Literature DB >> 29642902

The public health emergency management system in China: trends from 2002 to 2012.

Mei Sun1,2, Ningze Xu2, Chengyue Li1, Dan Wu3, Jiatong Zou1, Ying Wang1, Li Luo1, Mingzhu Yu4, Yu Zhang5, Hua Wang6, Peiwu Shi7, Zheng Chen8, Jian Wang9, Yueliang Lu10, Qi Li11, Xinhua Wang12, Zhenqiang Bi13, Ming Fan14, Liping Fu15, Jingjin Yu4, Mo Hao16.   

Abstract

BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.

Entities:  

Keywords:  China; Preparation; Public health emergency management system; Readiness; Recovery; Response; Trend

Mesh:

Year:  2018        PMID: 29642902      PMCID: PMC5896068          DOI: 10.1186/s12889-018-5284-1

Source DB:  PubMed          Journal:  BMC Public Health        ISSN: 1471-2458            Impact factor:   3.295


Background

Since the early twenty-first century, frequently appearing public health emergencies such as severe acute respiratory syndrome (SARS), Middle Eastern respiratory syndrome, and Ebola have threatened population health and social stability [1]. This has critically challenged the public health emergency management systems (PHEMSs) of many countries [2], especially developing countries. The global community quickly reached a consensus on the development of the PHEMSs [3]. In 2005, the 58th World Health Assembly (WHA) adopted the revised International Health Regulations, which instructed the World Health Organization (WHO) member states to collaboratively confront public health emergencies of global concern. A World Health Report in 2007 also focused on global public health security in the twenty-first century. The Ebola outbreak in 2014–2015 has pushed the process of WHO reform into high gear [4], giving top priority to changes in the WHO’s emergency operations and a need to build resilient health systems that can withstand epidemics. China has the largest population and the second biggest economy in the world. China has played an increasingly important role in preventing and controlling the global spread of epidemics in recent years and gradually changed from aid recipient to aid donor [5]. China used to have a fragile PHEMS; however, the 2003 SARS outbreak exposed many weaknesses and problems [6], such as an ineffective response system, lagging epidemiological field investigation and laboratory testing skills, and inaccurate and untimely information communication. These aroused the public’s horror and international community’s blame. The central government urged governments at different levels to make political commitments and take forceful actions to build the PHEMS. After more than one decade’s efforts, what are the trends of China’s PHEMS? What are the improvements and remaining problems? What are the implications for China and global health security? In recent years, the development of PHEMS has received increased attention in the literatures. Some researchers expressed the importance of PHEMS and the progress after SARS qualitatively [7, 8]. Others quantitatively accessed the trends using regional data, usually at a certain level or within a certain province or city [9-12]. Time spans were restricted to early-phase usually around 2005 [13]. To our knowledge, little evidence could tell the differences that happened in China’s PHEMS in this decade. Based on two national surveys in 2006 and 2013, we previously reported that resource allocation of CDCs increased and the general completeness of PHEMS improved between 2002 and 2012 [14]. However, what measures PHEMS carried out and how it changed still remained unclear. This paper will attempt to answer these questions specifically. This article consists of the follows. The next section provides details on methodology,including sampling, indicator selection and measurements, data collection, and data analysis methods. The third section shows the results, followed by discussion corresponding to the results. The final section is about conclusion and policy implications.

