Anterior peri-sacroiliac joint osteotomy in the treatment of malunion and nonunion of complex pelvic ring fracture: techniques and preliminary results.

PURPOSE: To introduce anterior peri-sacroiliac joint osteotomy (APSJO) through the lateral-rectus approach (LRA) for treating pelvic fracture malunion and nonunion, and to evaluate the safety, feasibility, and potential effectiveness. METHODS: Data of 15 patients with pelvic fracture malunion and nonunion who underwent treatment by APSJO were selected and analyzed. The reduction quality was assessed using the Mears and Velyvis criteria, while the pre-operative and post-operative function was revealed by the Majeed scoring system. The British Medical Research Council (BMRC) grading system was recruited for the evaluation of lumbosacral plexus function. RESULTS: The average operative duration was 264.00 ± 86.75 min, while the intra-operative blood loss was 2000 (600, 3000) mL. Anatomical reduction was complete in three cases, satisfactory in ten cases, and unsatisfactory in two cases. Among the seven patients with lumbosacral plexus injury, the pre-operative Majeed grades were good in two cases, fair in two cases, and poor in three cases, while the post-operative Majeed grades were excellent in three cases, good in three cases, and fair in one case. Muscle strength recovered to M5 in two cases, M4 in three cases, and showed no recovery in two cases. The pre-operative Majeed grades were good in five cases, fair in two cases, and poor in one case of the series without lumbosacral plexus injury, while the post-operative Majeed grades were excellent in seven cases and good in one case. CONCLUSION: APSJO through LRA may be a feasible strategy for treating pelvic fracture malunion and nonunion with promising application.

Simulation of average monthly ozone exposure concentrations in China: A temporal and spatial estimation method.

BACKGROUND: Ozone has adverse effects on human health, it is necessary to obtain the refined ozone exposure concentration. At present, most of existing ozone exposure research is based on ground air quality monitoring station (MS) which gather urban area information only. It is diffcult to estimate the ozone in the areas where MSs are scarce. OBJECTIVE: By combining accurate but uneven data of outdoor ozone exposure concentrations based on MSs and unbiased coverage data based on RS in China, we can improve the accuracy of simulation of average monthly ozone exposure concentrations in monitor-free area. Since ozone concentrations are usually low at night, ozone exposure is assessed during the day (e.g., 10:00-18:00). METHODS: We proposed a space-time geostatistical kriging interpolation based on the composite space/time mean trend model (CSTM) to predict ozone exposure in mainland China, having obtained a refined ozone exposure concentration interpolation map from an MS. We verified the accuracy of the interpolation results and remote sensing (RS) data, while simultaneously determining the distance threshold (according to the data accuracy) to improve the accuracy of the hybrid map. RESULTS: We used a refined smoothing filter to reduce the influence of spatial and seasonal trends on ozone concentration. We found a cutoff separation distance of 175 km at which the two data showed an equal estimation accuracy, and the estimation result was fused with RS data through the distance threshold. Finally, The multi-source data with the best accuracy were fused to obtain the refined map. In China, ozone exposure concentration mainly gathers in the northern and eastern regions as well as part of the central mainland. CONCLUSIONS: RS data can be used to characterize ground ozone exposure concentrations when 24th-layer data and MS data for monitoring ozone exposure concentrations are combined to estimate temporal and spatial ozone exposure in China. Ozone exposure in China can be explored further to provide suggestions for human health and regional economic development.

Pollution zone identification research during ozone pollution processes.

Identifying an ozone pollution zone during the pollution processes is significant for ozone pollution management and environmental health risk assessment. However, few studies have focused on ozone pollution zone identification during pollution processes. A spatial-temporal clustering framework for identifying pollution zones during ozone pollution processes was initially proposed in this study, and an ozone pollution process in China in May 2017 was selected as a case. The results showed that the framework can help selecting one more accurate method to identify the pollution zone according to the pollution characteristics of air pollution process. In addition, different ozone pollution zone identification methods work well in different scenarios: The self-organizing map (SOM) method was suitable for identifying the zone with the duration of pollution between 24 and 48 h, the image fusion based on wavelet transform (IFbWT) method for the zone with the duration of pollution over 48 h and the Apriori method for the zone with obvious boundaries between high-value and low-value ozone concentrations. The proposed procedure can also be applied to identify the pollution zone of the pollution process of other pollutants.

