COVID-19-associated pulmonary aspergillosis in a tertiary care center in Shenzhen City.

OBJECTIVES: The severe coronavirus disease 2019 (COVID-19) is characterized by acute respiratory distress syndrome (ARDS) and risk of fungal co-infection, pulmonary aspergillosis in particular. However, COVID-19 associated pulmonary aspergillosis (CAPA) cases remain limited due to the difficulty in diagnosis. METHODS: We describe presumptive invasive aspergillosis in eight patients diagnosed with COVID-19 in a single center in Shenzhen, China. Data collected include underlying conditions, mycological findings, immunodetection results, therapies and outcomes. RESULTS: Four of the eight patients had tested positive for Aspergillus by either culture or Next-generation sequencing analysis of sputum or bronchoalveolar lavage fluid (BALF), while the rest of patients had only positive results in antigen or antibody detection. Although all patients received antifungal therapies, six of these eight patients (66.7%) died. CONCLUSION: Due to the high mortality rate of CAPA, clinical care in patients with CAPA deserves more attention.

Optimal Reopening Pathways With COVID-19 Vaccine Rollout and Emerging Variants of Concern.

We developed a stochastic optimization technology based on a COVID-19 transmission dynamics model to determine optimal pathways from lockdown toward reopening with different scales and speeds of mass vaccine rollout in order to maximize social economical activities while not overwhelming the health system capacity in general, hospitalization beds, and intensive care units in particular. We used the Province of Ontario, Canada as a case study to demonstrate the methodology and the optimal decision trees; but our method and algorithm are generic and can be adapted to other settings. Our model framework and optimization strategies take into account the likely range of social contacts during different phases of a gradual reopening process and consider the uncertainties of these contact rates due to variations of individual behaviors and compliance. The results show that, without a mass vaccination rollout, there would be multiple optimal pathways should this strategy be adopted right after the Province's lockdown and stay-at-home order; however, once reopening has started earlier than the timing determined in the optimal pathway, an optimal pathway with similar constraints no longer exists, and sub-optimal pathways with increased demand for intensive care units can be found, but the choice is limited and the pathway is narrow. We also simulated the situation when the reopening starts after the mass vaccination has been rolled out, and we concluded that optimal pathways toward near pre-pandemic activity level is feasible given an accelerated vaccination rollout plan, with the final activity level being determined by the vaccine coverage and the transmissibility of the dominating strain.

A window of opportunity for intensifying testing and tracing efforts to prevent new COVID-19 outbreaks due to more transmissible variants.

BACKGROUND: When public health interventions are being loosened after several days of decline in the number of coronavirus disease 2019 (COVID-19) cases, it is of critical importance to identify potential strategies to ease restrictions while mitigating a new wave of more transmissible variants of concern (VOCs). We estimated the necessary enhancements to public health interventions for a partial reopening of the economy while avoiding the worst consequences of a new outbreak, associated with more transmissible VOCs. METHODS: We used a transmission dynamics model to quantify conditions that combined public health interventions must meet to reopen the economy without a large outbreak. These conditions are those that maintain the control reproduction number below unity, while accounting for an increase in transmissibility due to VOC. RESULTS: We identified combinations of the proportion of individuals exposed to the virus who are traced and quarantined before becoming infectious, the proportion of symptomatic individuals confirmed and isolated, and individual daily contact rates needed to ensure the control reproduction number remains below unity. CONCLUSION: Our analysis indicates that the success of restrictive measures including lockdown and stay-at-home orders, as reflected by a reduction in number of cases, provides a narrow window of opportunity to intensify case detection and contact tracing efforts to prevent a new wave associated with circulation of more transmissible VOCs.

Clinical and etiological analysis of co-infections and secondary infections in COVID-19 patients: An observational study.

