Taizhou's COVID-19 prevention and control experience with telemedicine features.

The outbreak of coronavirus disease 2019 (COVID-19) has spread rapidly around the world. As of May 30, 2020, a total of 84 568 confirmed COVID-19 cases have been recorded in China, with a mortality rate of approximately 5.5%. Taizhou is a prefecture-level city in Zhejiang Province. A total of 146 cases were diagnosed in this epidemic, with a fatality rate of 0%. This condition is due to the establishment of an "Internet +" diagnosis and treatment model based on online medical application (APP), telemedicine, WeChat service, and consultation hotline in Taizhou. Taizhou led in opening the "COVID-19 Prevention and Treatment Special Line" in China, which is conducive to pre-hospital screening, suppressing social panic, and clinical support. Hospitals also carried out related online lectures and popularization of science. We summarize Taizhou's COVID-19 prevention and control experience with telemedicine features, with a view to providing reference for the control of the epidemic at home and abroad.

Income-related health inequality of migrant workers in China and its decomposition: An analysis based on the 2012 China Labor-force Dynamics Survey data.

BACKGROUND: Although migrant workers are a vulnerable group in China, they demonstrably contribute to the country's economic growth and prosperity. This study aimed to describe and assess the inequality of migrant worker health in China and its association with socioeconomic determinants. METHODS: The data utilized in this study were obtained from the 2012 China Labor-force Dynamics Survey conducted in 29 Chinese provinces. This study converted the self-rated health of these migrant workers into a general cardinal ill-health score. Determinants associated with migrant worker health included but were not limited to age, marital status, income, and education, among other factors. Concentration index, concentration curve, and decomposition of the concentration index were employed to measure socioeconomic inequality in migrant workers' health. RESULTS: Prorich inequality was found in the health of migrant workers. The concentration index was -0.0866, as a score indicator of ill health. Decomposition of the concentration index revealed that the factors most contributing to the observed inequality were income, followed by gender, age, marital status, and smoking history. CONCLUSION: It is generally known that there is an unequal socioeconomic distribution of migrant worker health in China. In order to reduce the health inequality, the government should make a substantial effort to strengthen policy implementation in improving the income distribution for vulnerable groups. After this investigation, it is apparent that the findings we have made warrant further investigation.