Effects of Governmental Intervention on Foodborne Disease Events: Evidence from China.

Foodborne disease events (FDEs) endanger residents' health around the world, including China. Most countries have formulated food safety regulation policies, but the effects of governmental intervention (GI) on FDEs are still unclear. So, this paper purposes to explore the effects of GI on FDEs by using Chinese provincial panel data from 2011 to 2019. The results show that: (i) GI has a significant negative impact on FDEs. Ceteris paribus, FDEs decreased by 1.3% when government expenditure on FDEs increased by 1%. (ii) By strengthening food safety standards and guiding enterprises to offer safer food, government can further improve FDEs. (iii) However, GI has a strong negative externality. Although GI alleviates FDEs in local areas, it aggravates FDEs in other areas. (iv) Compared with the eastern and coastal areas, the effects of GI on FDEs in the central, western, and inland areas are more significant. GI is conducive to ensuring Chinese health and equity. Policymakers should pay attention to two tasks in food safety regulation. Firstly, they should continue to strengthen GI in food safety issues, enhance food safety certification, and strive to ensure food safety. Secondly, they should reinforce the co-governance of regional food safety issues and reduce the negative externality of GI.

A dynamic model of the Coronavirus Disease 2019 outbreak to analyze the effectiveness of control measures.

ABSTRACT: The World Health Organization (WHO) classified the spread of COVID-19 (Coronavirus Disease 2019) as a global pandemic in March. Scholars predict that the pandemic will continue into the coming winter and will become a seasonal epidemic in the following year. Therefore, the identification of effective control measures becomes extremely important. Although many reports have been published since the COVID-19 outbreak, no studies have identified the relative effectiveness of a combination of control measures implemented in Wuhan and other areas in China. To this end, a retrospective analysis by the collection and modeling of an unprecedented number of epidemiology records in China of the early stage of the outbreaks can be valuable.In this study, we developed a new dynamic model to describe the spread of COVID-19 and to quantify the effectiveness of control measures. The transmission rate, daily close contacts, and the average time from onset to isolation were identified as crucial factors in viral spreading. Moreover, the capacity of a local health-care system is identified as a threshold to control an outbreak in its early stage. We took these factors as controlling parameters in our model. The parameters are estimated based on epidemiological reports from national and local Center for Disease Control (CDCs).A retrospective simulation showed the effectiveness of combinations of 4 major control measures implemented in Wuhan: hospital isolation, social distancing, self-protection by wearing masks, and extensive medical testing. Further analysis indicated critical intervention conditions and times required to control an outbreak in the early stage. Our simulations showed that South Korea has kept the spread of COVID-19 at a low level through extensive medical testing. Furthermore, a predictive simulation for Italy indicated that Italy would contain the outbreak in late May under strict social distancing.In our general analysis, no single measure could contain a COVID-19 outbreak once a health-care system is overloaded. Extensive medical testing could keep viral spreading at a low level. Wearing masks functions as favorably as social distancing but with much lower socioeconomic costs.