BACKGROUND: Co-infections, secondary bacterial or fungal infections, are important risk factors for poor outcomes in viral infections. The prevalence of co-infection and secondary infection in patients infected with SARS-CoV-2 is not well understood. AIMS: To investigate the role of co-infections and secondary infections in disease severity of hospitalized individuals with COVID-19. MATERIALS AND METHODS: A retrospective study was carried out between 11 January 2020 and 1 March 2020 among 408 laboratory confirmed COVID-19 patients in China. These patients were divided into three groups based on disease severity: mild or moderate, severe, or critically ill. Microbiological pathogens in blood, urine, and respiratory tract specimens were detected by the combination of culture, serology, polymerase chain reaction, and metagenomic next-generation sequencing (mNGS). RESULTS: The median age of participants was 48 years (IQR 34-60 years). Fifty-two patients (12.7%) had at least one additional pathogen, 8.1% were co-infected, and 5.1% had a secondary infection. There were 13 Mycoplasma pneumoniae cases, 8 Haemophilus influenzae cases, 8 respiratory viruses, and 3 Streptococcus pneumoniae cases, primarily detected in mild and moderate COVID-19 patients. Hospital-acquired infection pathogens were more common in critically ill patients. Compared to those without additional pathogens, patients with co-infections and/or secondary infections were more likely to receive antibiotics (p < 0.001) and have elevated levels of d-dimer (p = 0.0012), interleukin-6 (p = 0.0027), and procalcitonin (p = 0.0002). The performance of conventional culture was comparable with that of mNGS in diagnosis of secondary infections. CONCLUSION: Co-infections and secondary infections existed in hospitalized COVID-19 patients and were relevant to the disease severity. Screening of common respiratory pathogens and hospital infection control should be strengthened.

Spatiotemporal transmission dynamics of the COVID-19 pandemic and its impact on critical healthcare capacity.

The role of geospatial disparities in the dynamics of the COVID-19 pandemic is poorly understood. We developed a spatially-explicit mathematical model to simulate transmission dynamics of COVID-19 disease infection in relation with the uneven distribution of the healthcare capacity in Ohio, U.S. The results showed substantial spatial variation in the spread of the disease, with localized areas showing marked differences in disease attack rates. Higher COVID-19 attack rates experienced in some highly connected and urbanized areas (274 cases per 100,000 people) could substantially impact the critical health care response of these areas regardless of their potentially high healthcare capacity compared to more rural and less connected counterparts (85 cases per 100,000). Accounting for the spatially uneven disease diffusion linked to the geographical distribution of the critical care resources is essential in designing effective prevention and control programmes aimed at reducing the impact of COVID-19 pandemic.

Quantifying the shift in social contact patterns in response to non-pharmaceutical interventions.

Social contact mixing plays a critical role in influencing the transmission routes of infectious diseases. Moreover, quantifying social contact mixing patterns and their variations in a rapidly evolving pandemic intervened by changing public health measures is key for retroactive evaluation and proactive assessment of the effectiveness of different age- and setting-specific interventions. Contact mixing patterns have been used to inform COVID-19 pandemic public health decision-making; but a rigorously justified methodology to identify setting-specific contact mixing patterns and their variations in a rapidly developing pandemic, which can be informed by readily available data, is in great demand and has not yet been established. Here we fill in this critical gap by developing and utilizing a novel methodology, integrating social contact patterns derived from empirical data with a disease transmission model, that enables the usage of age-stratified incidence data to infer age-specific susceptibility, daily contact mixing patterns in workplace, household, school and community settings; and transmission acquired in these settings under different physical distancing measures. We demonstrated the utility of this methodology by performing an analysis of the COVID-19 epidemic in Ontario, Canada. We quantified the age- and setting (household, workplace, community, and school)-specific mixing patterns and their evolution during the escalation of public health interventions in Ontario, Canada. We estimated a reduction in the average individual contact rate from 12.27 to 6.58 contacts per day, with an increase in household contacts, following the implementation of control measures. We also estimated increasing trends by age in both the susceptibility to infection by SARS-CoV-2 and the proportion of symptomatic individuals diagnosed. Inferring the age- and setting-specific social contact mixing and key age-stratified epidemiological parameters, in the presence of evolving control measures, is critical to inform decision- and policy-making for the current COVID-19 pandemic.