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Monoclonal antibody (mAb) coformulation containing two therapeutic proteins provides benefits of improved therapeutic efficacy and better patient compliance. Monitoring of the individual mAb stability in the coformulation is critical to ensure its quality and safety. Among post-translational modifications (PTMs), oxidation is often considered as one of the critical quality attributes (CQAs) as it potentially affects the structure and potency. Although hydrophobic interaction chromatography (HIC) and reversed phase liquid chromatography (RPLC) have been used to monitor overall protein oxidation, mass spectrometry of peptide digests resolved by LC methods can afford superior selectivity and sensitivity for specific PTMs. With the advent of the Quadrupole Dalton (QDa) mass spectrometer as an affordable add-on detector, implementation of targeted oxidation assays in development and quality control (QC) laboratories is now feasible. In this study, as the first effort to implement MS-based methods for antibody coformulation in QC laboratories, we developed and validated a high-throughput and robust focused peptide mapping method using QDa for simultaneous site-specific monitoring of oxidation of methionine and tryptophan residues in heavy-chain (HC) complementary determining regions (CDRs) of two co-formulated mAbs. The method was validated in terms of accuracy, precision, linearity, range, quantitation limit (QL), specificity, and solution stability per recommendations in ICH Q2. The method robustness was systematically assessed involving multiple sample preparation and instrument method parameters. The method met the validation criteria in GMP laboratories with excellent robustness and was implemented in both GMP and development environments.

Backgrounds Tuberculosis (TB) remains a serious public health and human development problem, especially in developing countries. Despite the effectiveness of directly observed therapy, short course programs in reducing transmission and progression of TB, poverty reduction and socioeconomic development remain crucial factors in decreasing TB incidence. However, the geographical pathway on the planet is not yet clear. Objectives This study was to reconstruct the geographical evolutionary process of TB in 173 countries and territories from 2010 to 2019 to analyze the socioeconomic determinants that impact the global TB epidemic. In addition, the TB incidence in 2030 was predicted. Methods This study analyses TB incidence data from 173 countries and territories between 2010 and 2019. The Geotree model would be used to reconstruct the geographical evolutionary process of TB, which provides a simplified schema for geo-visualizing the trajectories of TB incidence and their socioeconomic drivers. Additionally, to estimate the future TB incidence in 2030, a multilevel model was utilized in conjunction with the hierarchical nature of the Geotree based on a stratified heterogeneity analysis. Results Global TB incidence was found to be associated with the country type and development stages. Between 2010 and 2019, the average TB incidence rate in 173 countries and territories was -27.48%, with marked spatially stratified heterogeneity by country type and development stage. Low-income and lower-middle-income countries were most vulnerable to TB. Upper-middle-income countries experienced a faster decline in TB incidence than high-income countries, and TB incidence generally decreased as the development stage increased, except for the lower-middle development stage in 2019.The highest average rate of decline in TB incidence was observed in the upper-middle development stage of high-income countries, with a reduction of 45.24%. Meanwhile, 37 high-income countries in the high development stage demonstrated an average rate of change of -13.93%. Socioeconomic determinants, including gross domestic product per capita, urbanization rate, and sociodemographic index, were found to inhibit TB incidence. Based on current trends, the predicted average global TB incidence in 2030 is 91.581 per 100,000 population. Conclusions The trajectories of the global TB incidence have been reconstructed to formulate targeted public health responses. To eliminate TB, countries at similar development stage can draw on the experiences of countries at higher development stages that are tailored to their unique characteristics. By learning from successful TB control strategies, countries can take strategic steps toward eradicating TB and improving public health outcomes.

Background: China has the third largest number of TB cases in the world, and the average annual floating population in China is more than 200 million, the increasing floating population across regions has a tremendous potential for spreading infectious diseases, however, the role of increasing massive floating population in tuberculosis transmission is yet unclear in China. Methods: 14,027 tuberculosis flow data were derived from the new smear-positive pulmonary tuberculosis cases in China. Spatial interaction model was used to model the tuberculosis flow and the regional socioeconomic factors. Results: Tuberculosis transmission flow presented spatial heterogeneity. The Pearl River Delta in southern China and the Yangtze River Delta along China’s east coast presented as the largest destination and concentration areas of tuberculosis inflows. Socioeconomic factors were determinants of tuberculosis flow. Some impact factors showed different spatial associations with tuberculosis transmission flow. A 10% increase in per capita GDP was associated with 2.1% decrease in tuberculosis outflows from the provinces of origin, and 0.5% increase in tuberculosis inflows to the destinations and 18.9% increase in intraprovincial flow. Per capita net income of rural households and per capita disposable income of urban households were positively associated with tuberculosis flows. A 10% increase in per capita net income corresponded to 3.6% increase in outflows from the origin, 12.8% increase in inflows to the destinations and 47.9% increase in intraprovincial flows. Tuberculosis incidence had positive impacts on tuberculosis flows. A 10% increase in the number of tuberculosis cases corresponded to 1.1% increase in tuberculosis inflows to the destinations, 2.0% increase in outflows from the origins, and 2.2% increase in intraprovincial flows. Conclusions: Tuberculosis flows had clear spatial stratified heterogeneity and spatial autocorrelation, regional socio-economic characteristics had diverse and statistical significant effects on tuberculosis flows in the origin and destination, and income factor played an important role among the determinants.

