Exploring the spatial pattern of house collapse rates caused by extreme rainfall in central China: The role of natural and social factors.

The collapse of houses represents a prominent hazard associated with floods, mudslides, and other disastrous events resulting from extreme rainfall. Nevertheless, previous research in this area has been insufficiently dedicated to comprehending the factors that specifically contribute to house collapse triggered by extreme rainfall. This study endeavors to address this knowledge gap by proposing a hypothesis that the occurrence of house collapse, induced by extreme rainfall, demonstrates spatial heterogeneity and is subject to the interactive impacts of various factors. In the study, we investigate the relationship between house collapse rates and natural and social factors in the provinces of Henan, Shanxi, and Shaanxi provinces in 2021. These provinces are representative of flood-prone areas in central China. Spatial scan statistics and GeoDetector model were used to analyze spatial hotspot areas of house collapse rates and determinant power of natural and social factors on the spatial heterogeneity of house collapse rates, respectively. Our analysis reveals that the spatial hotspot areas predominantly concentrated in regions characterized by high rainfall, including areas along riverbanks and low-lying regions. Multiple factors contribute to the variations in house collapse rates. Among these factors, precipitation (q = 0.32) is the most significant, followed by the ratio of brick-concrete houses (q = 0.24), per capita GDP (q = 0.13), elevation (q = 0.13) and other factors. Notably, the interaction of precipitation and slope explains 63 % of the damage pattern, making it the strongest causal factor. The results substantiate our initial hypothesis and underscore the fact that the pattern of damage does not solely rely on a singular factor but rather on the interaction of multiple factors. These findings hold significance in advancing the formulation of more precise strategies aimed at bolstering safety measures and safeguarding properties within regions susceptible to flooding.

Fine-scale population spatialization data of China in 2018 based on real location-based big data.

Accurate location-based big data has a high resolution and a direct interaction with human activities, allowing for fine-scale population spatial data to be realized. We take the average of Tencent user location big data as a measure of ambient population. The county-level statistical population data in 2018 was used as the assigned input data. The log linear spatially weighted regression model was used to establish the relationship between location data and statistical data to allocate the latter to a 0.01° grid, and the ambient population data of mainland China was obtained. Extracting street-level (lower than county-level) statistics for accuracy testing, we found that POP2018 has the best fit with the actual permanent population (R2 = 0.91), and the error is the smallest (MSEPOP2018 = 22.48

A new method for interpolation of missing air quality data at monitor stations.

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.

Unbalanced Risk of Pulmonary Tuberculosis in China at the Subnational Scale: Spatiotemporal Analysis.

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<.001), followed by Guizhou (117/100,000; RR 1.8, 95% CI 1.3-1.9; P<.001) and Tibet (108/100,000; RR 1.7, 95% CI 1.3-2.1; P<.001). The RR for PTB showed a steady downward trend. Gansu (local trend [LT] 0.95, 95% CI 0.93-0.96; P<.001) and Shanxi (LT 0.94, 95% CI 0.92-0.96; P<.001) experienced the fastest declines. However, the RRs for PTB in the western region (such as counties in Xinjiang, Guizhou, and Tibet) were significantly higher than those in the eastern and central regions (P<.001), and the decline rate of the RR for PTB was lower than the overall level (P<.001). 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.

Lagged Effects of Exposure to Air Pollutants on the Risk of Pulmonary Tuberculosis in a Highly Polluted Region.

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.

The "m6A writer" METTL3 and the "m6A reader" IGF2BP2 regulate cutaneous T-cell lymphomas progression via CDKN2A.

