Spatiotemporal pattern recognition and dynamical analysis of COVID-19 in Shanghai, China

An SEIHR model with age group and social contact for analysis of Fuzhou COVID-19 large wave

Background

The structure of age groups and social contacts of the total population influenced infection scales and hospital-bed requirements, especially influenced severe infections and deaths during the global prevalence of COVID-19. Before the end of the year 2022, Chinese government implemented the national vaccination and had built the herd immunity cross the country, and announced Twenty Measures (November 11) and Ten New Measures (December 7) for further modifications of dynamic zero-COVID polity on the Chinese mainland. With the nation-wide vaccination and modified measures background, Fuzhou COVID-19 large wave (November 19, 2022-February 9, 2023) led by Omicron BA.5.2 variant was recorded and prevailed for three months in Fujian Province.

Methods

A multi-age groups susceptible-exposed-infected-hospitalized-recovered (SEIHR) COVID-19 model with social contacts was proposed in this study. The main object was to evaluate the impacts of age groups and social contacts of the total population. The idea of Least Squares method was governed to perform the data fittings of four age groups against the surveillance data from Fujian Provincial Center for Disease Control and Prevention (Fujian CDC). The next generation matrix method was used to compute basic reproduction number for the total population and for the specific age group. The tendencies of effective reproduction number of four age groups were plotted by using the Epiestim R package and the SEIHR model for in-depth discussions. The sensitivity analysis by using sensitivity index and partial rank correlation coefficients values (PRCC values) were operated to reveal the differences of age groups against the main parameters.

Results

The main epidemiological features such as basic reproduction number, effective reproduction number and sensitivity analysis were extensively discussed for multi-age groups SEIHR model in this study. Firstly, by using of the next generation matrix method, basic reproduction number R0 of the total population was estimated as 1.57 using parameter values of four age groups of Fuzhou COVID-19 large wave. Given age group k, the values of R0k (age group k to age group k), the values of R 0 k (an infected of age group k to the total population) and the values of R ^ 0 k (an infected of the total population to age group k) were also estimated, in which the explorations of the impacts of age groups revealed that the relationship R 0 k > R 0 k > R ^ 0 k was valid. Then, the fluctuating tendencies of effective reproduction number Rt were demonstrated by using two approaches (the surveillance data and the SEIHR model) for Fuzhou COVID-19 large wave, during which high-risk group (G4 group) mainly contributed the infection scale due to high susceptibility to infection and high risks to basic diseases. Further, the sensitivity analysis using two approaches (the sensitivity index and the PRCC values) revealed that susceptibility to infection of age groups played the vital roles, while the numerical simulation showed that infection scale varied with the changes of social contacts of age groups. The results of this study claimed that the high-risk group out of the total population was concerned by the local government with the highest susceptibility to infection against COVID-19.

Conclusions

This study verified that the partition structure of age groups of the total population, the susceptibility to infection of age groups, the social contacts among age groups were the important contributors of infection scale. The less social contacts and adequate hospital beds for high-risk group were profitable to control the spread of COVID-19. To avoid the emergence of medical runs against new variant in the future, the policymakers from local government were suggested to decline social contacts when hospital beds were limited.

The impact of isolation on comorbidity of PTSD symptoms and depression: evidence from PTRP-5-6 in China

BACKGROUND

The Omicron pandemic struck Shanghai, China, resulting in impairments of both physical and psychological health on those patients who were confirmed and transferred to the Fangcang shelters. The way of isolation led to high risk of posttraumatic stress symptoms (PTSS) and depressive symptoms among the patients in Fangcang shelters. We aim to estimate the prevalence and comorbidity of PTSS and depressive symptoms in patients from China's Fangcang shelters during the epidemic.

METHODS

Demographic information questionnaire, the posttraumatic stress disorder checklist for DSM-5 (PCL-5), and Patient Health Questionnaire (PHQ-9) were used in the study. The data were collected online via mobile phones during 10th April to 20th April, 2022, as part of our Psychological Trauma Recover Project-5-6 (PTRP-5-6), a longitudinal study focusing on individuals who have experienced trauma.

RESULTS

A total of 336 subjects were included in the analysis. The results revealed (1) the prevalence of depressive symptoms, and PTSS were 30.1% (cut-off = 10) and 6% (cut-off = 33); (2) Multiple logistic regression showed that female (OR = 3.04, p < 0.05), suffering from dyspnea (OR = 5.83, p < 0.05) or gastrointestinal symptoms (OR = 6.38, p < 0.05) were risk factors for PTSS; higher education level (OR = 3.27, p < 0.05) and suffering from dizziness or headache (OR = 2.46, p < 0.05) were risk factors for depressive symptoms; (3)Respectively, 85% of the patients who reported PTSS also experienced depressive symptoms, 16.8% of the patients who reported depressive symptoms presented PTSS.

CONCLUSION

In the context of COVID-19, the comorbidity rate of PTSS and depressive symptoms among patients in Fangcang shelters increased with the severity of depressive symptoms.