Methods

Sample

The survey methods have previously been published [14]. Briefly, we conducted two rounds of cross-sectional surveys in 2006 and 2013. The two surveys were retrospective and selected the same agencies in the two rounds. The survey of 2006 collected the data from 2002 to 2005, and the survey of 2013 collected data of 2012. We conducted a multistage sampling to select CDCs at different administration levels, selected all 32 provincial CDCs and used systematic random sampling to select municipal and county CDCs. As governmental funding is the most critical control point of public health emergency management for the CDCs [15],we used “governmental funding to CDCs per thousand people” as a basis to determine sample size [16]. A sample size of 123 municipal and 457 county CDCs was calculated based on the following formula [17].where n is the number of the minimal sample size; αis the probability of type I error, and β is the probability of type II error, here α = 0.05,β = 0.05; uαand uβare standard normal distribution values corresponding to α and β respectively;σis the population standard deviation, hereσ = 404.3 yuan; δ is the allowable error. For municipal CDCs, δ = 54.9yuan, σ = 210.0 yuan. For county-level CDCs, δ = 62.5yuan, σ = 404.3yuan (1 U.S. dollar = 6.6 yuan). The municipal and county level CDCs were all selected through random sampling. The sampling process was conducted based on the national standard coding (GB coding, the corresponding administrative regional code which is unique for each city or county [14]). We used a computer-generated random number to identify the first institution, and then selected every third municipal CDC and every sixth county level CDC. Finally, we selected 32 provincial CDCs, 139 municipal CDCs, and 489 county CDCs. The study was approved by the former Ministry of Health (MOH) in China and reviewed by the Medical Research Ethics Committee at the School of Public Health of Fudan University.

Measures

We selected twenty-one indicators associated with the PHEMS from the National Assessment Criteria for CDC Performance. Based on the crisis management theory which was commonly used in the field of public emergency management [18, 19], the whole process was divided into four stages including preparation, readiness, response and recovery [20]. According to the framework, we grouped the indicators into 4 stages and 13 capabilities. Table 1 showed the features, units and measurements of these indicators.
Table 1

Measurements of public health emergency management system

StageCapabilityIndicatorUnitResponse measurement and indicator calculation
1.Preparation1.1OrganizationPercentage of establishing emergency response office%yes/no; number of CDCs’ responses/sample size
Percentage of forming leadership group%
Percentage of forming expert panel%
1.2MechanismsPercentage of building information sharing mechanism%
Percentage of building on-site treatment mechanism%
Percentage of building material deployment mechanism%
1.3WorkforceAverage number of emergency response personnelPersonnumber; total number of personnel/sample size
1.4StockpilePercentage of fully stockpiling emergency resources%yes/no; number of stockpiling emergency resources/fully stockpiling emergency resources
2.Readiness2.1PlanningPercentage of formulating emergency response plan%yes/no; number of CDCs’ responses/sample size
2.2TrainingAverage length of emergency response trainingDay/ persontotal days of emergency response training/total emergency response personnel
2.3ExercisingAverage times of exercises of emergency response planNumber of timestotal times of exercises /sample size
2.4MonitoringDisease surveillance and analytical periodFrequencyby day, week, ten days, month, quarter, year
2.5Direct reportPercentage of internet direct report building%number; number of internet direct reports/total reports
3.Response3.1ReportingPercentage of timely reporting%number; number of timely reports/total reports
3.2CopingConfirmation ScorePointsTen-point scale, full points of 10 = good; Total scores/sample size
Specific Preparedness ScorePoints
On-scene/field handling/disposal scorePoints
Implementation score for control measuresPoints
4.Recovery4.1ArchivingArchive of relevant materialsPoints
4.2AnalyzingAnalytical report and impact evaluationPoints
4.3ConcludingConcluding reportPoints

Note CDC means Center for Disease Prevention and Control

Measurements of public health emergency management system Note CDC means Center for Disease Prevention and Control According to the National Regulations on Public Health Emergency Management [21], each sampled CDC graded five public health emergencies handled in the year before the survey with the full mark of 10 points for each indicator; at CDCs where the total numbers of handled public health emergencies were fewer than five, all public health emergencies were graded instead.

Quality control

The Bureau of Disease Prevention and Control of the former MOH approved and organized two rounds of field surveys, and 32 provincial Health Departments coordinated data collection. A pilot survey was conducted to ensure validity and reliability. After receiving uniform training from the MOH, the provincial quality supervisors trained investigators from sampled CDCs in their corresponding provinces. The investigators collected relevant data from sampled CDCs and submitted the completed questionnaires to their provincial quality supervisors via e-mail or CD-ROM. Simultaneously, paper copies with official stamps were submitted. The second round of survey data were obtained from National Disease Control and Prevention Performance Evaluation Platform. The quality control process was set up and carried out by the platform with backend logic judgments and audit procedures. As the final step of quality control in both surveys, research group rechecked data and contacted CDCs with abnormal or absent values via email or phone. Finally, the overall response rate was 95.8% in 2002 and 99.5% in 2012.

