Current Status and Hospital-Level Differences in Care and Outcomes of Patients With Acute Non-ST-Segment Elevation Myocardial Infarction in China: Insights From China Acute Myocardial Infarction Registry

BackgroundWith the growing burden of non-ST-elevation myocardial infarction (NSTEMI), developing countries face great challenges in providing equitable treatment nationwide. However, little is known about hospital-level disparities in the quality of NSTEMI care in China. We aimed to investigate the variations in NSTEMI care and patient outcomes across the three hospital levels (province-, prefecture- and county-level, with decreasing scale) in China.MethodsData were derived from the China Acute Myocardial Infarction Registry on patients with NSTEMI consecutively registered between January 2013 and November 2016 from 31 provinces and municipalities throughout mainland China. Patients were categorized according to the hospital level they were admitted to. Multilevel generalized mixed models were fitted to examine the relationship between the hospital level and in-hospital mortality risk.ResultsIn total, 8,054 patients with NSTEMI were included (province-level: 1,698 patients; prefecture-level: 5,240 patients; county-level: 1,116 patients). Patients in the prefecture- and county-level hospitals were older, more likely to be female, and presented worse cardiac function than those in the province-level hospitals (P <0.05). Compared with the province-level hospitals, the rate of invasive strategies was significantly lower in the prefecture- and county-level hospitals (65.3, 43.3, and 15.4%, respectively, P <0.001). Invasive strategies were performed within the guideline-recommended timeframe in 25.4, 9.7, and 1.7% of very-high-risk patients, and 16.4, 7.4, and 2.4% of high-risk patients in province-, prefecture- and county-level hospitals, respectively (both P <0.001). The use of dual antiplatelet therapy in the county-level hospitals (87.2%) remained inadequate compared to the province- (94.5%, P <0.001) and prefecture-level hospitals (94.5%, P <0.001). There was an incremental trend of in-hospital mortality from province- to prefecture- to county-level hospitals (3.0, 4.4, and 6.9%, respectively, P-trend <0.001). After stepwise adjustment for patient characteristics, presentation, hospital facilities and in-hospital treatments, the hospital-level gap in mortality risk gradually narrowed and lost statistical significance in the fully adjusted model [Odds ratio: province-level vs. prefecture-level: 1.23 (0.73–2.05), P = 0.441; province-level vs. county-level: 1.61 (0.80–3.26), P = 0.182; P-trend = 0.246].ConclusionsThere were significant variations in NSTEMI presentation and treatment patterns across the three hospital levels in China, which may largely explain the hospital-level disparity in in-hospital mortality. Quality improvement initiatives are warranted, especially among lower-level hospitals.

Spatiotemporal Cluster Patterns of Hand, Foot, and Mouth Disease at the Province level in Mainland China, 2009-2018

BackgroundAlthough three monovalent EV-A71 vaccines have been launched in mainland China since 2016, hand, foot, and mouth disease (HFMD) still causes a considerable disease burden in China. Vaccines’ use may change the epidemiological characters of HFMD. This study aims to analyze the spatiotemporal cluster of HFMD at the province level in mainland China from 2009 to 2018 and compare the difference before and after the vaccines were launched. MethodsAll HFMD cases’ data from January 2009 to December 2018 were obtained from the public health science data center given by the Chinese Center for Diseases Control and Prevention. Spatial autocorrelation analysis and space-time scan statistics analysis were used to explore the spatiotemporal distribution pattern of this disease at the provincial level in mainland China. ResultsThe median annual incidence of HFMD was 143.22 per 100,000 (ranging from 87.01 to 205.06) in mainland China from 2009 to 2018. Two peaks of infections were observed per year. Children 5 years and under were the main morbid population. The global autocorrelation analysis showed that the spatial distribution of HFMD was presented a significant clustering pattern in each year (P<0.001), and the local autocorrelation analysis indicated that the high incidence areas were clustered in the southern and southeastern coastal provinces. The distribution of HFMD cases was clustered in time and space. The range of cluster time was between April and October. The most likely cluster appeared in the southern coastal provinces (Guangxi, Guangdong, Hainan) from 2010 to 2017 and in the southeastern coastal provinces (Shanghai, Jiangsu, Zhejiang) in 2018. ConclusionChanges in the spatiotemporal cluster of HFMD after the launch of EV-A71 vaccines were observed at the province level in mainland China in 2018. It is necessary to advance the EV-A71 vaccination plan, analyze the spatial-temporal distribution characteristics of different enterovirus pathogens of HFMD, and promote HFMD multivalent vaccines.

