For providing evidences for further modification of China Infectious Diseases Automated-alert and Response System (CIDARS) by comparing the early-warning performance of the temporal model and temporal-spatial model in CIDARS.The application performance for outbreak detection of temporal model and temporal-spatial model simultaneously running among 208 pilot counties in 20 provinces from 2011 to 2013 was compared; the 16 infectious diseases were divided into two classes according to the disease incidence level; cases data in nationwide Notifiable Infectious Diseases Reporting Information System was combined with outbreaks reported to Public Health Emergency Reporting System, by adopting the index of the number of signals, sensitivity, false alarm rate and time for detection.The overall sensitivity of temporal model and temporal-spatial model for 16 diseases was 96.23% (153/159) and 90.57% (144/159) respectively, without significant difference (Z = -1.604, P = 0.109), and the false alarm rate of temporal model (1.57%, 57 068/3 643 279) was significantly higher than that of temporal-spatial model (0.64%, 23 341/3 643 279) (Z = -3.408, P = 0.001), while the median time for detection of these two models was not significantly different, which was 3.0 days and 1.0 day respectively (Z = -1.334, P = 0.182).For 6 diseases of type I which represent the lower incidence, including epidemic hemorrhagic fever,Japanese encephalitis, dengue, meningococcal meningitis, typhus, leptospirosis, the sensitivity was 100% for both models (8/8, 8/8), and the false alarm rate of both temporal model and temporal-spatial model was 0.07% (954/1 367 437, 900/1 367 437), with the median time for detection being 2.5 days and 3.0 days respectively. The number of signals generated by temporal-spatial model was reduced by 2.29% compared with that of temporal model.For 10 diseases of type II which represent the higher incidence, including mumps, dysentery, scarlet fever, influenza, rubella, hepatitis E, acute hemorrhagic conjunctivitis, hepatitis A, typhoid and paratyphoid, and other infectious diarrhea, the sensitivity of temporal model was 96.03% (145/151), and the sensitivity of temporal-spatial model was 90.07% (136/151), the number of signals generated by temporal-spatial model was reduced by 59.36% compared with that of temporal model. Compared to temporal model, temporal-spatial model reduced both the number of signals and the false alarm rate of all the type II diseases;and the median of outbreak detection time of temporal model and temporal-spatial model was 3.0 days and 1.0 day, respectively.Overall, the temporal-spatial model had better outbreak detection performance, but the performance of two different models varies for infectious diseases with different incidence levels, and the adjustment and optimization of the temporal model and temporal-spatial model should be conducted according to specific infectious disease in CIDARS.
Abstract Background This study aimed to assess the long-term effects of size-specific particulate matter (PM) on frailty transitions in middle-aged and older Chinese adults. Methods We included 13 910 participants ≥45 y of age from the China Health and Retirement Longitudinal Study (CHARLS) for 2015 and 2018 who were classified into three categories in 2015 according to their frailty states: robust, prefrail and frail. Air quality data were obtained from the National Urban Air Quality Real-time Publishing Platform. A two-level logistic regression model was used to examine the association between concentrations of PM and frailty transitions. Results At baseline, the total number of robust, prefrail and frail participants were 7516 (54.0%), 4324 (31.1%) and 2070 (14.9%), respectively. Significant associations were found between PM concentrations and frailty transitions. For each 10 μg/m3 increase in the 3-y averaged 2.5-μm PM (PM2.5) concentrations, the risk of worsening in frailty increased in robust (odds ratio [OR] 1.06 [95% confidence interval {CI} 1.01 to 1.12]) and prefrail (OR 1.07 [95% CI 1.01 to 1.13]) participants, while the probability of improvement in frailty in prefrail (OR 0.91 [95% CI 0.84 to 0.98]) participants decreased. In addition, the associations of PM10 and coarse fraction of PM with frailty transitions showed similar patterns. Conclusions Long-term exposure to PM was associated with higher risks of worsening and lower risks of improvement in frailty among middle-aged and older adults in China.
Abstract During the formulation of employment disability policy, policymakers are often interested in regional variations of disability employment. Decision‐makers are required to distinguish between various geographical factors. However, few previous studies take spatial heterogeneity into account and most of them conducted only a qualitative analysis. Geographical detectors based on spatial variation analyses of identified factors were applied in the study to establish connections between regional features and the disability employment rate, and to identify the city groups with significantly higher and lower percentage rates of disability employment. It is the first application of spatial statistics in studying the employment problem of the disabled. The findings can help the government formulate reasonable adjustments to both job opportunities for, and work roles of, disabled people.
