ABSTRACT
Over the past three years, we have gained some understanding of the transmission mechanisms of COVID-19. One of the key findings that experts have agreed on is that household transmission is an important pathway for the pandemic. However, most studies on the transmission patterns of COVID-19 focus on the community transmission only, while the equally important study on household transmission has lagged behind. We developed a stochastic dynamic model motivated by the cluster growth algorithm in Erdös–Rényi Random Graph to differentiate the COVID-19 transmission within households from that in the community by noting only a small fraction of the total susceptible population, replenished dynamically by the community transmission events, are indeed vulnerable to household transmission. Thus the model allowed us to the role and characteristics of household transmission within the full framework of virus transmission, beyond the intrinsic characteristics of household transmission. It was then applied to a comprehensive individual-level pandemic dataset collected in Yichang, China. Our findings showed that household transmission accounted for 25.1% and 38.5% of total infections before and during the lockdown, respectively, and that 80.9% of infections were unavoidable. Our model suggests that household-level contact tracing could have reduced the number of infections by over 50% and advanced the clearance date of active infection by 72 days. This model can be used to fit COVID-19 data outside Yichang or other infectious diseases, though modifications might be needed.
Subject(s)
COVID-19 , Communicable DiseasesABSTRACT
PurposeThe purpose of this paper is to examine the impact of two typical relationship management approaches (trust relationship with suppliers and reciprocity) on manufacturer resilience in the context of the COVID-19 crisis. Moreover, this paper aims to deepen the understanding of environmental uncertainty's moderating effect on the association between the trust relationship with suppliers (TRS) and reciprocity.Design/methodology/approachStructural equation modeling has been used to test the hypotheses on 361 Chinese manufacturing firms' managers and independent directors during the COVID-19 crisis.FindingsThe results reveal that reciprocity positively enhances three dimensions of manufacturer resilience, namely, preparedness, responsiveness and recovery capability. Reciprocity positively mediates the relationships between TRS and preparedness, responsiveness and recovery capability. Moreover, environmental uncertainty moderates the association between TRS and reciprocity.Practical implicationsThis study highlights the critical role of reciprocity, the relational governance approach, in enhancing manufacturer resilience in practice. This paper suggests that during emergencies such as the COVID-19 pandemic, managers should adopt trust and reciprocity in supplier relationship governance to strengthen the resilience of manufacturing companies and adapt effective strategies according to the environment.Originality/valueThis study is unique in developing new scales of manufacturer resilience through interviews and surveys with Chinese manufacturers and theoretical research. Based on the social capital theory and social exchange theory, this study shed light on the role of trust and reciprocity. It also bridges relational governance theory with the literature on manufacturing firm resilience literature to help manufacturers better understand the transdisciplinary links between relationship management and resilient operations in emergencies.
ABSTRACT
With the frequent occurrence of emergencies such as the COVID-19 pandemic in recent years, resilience has become increasingly important for the stable and sustainable development of the manufacturing companies. Despite growing interest in supply chain resilience, less attention has been paid to manufacturer resilience and how to improve it through supplier relationship governance. Based on resource-based view (RBV) theory, trust theory and the literature on resilience, this study developed new constructs of measuring manufacturer resilience by temporal logic and sheds light on how the trust relationship with suppliers affect manufacturer resilience via the information-sharing level. The data is collected from 351 respondents who are independent directors or managers of manufacturing companies in China. This study adopted exploratory factor analysis (EFA) and structural equation modeling (SEM) to explore the dimensions of manufacturer resilience and to test the hypotheses. The results reveal that the trust relationship with suppliers has significant positive impacts on three dimensions of manufacturer resilience, that is, preparedness, responsiveness, and recovery capability. In addition, the information-sharing level partially mediates the impact of the trust relationship with suppliers on manufacturer resilience. Specifically, the information-sharing level positively affects preparedness, responsiveness, and recovery capability. Moreover, the trust relationship with suppliers facilitates the information-sharing level. Finally, the study contributes to the manufacturer resilience literature and provides useful guidance for the manufacturing enterprises in enhancing resilience quickly.
ABSTRACT
Corona Virus Disease 2019 (COVID-19) has spread rapidly to more than 70 countries and regions overseas and over 80000 cases have been infected, resulting in more than three thousand deaths. Rapid diagnosis of patients remains a bottleneck in containing the progress of the epidemic. We used automated chemiluminescent immunoassay to detect serum IgM and IgG antibodies to 2019-nCoV of 736 subjects. COVID-19 patients were becoming reactive(positive) for specific antibodies from 7-12 days after the onset of morbidity. Specific IgM and IgG increased with the progression of the disease. The areas under the ROC curves of IgM and IgG were 0.988 and 1.000, respectively. Specific antibody detection has good sensitivity and specificity. Detection of specific antibodies in patients with fever can be a good distinction between COVID-19 and other diseases, so as to be a complement to nucleic acid diagnosis to early diagnosis of suspected cases.