The use of Cohort Size Shrinkage Index (CSSI) to quantify regional famine intensity during the Chinese famine of 1959-61

There has been a growing interest in studying the causes and impact of the Great Chinese Famine of 1959-61. The Cohort Size Shrinkage Index (CSSI) is the most widely used measure to examine famine intensity and was used in at least 28 Chinese famine studies to date. We examined the potential impact of violations of three requirements for a valid CSSI measure: reliable information on cohort size by year of birth; a stable trend of cohort size by year of birth; and the absence of significant regional migration. We used data from the 1% China 2000 Census to examine the trend of cohort size over time and concentrated on the time window between 1950-70 to exclude policies and events with a large impact on birth trends other than the famine itself. Across China we established a significant difference in cohort size trends between pre-famine births and post-famine births, violating one of the main requirements for a valid CSSI measure. This leads to systematic differences in CSSI depending on what non-famine years are selected for comparison. At the province level, CSSIs estimated based on pre- & post-famine births tend to overestimate famine intensity at higher exposure levels and underestimate intensity at lower levels compared to CSSIs based on pre-famine births alone. This is problematic and demonstrates that the CSSI is not as robust an estimator of famine intensity as had been assumed previously. We recommend therefore that all CSSI should be based on pre-famine birth trends. Using data from Sichuan province, we demonstrate a less pronounced dose-response relation between famine intensity and tuberculosis outcomes using pre-famine based CSSI as compared to reported patterns based on pre- & post-famine based CSSI. We encourage researchers to re-examine their results of Chinese famine studies as local differences in cohort size of pre-famine and post-famine births may lead to significant discrepancies of CSSI estimation and change the interpretation of their findings.

Government disclosure in influencing people’s behaviors during a public health emergency

We shed light on the importance of government disclosure in public emergency management. During the outbreak of COVID-19, provinces in China entered a government disclosure regime, which mandated the disclosure of the number of people infected with the virus on a daily basis. Each province also voluntarily disclosed its own virus situation. We find that various forms of province-level government disclosure generally reduced the number of trips made by the infected and sped up their diagnosis. They also raised attention paid to the virus and self-protection awareness as well as reduced mobility among the susceptible. Finally, government voluntary disclosure helped to reduce the duration of local epidemics. We conclude that government disclosure can be effective in instilling the correct human behaviors that are conducive to fighting the pandemic.

Beyond personal factors: Multilevel determinants of childhood stunting in Indonesia

Background Stunting is still a major public health problem in low- and middle-income countries, including Indonesia. Previous studies have reported the complexities associated with understanding the determinants of stunting. This study aimed to examine the household-, subdistrict- and province-level determinants of stunting in Indonesia using a multilevel hierarchical mixed effects model. Methods We analyzed data for 8045 children taken from the 2007 and 2014 waves of the Indonesian Family and Life Surveys (IFLS). We included individual-, family-/household- and community-level variables in the analyses. A multilevel mixed effects model was employed to take into account the hierarchical structure of the data. Moreover, the model captured the effect of unobserved household-, subdistrict- and province-level characteristics on the probability of children being stunted. Results Our findings showed that the odds of childhood stunting vary significantly not only by individual child- and household-level characteristics but also by province- and subdistrict-level characteristics. Among the child-level covariates included in our model, dietary habits, neonatal weight, a history of infection, and sex significantly affected the risk of stunting. Household wealth status and parental education are significant household-level covariates associated with a higher risk of stunting. Finally, the risk of stunting is higher for children living in communities without access to water, sanitation and hygiene. Conclusions Stunting is associated with not only child-level characteristics but also family- and community-level characteristics. Hence, interventions to reduce stunting should also take into account family and community characteristics to achieve effective outcomes.