Trends in geographical disparities for cervical cancer mortality in China from 1973 to 2013: a subnational spatio-temporal study.

OBJECTIVE: This study was designed to explore the time trends in geographical variations of cervical cancer mortality in mainland China over the period 1973 to 2013, to provide subnational spatio-temporal patterns for targeted promotion of human papillomavirus vaccine in China. METHODS: Data were extracted from three national retrospective death surveys and cancer registry. The rate ratio (RR) was estimated for the aggregated data for seven geographical regions using generalized linear models to evaluate time trends in geographical disparities of cervical cancer mortality. RESULTS: There was a significant decrease in cervical cancer mortality in China from 1973-1975 to 2004-2005, but leveled off thereafter to 2011-2013. Compared to the period 1973-1975 the RR for the three last time periods were 0.33 [95% confidence interval (95% CI): 0.30-0.37] for 1990-1992, 0.21 (95% CI: 0.19-0.24) for 2004-2005 and 0.24 (95% CI: 0.22-0.26) for 2011-2013. Females living in the Northwest China and Central China have a high risk of mortality from cervical cancer compared to the nationwide, with the RR being 2.09 (95% CI: 1.83-2.38) and 1.26 (95% CI: 1.11-1.44) respectively, while the RRs for South China, Northeast China and Southwest China were below 1.00, indicating the lower death risk. Despite the mortality rate had increased slightly from 2004 to 2013, there was an encouraging sign that the geographical disparities in cervical cancer mortality had gradually narrowed over time across China. CONCLUSIONS: Although cervical cancer mortality in China has reduced to very low levels, the high risk of cervical cancer in Northwest China and Central China is still noteworthy. Public health policies including the promotion of vaccine should be targeted to further reduction of geographical disparities in cervical cancer mortality.

Current recommendations on managing tuberculosis patients with diabetes & its epidemiology.

BACKGROUND & OBJECTIVE: Tuberculosis (TB) & Diabetes Mellitus (DM) are common diseases globally & both are mutually on rising trend, and co-existing together. To analyze the effect of TB on diabetes by causing hyperglycemia and causing impaired glucose tolerance. Impaired glucose tolerance that is one of the major risk factor for developing diabetes. STUDY DESIGN: Literature study regarding co-association of TB & DM with its complications and management through published articles. The drugs used to treat tuberculosis especially rifampicin and isoniazid interacts with oral anti-diabetic drugs and can lead to suboptimal glycemic control. Therefore the interaction of diabetes and tuberculosis is at multiple levels exacerbating each other. DM is also well recognized as an independent risk factor for lower respiratory tract infection. Infection with, staphylococcus aureus, gram negative bacteria, and fungi occur more frequently in diabetics. RESULT & CONCLUSION: The prevalence of diabetes globally is projected to rise from the current estimate of 150 million to 200 million in 2010 and to 300 million (5.4%) in 2025. The potential for increase in the number of cases of diabetes is greatest in Asia. It is an emerging public health problem leading in an associated significant proportion. This article reviews the association between diabetes and tuberculosis and suggests appropriate management for these conditions.

Spatial distribution estimation of malaria in northern China and its scenarios in 2020, 2030, 2040 and 2050.