Background Modern transportation plays a key role in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and new variants. However, little is known about the exact transmission risk of the virus on airplanes. Methods Using the itinerary and epidemiological data of coronavirus disease 2019 (COVID-19) cases and close contacts on domestic airplanes departing from Wuhan city in China before the lockdown on 23 January 2020, we estimated the upper and lower bounds of overall transmission risk of COVID-19 among travelers. Results In total, 175 index cases were identified among 5797 passengers on 177 airplanes. The upper and lower attack rates (ARs) of a seat were 0.60% (34/5622, 95% confidence interval [CI] .43–.84%) and 0.33% (18/5400, 95% CI .21–.53%), respectively. In the upper- and lower-bound risk estimates, each index case infected 0.19 (SD 0.45) and 0.10 (SD 0.32) cases, respectively. The seats immediately adjacent to the index cases had an AR of 9.2% (95% CI 5.7–14.4%), with a relative risk 27.8 (95% CI 14.4–53.7) compared to other seats in the upper limit estimation. The middle seat had the highest AR (0.7%, 95% CI .4%–1.2%). The upper-bound AR increased from 0.7% (95% CI 0.5%–1.0%) to 1.2% (95% CI .4–3.3%) when the co-travel time increased from 2.0 hours to 3.3 hours. Conclusions The ARs among travelers varied by seat distance from the index case and joint travel time, but the variation was not significant between the types of aircraft. The overall risk of SARS-CoV-2 transmission during domestic travel on planes was relatively low. These findings can improve our understanding of COVID-19 spread during travel and inform response efforts in the pandemic.

Background Cardiovascular disease (CVD) is the leading cause of death in China. No previous study has reported CVD mortality at county-level, and little was known about the nonmedical ecological factors of CVD mortality at such small scale in mainland China. Understanding the spatiotemporal variations of CVD mortality and examining its nonmedical ecological factors would be of great importance to tailor local public health policies. Methods By using national mortality registration data in China, this study used hierarchical spatiotemporal Bayesian model to demonstrate spatiotemporal distribution of CVD mortality in 2844 counties during 2006 to 2020 and investigate how nonmedical ecological determinants have affected CVD mortality inequities from the spatial perspectives. Results During 2006–2020, the age-standardized mortality rate (ASMR) of CVD decreased from 284.77 per 100,000 in 2006 to 241.34 per 100,000 in 2020. Among 2844 counties, 1144 (40.22%) were hot spots counties with a higher CVD mortality risk compared to the national average and located mostly in northeast, north central, and westernmost regions; on the contrary, 1551 (54.53%) were cold spots counties and located mostly in south and southeast coastal counties. CVD mortality risk decreased from 2006 to 2020 was larger in counties where CVD mortality rate had been higher in 2006 in most of the counties, vice versa. Nationwide, nighttime light intensity (NTL) was the major influencing factor of CVD mortality, a higher NTL appeared to be negatively associated with a lower CVD mortality, with one unit increase in NTL, and the CVD mortality risk will decrease 11% (relative risk of NTL was estimated as 0.89 with 95% confidence interval of 0.83–0.94). Conclusions Substantial between-county discrepancies of CVD mortality distribution were observed during past 15 years in mainland China. Nonmedical ecological determinants were estimated to significantly explain the overall and local spatiotemporal patterns of this CVD mortality risk. Targeted considerations are needed to integrate primary care with clinical care through intensifying further strategies to narrow unequally distribution of CVD mortality at local scale. The approach to county-level analysis with small area models has the potential to provide novel insights into Chinese disease-specific mortality burden.

A total of 55 volatiles including esters (29, 52.73%), alcohols (10, 18.18%), acids (3, 5.45%), alkanes (8, 14.55%), and other components (5, 9.09%) were evaluated in five regions. Total concentrations were 0.05–222.23 mg/L, which covered the highest esters (222.23 mg/L) and alcohols (120.65 mg/L) in Turpan, acid (0.53 mg/L) in Shihezi, and alkanes (1.43 mg/L) and others (3.10 mg/L) in the Ili River valley. It proved that numbers and concentrations of volatile compounds, including common ingredients of variety, were closely linked to ecological characteristics of a region. Esters and alcohols were the major ingredients in Xinjiang Cabernet Sauvignon wine. Additionally, appellation could affect performance of concentration, ODE, and OTH, especially for the same flavor substance by fermentation, aging, and even formation and transformation in wines. Therefore, three conditions for formation of flavors were successively appellations, metabolism and fermentation, and and appropriate altering according to technology and their decisive role in wine quality. Each volatile compound had its own flavor, the combination of which complicated the flavor. The unique materials in the region were grounded for the development of products with corresponding flavors by producing substrate for fermentation. When choosing a wine you enjoy, the right appellation should be considered first.