Mapping population distribution is an important field of geographical and related research because of the frequent need to combine spatial data representing socio‐demographic information across various incompatible spatial units. However, the research may become very complex and difficult when a population in multiple places is estimated by various factors. Previous efforts in the field have contributed to the selection of appropriate independent variables and the creation of different population models. However, the level of accuracy obtainable with these studies is limited by the spatial heterogeneity of population distribution within the individual census districts, particularly in large rural areas. A high‐accuracy modelling method for population estimation based on integration of Genetic Programming (GP) and Genetic Algorithms (GA) with Geographic Information Systems (GIS) is presented in this paper. GIS was applied to identify and quantify a set of natural and socioeconomic factors which contributed to population distribution, and then GP and GA were used to build and optimise the population model to automatically transform census population data to regular grids. The study indicated that the proposed method performed much better than the stepwise regression analysis and adapted gravity model methods in estimating the population of both urban and rural areas. More importantly, this proposed method could provide a single, unified approach to mapping population distribution in various areas because the paradigms of these algorithms are general.
Background Over the past two decades, major epidemics of hand, foot, and mouth disease (HFMD) have occurred throughout most of the West-Pacific Region countries, causing thousands of deaths among children. However, few studies have examined potential determinants of the incidence of HFMD. Methods Reported HFMD cases from 2912 counties in China were obtained for May 2008. The monthly HFMD cumulative incidence was calculated for children aged 9 years and younger. Child population density (CPD) and six climate factors (average-temperature [AT], average-minimum-temperature [ATmin], average-maximum-temperature [ATmax], average-temperature-difference [ATdiff], average-relative-humidity [ARH], and monthly precipitation [MP]) were selected as potential explanatory variables for the study. Geographically weighted regression (GWR) models were used to explore the associations between the selected factors and HFMD incidence at county level. Results There were 176,111 HFMD cases reported in the studied counties. The adjusted monthly cumulative incidence by county ranged from 0.26 cases per 100,000 children to 2549.00 per 100,000 children. For local univariate GWR models, the percentage of counties with statistical significance (p<0.05) between HFMD incidence and each of the seven factors were: CPD 84.3%, ATmax 54.9%, AT 57.8%, ATmin 61.2%, ARH 54.4%, MP 50.3%, and ATdiff 51.6%. The R2 for the seven factors' univariate GWR models are CPD 0.56, ATmax 0.53, AT 0.52, MP 0.51, ATmin 0.52, ARH 0.51, and ATdiff 0.51, respectively. CPD, MP, AT, ARH and ATdiff were further included in the multivariate GWR model, with R2 0.62, and all counties show statistically significant relationship. Conclusion Child population density and climate factors are potential determinants of the HFMD incidence in most areas in China. The strength and direction of association between these factors and the incidence of HFDM is spatially heterogeneous at the local geographic level, and child population density has a greater influence on the incidence of HFMD than the climate factors.
High-accuracy spatial distribution estimation is crucial for cancer prevention and control. Due to their complicated pathogenic factors, the distributions of many cancers' mortalities appear blocky, and spatial heterogeneity is common. However, most of the commonly used cancer mapping methods are based on spatial autocorrelation theory. Sandwich estimation is a new method based on spatial heterogeneity theory. A modified sandwich estimation method suitable for the estimation of cancer mortality distribution is proposed in this study. The variances of cancer mortality data are used to fuse sandwich estimation results from various auxiliary variables, the feasibility of which in estimating cancer mortality distributions is explained theoretically. The breast cancer (BC) mortality of the Chinese mainland in 2005 was taken as a case, and the accuracy of the modified sandwich estimation method was compared with that of the Hierarchical Bayesian (HB), the Co-Kriging (CK) and the Ordinary Kriging (OK) methods. The accuracy of the modified sandwich estimation method was better than the HB, the CK and the OK methods, and the estimation result from the modified sandwich estimation method was more likely to be acceptable. Therefore, this study represents an attempt to apply the sandwich estimation method to the estimation of cancer mortality distributions with strong spatial heterogeneity, which holds great potential for further application.