Clinical and virological features of asymptomatic and mild symptomatic patients with SARS-CoV-2 Omicron infection at Shanghai Fangcang shelter hospital

OBJECTIVE

The objective of this study is to evaluate and compare clinical and virological characteristics of asymptomatic and mild symptomatic patients of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2.2 variant infection and identify risk factors associated with the prolonged viral negative conversion duration.

METHODS

We conducted a retrospective observational study in a Shanghai (China) Fangcang shelter hospital from April 9 to May 17, 2022. The patient-related demographic or clinical data were retrospectively recorded. Comparisons of demographic and clinical characteristics between asymptomatic and mild-symptomatic patients were performed. Cox regression was performed to identify the risk factors of prolonged viral negative conversion duration.

RESULTS

A total of 551 patients confirmed with SARS-CoV-2 Omicron variant infection were enrolled in the study. Of these, 297 patients (53.9%) were asymptomatic and 254 patients (46.1%) had mild symptoms. When comparing the clinical and virological characteristics between the asymptomatic and mild symptomatic groups, several clinical parameters, including age, gender, time to viral clearance from the first positive swab, chronic comorbidities, and vaccination dose did not show statistically significant differences. In mild symptomatic patients, the median viral negative conversion duration (NCD) was 7 days (interquartile range [IQR]: 5-9), which was comparable to the median of 7 days (IQR: 5-10) in asymptomatic patients (p = .943). Multivariate Cox analysis revealed that patients age ≥ 60 years had a significantly higher hazard ratio (HR) for prolonged viral NCD (HR: 1.313; 95% confidence interval: 1.014-1.701, p = .039).

CONCLUSION

Asymptomatic and symptomatic patients with non-severe SARS-CoV-2 Omicron BA.2.2 variant infection have similar clinical features and virological courses. Old age was an independent risk factor for prolonged SARS-CoV-2 conversion time.

Lessons drawn from Shanghai for controlling highly transmissible SARS-CoV-2 variants: insights from a modelling study

BACKGROUND

The continuous emergence of novel SARS-CoV-2 variants with markedly increased transmissibility presents major challenges to the zero-COVID policy in China. It is critical to adjust aspects of the policy about non-pharmaceutical interventions (NPIs) by searching for and implementing more effective ways. We use a mathematical model to mimic the epidemic pattern of the Omicron variant in Shanghai to quantitatively show the control challenges and investigate the feasibility of different control patterns in avoiding other epidemic waves.

METHODS

We initially construct a dynamic model with a core step-by-step release strategy to reveal its role in controlling the spread of COVID-19, including the city-based pattern and the district-based pattern. We used the least squares method and real reported case data to fit the model for Shanghai and its 16 districts, respectively. Optimal control theory was utilized to explore the quantitative and optimal solutions of the time-varying control strength (i.e., contact rate) to suppress the highly transmissible SARS-CoV-2 variants.

RESULTS

The necessary period for reaching the zero-COVID goal can be nearly 4 months, and the final epidemic size was 629,625 (95%CI: [608,049, 651,201]). By adopting the city-based pattern, 7 out of 16 strategies released the NPIs more or earlier than the baseline and ensured a zero-resurgence risk at the average cost of 10 to 129 more cases in June. By adopting the district-based pattern, a regional linked release can allow resumption of social activity to ~ 100% in the boundary-region group about 14 days earlier and allow people to flow between different districts without causing infection resurgence. Optimal solutions of the contact rate were obtained with various testing intensities, and higher diagnosis rate correlated with higher optimal contact rate while the number of daily reported cases remained almost unchanged.

CONCLUSIONS

Shanghai could have been bolder and more flexible in unleashing social activity than they did. The boundary-region group should be relaxed earlier and more attention should be paid to the centre-region group. With a more intensive testing strategy, people could return to normal life as much as possible but still ensure the epidemic was maintained at a relatively low level.

A retrospective study investigating the anxiety and depression level of novel coronavirus Omicron patients in 2022

INTRODUCTION

The novel coronavirus disease 2019 continues to spread widely, not only causing physical disorders in patients but also impairing mental health, bringing a heavy burden on global public health. This study aimed to evaluate the anxiety and depression status of patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant in Shanghai.

METHODS/DESIGN

This study aimed to retrospectively analyze 2000 patients infected with the SARS-CoV-2 Omicron variant. Data from patients assessed with demographic information, anxiety and depressive symptoms were collected using a questionnaire. Clinical and laboratory data were collected using electronic medical system. Anxiety and depression were assessed using the Self-Rating Anxiety Scale, the Generalized Anxiety Disorder Scale, and the Patient Health Questionnaire. Clinical information and laboratory indicators included age, sex, blood pressure, blood glucose, basic disease, time of diagnosis onset, duration of hospitalization, vaccination status of novel coronavirus disease 2019, and virus-negative conversion time.

DISCUSSION

This study will provide evidence-based suggestions for early psychological intervention in patients infected with the SARS-CoV-2 Omicron Variant.