Data analysis

We established a dataset using Excel 2013(Microsoft Redmond WA). We only used the data of the year 2002 and 2012 for analysis. After data cleaning and sorting, descriptive analysis and statistical tests were performed using SPSS 21.0 (IBM SPSS, Chicago, IL, USA). We used McNemar’s test to test differences in proportions and paired sample t test to test differences in means between 2002 and 2012. Since noticeable differences existed between China’s regions, the division of regions was based on the 2003 Chinese Economics Yearbook and the First National Economic Census.

Results

Preparation stage

Establishing organization comprised building an emergency response office and forming a leadership group and an expert panel. The average percentage of CDCs with an emergency response office was 61.6% in 2002 and 95.0% in 2012. The average percentages with a leadership group and an expert panel were 47.9% and 78.6% in 2002 and 95.7% and 96.8% in 2012, respectively. Similar trends also occurred across different levels and regions (Table 2).
Table 2

Evaluation of preparation and readiness stage by levels and regions: 2002 and 2012 (differences in proportions)

Indicators20022012Growth (%)p-value
n%n%
1.1 Organization
 % of establishing emergency response office63261.664495.054.20.5110
  Provincial2964.33196.850.50.0310
  Municipal13556.313896.471.20.0080
  County46851.147594.584.90.1560
  East12455.612993.067.30.1040
  Central25454.725597.678.40.6910
  West25449.426093.589.30.5860
 % of forming leadership group63247.964495.799.8< 0.0001
  Provincial2978.63196.823.20.0210
  Municipal13547.413897.1104.9< 0.0001
  County46846.247595.2106.1< 0.0001
  East12453.212993.876.3< 0.0001
  Central25450.025597.394.6< 0.0001
  West25443.126095.0120.4< 0.0001
 % of forming expert panel63278.664496.823.2< 0.0001
  Provincial2982.13193.513.90.1090
  Municipal13538.513896.4150.4< 0.0001
  County46830.647584.0174.5< 0.0001
  East12437.912989.1135.1< 0.0001
  Central25439.025592.2136.4< 0.0001
  West25428.526081.2184.9< 0.0001
1.2 Mechanism< 0.0001
 % of building information sharing mechanism63248.064492.993.5< 0.0001
  Provincial2967.93193.537.70.0060
  Municipal13548.913896.497.1< 0.0001
  County46846.647591.897.0< 0.0001
  East12452.412992.276.0< 0.0001
  Central25446.925596.1104.9< 0.0001
  West25447.026090.091.5< 0.0001
 % of building on-site treatment mechanism63249.164493.089.4< 0.0001
  Provincial2979.33193.517.90.1090
  Municipal13548.113895.799.0< 0.0001
  County46847.447592.294.5< 0.0001
  East12454.812991.567.0< 0.0001
  Central25446.925595.7104.1< 0.0001
  West25448.426091.288.4< 0.0001
 % of building response material deployment mechanism63239.664490.1127.5< 0.0001
  Provincial2967.93190.333.00.0350
  Municipal13539.313895.7143.5< 0.0001
  County46838.047588.4132.6< 0.0001
  East12445.212991.5102.4< 0.0001
  Central25440.225593.3132.1< 0.0001
  West25436.426086.2136.8< 0.0001
2.1 Emergency plan
 % of making emergency plans63240.664489.9121.4< 0.0001
  Provincial2942.93193.5117.9< 0.0001
  Municipal13538.513889.1131.4< 0.0001
  County46841.047589.9119.3< 0.0001
  East12435.512986.0142.3< 0.0001
  Central25446.125592.5100.7< 0.0001
  West25437.526089.2137.9< 0.0001
2.4 Disease surveillance frequency560614
 Per day162.9294.762.10.0400
 Per week142.514123.0820.0< 0.0001
 Per ten days7112.7101.6−87.4< 0.0001
 Per month32458.039163.79.8< 0.0001
 Per quarter7112.7264.2−66.9< 0.0001
 Per year6311.3172.8−75.2< 0.0001
Evaluation of preparation and readiness stage by levels and regions: 2002 and 2012 (differences in proportions) The capability for building mechanisms in terms of information sharing and on-site treatment increased by 93.5% and 89.4%, respectively. Increasing by 127.5%, response-material deployment mechanism gained the highest growth rate. Municipal CDCs had the highest percentages, followed by provincial and county CDCs. The central region not only had the highest percentages, but also experienced the highest growth rate. Average number of emergency response personnel per CDC increased from 15 in 2002 to 31 in 2012, which was significant. In 2012, provincial CDCs had the highest number of personnel (n = 92), followed by municipal (n = 47) and county (n = 22) CDCs. Moreover, the average number decreased from eastern (n = 35) to western regions (n = 29) (Table 3).
Table 3