Previous studies indicate that the incidence of bacillary dysentery is closely related to meteorological factors. However, the impact of temperature and the spatial heterogeneity of the disease in regions of unbalanced socioeconomic development remains unclear. Therefore, this research collected data for 29,639 daily bacillary dysentery cases in children under 5 years of age, as well as the meteorological variables from China's Beijing-Tianjin-Hebei region, to analyze the spatial pattern of bacillary dysentery and reveal its nonlinear association with temperature. The SatScan method was employed first, to detect the spatial heterogeneity of the disease risk, and then the distributed lag nonlinear model (DLNM) was used to analyze the relationships between the daily minimum, mean, and maximum temperatures and bacillary dysentery in the stratified heterogeneous regions. The results indicated that bacillary dysentery incidence presented statistically significant spatial heterogeneity. The area of highest risk was found to be Beijing and its neighboring regions, which have high population densities. There was also a positive association between bacillary dysentery and temperature. Hotter temperatures were accompanied by higher relative risks. In the most likely spatial cluster region, the excess risk (ER) values for a 1°C rise in minimum, mean, and maximum temperatures above the median were 4.65%, 11.30%, and 19.21%, respectively. The effect of temperature on bacillary dysentery peaked at a lag of 3 to 4 days. The findings of this study will aid risk assessments and early warning systems for bacillary dysentery.

Acute lower respiratory infections 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. Our aim was to identify the dominant meteorological factors and to model their effects on common respiratory viruses in different regions of China. We analysed monthly virus data on patients from 81 sentinel hospitals in 22 provinces in mainland China from 2009 to 2013. The geographical detector method was used to quantify the explanatory power of each meteorological factor, individually and interacting in pairs. 28369 hospitalised patients with ALRI were tested, 10387 were positive for at least one virus, including RSV, influenza virus, PIV, ADV, hBoV, hCoV and hMPV. RSV and influenza virus had annual peaks in the north and biannual peaks in the south. PIV and hBoV had higher positive rates in the spring summer months. hMPV had an annual peak in winter spring, especially in the north. ADV and hCoV 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., 6 figures and tables

In this article, the problem of receiver autonomous integrity monitoring (RAIM) is transformed into a modeling problem using dynamic data and an artificial neural network. A new RAIM method based on a probabilistic neural network (P-RAIM) is presented to improve integrity monitoring performance. Compared with existing RAIM methods, P-RAIM has a greater ability to meet the monitoring requirements for localizer performance with vertical guidance down to altitudes of 250 feet (LPV-250) in a single global navigation satellite system. First, by projecting the pseudorange error model from the measurement domain into the positioning domain through multiconvolution, patterns including a satellite fault pattern and a fault-free pattern are obtained based on variance inflation theory. Second, the P-RAIM model is proposed as a modified dynamic-data-driven probabilistic neural network with five layers; moreover, unique methods for training sample collection and integrity support are presented. Then, particle swarm optimization is applied to optimize a fitness function based on the false alarm probability and missed detection probability thereby improving the ability of P-RAIM to meet the LPV-250 requirements, including the false alarm probability, missed detection probability, vertical alarm limit and alarm time. Finally, utilizing real satellite data from a receiver located in Beijing to verify the effectiveness and universality of P-RAIM, evaluation experiments show that both the false alarm probability and missed detection probability can be effectively reduced to meet the LPV-250 requirements when the positioning bias is no less than 40 m. Compared with least-squares-residuals RAIM, P-RAIM can more easily detect potential faulty satellites in a single constellation.

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 Z-Score of 3.17 and P 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.

Background Since the introduction of HIV self-testing by UNAIDS in 2014, the practice has been extensively implemented around the world. HIV self-testing (HIVST) was developed in China around 2015, and the online purchase of HIVST kits through e-commerce platforms has since become the most important delivery method for self-testing, with advantages such as user-friendliness, speed, and better privacy protection. Objective Understanding the spatiotemporal characteristics of online HIVST kit purchasing behavior and identifying potential impacting factors will help promote the HIV self-testing strategy. Methods The online retail data of HIVST kits from the 2 largest e-commerce platforms in China from 2015 to 2017 were collected for this study. The Bayesian spatiotemporal hierarchical model was used to investigate the spatiotemporal characteristics of online purchased HIVST kits. Ordinary least squares regression was used to identify potential factors associated with online purchase, including GDP per capita, population density, road density, HIV screening laboratory density, and newly diagnosed HIV/AIDS cases per 100,000 persons. The q statistics calculated by Geodetector were used to determine the interactive effect of every 2 factors on the online purchase. Results The online purchase of HIVST kits increased rapidly in China from 2015 to 2017, with annual peak sales in May and December. Five economically superior regions in China, Pearl River Delta, Yangtze River Delta, Chengdu and surrounding areas, Beijing and Tianjin areas, and Shandong Peninsula, showed a comparatively higher spatial preference for online purchased HIVST kits. The GDP per capita (P Conclusions Individuals in better-off areas are more inclined to purchase HIVST kits online. In addition to economic status, the severity of the HIV epidemic is also a factor influencing the online purchase of HIVST kits.

Typhoons are an environmental threat that mainly affects coastal regions worldwide. The interactive effects of natural and socioeconomic factors on the losses caused by typhoon disasters need further examination. In this study, GeoDetector was used to quantify the determinant powers of natural and socioeconomic factors and their interactive effects on the rate of house collapse in Guangdong and Guangxi Provinces of southeast China caused by Typhoon Mangkhut in 2018. We further identify the dominant factors that influenced the disaster losses. The local indicators of spatial association method was then introduced to explain the spatial heterogeneity of the disaster losses under the influence of the dominant factor. The results indicate that both natural and socioeconomic factors significantly affected the house collapse rate. The maximum precipitation was the dominant factor, with a q value of 0.21, followed by slope and elevation, with q values of 0.17 and 0.13, respectively. Population density and per capita gross domestic product had q values of 0.15 and 0.13, respectively. Among all of the interactive effects of the influencing factors, the interactive effect of elevation and the ratio of brick-wood houses had the greatest influence (q = 0.63) on the house collapse rate. These results can contribute to the formulation of more specific safety and property protection policies.