BACKGROUND: Malaria is one of the most severe parasitic diseases in the world. Spatial distribution estimation of malaria and its future scenarios are important issues for malaria control and elimination. Furthermore, sophisticated nonlinear relationships for prediction between malaria incidence and potential variables have not been well constructed in previous research. This study aims to estimate these nonlinear relationships and predict future malaria scenarios in northern China. METHODS: Nonlinear relationships between malaria incidence and predictor variables were constructed using a genetic programming (GP) method, to predict the spatial distributions of malaria under climate change scenarios. For this, the examples of monthly average malaria incidence were used in each county of northern China from 2004 to 2010. Among the five variables at county level, precipitation rate and temperature are used for projections, while elevation, water density index, and gross domestic product are held at their present-day values. RESULTS: Average malaria incidence was 0.107 ‰ per annum in northern China, with incidence characteristics in significant spatial clustering. A GP-based model fit the relationships with average relative error (ARE) = 8.127 % for training data (R(2) = 0.825) and 17.102 % for test data (R(2) = 0.532). The fitness of GP results are significantly improved compared with those by generalized additive models (GAM) and linear regressions. With the future precipitation rate and temperature conditions in Special Report on Emission Scenarios (SRES) family B1, A1B and A2 scenarios, spatial distributions and changes in malaria incidences in 2020, 2030, 2040 and 2050 were predicted and mapped. CONCLUSIONS: The GP method increases the precision of predicting the spatial distribution of malaria incidence. With the assumption of varied precipitation rate and temperature, and other variables controlled, the relationships between incidence and the varied variables appear sophisticated nonlinearity and spatially differentiation. Using the future fluctuated precipitation and the increased temperature, median malaria incidence in 2020, 2030, 2040 and 2050 would significantly increase that it might increase 19 to 29 % in 2020, but currently China is in the malaria elimination phase, indicating that the effective strategies and actions had been taken. While the mean incidences will not increase even reduce due to the incidence reduction in high-risk regions but the simultaneous expansion of the high-risk areas.

A study of spatiotemporal delay in hand, foot and mouth disease in response to weather variations based on SVD: a case study in Shandong Province, China.

BACKGROUND: A large number of hand, foot and mouth disease (HFMD) outbreaks was reported during 2008 in China. However, little is known about the effects of meteorological conditions on different temporal and spatial scales on HFMD incidence in children. The aim of this study was to explore the relationship between meteorological data on various temporal and spatial scales and HFMD incidence among children in Shandong Province, China. METHODS: The association between weekly HFMD cases and meteorological data on different temporal and spatial scales in Shandong Province from May 2008 to July 2008 and September 2008 to October 2008 was analyzed, using buffer analysis and the singular value decomposition method. RESULTS: Wind speed within a 50-km buffer circle of counties in Shandong Province with two-week lag and RH within a 10-km buffer circle of counties with eight-week lag were significantly associated with HFMD incidence. We found a positive correlation between wind speed within the 50-km buffer circle in the prior two weeks and wind speed within the province in the prior one week. CONCLUSIONS: This study revealed strong associations between HFMD incidence in children and wind speed and RH. Thus, meteorological anomalies in the prior two or eight weeks could be used as a valid tool for detecting anomalies during the peak periods of infectious disease.

[Comparing the performance of temporal model and temporal-spatial model for outbreak detection in China Infectious Diseases Automated-alert and Response System, 2011-2013, China].

OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

A New Integrated Interpolation Method for High Missing Unstable Disease Surveillance Data - 12 Urban Agglomerations, China, 2009-2020.

Introduction: The prevalence of unstable and incomplete monitoring data significantly complicates syndromic analysis. Many data interpolation methods currently available demonstrate inadequate effectiveness in overcoming this issue. Methods: To improve the accuracy of interpolation, we propose the integration of the SHapley Additive exPlanation model (SHAP) with the structural equation model (SEM), forming a combined SHAP-SEM approach. A case study is then performed to assess the enhanced performance of this novel model compared to traditional methods. Results: The SHAP-SEM model was utilized to develop an interpolation model employing data from the Chinese respiratory syndrome surveillance database. We executed three distinct experiments to establish the model datasets, comprising a total of 100 replicates. The performance of the model was evaluated using the root mean square error (RMSE), correlation coefficient (r), and F-score. The findings demonstrate that the SHAP-SEM model consistently achieves superior accuracy in data interpolation, which is evident across different seasons and in overall performance. Discussion: We conclude that the SHAP-SEM model demonstrates an exceptional capacity for accurately interpolating volatile and incomplete data. This capability is crucial for developing a comprehensive database that is essential for conducting risk assessments related to syndromes.

Differential effects of size-specific particulate matter on frailty transitions among middle-aged and older adults in China: findings from the China Health and Retirement Longitudinal Study (CHARLS), 2015-2018.

