Public health emergencies have challenged the public health emergency management systems (PHEMSs) of many countries critically and frequently since this century. As the world’s most populated country and the second biggest economy in the world, China used to have a fragile PHEMS; however, the government took forceful actions to build PHEMS after the 2003 SARS outbreak. After more than one decade’s efforts, we tried to assess the improvements and problems of China’s PHEMS between 2002 and 2012. We conducted two rounds of national surveys and collected the data of the year 2002 and 2012, including all 32 provincial, 139 municipal, and 489 county CDCs. The municipal and county CDCs were selected by systematic random sampling. Twenty-one indicators of four stages (preparation, readiness, response and recovery) from the National Assessment Criteria for CDC Performance were chosen to assess the ten-year trends. At the preparation stage, organization, mechanisms, workforce, and stockpile across all levels and regions were significantly improved after one decade’s efforts. At the readiness stage, the capability for formulating an emergency plan was also significantly improved during the same period. At the response stage, internet-based direct reporting was 98.8%, and coping scores were nearly full points of ten in 2012. At the recovery stage, the capabilities were generally lower than expected. Due to forceful leadership, sounder regulations, and intensive resources, China’s PHEMS has been improved at the preparation, readiness, and response stages; however, the recovery stage was still weak and could not meet the requirements of crisis management and preventive governance. In addition, CDCs in the Western region and counties lagged behind in performance on most indicators. Future priorities should include developing the recovery stage, establishing a closed feedback loop, and strengthening the capabilities of CDCs in Western region and counties.

Background: Although China began implementing medical reforms in 2009 aimed at fair allocation of the regional distribution of doctors, little is known of their impact. This study analyzed the geographic distribution of doctors from 2002 to 2017. Methods: This study calculated the Gini coefficient and Theil index among doctors in the eastern, central, and western regions (Category 1) of China, and in urban and rural areas (Category 2). The statistical significance of fairness changes was analyzed using the Mann–Whitney U test. Results: The annual growth rates of the number of doctors for the periods from 2002 to 2009 and 2010 to 2017 were 2.38% and 4.44%. The Gini coefficients among Category 1 were lower than those in Category 2, and statistically decreased after the medical reforms (P < 0.01) but continued to increase in Category 2 (P = 0.463). In 2017, the Theil decomposition result of Category 1 was 74.33% for the between-group, and in Category 2, it was 95.22% for the within-group. Conclusions: The fairness among the regional distribution of doctors in Category 1 is now at a high level and is better than that before the reforms. While the fairness in Category 2 is worse than that before the reforms, it causes moderate inequality and is continually decreasing. Overall unfairness was found to be derived from the between-group.

Background: Recently, the novel coronavirus disease (COVID-19) has already spread rapidly as a global pandemic, just like the H1N1 swine influenza in 2009. Evidences have indicated that the efficiency of emergency response was considered crucial to curb the spread of the emerging infectious disease. However, studies of COVID-19 on this topic are relatively few. Methods: A qualitative comparative study was conducted to compare the timeline of emergency responses to H1N1 (2009) and COVID-19, by using a set of six key time nodes selected from international literature. Besides, we also explored the spread speed and peak time of COVID-19 and H1N1 swine influenza by comparing the confirmed cases in the same time interval. Results: The government’s entire emergency responses to the epidemic, H1N1 swine influenza (2009) completed in 28 days, and COVID-19 (2019) completed in 46 days. Emergency responses speed for H1N1 was 18 days faster. As for the epidemic spread speed, the peak time of H1N1 came about 4 weeks later than that of COVID-19, and the H1N1 curve in America was flatter than COVID-19 in China within the first four months after the disease emerged. Conclusions: The speed of the emergency responses to H1N1 was faster than COVID-19, which might be an important influential factor for slowing down the arrival of the peak time at the beginning of the epidemic. Although COVID-19 in China is coming to an end, the government should improve the public health emergency system, in order to control the spread of the epidemic and lessen the adverse social effects in possible future outbreaks.

Background: China’s National Essential Medicines Policy (NEMP) has been implemented for over 15 years; yet empirical evidence on its long-term impacts is lacking, particularly in remote and rural regions. This study aims to assess the short-and long-term effects of NEMP on the drug availability, price, and usage in a deprived rural county in southwestern China.Methods: A quasi-experimental design was employed, featuring a single-group pre-and-post comparison. We gathered 74,436 procurement records spanning from 2009 to 2016 from the drug warehouses of local medical institutions. Pharmaceutical data were analyzed quarterly, considering various policy and therapeutic attributes. Fisher’s Drug Price Index (DPI-F) was calibrated for the retail and wholesale prices of a consistent collection of 405 medications. We conducted interrupted time-series analysis to examine the immediate and enduring impacts of NEMP’s initial (commencing in January 2011) and second (starting from December 2015) stages.Results: After initiation of NEMP, the number of available essential medicines surged by 115 but subsequently faced a steady quarterly decline (−9.1) in township healthcare centers (THCs, primary care). Conversely, county hospitals (secondary care) initially saw a reduction of 40 in drug availability but later exhibited a steady increase (+4.2 per quarter) up to the second-stage NEMP. Regarding price, THCs encountered abrupt (−26.1%/−15.9% in retail/wholesale price) and sustained (−0.2%/−0.3% per quarter) price drops after NEMP. The immediate price change after NEMP in county hospitals were milder but significant in non-essential medicines, and long-term declines were also observed in all drugs. As for total sales, a significant long-term disparity emerged between THCs (+0.9% per quarter) and county hospitals (+3.3% per quarter). Following the second-stage NEMP, retail prices in county hospitals further decreased, although wholesale prices did not; however, following price upward trends were observed in both THCs and county hospitals. Lastly, the influences of NEMP varied across different therapeutical categories of medicines.Conclusion: NEMP has successfully regulated drug prices in primary and secondary healthcare facilities in remote and rural areas, both short-term and long-term. However, a remarkable disparity in medicine availability and utilization was observed between different levels of facilities over time. Continuous monitoring is essential, with increased attention needed on the uneven impacts of the policy on diverse drugs, facilities, regions, and demographics.