Modelling the impact of timelines of testing and isolation on disease control.

Testing and isolation remain a key component of public health responses to both persistent and emerging infectious diseases. Although the value of these measures have been demonstrated in combating recent outbreaks including the COVID-19 pandemic and monkeypox, their impact depends critically on the timelines of testing and start of isolation during the course of disease. To investigate this impact, we developed a delay differential model and incorporated age-since-symptom-onset as a parameter for delay in testing. We then used the model to compare the outcomes of reverse-transcription polymerase chain reaction (RT-PCR) and rapid antigen (RA) testing methods when isolation starts either at the time of testing or at the time of test result. Parameterizing the model with estimates of SARS-CoV-2 infection and diagnostic sensitivity of the tests, we found that the reduction of disease transmission using the RA test can be comparable to that achieved by applying the RT-PCR test. Given constraints and inevitable delays associated with sample collection and laboratory assays in RT-PCR testing post symptom onset, self-administered RA tests with short turnaround times present a viable alternative for timely isolation of infectious cases.

Sleep quality and influencing factors and correlation with T-lymphocyte subpopulation counts in patients with pulmonary tuberculosis: a cross-sectional study.

BACKGROUND: Patients diagnosed with pulmonary tuberculosis (TB) have poor sleep quality due to multiple factors. We aimed to assess the sleep status and related factors of TB patients in Shenzhen, China. METHODS: A questionnaire survey was conducted on 461 TB patients hospitalized at Shenzhen Third People's Hospital from March 2021 to January 2022, and sleep quality was assessed using the Pittsburgh sleep quality index (PSQI). RESULTS: A total of 459 valid questionnaires were collected, and 238 of the 459 TB patients had general or poor sleep quality (PSQI > 5). Patients' gender, marriage, nutritional screening score, family atmosphere, fear of discrimination, fear of interactions, and the impact of the disease on their work life had significant effects on sleep quality (P < 0.05); PSQI scores of TB patients were negatively correlated with lymphocyte counts (r = - 0.296, P < 0.01), T-lymphocyte counts (r = - 0.293, P < 0.01), helper T lymphocyte counts (r = - 0.283, P < 0.01), killer T lymphocyte counts (r = - 0.182, P < 0.05), and were positively correlated with depression scores (r = 0.424, P < 0.01). Multivariable logistic regression analysis showed that male (OR = 1.64,95% CI 1.11-2.42, P < 0.05), unmarried (OR = 1.57, 95% CI 1.02-2.42, P < 0.05), NRS score grade 3(OR = 5.35, 95% CI 2.08-15.73, P < 0.01), general family atmosphere (OR = 2.23, 95% CI 1.07-4.93, P < 0.05), and the disease affecting work (OR = 1.66, 95% CI 1.11-2.50, P < 0.05) were factors influencing poor sleep quality. CONCLUSION: Most TB patients had varying degrees of sleep disturbance, which may be affected by their gender, marriage, family atmosphere, nutritional status, the effect of the disease on work life, and, depression, as well as lower absolute T-lymphocyte subpopulation counts. Appropriate interventions should be implemented to improve their sleep quality, when treating or caring for such patients.

ACE2 PET to reveal the dynamic patterns of ACE2 recovery in an infection model with pseudocorona virus.

Due to the COVID-19 pandemic, a series of sequelae, such as fatigue, tachypnea, and ageusia, appeared in long COVID patients, but the pathological basis was still uncertain. The targeted radiopharmaceuticals were of potential to systemically and dynamically trace the pathological changes. For the key ACE2 protein in the virus-host interaction, 68 Ga-cyc-DX600 was developed on the basis of DX600 as a PET tracer of ACE2 fluctuation and maintained the ability in differentiating ACE and ACE2. In the temporary infection model inhaled with the radio-traceable pseudovirus in the upper respiratory tract of male humanized ACE2 (hACE2) mice, organ-specific ACE2 dysfunction in acute period and the following ACE2 recovery in a relatively long period was visualized and quantified by ACE2 PET, revealing a complex pattern of virus concentration-dependent degree and time period-dependent tendency of ACE2 recovery, mainly a sudden decrease of apparent ACE2 in the heart, liver, kidneys, lungs, and so on, but the liver was of a quick functional compensation on ACE2 expression after a temporary decrease. ACE2 expression of most organs has recovered to a normal level at 15 days post inhalation, with brain and genitals still of a decreased SUVACE2 ;  meanwhile, kidneys were of an increased SUVACE2 . These findings on ACE2 PET were further verified by western blot. When compared with high-resolution computed tomography on structural changes and FDG PET on glycometabolism, ACE2 PET was superior in an earlier diagnostic window during infection and more comprehensive understanding of functional dysfunction post-infection. In the respective ACE2 PET/CT and ACE2 PET/MR scans of a volunteer, the repeatability of SUVACE2 and the ACE2 specificity were further confirmed. In conclusion, 68 Ga-cyc-DX600 was developed as an ACE2-specific tracer, and the corresponding ACE2 PET revealed the dynamic patterns of functional ACE2 recovery and provided a reference and approach to explore the ACE2-related pathological basis of sequelae in long COVID.

