G-Computation to Causal Mediation Analysis With Sequential Multiple Mediators—Investigating the Vulnerable Time Window of HBV Activity for the Mechanism of HCV Induced Hepatocellular Carcinoma

Regression-based approaches are widely used in causal mediation analysis. The presence of multiple mediators, however, increases the complexity and difficulty of mediation analysis. In such cases, regression-based approaches cannot efficiently address estimation issues. Hence, a flexible approach to mediation analysis is needed. Therefore, we developed a method for using g-computation algorithm to conduct causal mediation analysis in the presence of multiple ordered mediators. Compared to regression-based approaches, the proposed simulation-based approach increases flexibility in the choice of models and increases the range of the outcome scale. The Taiwanese Cohort Study dataset was used to evaluate the efficacy of the proposed approach for investigating the mediating role of early and late HBV viral load in the effect of HCV infection on hepatocellular carcinoma (HCC) in HBV seropositive patients (n = 2,878; HCV carrier n = 123). Our results indicated that early HBV viral load had a negative mediating role in HCV-induced HCC. Additionally, early exposure to a low HBV viral load affected HCC through a lag effect on HCC incidence [OR = 0.873, 95% CI = (0.853, 0.893)], and the effect of early exposure to a low HBV viral load on HCC incidence was slightly larger than that of a persistently low viral load on HCC incidence [OR = 0.918, 95% CI = (0.896, 0.941)].

Embedding Isolation, Contact Tracing, and Quarantine in Transmission Dynamics of the Coronavirus Epidemic—A Case Study of COVID-19 in Wuhan

Coronaviruses have caused multiple global pandemics. As an emerging epidemic, the coronavirus disease relies on nonpharmacological interventions to control its spread. However, the specific effects of these interventions are unknown. To evaluate their effects, we extend the susceptible–latent–infectious–recovered model to include suspected cases, confirmed cases, and their contacts and to embed isolation, close contact tracing, and quarantine into transmission dynamics. The model simplifies the population into two parts: the undiscovered part (where the virus spreads freely—the extent of freedom is determined by the strength of social distancing policy) and the discovered part (where the cases are incompletely isolated or quarantined). Through the isolation of the index case (suspected or confirmed case) and the subsequent tracing and quarantine of its close contacts, the infections flow from the undiscovered part to the discovered part. In our case study, multisource data of the novel coronavirus SARS-CoV-2 (COVID-19) in Wuhan were collected to validate the model, the parameters were calibrated based on the prediction of the actual number of infections, and then the time-varying effective reproduction number was obtained to measure the transmissibility of COVID-19 in Wuhan, revealing the timeliness and lag effect of the nonpharmacological interventions adopted there. Finally, we simulated the situation in the absence of a strict social distancing policy. Results show that the current efforts of isolation, close contact tracing, and quarantine can take the epidemic curve to the turning point, but the epidemic could be far from over; there were still 4,035 infected people, and 1,584 latent people in the undiscovered part on March 11, 2020, when the epidemic was actually over with a strict social distancing policy.

Information technology investment and innovation performance: does investment paradox exist?

Purpose The purpose of this study is to deepen the understanding of the effects of information technology (IT) investment on firm innovation performance and examining the investment paradox effect in China. Design/methodology/approach Using a sample of China’ public firms IT investment data between 2010 and 2016, the authors establish a test model of IT investment and innovation performance. Findings The result indicates that IT investment in firms have no effect on innovation performance in the investment period. However, in the full sample and manufacturing sample, the IT investment has a significant positive effect on innovation performance in the post-investment years. In addition, this study finds that large companies and low-age companies may contribute more to innovation when firm investment in IT. Research limitations/implications There are several limitations in this research. First, the authors are failed to obtain a larger sample about the IT investment information data set in China, so this study was compelled to use limited sample data from China, hence, this could lead to errors of too early generalization. Second, the authors use the number of invention patent applications to represent the performance of enterprise innovation, which may not show enterprise innovation effectively. Third, the firms in the sample are all in China Listed Companies, so this may not accurately reflect the entire environment of firm innovation performance, and could possibly. Practical implications The research confirms that there is a paradox and time lag effect in IT investment, which enterprises should pay attention to. Originality/value Existing research confirms that corporate IT investments can bring new products or services. However, the authors still do not know whether IT investment has improved the company’s ability of innovation. This study will fill this gap and the industry effect and time lag effect of the influence of IT investment on innovative performance are also examined.

Stability and Hopf Bifurcation of a Stage-Structured Cannibalism Model with Two Delays

In this work, we consider a stage-structured cannibalism model with two delays. One delay characterizes the lag effect of negative feedback of the prey species, the other has the effect of gestation of the adult predator population. Firstly, criteria for the local stability of feasible equilibria are established. Meanwhile, by choosing delay as a bifurcation parameter, the criteria on the existence of Hopf bifurcation are established. Furthermore, by the normal form theory and center manifold theorem, we derive the explicit formulas determining the properties of periodic solutions. Finally, the theoretical results are illustrated by numerical simulations, from which we can see that the predator’s gestation time delay can make the chaotic phenomenon disappear and maintain periodic oscillation, and that a large feedback time delay of prey can make predators extinct and prey form a periodic solution.

Impacts of Environmental Regulations on Tourism Carbon Emissions

This research analyzed the impact of environmental regulations and their power in suppressing tourism carbon emissions. The results showed that: (1) four types of environmental regulations had significant inhibiting effects on tourism carbon emissions, but different types of regulations had varying effects; and (2) environmental regulations had a significant time lag effect on tourism carbon emissions. The decay rates of the environmental regulation effects were dissimilar for supervisory management, market incentives, command and control, and public participation; and (3) environmental regulations had dissimilar influences on tourism carbon emissions at the regional level. Government agencies should choose differentiated environmental regulation tools, attach great importance to the time-lag effect of environmental regulations on tourism carbon emissions, and establish systems and mechanisms of public participation in environmental matters.

Dynamics of Vegetation Net Primary Productivity and Its Response to Drought in the Mongolian Plateau

Vegetation net primary productivity (NPP) is an important aspect of the global carbon cycle, and its change is closely related to climate change. This study analyzed the spatial-temporal variation of the standardized precipitation evapotranspiration index (SPEI) and NPP in the Mongolian Plateau, and investigated the effect of drought on NPP. To this end, NPP was simulated using the Carnegie-Ames-Stanford Approach (CASA) model. The results showed that from 1982 to 2014, NPP exhibited an upward trend in different seasons, and a significant increasing trend in most areas in the growing season and spring. The degree of drought also showed an increasing trend in each season. Moreover, the decrease in NPP and SPEI in Mongolia was larger than that in Inner Mongolia. Vegetation showed a positive correlation with SPEI in the growing season and summer, but a negative correlation in the other seasons. Moreover, the impact of drought on vegetation in the growing season showed a lag effect, whereas the lag response was inconspicuous during the early stages of the growing season. Different vegetation NPP responded strongly to the SPEI of the current month and the previous month.