In this work, a synthesis of the Bayesian maximum entropy (BME) and the Kalman filter (KF) methods, which enhances their individual strengths and overcomes certain of their weaknesses for spatiotem...

Spatial heterogeneity represents a general characteristic of the inequitable distributions of spatial issues. The spatial stratified heterogeneity analysis investigates the heterogeneity among vari...

Assessing the association between maps is a basic task in GIS. It not only helps to discover the consistency between mapped distributions and to reveal the relationship between various spatial patterns, but also implies attribution. Although literatures are rich in the map association measures, their applications are still tricky because of the complexity in spatial data. In this study, we investigate nine representative measures of map association, where each map could be in three scales of measurement: nominal, ordinal and quantitative (interval or ratio). The strengths and limitations of individual methods are addressed and compared, which include their applicability to different measurement scales, interpretability, and potential applications in complex scenarios. The theoretical comparisons are then demonstrated by two empirical examples. These works provide a rule of thumb for the selection of map association measures for practical purposes.

Given the growing concern over the ecological impacts of non-native species, exploring these species' expansion edge and distribution patterns and their driving factors is important for developing suitable management measures.

BACKGROUND China has one of the highest tuberculosis (TB) burdens in the world. However, the unbalanced spatial and temporal trends of TB risk at a fine level remain unclear. OBJECTIVE We aimed to investigate the unbalanced risks of pulmonary tuberculosis (PTB) at different levels and how they evolved from both temporal and spatial aspects using PTB notification data from 2851 counties over a decade in China. METHODS County-level notified PTB case data were collected from 2009 to 2018 in mainland China. A Bayesian hierarchical model was constructed to analyze the unbalanced spatiotemporal patterns of PTB notification rates during this period at subnational scales. The Gini coefficient was calculated to assess the inequality of the relative risk (RR) of PTB across counties. RESULTS From 2009 to 2018, the number of notified PTB cases in mainland China decreased from 946,086 to 747,700. The average number of PTB cases in counties was 301 (SD 26) and the overall average notification rate was 60 (SD 6) per 100,000 people. There were obvious regional differences in the RRs for PTB (Gini coefficient 0.32, 95% CI 0.31-0.33). Xinjiang had the highest PTB notification rate, with a multiyear average of 155/100,000 (RR 2.3, 95% CI 1.6-2.8; PPPPPPP CONCLUSIONS PTB risk showed significant regional inequality among counties in China, and western China presented a high plateau of disease burden. Improvements in economic and medical service levels are required to boost PTB case detection and eventually reduce PTB risk in the whole country.

Background China has one of the highest tuberculosis (TB) burdens in the world. However, the unbalanced spatial and temporal trends of TB risk at a fine level remain unclear. Objective We aimed to investigate the unbalanced risks of pulmonary tuberculosis (PTB) at different levels and how they evolved from both temporal and spatial aspects using PTB notification data from 2851 counties over a decade in China. Methods County-level notified PTB case data were collected from 2009 to 2018 in mainland China. A Bayesian hierarchical model was constructed to analyze the unbalanced spatiotemporal patterns of PTB notification rates during this period at subnational scales. The Gini coefficient was calculated to assess the inequality of the relative risk (RR) of PTB across counties. Results From 2009 to 2018, the number of notified PTB cases in mainland China decreased from 946,086 to 747,700. The average number of PTB cases in counties was 301 (SD 26) and the overall average notification rate was 60 (SD 6) per 100,000 people. There were obvious regional differences in the RRs for PTB (Gini coefficient 0.32, 95% CI 0.31-0.33). Xinjiang had the highest PTB notification rate, with a multiyear average of 155/100,000 (RR 2.3, 95% CI 1.6-2.8; P Conclusions PTB risk showed significant regional inequality among counties in China, and western China presented a high plateau of disease burden. Improvements in economic and medical service levels are required to boost PTB case detection and eventually reduce PTB risk in the whole country.

Studies in environmental fields often suffer from air quality datasets incomplete at certain places and times. Here, a Spatial-Temporal Point Interpolation based on Biased Sentinel Hospitals Areal Disease Estimation (STPI-BSHADE) interpolation method was introduced to address this issue. The method was based on the spatial statistic trinity theory, where the statistical error is determined by the population properties, the condition of the sample, and the method of estimation. In our study, the spatial association of the variables was quantified by the covariance and the ratio of air quality data between stations, resulting in linear unbiased estimates of the missing data. STPI-BSHADE was compared with two widely used statistical methods, inverse distance weighting (IDW) and Kriging. Theoretically, IDW and Kriging are short of the capacity of using the heterogeneous characteristics of the population and remedying the sample bias. Empirically, the accuracy of the STPI-BSHADE method was assessed using hourly particulate matter 2.5 data, collected from May 13 to December 31, 2014, in the Beijing-Tianjin-Hebei areas, where air quality presents spatial heterogeneity. The experimental results also demonstrated that STPI-BSHADE significantly outperformed the traditional methods.