It has been established that Cutaneous T-Cell lymphomas (CTCL) are caused by the monoclonal proliferation of T lymphocytes in the skin. This heterogeneous group of diseases represents a significant source of distress to patients since the diagnosis and treatment are often challenging. As one of the most abundant internal modifications in mRNA in higher eukaryotes, N6-methyladenosine (m6A) is widely recognized to affect the development and progression of cancers. However, knowledge on the involvement of m6A in CTCL is still limited. In this work, we revealed the role of METTL3-mediated m6A modification in CTCL progression. ELISA, western blot, and qRT-PCR assays demonstrated that METTL3 was significantly downregulated in CTCL cells both in vivo and in vitro. CCK-8, EdU, flow cytometry, and transwell assays showed that the decline in METTL3 levels was responsible for CTCL cell proliferation and migration. Furthermore, using small interfering RNAs against METTL3 and the RIP assay, we showed that CDKN2A was a key regulator during this process in vitro and in vivo, and insufficient methylation modification blocked the interaction between CDKN2A and m6A reader IGF2BP2, resulting in mRNA degradation. To the best of our knowledge, this is the first study to depict the role of m6A in CTCL development and provide potential bio-targets for therapy.

Impacts of worldwide individual non-pharmaceutical interventions on COVID-19 transmission across waves and space.

Governments worldwide have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic. However, the effect of these individual NPI measures across space and time has yet to be sufficiently assessed, especially with the increase of policy fatigue and the urge for NPI relaxation in the vaccination era. Using the decay ratio in the suppression of COVID-19 infections and multi-source big data, we investigated the changing performance of different NPIs across waves from global and regional levels (in 133 countries) to national and subnational (in the United States of America [USA]) scales before the implementation of mass vaccination. The synergistic effectiveness of all NPIs for reducing COVID-19 infections declined along waves, from 95.4% in the first wave to 56.0% in the third wave recently at the global level and similarly from 83.3% to 58.7% at the USA national level, while it had fluctuating performance across waves on regional and subnational scales. Regardless of geographical scale, gathering restrictions and facial coverings played significant roles in epidemic mitigation before the vaccine rollout. Our findings have important implications for continued tailoring and implementation of NPI strategies, together with vaccination, to mitigate future COVID-19 waves, caused by new variants, and other emerging respiratory infectious diseases.

Risk of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission Among Air Passengers in China.

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.

Spatio-temporal variation in tuberculosis incidence and risk factors for the disease in a region of unbalanced socio-economic development.

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.

Differential expression of miRNAs as biomarkers for predicting the outcomes of diffuse large B-cell lymphoma patients.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) used to be defined as germinal center B-like and non-germinal center B-like subtypes, associated with different prognoses, but the conventional classification does not meet the needs of clinical practice because of DLBCL heterogeneity, a problem that might be improved by selection of miRNAs as biomarkers. METHODS: Twelve patients with DLBCLs were used to screen out the aberrant miRNA profile using miRNA microarray technology in two patient subtypes (six germinal center B-like and six non-germinal center B-like patients). The potential biomarkers were further analyzed using the quantitative reverse transcription-polymerase chain reaction method in 95 DLBCL patients to investigate relationships among expression levels of potent miRNA, clinicopathological features and survival rates of patients. RESULTS: miR-208a-5p, miR-296-5p and miR-1304-5p were screened as potential biomarkers. miR-208a-5p and miR-296-5p were shown to be associated with better survival of patients after Kaplan-Meier analysis, whereas miR-1304-5p overexpression indicated a poor survival prognosis independent of the DLBCL subtype. In addition, changes of miR-296-5p and miR-1304-5p expression, the International Prognostic Index (IPI) status and the age of patients were all independent indicators for DLBCL prognosis. We also found that high miR-208a-5p expression led to better outcomes in DLBCL patients with similar IPI scores; however high miR-1304-5p expression tended to indicate the opposite. CONCLUSIONS: MiR-208a-5p, miR-296-5p and miR-1304-5p levels might be potential biomarkers for the prediction of the prognosis of DLBCL patients.

[Application of different spatial interpolation methods in sodium intake estimation].