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.

Field measurement of emission factors of PM, EC, OC, parent, nitro-, and oxy- polycyclic aromatic hydrocarbons for residential briquette, coal cake, and wood in rural Shanxi, China.

Air pollutants from residential solid fuel combustion are attracting growing public concern. Field measured emission factors (EFs) of various air pollutants for solid fuels are close to the reality and urgently needed for better emission estimations. In this study, emission factors of particulate matter (PM), organic carbon (OC), elemental carbon (EC), and various polycyclic aromatic hydrocarbons (PAHs) from residential combustions of coal briquette, coal cake, and wood were measured in rural Heshun County, China. The measured EFs of PM, OC, and EC were 8.1-8.5, 2.2-3.6, 0.91-1.6 g/kg for the wood burnt in a simple metal stove, 0.54-0.64, 0.13-0.14, 0.040-0.0041 g/kg for the briquette burned in an improved stove with a chimney, and 3.2-8.5, 0.38-0.58, 0.022-0.052 g/kg for the homemade coal cake combusted in a brick stove with a flue, respectively. EFs of 28 parent PAHs, 4 oxygenated PAHs, and 9 nitro-PAHs were 182-297, 7.8-10, 0.14-0.55 mg/kg for the wood, 14-16, 1.7-2.6, 0.64-0.83 mg/kg for the briquette, and 168-223, 4.7-9.5, 0.16-2.4 mg/kg for the coal cake, respectively. Emissions from the wood and coal cake combustions were much higher than those for the coal briquette, especially true for high molecular weight PAHs. Most EFs measured in the field were higher than those measured in stove combustions under laboratory conditions.

A dataset of a proxy variable for the poultry trade flows in China.

Understanding the intercity poultry trading network is crucial for assessing the risk of avian influenza prevalence. Unfortunately, the poultry trading network in China has rarely been described. Here, with a modified radiation model, we obtain values for a proxy variable for poultry trade flows among 318 prefecture-level cities in China in 2015 utilizing the product capacity and demand quantity of poultry of the cities. The results are validated by comparing the proxy variable values with the trade volumes investigated in the literature, and it is found that the modified radiation model can accurately predict the main poultry trade flows among cities. This is the first dataset on China's poultry trade pattern, and it can be used to analyze the production and consumption structure of poultry in prefecture-level cities within China. The dataset can be a tool for avian influenza epidemic risk assessment as well as a basis to develop prevention and control measures during an epidemic.

Spatial-temporal heterogeneity and determinants of HIV prevalence in the Mano River Union countries.

BACKGROUND: Utilizing population-based survey data in epidemiological research with a spatial perspective can integrate valuable context into the dynamics of HIV prevalence in West Africa. However, the situation in the Mano River Union (MRU) countries is largely unknown. This research aims to perform an ecological study to determine the HIV prevalence patterns in MRU. METHODS: We analyzed Demographic and Health Survey (DHS) and AIDS Indicator Survey (AIS) data on HIV prevalence in MRU from 2005 to 2020. We examined the country-specific, regional-specific and sex-specific ratios of respondents to profile the spatial-temporal heterogeneity of HIV prevalence and determine HIV hot spots. We employed Geodetector to measure the spatial stratified heterogeneity (SSH) of HIV prevalence for adult women and men. We assessed the comprehensive correct knowledge (CCK) about HIV/AIDS and HIV testing uptake by employing the Least Absolute Shrinkage and Selection Operator (LASSO) regression to predict which combinations of CCKs can scale up the ratio of HIV testing uptake with sex-specific needs. RESULTS: In our analysis, we leveraged data for 158,408 respondents from 11 surveys in the MRU. From 2005-2015, Cote d'Ivoire was the hot spot for HIV prevalence with a Gi_Bin score of 3, Z-Score 8.0-10.1 and P < 0.001. From 2016 to 2020, Guinea and Sierra Leone were hot spots for HIV prevalence with a Gi_Bin score of 2, Z-Score of 3.17 and P < 0.01. The SSH confirmed the significant differences in HIV prevalence at the national level strata, with a higher level for Cote d'Ivoire compared to other countries in both sexes with q-values of 0.61 and 0.40, respectively. Our LASSO model predicted different combinations of CCKs with sex-specific needs to improve HIV testing uptake. CONCLUSIONS: The spatial distribution of HIV prevalence in the MRU is skewed and the CCK about HIV/AIDS and HIV testing uptake are far below the threshold target set by UNAIDS for ending the epidemic in the sub-region. Geodetector detected statistically significant SSH within and between countries in the MRU. Our LASSO model predicted that different emphases should be implemented when popularizing the CCK about HIV/AIDS for adult women and men.