Evaluation of preparation and readiness stage by levels and regions: 2002 and 2012 (differences in means)

Indicators20022012Growth (%)p-value
nMeannMean
1.3 Personnel4751562331106.7< 0.0001
 Provincial26283092228.6< 0.0001
 Municipal1022213447113.6< 0.0001
 County347124592283.3< 0.0001
 East1241412535150< 0.0001
 Central2541525231106.7< 0.0001
 West254162462981.3< 0.0001
1.4 Emergency stockpile63216.760141.2146.7< 0.0001
 Provincial2936.73074.2102.2< 0.0001
 Municipal13520.712756.8174.4< 0.0001
 County46814.344434.5141.3< 0.0001
 East12422.712156.7149.8< 0.0001
 Central25418.224942.5133.5< 0.0001
 West25412.223131.7159.8< 0.0001
2.2 Length of response training4159.762014.650.50.6060
 Provincial2025.03044.377.20.0060
 Municipal848.713221.1142.50.1600
 County3119.045810.820.00.3290
 East1117.112314.8108.50.3360
 Central15511.825315.329.70.0010
 West1499.224413.951.10.1770
2.3 Times of Emergency exercise3182.36192.2−4.3< 0.0001
 Provincial161.1301.536.4< 0.0001
 Municipal632.11331.7−19.0< 0.0001
 County2392.54562.4−4.0< 0.0001
 East1071.41241.828.60.0090
 Central1122.92522.1−27.6< 0.0001
 West992.92432.7−6.90.0200
Evaluation of preparation and readiness stage by levels and regions: 2002 and 2012 (differences in means) The percentage of fully stockpiling emergency resources significantly increased from 16.7% in 2002 to 41.2% in 2012. Provincial CDCs had the highest percentage (74.2%) in 2012 and increased by 102.2%, whereas county CDCs had the lowest percentage (34.5%) in 2012 and increased by 141.3%. Nevertheless, the average percentage at each administrative level did not meet the corresponding performance assessment criteria. Average percentages of fully stockpiling emergency resources decreased from eastern (56.7%) to western (31.7%) regions.

Readiness stage

The mean percentage of formulating emergency plan increased from 40.6% in 2002 to 89.9% in 2012, statistically significantly increasing by 121.4%. Provincial CDCs had the highest percentage (93.5%) in 2012, and the difference between municipal (89.1%) and county CDCs (89.9%) was not significant. CDCs in central region had the highest percentage (92.5%), followed by western (89.2%) and eastern (86.0%) regions (Table 2). The average length of emergency response training increased from 9.7 days per person in 2002 to 14.6 days per person in 2012; however, this 50.5% increase was not statistically significant. Provincial CDCs had the highest average length of response training (44.3 days per person), followed by municipal and county CDCs (Table 3). Comparing the statistics in 2002 and 2012, the average times of exercises did not change with statistical significance. In 2012, county CDCs had higher average times of exercises than did municipal (1.7) and provincial (1.5) CDCs; nevertheless, only provincial CDCs had increased average times of exercises during the past decade. From regional perspective, the average times of exercises decreased from western (2.7) to eastern (1.8) regions (Table 3). There were 63.7% and 23.0% of disease surveillances conducted per month and per week in 2012, respectively. Compared with statistics in 2002, frequencies of daily, weekly, and monthly surveillance analysis increased, among which weekly surveillance analysis increased with statistical significance. Meanwhile, the frequencies of disease surveillance analysis per ten days, quarter, and year decreased with statistical significance (Table 2).