OBJECTIVE: The spatial interpolation method was used to estimate the intake of sodium in the areas without dietary sodium intake data. METHODS: The data of dietary sodium consumption in this study are from the 2010-2012 China National Nutrition and Health Surveillance(CNNHS), the CNNHS was carried out on stratified multistage systematic clustered random sampling method with proportional to the population to form a representative sample of China as a whole, including 150 survey site. Dietary data was collected through face-to-face interview, based on a combination of three consecutive days of 24-h recalls combined with a household food weighting method, a total of 48 826 participants aged 20 years old and more were recruited in this study. The average sodium intake among 150 survey sites were calculated according to data of the CNNHS 2010-2012. The accuracy of spatial analysis techniques, such as Inverse Distance Weight, Ordinary Kriging, Cooperative Kriging method and Regression Kriging Interpolation method, was compared in the estimation of dietary sodium intake. The spatial analysis method with the highest accuracy was used to estimate the daily dietary sodium intake of each district and county in China, and then the dietary sodium intake of each province was calculated according to the population weight. RESULTS: The average sodium intake among Chinese adults was 5. 18 g, among which the average intake of men is 5. 33 g and that of women was 5. 03 g. Comparing the accuracy of four spatial analysis method in estimating dietary sodium intake, it was found that the Regression Kriging Interpolation method was superior to the other three methods, with root mean square error and mean absolute error of 0. 54 and 0. 44. The Regression Kriging Interpolation method was used to estimate the dietary sodium intake in different regions of China, the estimated national dietary sodium intake by population weighted calculation was 5. 17 g/d, the estimated national dietary sodium intake was 5. 33 g/d for men and 5. 01 g/d for women. The difference rate between the measured and estimated dietary sodium intake for all age groups was not more than 10%. Shandong Province, Tianjin City and Hebei Province had the highest sodium intake, which was 5. 98 g/d, 5. 83 g/d and 5. 82 g/d, respectively. Guizhou Province had the lowest sodium intake, with an estimated intake value of 4. 27 g/d. CONCLUSION: The spatial interpolation method can be used to estimate the intake of sodium, and the accuracy of Regression Kriging Interpolation method is higher than other spatial interpolation method.

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.

Risk of Coronavirus Disease 2019 Transmission in Train Passengers: an Epidemiological and Modeling Study.

BACKGROUND: Train travel is a common mode of public transport across the globe; however, the risk of coronavirus disease 2019 (COVID-19) transmission among individual train passengers remains unclear. METHODS: We quantified the transmission risk of COVID-19 on high-speed train passengers using data from 2334 index patients and 72 093 close contacts who had co-travel times of 0-8 hours from 19 December 2019 through 6 March 2020 in China. We analyzed the spatial and temporal distribution of COVID-19 transmission among train passengers to elucidate the associations between infection, spatial distance, and co-travel time. RESULTS: The attack rate in train passengers on seats within a distance of 3 rows and 5 columns of the index patient varied from 0 to 10.3% (95% confidence interval [CI], 5.3%-19.0%), with a mean of 0.32% (95% CI, .29%-.37%). Passengers in seats on the same row (including the adjacent passengers to the index patient) as the index patient had an average attack rate of 1.5% (95% CI, 1.3%-1.8%), higher than that in other rows (0.14% [95% CI, .11%-.17%]), with a relative risk (RR) of 11.2 (95% CI, 8.6-14.6). Travelers adjacent to the index patient had the highest attack rate (3.5% [95% CI, 2.9%-4.3%]) of COVID-19 infection (RR, 18.0 [95% CI, 13.9-23.4]) among all seats. The attack rate decreased with increasing distance, but increased with increasing co-travel time. The attack rate increased on average by 0.15% (P = .005) per hour of co-travel; for passengers in adjacent seats, this increase was 1.3% (P = .008), the highest among all seats considered. CONCLUSIONS: COVID-19 has a high transmission risk among train passengers, but this risk shows significant differences with co-travel time and seat location. During disease outbreaks, when traveling on public transportation in confined spaces such as trains, measures should be taken to reduce the risk of transmission, including increasing seat distance, reducing passenger density, and use of personal hygiene protection.

Anonymous Linkage Between College Students and Human Immunodeficiency Virus (HIV) Facilities: Systematic Evaluation of Urine Self-Collection for HIV Testing Initiative in China.

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.

Spatiotemporal Analysis of Men Who Have Sex With Men in Mainland China: Social App Capture-Recapture Method.