Characterization of influenza seasonality in China, 2010-2018: Implications for seasonal influenza vaccination timing.

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, and ≥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. RESULTS: 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- to 18-year-old children and larger cities. CONCLUSIONS: 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.

Hand, foot and mouth disease: spatiotemporal transmission and climate.

BACKGROUND: The Hand-Foot-Mouth Disease (HFMD) is the most common infectious disease in China, its total incidence being around 500,000~1,000,000 cases per year. The composite space-time disease variation is the result of underlining attribute mechanisms that could provide clues about the physiologic and demographic determinants of disease transmission and also guide the appropriate allocation of medical resources to control the disease. METHODS AND FINDINGS: HFMD cases were aggregated into 1456 counties and during a period of 11 months. Suspected climate attributes to HFMD were recorded monthly at 674 stations throughout the country and subsequently interpolated within 1456 × 11 cells across space-time (same as the number of HFMD cases) using the Bayesian Maximum Entropy (BME) method while taking into consideration the relevant uncertainty sources. The dimensionalities of the two datasets together with the integrated dataset combining the two previous ones are very high when the topologies of the space-time relationships between cells are taken into account. Using a self-organizing map (SOM) algorithm the dataset dimensionality was effectively reduced into 2 dimensions, while the spatiotemporal attribute structure was maintained. 16 types of spatiotemporal HFMD transmission were identified, and 3-4 high spatial incidence clusters of the HFMD types were found throughout China, which are basically within the scope of the monthly climate (precipitation) types. CONCLUSIONS: HFMD propagates in a composite space-time domain rather than showing a purely spatial and purely temporal variation. There is a clear relationship between HFMD occurrence and climate. HFMD cases are geographically clustered and closely linked to the monthly precipitation types of the region. The occurrence of the former depends on the later.

Arsenic levels in the soil and risk of birth defects: a population-based case-control study using GIS technology.

Arsenic is a highly dangerous metal that has been linked to a number of adverse health effects in both adults and children, including birth defects. Yet few epidemiologic studies have examined the relationship between arsenic levels in the soil and the risk of birth defects. The purpose of the authors' study was to examine this association among people exposed to environmental pollution in a developed area of China. The authors used global positioning system to locate the coordinates of 80 villages in 40 towns for soil sampling. Soil samples were analyzed for arsenic content. Logistic regression was used to investigate the relationship between exposure to arsenic and birth defects, controlling for potentially confounding factors. The authors found that exposure to arsenic in any amount increased the risk of birth defects. The positive association found between arsenic exposure and birth defects warrants further study, and future large-scale population-based studies are needed with an emphasis on individual-level exposure and confounding variables.

Evaluating an intervention for neural tube defects in coal mining cites in China: a temporal and spatial analysis.

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

Spatial distribution of esophageal cancer mortality in China: a machine learning approach.

BACKGROUND: Esophageal cancer (EC) is one of the most common cancers, causing many people to die every year worldwide. Accurate estimations of the spatial distribution of EC are essential for effective cancer prevention. METHODS: EC mortality surveillance data covering 964 surveyed counties in China in 2014 and three classes of auxiliary data, including physical condition, living habits and living environment data, were collected. Genetic programming (GP), a hierarchical Bayesian model and sandwich estimation were used to estimate the spatial distribution of female EC mortality. Finally, we evaluated the accuracy of the three mapping methods. RESULTS: The results show that compared with the root square mean error (RMSE) of the hierarchical Bayesian model at 6.546 and the sandwich estimation at 7.611, the RMSE of GP is the lowest at 5.894. According to the distribution estimated by GP, the mortality of female EC was low in some regions of Northeast China, Northwest China and southern China; in some regions downstream of the Yellow River Basin, north of the Yangtze River in the Yangtze River Basin and in Southwest China, the mortality rate was relatively high. CONCLUSIONS: This paper provides an accurate map of female EC mortality in China. A series of targeted preventive measures can be proposed based on the spatial disparities displayed on the map.