The environmental Kuznets curve (EKC) is often used to analyze the relationship between environmental pollution health indicators and economic development level in different regions. In developed countries, the blood lead levels (BLLs) of children have been declining fitting the EKC since the 1970s. However, such figures in China have remained at relatively high levels, without any obvious decline, since 2010. We explored spatial variations and graded countermeasures using reported data on BLLs including the lead poisoning rates (LPRs) of children. We found that there were prefectures where either the mean BLLs of the children had reached 100.00 μg/L or the LPRs of more than 40% of the children had reached 100 μg/L. When we reduced the average BLLs to 50 μg/L or lowered the proportion of children with a lead poisoning rate (LPR) above 100 μg/L to 10.00%, the EKC trend decreased, and the linear slope after 2010 became -0.202. If the areas where children's BLLs exceeded 50.00 μg/L or the proportion of children with an LPR above 100 μg/L was more than 10.00% will be controlled, the linear slope of the EKC decrease trend after 2010 will became -0.989, and the national average of children's BLLs would decline by 22.17%. The study concluded that children's BLLs in different regions of China are situated at different EKC stages, and urgent prevention and control strategies must be put in place for undeveloped areas.

Enterovirus 71 (EV71) can cause large outbreaks of hand, foot, and mouth disease (HFMD) and severe neurological diseases, which is regarded as a major threat to public health, especially in Asia-Pacific regions. However, the global spatiotemporal spread of this virus has not been identified. In this study, we used large sequence datasets and a Bayesian phylogenetic approach to compare the molecular epidemiology and geographical spread patterns of different EV71 subgroups globally. The study found that subgroups of HFMD presented global spatiotemporal variation, subgroups B0, B1, and B2 have caused early infections in Europe and America, and then subgroups C1, C2, C3, and C4 replaced B0-B2 as the predominant genotypes, especially in Asia-Pacific countries. The dispersal patterns of genotype B and subgroup C4 showed the complicated routes in Asia and the source might in some Asian countries, while subgroups C1 and C2 displayed more strongly supported pathways globally, especially in Europe. This study found the predominant subgroup of EV71 and its global spatiotemporal transmission patterns, which may be beneficial to reveal the long-term global spatiotemporal transmission patterns of human EV71 and carry out the HFMD vaccine development.

When a marine study area is large, the environmental variables often present spatially stratified non-homogeneity, violating the spatial second-order stationary assumption. The stratified non-homog...

The Huai River basin (located in eastern China) has a population of 180 million and has the highest risk of esophageal cancer (EC) mortality in China. Some studies found that contaminants in drinking water are a major risk factor for cancers of the digestive system. However, the effect of water pollution in the historical period on the current EC mortality remains unclear. Data were collected on the EC mortality rate in 2004 in the Huai River basin in 11 counties, and data on the surface water quality in the region from 1987 to 2004 were used. The Pearson correlation and the GeoDetector q-statistic were employed to explore the association between water pollution and the EC mortality rate in different lag periods, from linear and nonlinear perspectives, respectively. The study showed apparently spatial heterogeneity of the EC mortality rate in the region. The EC mortality rate downstream is significantly higher than that in other regions; in the midstream, the region north of the mainstream has a lower average mortality rate than that south of the area. Upstream, the region north of the mainstream has a higher mortality rate than that in the southern area. The spatial pattern was formed under the influence of water pollution in the historical period. 1996, 1997, and 1998 have the strongest linear or nonlinear effect on the EC mortality rate in 2004, in which the Pearson correlation coefficient and the q-statistic were the highest, 0.79 and 0.89, respectively. Rapid industrialization in the past 20 years has caused environmental problems and poses related health risks. The study indicated that the current EC mortality rate was mainly caused by water pollution from the previous 8 years. The findings provide knowledge about the lag time for pollution effects on the EC mortality rate, and can contribute to the controlling and preventing esophageal cancer.

In the last decade, extensive application of hydraulic fracturing technologies to unconventional low-permeability hydrocarbon-rich formations has significantly increased natural-gas production in the United States and abroad. The injection of surface-sourced fluids to generate fractures in the deep subsurface introduces microbial cells and substrates to low-permeability rock. A subset of injected organic additives has been investigated for their ability to support biological growth in shale microbial community members; however, to date, little is known on how complex xenobiotic organic compounds undergo biotransformations in this deep rock ecosystem. Here, high-resolution chemical, metagenomic, and proteomic analyses reveal that widely-used surfactants are degraded by the shale-associated taxa Halanaerobium, both in situ and under laboratory conditions. These halotolerant bacteria exhibit surfactant substrate specificities, preferring polymeric propoxylated glycols (PPGs) and longer alkyl polyethoxylates (AEOs) over polyethylene glycols (PEGs) and shorter AEOs. Enzymatic transformation occurs through repeated terminal-end polyglycol chain shortening during co-metabolic growth through the methylglyoxal bypass. This work provides the first evidence that shale microorganisms can transform xenobiotic surfactants in fracture fluid formulations, potentially affecting the efficiency of hydrocarbon recovery, and demonstrating an important association between injected substrates and microbial growth in an engineered subsurface ecosystem.

