Analysis of risk factors of fungal superinfections in viral pneumonia patients: A systematic review and meta-analysis.

BACKGROUND: Infections with fungi, such as Aspergillus species, have been found as common complications of viral pneumonia. This study aims to determine the risk factors of fungal superinfections in viral pneumonia patients using meta-analysis. OBJECTIVE: This study aims to determine the risk factors of fungal infection s in viral pneumonia patients using meta-analysis. METHODS: We reviewed primary literature about fungal infection in viral pneumonia patients published between January 1, 2010 and September 30, 2020, in the Chinese Biomedical Literature, Chinese National Knowledge Infrastructure, Wanfang (China), Cochrane Central Library, Embase, PubMed, and Web of Science databases. These studies were subjected to an array of statistical analyses, including risk of bias and sensitivity analyses. RESULTS: In this study, we found a statistically significant difference in the incidence of fungal infections in viral pneumonia patients that received corticosteroid treatment as compared to those without corticosteroid treatment (p < .00001). Additionally, regarding the severity of fungal infections, we observed significant higher incidence of invasive pulmonary aspergillosis (IPA) in patients with high Acute Physiology and Chronic Health Evaluation (APACHE) II scores (p < .001), tumors (p = .005), or immunocompromised patients (p < .0001). CONCLUSIONS: Our research shows that corticosteroid treatment was an important risk factor for the development of fungal infection in patients with viral pneumonia. High APACHE II scores, tumors, and immunocompromised condition are also important risk factors of developing IPA. The diagnosis of fungal infection in viral pneumonia patients can be facilitated by early serum galactomannan (GM) testing, bronchoalveolar lavage fluid Aspergillus antigen testing, culture, and biopsy.

Random Network Transmission and Countermeasures in Containing Global Spread of COVID-19-Alike Pandemic: A Hybrid Modelling Approach

Since the outbreak of the novel coronavirus disease (COVID-19) at the beginning of December 2019, there have been more than 28.69 million cumulative confirmed cases worldwide as of 12th September 2020, affecting over 200 countries and regions with more than 920,463 deaths. The COVID-19 pandemic has been sweeping worldwide with unexpected rapidity. In this paper, a hybrid modelling strategy based on tessellation structure- (TS-) configured SEIR model is adopted to estimate the scale of the pandemic spread. Building on the data pertaining to the global pandemic transmission over the last six months around the world, key impact factors in the transmission and control procedure have been analysed, including isolation rate, number of the infected cases before taking prevention measures, degree of contact scope, and medical level, so as to capture the fundamental factor influencing the pandemic. The quantitative evaluation allowed us to illustrate the magnitude of risks of pandemic and to recommend appropriate national health policy of prevention measures for effectively controlling both intra- and interregional pandemic spread. Our modelling results clearly indicate that the early-stage preventive measures are the most effective action to be taken to contain the pandemic spread of the highly contagious nature of the COVID-19.

The global COVID-19 pandemic at a crossroads: relevant countermeasures and ways ahead.

BACKGROUND: Since the outbreak of novel coronavirus disease (COVID-19) in Wuhan, China at the beginning of December 2019, there have been over 11,200,000 confirmed cases in the world as of the 3rd July 2020, affecting over 213 countries and regions with nearly 530,000 deaths. The pandemic has been sweeping all continents, North America, Latin America, Europe, Middle East and South Asia among others at an alarming rapidity. Here, we provide an estimate of the scale of the pandemic spread under different scenarios of variation in key influencing parameters with a hybrid model. METHODS: We developed a new hybrid model of infectious disease transmission based on Cellular Automata (CA)-configured SEIR to analyse the COVID-19 outbreak and estimate its transmission pattern. A probabilistic contamination network is embedded in the pandemic transmission model to capture the randomness feature of person-to-person spread of the novel virus. We used the improved SEIR model to quantify the population contact state with isolation measures under different continuous time series contact probability via CA. We adjusted the modelling parameters to verify the model performance in accordance to the data from the reports published by the Chinese Center for Disease Control and Prevention. We simulated several scenarios by varying such key parameters as number of isolation rate, average contact times of the population, number of infected people before taking prevention and control measures, medical level and number of imported cases. RESULTS: In the baseline model, we identified that the isolation control as the most influencing factor that had the largest impact on decreasing the speed of the reproductive number, accelerating the arrival of the "inflection point" of pandemic prevention and control, and the death rate reduction. We estimated that the probability of people contacts and the number of the onset infected cases before prevention measures also had significant effect on the infection rate reduction with appropriate prevention measures adoption, which partly reflects the impact of timely measure on the severity of the outbreak. We found that imported cases will risk the domestic prevention. CONCLUSIONS: Our modelling results clearly indicate that early-stage preventive measures are the most effective way to contain the pandemic spread and a strong interventionist approach needs to be adopted by policymakers vis-à-vis of the highly contagious nature of the COVID-19. Human resources, intensified isolation and confinement as well as special hospital buildings should be prioritised in countries with large number of infections to constrain the global transmission of the virulent infection. To do so, internationally coordinated actions require to be taken to replicate good practices to less infected countries and regions immediately.