BACKGROUND: In China, the cases of newly diagnosed HIV/AIDS in men who have sex with men (MSM) have increased more than tenfold since 2006. However, the MSM population size, geographical distribution, and migration patterns are largely unknown. OBJECTIVE: Our aim is to estimate the number, spatial distribution, and migration of MSM populations in mainland China using big data from social networking. METHODS: We collected 85 days of data on online users of a social networking MSM app in mainland China. Daily online MSM users and their migration across the country were investigated during a holiday period and a nonholiday period. Using the capture-mark-recapture model, we designed an experiment consisting of two independent samples to estimate the total provincial MSM population. RESULTS: The estimate of MSM in mainland China was 8,288,536 (95% CI 8,274,931-8,302,141), accounting for 1.732% (95% CI 1.729%-1.734%) of adult men aged 18 to 64 years. The average daily number of MSM social networking online across mainland China was 1,198,682 during the nonholiday period. The five provinces (including municipalities) with the highest average number of daily online MSM numbers were Guangdong (n=141,712), Jiangsu (n=90,710), Zhejiang (n=72,212), Shandong (n=68,065), and Beijing (n=66,057). The proportion of daily online MSM among adult men in different cities varied from 0.04% to 0.96%, with a mean of 0.20% (SD 0.14%). Three migrating centers-Guangdong, Beijing, and the Yangtze River Delta (Shanghai-Zhejiang-Jiangsu)-accounted for 57.23% of MSM migrants in the county. CONCLUSIONS: The percentage of MSM among adult men in mainland China is at the middle level compared with other Asia and Pacific countries. However, the number of MSM is very large, and the distribution is uneven. Both MSM distribution and migration are highly affected by socioeconomic status.

Spatiotemporal assessment of marine environmental monitoring programme based on DIN concentration in the Yangtze River estuary and its adjacent sea.

The marine environment is rigorously protected in the Yangtze River Estuary (YRE) and its adjacent sea, and routine monitoring is constantly upgraded. Therefore, scientific and efficient monitoring programmes are needed. Nitrogen is one of the most serious pollutants in the YRE. Obtaining the precise pollution areas of water quality grades (WQGs) are a scientific and management issue that requires optimization of monitoring programmes and interpolation methods. Based on spatiotemporal regression point means of surface with non-homogeneity (STR-PMSN), dissolved inorganic nitrogen (DIN) concentrations were estimated in a stratified heterogeneous estuary. The annual average areas of DIN Grades I and II were classified by interpolating the concentrations; the values were 3145 km2, 1626 km2, 2320 km2 and 3758 km2 for February, May, August and November, respectively. This means that November had the best water condition, and May had the worst. Meanwhile, DIN area changes showed that the water condition changed due to removal of data much more in August and May than in February and November. The descending order of importance was August, May, February and November. Every month represented different runoff periods. Monitoring frequency should not be reduced. Removal of sampling data for the third stratum had a significant effect on the area. When the sampling data for outer boundary meshes of the third stratum were removed, the water condition became worse. However, when the sampling data for inner boundary meshes were removed, the water condition improved. New sites should be added to the outer boundary region to avoid interpolation instability and reduce the sensitivity of the existing sites. This study assesses the spatiotemporal effect of the marine environmental monitoring programmes on pollutant distribution by STR-PMSN, and it offers guidance for more precise data acquisition and processing methods in the YRE and its adjacent sea.

A spatiotemporal interpolation method for the assessment of pollutant concentrations in the Yangtze River estuary and adjacent areas from 2004 to 2013.