Hand, foot and mouth disease (HFMD) remains an increasing public health concern. The spatiotemporal variation of HFMD can be represented from multiple-perspectives, and it may be driven by different dominant factors. In this study, the HFMD cases in children under the age of five years in each county in Henan province, China, from 2009 to 2013 were assessed to explore the integrative spatiotemporal patterns of HFMD and investigate their driving factors. The empirical orthogonal function was applied to identify representative spatiotemporal patterns. Then, GeoDetector was used to quantify the determinant powers of driving factors to the disease. The results indicated that the most prominent spatiotemporal pattern explained 56.21% of the total variance, presented in big cities, e.g. capital city and municipal districts. The dominant factors of this pattern were per capita gross domestic product and relative humidity, with determinant powers of 62% and 42%, respectively. The secondary spatiotemporal pattern explained 10.52% of the total variance, presented in the counties around big cities. The dominant factors for this pattern were the ratio of urban to rural population and precipitation, with determinant powers of 26% and 41%, respectively. These findings unveiled the key spatiotemporal features and their determinants related to the disease; this will be helpful in establishing accurate spatiotemporal preventing of HFMD.

To better understand the physiological processes involved in responses of trellises to the transportation and distribution of nutrient within shoots of grapevines, analysis method of disodium ethylenediamine tetraacetate (EDTA - Na2) was employed at the whole development stages of vine. In the trial, the traditional independent long-stem pruning (ILSP) was taken as control to compare the effect of new single crawled cordon training (SCCT) on the transportation and distribution of phloem sap on the experimental material Ecolly. Thus the consumption level of phloem sap in the grapevine shoots of various trellises was analyzed by EDTA-Na2 phloem sap exudation technique during the whole development. Results was that the consumption rate of EDTA - Na2 solution in the SCCT and ILSP shoots increased before August 15 (15.130 g–16.216 g in SCCT and 10.653 g–15.042 g in ILSP, respectively) including 16.348–20.809 g in SCCT and 11.912–19.593 g in ILSP from August 25 to September 4 as well as decreased in August 15–25 (17.216–16.348 g in SCCT and 15.042–11.912 g in ILSP, respectively) and after September 4 (20.809–7.669 g in SCCT and 19.593–4.072 g in ILSP), respectively, and values of SCCT were always higher than that of ILSP during the whole growth. In addition, EDTA - Na2 consumption content in the phloem sap per shoots in SCCT kept almost around 16 g, more than that in ILSP, from 21 July to 25 August. Therefore, SCCT was more advantageous to accumulate nutrient compared with ILSP, and ensured an even distribution of phloem sap in the grape shoots from berry growth to maturity.

Uneven spatial distribution of population and human activity still remain an inevitable problem for China's urbanization strategy and regional policies. The geographical detector technique was employed to re-investigated “Hu Line”, an important population dividing line in China, and impact factors of population distribution from 1953 to 2010. Different from traditional views, we believe that rapid population concentration driven by social and economic factors leads to increasing similar spatial patterns between two sides of the “Hu Line”. This trend offers a chance to realize a more balanced development by focusing on small-scale population concentration areas such as urban agglomerations. However, due to fundamental influence of some natural factors, gap among large-scale regions hard to be eliminated in China.

Landslides are destructive not only to property and infrastructure but also to people living in landslide-prone regions. Landslide susceptibility mapping (LSM) is critical for preventing and mitigating the negative impacts of landslides. However, many previously proposed LSM modeling techniques included only the attribute information of spatial objects and ignored the spatial structural information of spatial objects, which led to suboptimal LSM. In addition, the selection of condition factors was not objective to such an extent that it may have reduced the reliability of LSM. To address these problems, a new method based on GeoDetector and a spatial logistic regression (SLR) model is proposed. GeoDetector is used to select condition factors based on the spatial distribution of landslides. The SLR model is used to make full use of the structural and attribute information of spatial objects simultaneously in LSM. The GeoDetector-SLR model is validated using data from the Duwen Highway Basin, which includes the epicenter of the May 12, 2008 Wenchuan earthquake in southwestern China. Prediction accuracy of the GeoDetector-SLR model is found to be 86.1%, which is an 11.9% improvement over the traditional logistic regression model, indicating an improved and reliable solution for evaluating landslide susceptibility.

Most previous studies have indicated inconsistent relationships between rice cadmium (Cd) and the soil properties of paddy fields at a regional scale under the adverse effects of confounding factors and spatial heterogeneity. In order to reduce these effects, this study integrates Geodetector, a stepwise regression model, and a hierarchical Bayesian method (collectively called GDSH). The GDSH framework is validated in a large typical rice production area in southeastern China. According to the results, significant stratified heterogeneity of the bioaccumulation factor is observed among different subregions and pH strata (q = 0.23, p 0.01). Additionally, the soil-rice relationships and dominant factors vary by the subregions, and the available soil Cd and pH are found to be the dominant factors in 64% and 50% of subregions, respectively. In the entire region, when the pH 6, the dominant factors are organic matter and available Cd, and when pH ≥ 6 they are organic matter, pH, and available Cd. Furthermore, these factors presented different sensitivity to the spatial heterogeneity. The results indicate that, at the subregional level, the GDSH framework can reduce the confounding effects and accurately identify the dominant factors of rice Cd. At the regional level, this model can evaluate the sensitivity of the dominant factors to spatial heterogeneity in a large area. This study provides a new scheme for the complete utilization of regional field survey data, which is conducive to formulating precise pollution control strategies.

Additional file 1. The relationship between COVID-19 risk and the socioeconomic risk factors.