Response stage

According to “contingency rules of paroxysmal public health events”, public health emergency events are classified into four levels (I, II, III and IV), with severity decreasing from Level I to Level IV. In 2012, there were 3092 public health emergencies directly reported via the Disease Surveillance Information Management System, which accounted for 98.8%.The percentage of timely reporting by county CDCs emergency levels in 2012 was presented in Table 4. Moreover, the average scores for indicators of coping capability were high in 2012 (Table 4).
Table 4

Percentage of timely reporting by county CDCs by emergency levels in 2012

RegionLevel ILevel IILevel IIILevel IVUnclassifiedTotal
East100.0-100.057.459.459.5
Central--100.092.996.496.3
West75.0100.092.391.589.089.7
Total83.3100.094.178.784.183.6

Note “-” means there was no such emergency at the corresponding level. The severity of public health emergency decreased from level I to level IV. CDC means Center for Disease Prevention and Control

Percentage of timely reporting by county CDCs by emergency levels in 2012 Note “-” means there was no such emergency at the corresponding level. The severity of public health emergency decreased from level I to level IV. CDC means Center for Disease Prevention and Control

Recovery stage

The average scores for capabilities at recovery stage were lower than those for capabilities at response stage. The average score for data archiving was 8.33, then followed by those for data analyzing (5.83) and concluding (5.69) (Table 5).
Table 5

Evaluation of coping capability and recovery stage by levels and regions in 2012

Level/regionnEmergency confirmationResponse preparednessOn-site responseImplementation of control measuresArchivingAnalyzingConcluding
Points95% CIPoints95% CIPoints95% CIPoints95% CIPoints95% CIPoints95% CIPoints95% CI
Average2719.619.52–9.699.259.15–9.349.219.12–9.309.179.08–9.268.338.15–8.525.835.59–6.075.695.45–5.95
Provincial259.739.53–9.889.759.66–9.839.779.71–9.839.659.54–9.767.987.46–8.485.855.18–6.496.175.57–6.80
Municipal1029.859.78–9.929.449.33–9.539.439.35–9.519.469.38–9.548.548.27–8.815.374.99–5.765.344.96–5.70
County1149.279.08–9.468.828.63–9.028.738.54–8.938.638.44–8.838.227.90–8.536.406.00–6.805.935.57–6.31
East709.659.50–9.809.209.01–9.369.249.07–9.409.038.84–9.207.807.41–8.185.745.29–6.205.455.00–5.94
Central819.549.36–9.719.239.05–9.398.988.79–9.149.098.90–9.268.738.43–9.035.445.00–5.895.384.96–5.83
West1209.639.51–9.749.319.17–9.439.389.26–9.499.349.22–9.468.398.07–8.686.225.81–6.606.115.73–6.46
Evaluation of coping capability and recovery stage by levels and regions in 2012