Nitrogen is one of the most significant pollutants in the Yangtze River estuary (YRE), China. Reliable estimation of nitrogen concentration in the water is crucial for assessment of the water quality of the estuary. Because ocean fronts exist in the YRE, which divide water masses into different regions, it is necessary to account for the heterogeneity of the water surface when predicting nitrogen concentrations. A new geostatistical method, called spatiotemporal point mean of surface with non-homogeneity (ST-PMSN), is proposed to model the non-stationary spatiotemporal random process of nitrogen concentrations between 2004 and 2013 in the YRE. The method considers the spatiotemporal correlation of surface water nitrogen and uses information from both sides of a boundary for heterogeneous water masses. Comparing with several other interpolating methods, including spatial ordinary kriging (OK), stratified ordinary kriging (SOK), point mean of surface with non-homogeneity (P-MSN), spatiotemporal ordinary kriging (STK), and stratified spatiotemporal ordinary kriging (SSTK), the cross-validation results show that ST-PMSN has the highest accuracy, followed by SSTK, STK, P-MSN, SOK, and OK in descending order. ST-PMSN is therefore demonstrated to be effective in estimating the nitrogen pollutant concentrations in a stratified estuary. According to interpolated nitrogen concentrations in the YRE, water quality has generally deteriorated-with fluctuations-from 2004 to 2013. The average annual reduction in area of water quality of Grades I and II from 2004 to 2013 was 1.10%. At the same time, the average annual increase in area of water quality of Grades III and IV was 0.89% and that of Grade V was 0.21%. The results of this study provide a new and more accurate interpolating method for assessing the pollutant concentration in the marine and offers guidance for more precise classification of water quality in the YRE.

Evaluation of scrub typhus diagnosis in China: analysis of nationwide surveillance data from 2006 to 2016.

BACKGROUND: Scrub typhus is a life-threatening disease caused by Orientia tsutsugamushi, and specific antimicrobial medicine is available. Early and accurate diagnosis is essential for reducing the risk of severe complications and death. In this study, we aimed to evaluate the case diagnosis situation among medical care institutions and geographical regions in China, and the results will benefit both clinical practice and the disease surveillance system. METHODS: We extracted individual scrub typhus case data 2006-2016 from a national disease surveillance system in China. The diagnosis category and interval time from illness onset to diagnosis were compared among three levels of medical care institutions and provinces. The descriptive analysis method was performed in our study. RESULTS: During the 11-year study period, 93 481 scrub typhus cases, including 57 deaths, were recorded in the nationwide surveillance system. The overall proportion of laboratory-confirmed cases was only 4.7%, and this proportion varied greatly among primary medical centres (2.8%), county level hospitals (4.2%), and city level hospitals (6.3%). Notably, the proportion of laboratory-confirmed cases has consistently decreased from 16.3% in 2006 to 2.6% in 2016, and the same decreasing trend was found among all three levels of medical care institutions. The interval from illness onset to case diagnosis (Tdiag) for all cases was 5 days (interquartile range [IQR]: 2-9 days) and decreased from 7 days (IQR: 3-11 days) in 2006 to 5 days (IQR: 2-8 days) in 2016. The risk of death for patients with a Tdiag of > 7 days was 2.2 times higher (OR = 2.21, 95% CI: 1.05-5.21) than that of patients with a Tdiag of < 2 days. CONCLUSIONS: The interval time from illness onset to diagnosis for scrub typhus cases decreased greatly in China; however, the diagnosis rate of cases with laboratory-confirmed results must be increased among all levels of medical care institutions to reduce both the risk of death and the misuse of antibiotics associated with scrub typhus.

Geographical detection of groundwater pollution vulnerability and hazard in karst areas of Guangxi Province, China.

Groundwater pollution is a critical concern in karst areas. This study used the PLEIK (P: protective cover; L: land use; E: epikarst development; I: infiltration conditions; K: karst development) method to assess the vulnerability of groundwater pollution in Guangxi Province, which is the largest karst area in China. The pollution sources and attenuation consist of groundwater pollution hazards. The attributions for the vulnerability and hazard were measured using the geodetector method from geographical information system in Luzhai County in Guangxi. The results confirmed that the vulnerability of groundwater pollution was higher in karst areas than in non-karst areas. In Guangxi, 36.35% of the groundwater samples were polluted. A total of 49.73% of the areas in Luzhai County contained hazardous levels of pollution. The risk assessment map, which interacted with the vulnerability and hazards, was 58.2% similar to the groundwater pollution distribution. The influence of the hazard on groundwater pollution was 2.6 times that of the vulnerability. It is crucial to control pollution sources to prevent groundwater pollution.