas esteem was non-significant. CONCLUSIONS: This study confirmed the harmful effects of effort and over-commitment on mental health among public health workers during the COVID-19 pandemic in China. Such effects could be alleviated through an appropriate reward system, especially the development and job acceptance dimensions of such a system. These findings highlight the importance of establishing an emergency reward system, comprising reasonable work-allocation mechanism, bonuses and honorary titles, a continuous education system and better career-development opportunities.

Mortality risk of COVID-19 in elderly males with comorbidities: a multi-country study.

The COVID-19 pandemic causes severe morbidity and mortality. This multi-country study aimed to explore risk factors that drive mortality in COVID-19 patients who received neither dexamethasone nor remdesivir. We analyzed a cohort of 568 survivors and 507 non-survivors from China, European regions, and North America. Elderly males ≥70 years accounted for only 25% of survivors, but this rate was significantly higher in non-survivors from China (55%), European regions (63%), and North America (47%). Compared with survivors, non-survivors had more incidences of comorbidities such as cerebrovascular disease and chronic obstructive pulmonary disease (COPD, p-values<0.05). Survival analyses revealed age, male gender, shortness of breath, cerebrovascular disease, and COPD as mortality-associated factors. Survival time from symptom onset was significantly shorter in elderly versus young patients (median: 29 versus 62 days), males versus females (median: 46 versus 59 days), and patients with versus without comorbidities (mean: 41 versus 61 days). Mortality risk was higher in elderly males with comorbidities than in young females without comorbidities (p-value<0.01). Elderly male survivors with comorbidities also had longer hospital stays than other survivors (25 versus 18.5 days, p-value<0.01). Overall, the high mortality risk in elderly males with COVID-19-associated comorbidities supports early prevention and critical care for elderly populations.

Working conditions and health status of 6,317 front line public health workers across five provinces in China during the COVID-19 epidemic: a cross-sectional study.

BACKGROUND: Public health workers at the Chinese Centre for Disease Control and Prevention (China CDC) and primary health care institutes (PHIs) were among the main workers who implemented prevention, control, and containment measures. However, their efforts and health status have not been well documented. We aimed to investigate the working conditions and health status of front line public health workers in China during the COVID-19 epidemic. METHODS: Between 18 February and 1 March 2020, we conducted an online cross-sectional survey of 2,313 CDC workers and 4,004 PHI workers in five provinces across China experiencing different scales of COVID-19 epidemic. We surveyed all participants about their work conditions, roles, burdens, perceptions, mental health, and self-rated health using a self-constructed questionnaire and standardised measurements (i.e., Patient Health Questionnaire and General Anxiety Disorder scale). To examine the independent associations between working conditions and health outcomes, we used multivariate regression models controlling for potential confounders. RESULTS: The prevalence of depression, anxiety, and poor self-rated health was 21.3, 19.0, and 9.8%, respectively, among public health workers (27.1, 20.6, and 15.0% among CDC workers and 17.5, 17.9, and 6.8% among PHI workers). The majority (71.6%) made immense efforts in both field and non-field work. Nearly 20.0% have worked all night for more than 3 days, and 45.3% had worked throughout the Chinese New Year holiday. Three risk factors and two protective factors were found to be independently associated with all three health outcomes in our final multivariate models: working all night for >3 days (multivariate odds ratio [ORm]=1.67~1.75, p<0.001), concerns about infection at work (ORm=1.46~1.89, p<0.001), perceived troubles at work (ORm=1.10~1.28, p<0.001), initiating COVID-19 prevention work after January 23 (ORm=0.78~0.82, p=0.002~0.008), and ability to persist for > 1 month at the current work intensity (ORm=0.44~0.55, p<0.001). CONCLUSIONS: Chinese public health workers made immense efforts and personal sacrifices to control the COVID-19 epidemic and faced the risk of mental health problems. Efforts are needed to improve the working conditions and health status of public health workers and thus maintain their morale and effectiveness during the fight against COVID-19.

The time course of chest CT lung changes in COVID-19 patients from onset to discharge.

BACKGROUND & AIMS: Computed tomography (CT) is widely used to evaluate the severity of COVID-19 infection and track disease progression. We described the changes in chest CT to enable better understanding of the progression of COVID-19 during hospitalization. METHODS: Consecutively hospitalized COVID-19 patients admitted from January 11, 2020 to February 16, 2020 and followed until March 26, 2020 at the Third People's Hospital of Shenzhen, China were included. Semi- quantitative analysis was used to assess the shape, distribution, and range of lung lesions. For each image, the lungs were divided into six regions. The total CT score was the sum of individual region scores. RESULTS: 305 patients underwent a total of 1442 chest CT scans with a mean interval of 5 days (interquartile range (IQR) = 3-6 days). All patients were discharged after an average hospitalization of 25 days (IQR = 20-33 days). From the onset of initial symptoms, the total CT score peaked at an earlier date in the non-severe than the severe cases (13 days versus 15 days). Typical CT image of non-severe cases mainly presented as ground-glass opacities (GGO), whilst GGO mixed with consolidation was more seen in severe cases. In addition, severe versus non-severe cases had higher prevalence of fibrosis and air bronchogram in CT scans (P from <0.001 to 0.05, P = 0.001, respectively). The proportion of patients with fibrosis and air bronchogram appeared to decrease from the fourth (20 days from onset, IQR = 16-24) and the third pulmonary CT scan (15 days from onset, IQR = 12-19), respectively. CONCLUSION: COVID-19 pneumonia demonstrated progressions in early stage, with the greatest pulmonary damage on CT occurred at approximately 13 days after initial onset of symptoms. Worse bilateral pulmonary infiltrates were found in severe cases, indicating continuous health care for pulmonary rehabilitation and consecutive follow-up to monitor irreversible fibrosis and consolidation are necessary.

Implementation of Clinical Diagnostic Criteria and Universal Symptom Survey Contributed to Lower Magnitude and Faster Resolution of the COVID-19 Epidemic in Wuhan.

The majority of cases infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China centered in the city of Wuhan. Despite a rapid increase in the number of cases and deaths due to the coronavirus disease 2019 (COVID-19), the epidemic was stemmed via a combination of epidemic mitigation and control measures. This study evaluates how the implementation of clinical diagnostics and universal symptom surveys contributed to epidemic control in Wuhan. We extended the susceptibles-exposed-infectious-removed (SEIR) transmission dynamics model by considering three quarantined compartments (SEIR+Q). The SEIR+Q dynamics model was fitted using the daily reported number of confirmed infections and unconfirmed cases by clinical diagnostic criteria up to February 14, 2020, in Wuhan. Applying the model to carry forward the pre-February 14 trend in Wuhan, the number of daily new diagnosed cases would be expected to drop below 100 by March 25, below 10 by April 29, and reach 0 by May 31, 2020. The observed case counts after February 14 demonstrated that the daily new cases fell below 100 by March 6, below 10 by March 11, and reached 0 by March 18, respectively, 19, 49, and 74 d earlier than model predictions. By March 30, the observed number of cumulative confirmed cases was 50 006, which was 19 951 cases fewer than the predicted count. Effective reproductive number R(t) analysis using observed frequencies showed a remarkable decline after the implementation of clinical diagnostic criteria and universal symptom surveys, which was significantly below the R(t) curve estimated by the model assuming that the pre-February 14 trend was carried forward. In conclusion, the proposed SEIR+Q dynamics model was a good fit for the epidemic data in Wuhan and explained the large increase in the number of infections during February 12-14, 2020. The implementation of clinical diagnostic criteria and universal symptom surveys contributed to a contraction in both the magnitude and the duration of the epidemic in Wuhan.