Seasonal association between viral causes of hospitalised acute lower respiratory infections and meteorological factors in China: a retrospective study.

BACKGROUND: Acute lower respiratory infections (ALRIs) caused by respiratory viruses are common and persistent infectious diseases worldwide and in China, which have pronounced seasonal patterns. Meteorological factors have important roles in the seasonality of some major viruses, especially respiratory syncytial virus (RSV) and influenza virus. Our aim was to identify the dominant meteorological factors and to model their effects on common respiratory viruses in different regions of China. METHODS: We analysed monthly virus data on patients hospitalised with ALRI from 81 sentinel hospitals in 22 provinces in mainland China from Jan 1, 2009, to Sept 30, 2013. We considered seven common respiratory viruses: RSV, influenza virus, human parainfluenza virus, adenovirus, human metapneumovirus, human bocavirus, and human coronavirus. Meteorological data of the same period were used to analyse relationships between virus seasonality and seven meteorological factors according to region (southern vs northern China). The geographical detector method was used to quantify the explanatory power of each meteorological factor, individually and interacting in pairs, on the respiratory viruses. FINDINGS: 28 369 hospitalised patients with ALRI were tested, 10 387 (36·6%) of whom were positive for at least one virus, including RSV (4091 [32·0%] patients), influenza virus (2665 [20·8%]), human parainfluenza virus (2185 [17·1%]), adenovirus (1478 [11·6%]), human bocavirus (1120 [8·8%]), human coronavirus (637 [5·0%]), and human metapneumovirus (615 [4·8%]). RSV and influenza virus had annual peaks in the north and biannual peaks in the south. Human parainfluenza virus and human bocavirus had higher positive rates in the spring-summer months. Human metapneumovirus had an annual peak in winter-spring, especially in the north. Adenovirus and human coronavirus exhibited no clear annual seasonality. Temperature, atmospheric pressure, vapour pressure, and rainfall had most explanatory power on most respiratory viruses in each region. Relative humidity was only dominant in the north, but had no significant explanatory power for most viruses in the south. Hours of sunlight had significant explanatory power for RSV and influenza virus in the north, and for most viruses in the south. Wind speed was the only factor with significant explanatory power for human coronavirus in the south. For all viruses, interactions between any two of the paired factors resulted in enhanced explanatory power, either bivariately or non-linearly. INTERPRETATION: Spatiotemporal heterogeneity was detected for most viruses in this study, and interactions between pairs of meteorological factors were found to enhance their influence on virus variation. These findings might be helpful to guide government planning, such as public health interventions, infection control practice, and timing of passive immunoprophylaxis, and might facilitate the development of future vaccine strategies. FUNDING: National Natural Science Foundation of China, the Ministry of Science and Technology of China, and the Technology Major Project of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Temporal and spatial distribution trends of human brucellosis in Liaoning Province, China.

Brucellosis is a natural epidemic zoonotic disease. Liaoning province, north-east of China, has been among the top 10 provinces with highest brucellosis incidence. In this study, the spatial and temporal distribution of brucellosis in Liaoning Province from 2006 through 2017 was analysed using the Bayesian theory of space-time modelling. The study found that in Liaoning Province, (a) all regions of the entire study area were stable counties; (b) the risk of brucellosis declined slowly with time without an obvious trend; (c) the declining trend of disease risk in three sub-hot-spot counties was faster than the overall trend, whereas in other counties, the trend was similar to the overall trend. Furthermore, the time and spatial trends of brucellosis incidence in Liaoning Province were calculated and analysed. These results may provide a theoretical and scientific basis for the public health department to develop targeted effective prevention and control measures for the disease.