Social determinants of health (SDOH) produce a broad range of life expectancy (LE) disparities. In China, limited literatures were found to report association between SDOH and LE at ecological level during a consecutive period of time from the spatial perspectives. This study aimed to determine the existence, quantify the magnitude, and interpret the association between SDOH and LE in China.Provincial-level LE were estimated from mortality records during 2005-2020 from National Mortality Surveillance System in China. A spatial panel Durbin model was used to investigate LE associated SDOH proxies. Spatial spillover effects were introduced to interpret direct and indirect effects caused by SDOH during long-term and short-term period on LE disparities.Nationwide, LE increased from 73.1 (95% confidence interval (CI): 71.3, 74.4) years to 77.7 (95%CI: 76.5, 78.7) years from 2005 to 2020. Unequally spatial distribution of LE with High-High clustering in coastal areas and Low-Low clustering in western regions were observed. Locally, it was estimated that SDOH proxies statistically significant related to an increase of LE, including GDP (coefficient: 0.02, 95%CI: 0.00, 0.03), Gini index (coefficient: 2.35, 95%CI: 1.82, 2.88), number of beds in health care institutions (coefficient: 0.02, 95%CI: 0.00, 0.05) and natural growth rate of resident population (coefficient: 0.02, 95%CI: 0.01, 0.02). Direct and indirect effects decomposition during long-term and short-term of LE associated SDOH proxies demonstrated that GDP, urbanization rate, unemployment rate, education attainment, Gini index, number of beds in health care institutions, sex ratio, gross dependence ratio and natural growth rate of resident population not only affected local LE, but also exerted spatial spillover effects towards geographical neighbors.Spatial variations of LE existed at provincial-level in China. SDOH regarding socioeconomic development and equity, healthcare resources, as well as population characteristics not only affected LE disparities at local scale but also among nearby provinces. Externalities of policy of those SDOH proxies should be took into consideration to promote health equity nationally. Comprehensive approaches on the basis of population strategy should be consolidated to optimize supportive socioeconomic environment and narrow the regional gap to reduce health disparities and increase LE.National Key ResearchDevelopment Program of China (Grant No.2018YFC1315301); Ministry of Education of China Humanities and Social Science General Program (Grant No.18YJC790138).

Background: Although significant correlations have been observed between air pollutants and the development of pulmonary tuberculosis (PTB) in many developed countries, data are scarce for developing and highly polluted regions. Method: A combined Poisson generalized linear regression–distributed lag nonlinear model was used to determine the associations between long-term exposure (2005–2017) to air pollutants and the risk of PTB in the Beijing–Tianjin–Hebei region. Results: The monthly PTB cases exhibited a fluctuating downward trend. For each 10 μg/m3 increase in concentration, the maximum lag-specific risk and cumulative relative risk (RR) were 1.011 (95% confidence interval (CI): 1.0091.012, lag: 3 months) and 1.042 (1.036–1.048, 5 months) for PM2.5, and 1.023 (1.015–1.031, 0 months) and 1.041 (1.026–1.055, 2 months) for NO2. The risk of PTB was negatively correlated with O3 exposure, and the minimum lag-specific risk and cumulative RR were 0.991 (95% CI: 0.987–0.994, lag: 0 months) and 0.974 (0.968–0.981, 4 months), respectively. No age-dependent effects were observed. Conclusions: Our results revealed potential associations between outdoor exposure to PM2.5, NO2, and O3 and the risk of PTB. Further research should explore the corresponding interactions and potential mechanisms.

Background: Previous studies had indicated that the incidence of Tuberculosis (TB) was closed related to the regional aging population and socio-economic condition. However, spatio-temporal variation and risk determinants of TB in aging population and socio-economic development unbalanced region have been unclear.Methods: The data on TB registered cases and social-economic factors from 2009 to 2014 were collected for each district/county in the region with Beijing, Tianjin and Hebei province of China, which is consist of aging population and social-economic development disparity region. The Bayesian space–time hierarchy model was used to reveal the spatio-temporal variation of elderly TB incidence from 2009 to 2014, and GeoDetector was applied to measure the determinant power (q statistic) of elderly TB risk factors.Results: Elderly TB incidence present geographical spatial heterogeneity, they were higher in underdeveloped rural areas compared with that in urban areas. The hotspots of elderly TB incidence risk were mostly located in the northeastern and southern regions of the study region distant from metropolitan areas. Areas with low risk were mainly distributed in the Beijing-Tianjin metropolitan areas. Social-economic factors presented nonlinear influence on elderly TB incidence, the dominant factors were income of rural populations (q statistic = 0.20) and medical conditions (q statistic = 0.17). These factors presented nonlinearly interact with each other in influencing the elderly TB incidence; medical conditions and level of economic development showed the strongest relationship (q statistic = 0.54).Conclusions: These findings explain spatiotemporal variation and risk determinants of elderly TB incidence where there are social-economic development disparities. High-risk zones were mainly located in rural areas far from metropolitan centers. Medical conditions and economic development level were significantly association with elderly TB incidence, and they showed nonlinearly interact with each other in influencing the elderly TB incidence. Knowing this helps to optimize the allocation of health resources and to control the transmission of the TB epidemic in the aging population in this region.