Neural tube defects (NTDs) are congenital birth defects of the central nervous system that affect 0.5-2 per 1000 pregnancies worldwide. Therefore effective interventions for birth defects, especially NTDs, are very important.Yuanping City is a coal mining city in Shanxi Province, China, with a high incidence of NTDs. This study evaluates the effects of NTD interventions in this city after adjusting for covariates that characterize the native environment. The number of NTD cases and births for the 18 towns in Yuanping City from 2007 to 2014 were included in the study. A shared-component zero-inflated Poisson regression was applied to analyse the temporal-spatial variance among the incidence rates of NTDs in Yuanping City before and after the interventions.The results showed that existing interventions to mitigate birth defects, such as folic acid supplementation, reduced the incidence of NTDs by 53.5% in coal mining areas in Yuanping City. However, the NTD risk in areas near coal mines, especially unrestored coal mines, was still high, even after the intervention.The government should focus on health hazards related to mining and agricultural production and should provide education and resources to reduce environmental exposure. Reducing environmental risks should be regarded as an early intervention strategy to mitigate birth defects.
Abstract Since the disclosure of the “Illegal vaccine operation series case in Jinan, Shandong” in March, 2016, this issue has attracted a great deal of attention and has led to public concerns about the safety and efficacy of the vaccines involved in this case. The main purpose of this paper is to scientifically and scrupulously predict the possible geographic distribution of illegal vaccines in China, and provide a foundation to guide future governmental policies and actions. A species distribution model was used because of the advantages of using presence/pseudo-absence or presence-only data, and it performs well with incomplete species distribution data. A series of socioeconomic variables were used to simulate habitat suitability distribution. Maxent (Maximum Entropy Model) and GARP (Genetic Algorithm for Rule set Production) were used to predict the risks of illegal vaccines in China, and define the spatial distribution and significant factors of the area at risk from illegal vaccines. Jackknife tests were used to evaluate the relative importance of socioeconomic variables. It was found that: (1) Shandong, Hebei, Henan, Jiangsu and Anhui are the main high-risk areas impacted by the vaccines involved in Jinan case. (2) Population density and industrial structure are the main socioeconomic factors affecting areas which may be at risk from illegal vaccines.
Background: Optimizing the timing of influenza vaccination based on regional temporal seasonal influenza illness patterns may make seasonal influenza vaccination more effective in China. Methods: We obtained provincial weekly influenza surveillance data for 30 of 31 provinces in mainland China from the Chinese Center for Disease Control and Prevention for the years 2010-2018. Influenza epidemiological regions were constructed by clustering analysis. For each region, we calculated onset date, end date, and duration of seasonal influenza epidemics by the modified mean threshold method. To help identify initial vaccination target populations, we acquired weekly influenza surveillance data for four age groups (0-4, 5-18, 19-59, ≥60 years) in each region and in 171 cities of wide-ranging size. We used linear regression analyses to explore the association of epidemic onset dates by age group, city, and epidemiological region and provide evidence for initial target populations for seasonal influenza vaccination. Findings: We determined that northern, mid, southwestern, southeast regions of mainland China have distinct seasonal influenza epidemic patterns. We found significant regional, temporal, and spatial heterogeneity of seasonal influenza epidemics. There were significant differences by age group and city size in the interval between epidemic onset in the city or age group and regional spread (epidemic lead time), with longer epidemic lead times for 5-18-year-old children and larger cities. Interpretation: Knowledge of influenza epidemic characteristics may help optimize local influenza vaccination timing and identify initial target groups for seasonal influenza vaccination in mainland China. Similar analyses may help inform seasonal influenza vaccination strategies in other regions and countries.Funding: National Natural Science Foundation of China (Grant No: 42171419 and 91846302)Declaration of Interest: None to declare.
Using (2.712±0.014)×109ψ(2S) events collected with the BESIII detector operating at the BEPCII, we search for the ηc(2S)→K+K−η′ decay. Its decay branching fraction is measured to be (11.11±4.67(stat)±1.82(syst)±4.24(extr))×10−4, where the first uncertainty is statistical, the second is systematic, and the third uncertainty is from the branching fraction of the ψ(2S)→γηc(2S) decay. The statistical significance is 2.8σ. The upper limit on the product branching fraction B[ψ(2S)→γηc(2S)]×B[ηc(2S)→K+K−η′] is set to be 0.94×10−6 at 90% confidence level. In addition, the branching fractions of χc1→K+K−η′ and χc2→K+K−η′ are updated to be (8.48±0.10(stat)±0.47(syst))×10−4 and (1.53±0.04(stat)±0.08(syst))×10−4, respectively. The precision is improved by twofold. Published by the American Physical Society 2025
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