Immigrants' health education and economic behaviours: saving rates, social medical insurance and house purchase

Healthy China is a crucial policy for advancing global health, addressing inequality between rural and urban health education, and helping the domestic markets recover after the COVID-19 outbreak. This study combines life cycle mechanisms and safety beliefs to evaluate the long-lasting values of health education. We employed data from the China Migration Dynamic Surveys to examine the economic behaviours of 720,900 immigrants using a robust empirical approach combining an Extended Regression Model (E.R.M.), Average Treatment Effects (A.T.E.), and heterogeneous treatment effects. We find that health education increases participation in social medical insurance and the likelihood of purchasing a house. In contrast, the relationship between health education and saving rates is non-linear effects. Empirically robust heterogeneous treatment effects account for heterogeneity in the previous and the younger generations, as well as urban and rural citizens' long-run effects of health education. This study's findings suggest that health education stimulates immigrants' consumption behaviours;however, extra health education is not desirable. Rural-urban citizenship acquisition bias is found to significantly affect health education.

[The role of large-scale testing platform in the prevention and control of the COVID-19 pandemic: an empirical study based on a novel numerical model].

Objective: China adopted an unprecedented province-scale quarantine since January 23rd 2020, after the novel coronavirus (COVID-19) broke out in Wuhan in December 2019. Responding to the challenge of limited testing capacity, large-scale (>20 000 tests per day) standardized and fully-automated laboratory (Huo-Yan) was built as an ad-hoc measure. There is so far no empirical data or mathematical model to reveal the impact of the testing capacity improvement since quarantine. Methods: Based on the suspected case data released by the Health Commission of Hubei Province and the daily testing data of Huo-Yan Laboratory, the impact of detection capabilities on the realization of "clearing" and "clearing the day" of supected cases was simulated by establishing a novel non-linear and competitive compartments differential model. Results: Without the establishment of Huo-Yan, the suspected cases would increase by 47% to 33 700, the corresponding cost of quarantine would be doubled, the turning point of the increment of suspected cases and the achievement of "daily settlement" (all newly discovered suspected cases are diagnosed according to the nucleic acid testing result) would be delayed for a whole week and 11 days. If the Huo-Yan Laboratory could ran at its full capacity, the number of suspected cases could start to decrease at least a week earlier, the peak of suspected cases would be reduced by at least 44%, and the quarantine cost could be reduced by more than 72%. Ideally, if a daily testing capacity of 10 500 tests was achieved immediately after the Hubei lockdown, "daily settlement" for all suspected cases could be achieved. Conclusions: Large-scale, standardized clinical testing platform, with nucleic acid testing, high-throughput sequencing, and immunoprotein assessment capabilities, need to be implemented simultaneously in order to maximize the effect of quarantine and minimize the duration and cost of the quarantine. Such infrastructure, for both common times and emergencies, is of great significance for the early prevention and control of infectious diseases.