Discussion

The main findings indicated that China had made significant progress in the four stages after a decade’s efforts, especially in preparation, readiness, and response stages. This has been demonstrated by other researches [7, 8]. The average percentages of CDCs with an emergency response office, a leadership group and an expert panel were 95.0%, 95.7% and 96.8% in 2012, respectively. This suggests that a PHPM system with better leadership has been established in China. Soon after the SARS outbreak, Chinese governments at different levels were urged to establish a SARS headquarters at CDCs to shoulder the responsibilities of unified leadership and command during public health emergencies. The Emergency Response Law of the People’s Republic of China issued in 2007 formally and strongly stipulated the establishment of the emergency management system that urged unified leadership, comprehensive coordination, categorized management, graded responsibility, and territorial management. The capability for building mechanisms comprised of information sharing, on-site treatment and response-material deployment increased to more than 95% in 2012. Boosted by the SARS outbreak in 2003, various authorities consecutively issued a series of regulations that standardized the PHEMS in terms of macro-level management, professional categories, disposal processes, etc. From the perspective of macro-level management, regulations included emergency management [22], organizational establishment [23], coordination mechanisms [24], etc. From the perspective of professional categories, regulations standardized the responses to nuclear accidents [25], infectious disease outbreaks [26], etc. From the perspective of disposal processes, regulations clearly guided emergency response plans [27], exercising [28], information reporting [29], etc. Another notable foundation is that the growth of resources including workforce and stockpile was 106.7% and 146.7%, respectively. Since 2003, intensive investments by governments have contributed to the improvements on the following aspects. First, funding for CDCs across different levels changed from balanced allocation to full fiscal funding after 2003. Total income governmental funding increased from 40.75% in 2002 to 63.3% in 2012 [30]. Second, CDCs’ staff were overall more educated. The percentage of staff with bachelor degree or higher increased from 12.7% in 2002 to 29.4% in 2012 [31]. Last, the total value of fixed assets of all CDCs increased from 0.42 billion CN¥ in 2002 to 12.9 billion CN¥ in 2012 [31]. Available research showed that the quantity and quality of emergency staff, governmental-funding level, and fixed assets played important roles in improving the implementation of CDCs’ capabilities in the PHEMS [15]. A firm leadership, a favorable mechanism and sufficient resources are the key elements of a well-developed PHPMS [32]. It is undeniable that the PHEMS’ achievements in the past decade are remarkable. China’s active and constructive contributions have been highly valued by the global community; for example, China’s response to H7N9 in 2013 was recognized as “exemplary” by the WHO [33]. The three leading guarantees of China could be referenced by developing and other underdeveloped countries. However, to cope with future challenges in global health security, the following aspects require strengthening. First, preventive governance is necessary. The recovery stage capabilities were the weakest, which is far from achieving the standard of full recovery including sustainability, resilience after crisis and feedback to preparation-stage. The prediction, communication, and social services during and after emergencies require improvement. Second, balanced development at different regions and levels is very important. County CDCs in the front lines [34] had the weakest capabilities. One possible reason was that the relevant policies including contingency plan, work specifications, and guidelines were not instructive and operable enough for county CDCs [35]. Another reason was an inequitable distribution of personnel in urban and rural areas [36]. Available data showed that compared with county CDCs, a greater number of personnel with degree higher than bachelor worked at provincial and municipal CDCs [37]. Additionally, the governmental funding per staff for county CDCs in 2012 was 0.1557 million CN¥, which was much lower than the funding at municipal and provincial CDCs (0.2593 and 0.5406 million CN¥, respectively) [38]. From the perspective of regional disparity, CDCs in Western region were the weakest. Reasons include that it had the poorest fiscal capacity to fund CDCs; a limited personnel size; and an inadequate stockpile in terms of working budget, timely reserves, and prompt delivery [39]. Third, the application of new technologies should keep pace with science and technology development. For example, the disease surveillance systems need to be integrated with the use of standard data formats and allow the public health community to respond more quickly to public health threats [40]. A Stockpile Management and Tracking System could also be designed and used to manage stockpiles across different levels and regions [41].

Limitations

The available assessment indicators are relatively narrower in comparison with those such as the Capability Assessment for Readiness and the Target Capabilities List of Homeland Security Exercise and Evaluation Program in the United States. Nearly half the indicators were binary (“yes” or “no”), so the quality of policy implementation and accountability could not be judged. Although logic judgments and audit procedures were conducted, recall bias may still exist. Despite these limitations, the main contribution of this paper are the findings based on the data from two rounds of national field surveys conducted in 2002 to 2012 in China. We believe that this contribution is theoretically and practically relevant because the lessons China’s government learned from the 2003 SARS outbreak provide an emergency response framework that can be employed by developing countries.

Conclusions

Since the 2003 SARS outbreak, China has built an effective PHEMS and achieved comprehensive progress and improvements at preparation, readiness, response, and recovery. Nevertheless, lacks of conceptual crisis management and preventive governance, disparities across regions and levels, and insufficient application of new technologies remain. Future priorities should be to develop the recovery stage, establish a closed-feedback loop between recovery and preparation stages, and strengthen capability-building CDCs in Western areas through increasing governmental funding and improving the quality of response personnel. The guarantees of leadership, regulations, and resources provide useful references for other developing countries.
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Review 9.  Promoting public health legal preparedness for emergencies: review of current trends and their relevance in light of the Ebola crisis.