Vegetation productivity dynamics are closely related to climate change, and water availability determines vegetation growth in water-limited ecosystems. Nevertheless, how changes in the interactions between climatic factors and vegetation activity variation regulate the relationship between their trends remains unclear. The Normalized Difference Vegetation Index (NDVI) is an effective proxy of vegetation growth. First, we investigated the NDVI trends, and the results revealed a vegetation activity with weaker greening and greater spatial heterogeneity after an obvious land-cover breakpoint in 1999 compared with that before 1999 in northwest China. Notably, the Loess Plateau greatly led the greenness trends, but the Tibet Plateau showed mean browning after 1999, which implied that the coupling of climate change and vegetation trends varied with spatio-temporal changes. Subsequently, using the Geographical Detector Method (GDM), we quantified and compared the association between climate change and the interannual variability of NDVI in the two stages. Vegetation productivity variation is more closely related to changes in climatic factors after 1999 compared with that before 1999. Precipitation (PPT) and vapor pressure deficit (VPD) are the primary constraints to vegetation growth in both stages. Patterns in NDVI trend increases are consistent with those of increased PPT and decreased VPD and vice versa after 1999. However, the same patterns were not observed before 1999 because of the weak association between climate change and NDVI variation. This implicated a great significance of the association between climate change and changes in vegetation activity for the prediction of potential carbon sequestration due to the shift of dominant factors and their trends under future climate change.

Background Previous research pointed to a close relationship between the incidence of tuberculosis (TB) in aging populations and socio-economic conditions, however there has been lack of studies focused on a region of unbalanced socio-economic development. The aim of this paper is to explore the spatio-temporal variation in TB incidence and examine risk determinants of the disease among aging populations in a typical region. Methods Data on TB-registered cases between 2009 and 2014, in addition to social-economic factors, were collected for each district/county in Beijing, Tianjin and Hebei, a region characterized by an aging population and disparities in social-economic development. A Bayesian space–time hierarchy model (BSTHM) was used to reveal spatio-temporal variation in the incidence of TB among the elderly in this region between 2009 to 2014. GeoDetector was applied to measure the determinant power (q statistic) of risk factors for TB among the elderly. Results The incidence of TB among the elderly exhibited geographical spatial heterogeneity, with a higher incidence in underdeveloped rural areas compared with that in urban areas. Hotspots of TB incidence risk among the elderly were mostly located in north-eastern and southern areas in the study region, far from metropolitan areas. Areas with low risk were distributed mainly in the Beijing-Tianjin metropolitan areas. Social-economic factors had a non-linear influence on elderly TB incidence, with the dominant factors among rural populations being income (q = 0.20) and medical conditions (q = 0.17). These factors had a non-linear interactive effect on the incidence of TB among the elderly, with medical conditions and the level of economic development having the strongest effect (q = 0.54). Conclusions The findings explain spatio-temporal variation in TB incidence and risk determinants of elderly TB in the presence of disparities in social-economic development. High-risk zones were located mainly in rural areas, far from metropolitan centres. Medical conditions and the economic development level were significantly associated with elderly TB incidence, and these factors had a non-linear interactive effect on elderly TB incidence. The findings can help to optimize the allocation of health resources and to control TB transmission in the aging population in this region.

Background Identifying young individuals living with human immunodeficiency virus (HIV) who are unaware of their status is a major challenge for HIV control in China. To address this, an innovative, anonymous vending machine–based urine self-collection for HIV testing (USCT) program was implemented in 2016 in colleges across China. Methods From June 2016 to December 2019, 146 vending machines stocked with urine self-collection kits were distributed on 73 college campuses across 11 provinces of China. Urine samples were collected, delivered, and tested in an anonymous manner. We analyzed the returned rate, reactive rate (likelihood of HIV screening positive), testing effectiveness (the annual number of college students living with HIV screened by USCT or other testing methods), and the spatiotemporal relationship between USCT usage and student activity per college generated from the usage of a social networking application. Results Among the 5178 kits sold, 3109 (60%) samples were returned; of these, 2933 (94%) were eligible for testing. The HIV reactive rate was 2.3% (66 of 2933). The average effectiveness ratio among the 34 participating Beijing colleges was 0.39 (12:31) between USCT and conventional testing methods. A strong spatiotemporal correlation between USCT numbers and online student activity was observed during school semesters in Beijing. Conclusions USCT is a powerful complement to current interventions that target at-risk students and promote HIV testing. The social networking–based evaluation framework can be a guide in prioritizing at-risk target populations.

Previous studies indicate that the incidence of bacillary dysentery is closely related to meteorological factors. However, the impact of temperature and the spatial heterogeneity of the disease in regions of unbalanced socioeconomic development remains unclear. Therefore, this research collected data for 29,639 daily bacillary dysentery cases in children under 5 years of age, as well as the meteorological variables from China's Beijing-Tianjin-Hebei region, to analyze the spatial pattern of bacillary dysentery and reveal its nonlinear association with temperature. The SatScan method was employed first, to detect the spatial heterogeneity of the disease risk, and then the distributed lag nonlinear model (DLNM) was used to analyze the relationships between the daily minimum, mean, and maximum temperatures and bacillary dysentery in the stratified heterogeneous regions. The results indicated that bacillary dysentery incidence presented statistically significant spatial heterogeneity. The area of highest risk was found to be Beijing and its neighboring regions, which have high population densities. There was also a positive association between bacillary dysentery and temperature. Hotter temperatures were accompanied by higher relative risks. In the most likely spatial cluster region, the excess risk (ER) values for a 1°C rise in minimum, mean, and maximum temperatures above the median were 4.65%, 11.30%, and 19.21%, respectively. The effect of temperature on bacillary dysentery peaked at a lag of 3 to 4 days. The findings of this study will aid risk assessments and early warning systems for bacillary dysentery.