Decreasing methane emissions from China's coal mining with rebounded coal production

China is the world’s largest anthropogenic methane (CH4) emitter, with coal mine methane (CMM) as one of the main contributors. However, previous studies have not reach consensus on the magnitude and trend of China’s CMM emissions since 2010. Through distribution fitting and Monte Carlo methods, dynamic emission factors (EFs) of CMM at the province-level were derived with high confidence; along with the updated data on surface mining, abandoned coal mines, and methane utilization, we revealed that China’s annual CMM emissions were estimated at 20.11 Tg between 2010 and 2019 with a decline of 0.93 Tg yr-1. Although coal production was revived in 2017, we found that the growing trend of China’s CMM emissions since 2012 were curbed by the previously-overlooked factors including the growth of CMM utilization and coal production from surface mining, and decrease of emission factors driven by the closure of high CH4-content coal mines and a regional production shift to lower-emission areas.

Effects of mobility restrictions during COVID19 in Italy

To reduce the spread and the effect of the COVID-19 global pandemic, non-pharmaceutical interventions have been adopted on multiple occasions by governments. In particular lockdown policies, i.e., generalized mobility restrictions, have been employed to fight the first wave of the pandemic. We analyze data reflecting mobility levels over time in Italy before, during and after the national lockdown, in order to assess some direct and indirect effects. By applying methodologies based on percolation and network science approaches, we find that the typical network characteristics, while very revealing, do not tell the whole story. In particular, the Italian mobility network during lockdown has been damaged much more than node- and edge-level metrics indicate. Additionally, many of the main Provinces of Italy are affected by the lockdown in a surprisingly similar fashion, despite their geographical and economic dissimilarity. Based on our findings we offer an approach to estimate unavailable high-resolution economic dimensions, such as real time Province-level GDP, based on easily measurable mobility information.

The existing and expectations of BPP capacity in the strategic command for agricultural development program

The focus program of the Ministry of Agriculture in 2019-2020 is the strategic command for agricultural development (KOSTRATANI), stated in the Minister of Agriculture No./Kpts/OT.050/I/02/2020. The expectations and targets to be achieved from BPP as KOSTRATANI are (1) data and information; (2) the agricultural development; (3) learning; (4) agribusiness consulting; and (5) partnership networks. To meet the expectation, research to know the capacity of BPP should be done. This paper presents information on the capacity of BPP (human resources, infrastructure and management). The research was conducted in Central Java Province, focused on BPP in Grobogan District, especially BPP in Pulokulon and Tegowanu Subdistrict. The research was done through a survey during March 2021, the data and information were collected based on group discussion and individual interview with total respondents of 31, then analyzed descriptively. Found that the human resources capacity at province level were only supported by 16% of extension officer. At subdistrict level, an extension officer responsible for 3-4 villages while at Tegowanu 4-5 villages.The infrastructure of Pulokulon was worse than Tegalwanu and Both BPP have some program out side the main responsibility as BPP. Concluded that KOSTRATANI should not be implemented in all BPPs simultaneously. The Ministry of Agriculture would decide which certain BPP is considered the appropriate mode for implementing KOSTRATANI. Therefore, suggested that further research on the capacity of more BPP with more samples with special characteristics such as agroecosystem and main commodity should be conducted.

Detailed reconstruction of the Iranian COVID-19 epidemic reveals high attack rates of SARS-CoV-2 in several provinces

Since the first cases of COVID-19 were reported in Qom, Iran, almost 19 months ago, the transmission dynamics across the country and the health burden of COVID-19 has remained largely unknown due to the scarcity of epidemiological analyses and lack of provincial data on the number of COVID-19 cases and deaths. For the first time, we reconstruct the epidemic trajectory across the country and assess the level of under-reporting in infections and deaths using province-level age-stratified weekly all-cause mortality data. Our estimates suggest that as of 2021-09-17, only 48% (95% confidence interval 43-55%) of COVID-19 deaths in Iran have been reported. We find that in the most affected provinces such as Qazvin, Qom, and East Azerbaijan approximately 0.4% of the population have died of COVID-19 so far. We also find significant heterogeneity in the estimated attack rates across the country with 11 provinces reaching close to or higher than 100% attack rates. Despite a relatively young age structure in Iran, our analysis reveals that the infection fatality rate gradually increased over time in several provinces and reached levels that are comparable some of the high-income countries with a larger percentage of older adults, suggesting that limited access to medical services, coupled with undercounting of COVID-19-related deaths, can have a significant impact on COVID-19 fatalities. These results also show that despite several waves of infection and high attack rates in many provinces with largely unmitigated epidemics, herd immunity through natural infection has not been achieved.