Authors:  Odeya Cohen; Paula Feder-Bubis; Yaron Bar-Dayan; Bruria Adini
Journal:  Glob Health Action       Date:  2015-10-07       Impact factor: 2.640

Review 10.  China's distinctive engagement in global health.

Authors:  Peilong Liu; Yan Guo; Xu Qian; Shenglan Tang; Zhihui Li; Lincoln Chen
Journal:  Lancet       Date:  2014-08-30       Impact factor: 79.321

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  12 in total

Review 1.  Liver diseases in the Asia-Pacific region: a Lancet Gastroenterology & Hepatology Commission.

Authors:  Shiv K Sarin; Manoj Kumar; Mohammed Eslam; Jacob George; Mamun Al Mahtab; Sheikh M Fazle Akbar; Jidong Jia; Qiuju Tian; Rakesh Aggarwal; David H Muljono; Masao Omata; Yoshihiko Ooka; Kwang-Hyub Han; Hye Won Lee; Wasim Jafri; Amna S Butt; Chern H Chong; Seng G Lim; Raoh-Fang Pwu; Ding-Shinn Chen
Journal:  Lancet Gastroenterol Hepatol       Date:  2019-12-15

2.  Epidemiological characteristics and disease spectrum of emergency patients in two cities in China: Hong Kong and Shenzhen.

Authors:  Shao-Xi Chen; Karren Fan; Ling-Pong Leung
Journal:  World J Emerg Med       Date:  2020

3.  Comprehensive Risk Assessment of Schistosomiasis Epidemic Based on Precise Identification of Oncomelania hupensis Breeding Grounds-A Case Study of Dongting Lake Area.

Authors:  Jun Xu; Xiao Ouyang; Qingyun He; Guoen Wei
Journal:  Int J Environ Res Public Health       Date:  2021-02-17       Impact factor: 3.390

4.  The Impact of Transformational Leadership on Physicians' Performance in China: A Cross-Level Mediation Model.

Authors:  Haiyun Chu; Binbin Qiang; Jiawei Zhou; Xiaohui Qiu; Xiuxian Yang; Zhengxue Qiao; Xuejia Song; Erying Zhao; Depin Cao; Yanjie Yang
Journal:  Front Psychol       Date:  2021-03-09

5.  Nurses' core emergency competencies for COVID-19 in China: A cross-sectional study.

Authors:  Hongdan Li; Shuju Dong; Li He; Rui Wang; Shiyan Long; Fengming He; Huairong Tang; Ling Feng
Journal:  Int Nurs Rev       Date:  2021-05-27       Impact factor: 3.384

6.  Appraisal of China's Response to the Outbreak of COVID-19 in Comparison With SARS.

Authors:  Jiajia Li; Shixue Li; Wuchun Cao; Zhongli Wang; Zhuohui Liang; Wenhao Fu; Jinfeng Zhao
Journal:  Front Public Health       Date:  2021-07-07

7.  Archetype analysis of older adult immunization decision-making and implementation in 34 countries.

Authors:  Lois Privor-Dumm; Prarthana Vasudevan; Kana Kobayashi; Jaya Gupta
Journal:  Vaccine       Date:  2020-04-16       Impact factor: 3.641

8.  Measuring inequalities in the public health workforce at county-level Centers for Disease Control and Prevention in China.

Authors:  Weiqin Cai; Chengyue Li; Mei Sun; Mo Hao
Journal:  Int J Equity Health       Date:  2019-11-21

Review 9.  The public health response to the COVID-19 outbreak in mainland China: a narrative review.

Authors:  Mark Zanin; Cheng Xiao; Tingting Liang; Shiman Ling; Fengming Zhao; Zhenting Huang; Fangmei Lin; Xia Lin; Zhanpeng Jiang; Sook-San Wong
Journal:  J Thorac Dis       Date:  2020-08       Impact factor: 3.005

10.  A comparative study of international and Chinese public health emergency management from the perspective of knowledge domains mapping.

Authors:  Juan Li; Yuhang Zhu; Jianing Feng; Weijing Meng; Kseniia Begma; Gaopei Zhu; Xiaoxuan Wang; Di Wu; Fuyan Shi; Suzhen Wang
Journal:  Environ Health Prev Med       Date:  2020-10-02       Impact factor: 3.674

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