Retrospective study of the immunogenicity and safety of the CoronaVac SARS-CoV-2 vaccine in people with underlying medical conditions.

BACKGROUND: People living with chronic disease, particularly seniors (≥60 years old), made up of most severe symptom and death cases among SARS-CoV-2 infected patients. However, they are lagging behind in the national COVID-19 vaccination campaign in China due to the uncertainty of vaccine safety and effectiveness. Safety and immunogenicity data of COVID-19 vaccines in people with underlying medical conditions are needed to address the vaccine hesitation in this population. METHODS: We included participants (≥40 years old) who received two doses of CoronaVac inactivated vaccines (at a 3-5 week interval) and were healthy or had at least one of 6 common chronic diseases. The incidence of adverse events after vaccination was monitored. Vaccine immunogenicity was studied by determining neutralizing antibodies and SARS-CoV-2-specific T cell responses post vaccination. RESULTS: Here we show that chronic diseases are associated with a higher rate of mild fatigue following the first dose of CoronaVac. By day 14-28 post vaccination, the neutralizing antibody level shows no significant difference between disease groups and healthy controls, except for people with coronary artery disease (p = 0.0287) and chronic respiratory disease (p = 0.0416), who show moderate reductions. Such differences diminish by day 90 and 180. Most people show detectable SARS-CoV-2-specific T cell responses at day 90 and day 180 without significant differences between disease groups and healthy controls. CONCLUSIONS: Our results highlight the comparable safety, immunogenicity and cellular immunity memory of CoronaVac in seniors and people living with chronic diseases. This data should reduce vaccine hesitancy in this population.

People living with chronic diseases, particularly those over the age of 60, are more likely to have severe symptoms and die following SARS-CoV-2 infection. However, many have not been vaccinated during the national COVID-19 vaccination campaign in China due to concerns about vaccine safety and effectiveness. Here we show that the inactivated COVID-19 vaccine, CoronaVac, is as safe in older people with chronic diseases as it is for healthy people. Also, only slightly differences are seen in the immune response of people with diseases compared to healthy people. Overall, our results highlight that the CoronaVac vaccine is safe and effective in people living with chronic diseases.

Some characteristics of clinical sequelae of COVID-19 survivors from Wuhan, China: A multi-center longitudinal study.

BACKGROUND: The pandemic of COVID-19 has a persistent impact on global health, yet its sequelae need to be addressed at a wide scale around the globe. This study aims to investigate the characteristics, prevalence, and risk factors for mid-term (>6 months) clinical sequelae in a cohort of COVID-19 survivors. METHODS: Totally 715 COVID-19 survivors discharged before April 1, 2020, from three medical centers in Wuhan, China, were included. The longitudinal study was conducted by telephone interviews based on a questionnaire including the clinical sequelae of general, respiratory, and cardiovascular systems. Demographics and some characteristics of clinical sequelae of the survivors were recorded and analyzed. Multivariate logistic regression analysis was applied to explore the risk factors for the sequelae. RESULTS: The median time interval from discharge to telephone interview was 225.0 days. The COVID-19 survivors' median ages were 69 years, and 51.3% were male. Among them, 29.9% had at least one clinical sequela. There were 19.2%, 22.7%, and 5.0% of the survivors reporting fatigue, respiratory symptoms, and cardiovascular symptoms, respectively. Comorbidities, disease severity, the application of mechanical ventilation and high-flow oxygen therapy, and the history of re-admission were associated with the presence of clinical sequelae. CONCLUSIONS: Our study provides further evidence for the prevalence and characteristics of clinical sequelae of COVID-19 survivors, suggesting long-term monitoring and management is needed for their full recovery.

Re-examination of the impact of some non-pharmaceutical interventions and media coverage on the COVID-19 outbreak in Wuhan.

In this paper, based on the classic Kermack-McKendrick SIR model, we propose an ordinary differential equation model to re-examine the COVID-19 epidemics in Wuhan where this disease initially broke out. The focus is on the impact of all those major non-pharmaceutical interventions (NPIs) implemented by the local public healthy authorities and government during the epidemics. We use the data publicly available and the nonlinear least-squares solver lsqnonlin built in MATLAB to estimate the model parameters. Then we explore the impact of those NPIs, particularly the timings of these interventions, on the epidemics. The results can help people review the responses to the outbreak of the COVID-19 in Wuhan, while the proposed model also offers a framework for studying epidemics of COVID-19 and/or other similar diseases in other places, and accordingly helping people better prepare for possible future outbreaks of similar diseases.