Spatial Dynamics of Chickenpox Outbreaks in Rapidly Developing Regions: Implications for Global Public Health.

Objective: The occurrence of chickenpox in rapidly developing areas poses substantial seasonal risk to children. However, certain factors influencing local chickenpox outbreaks have not been studied. Here, we examined the relationship between spatial clustering, heterogeneity of chickenpox outbreaks, and socioeconomic factors in Southern China. Methods: We assessed chickenpox outbreak data from Southern China between 2006 and 2021, comprising both relatively fast-growing parts and slower sub-regions, and provides a representative sample of many developing regions. We analyzed the spatial clustering attributes associated with chickenpox outbreaks using Moran's I and local indicators of spatial association and quantified their socioeconomic determinants using Geodetector q statistics. Results: There were significant spatial heterogeneity in the risk of chickenpox outbreaks, with strong correlations between chickenpox risk and various factors, particularly demographics and living environment. Furthermore, interactive effects among specific are factors, such as population density and per capita residential building area, percentage of households with toilets, percentage of rental housing, exhibited q statistics of 0.28, 0.25, and 0.24, respectively. Conclusion: This study provides valuable insights into the spatial dynamics of chickenpox outbreaks in rapidly developing regions, revealing the socioeconomic factors affecting disease transmission. These implications extend the formulation of effective public health strategies and interventions to prevent and control chickenpox outbreaks in similar global contexts.

Spatiotemporal Distribution and Epidemiological Characteristics of Hospital Admissions for Carbon Monoxide Poisoning in Guangdong, China, 2013-2020.

Objective: This study aimed to determine the spatiotemporal distribution and epidemiological characteristics of hospital admissions for carbon monoxide poisoning (COP) in Guangdong, China, from 2013 to 2020. Methods: Data on age- and sex- specific numbers of hospital admissions due to COP in Guangdong (2013-2020) were collected. Daily temperatures were downloaded through the China Meteorological Data Sharing Service System. We analyzed temporal trends through time series decomposition and used spatial autocorrelation analysis to detect spatial clustering. The distributed lag nonlinear model was used to quantify the effects of temperature. Results: There were 48,854 COP admissions over the study period. The sex ratio (male to female) was 1:1.74. The concentration ratios (M) ranged from 0.73-0.82. The highest risk occurred in January (season index = 3.59). Most cases were concentrated in the northern mountainous areas of Guangdong with high-high clustering. COP in the study region showed significant spatial autocorrelation, and the global Moran's Ivalue of average annual hospital admission rates for COP was 0.447 ( P < 0.05). Low temperatures were associated with high hospital admission rates for COP, with a lag lasting 7 days. With a lag of 0 days, the effects of low temperatures [5th (12 °C)] on COP were 2.24-3.81, as compared with the reference temperature [median (24 °C)]. Conclusion: COP in Guangdong province showed significant temporal and spatial heterogeneity. Low temperature was associated with a high risk of COP, and the influence had a lag lasting 7 days.

Hypertension Prevalence, Awareness, Treatment, and Control and Their Associated Socioeconomic Factors in China: A Spatial Analysis of A National Representative Survey.

OBJECTIVE: We aimed to investigate and interpret the associations between socioeconomic factors and the prevalence, awareness, treatment, and control of hypertension at the provincial level in China. METHODS: A nationally and provincially representative sample of 179,059 adults from the China Chronic Disease and Nutrition Surveillance study in 2015-2016 was used to estimate hypertension burden. The spatial Durbin error model was fitted to investigate socioeconomic factors associated with hypertension indicators. RESULTS: Overall, it was estimated that 29.20% of the participants were hypertensive nationwide, among whom, 34.32% were aware of their condition, 27.69% had received antihypertensive treatment, and 7.81% had controlled their condition. Per capita gross domestic product (GDP) was associated with hypertension prevalence (coefficient: -2.95, 95% CI: -5.46, -0.45) and control (coefficient: 6.35, 95% CI: 1.36, 11.34) among adjacent provinces and was also associated with awareness (coefficient: 2.93, 95% CI: 1.12, 4.74) and treatment (coefficient: 2.67, 95% CI: 1.21, 4.14) in local province. Beds of internal medicine (coefficient: 2.66, 95% CI: 1.08, 4.23) was associated with control in local province. Old dependency ratio (coefficient: -3.58, 95% CI: -5.35, -1.81) was associated with treatment among adjacent provinces and with control (coefficient: -1.69, 95% CI: -2.42, -0.96) in local province. CONCLUSION: Hypertension indicators were not only directly influenced by socioeconomic factors of local area but also indirectly affected by characteristics of geographical neighbors. Population-level strategies should involve optimizing supportive socioeconomic environment by integrating clinical care and public health services to decrease hypertension burden.

Association between Selenium in Soil and Diabetes in Chinese Residents Aged 35-74 Years: Results from the 2010 National Survey of Chronic Diseases and Behavioral Risk Factors Surveillance.

OBJECTIVE: To explore the association between soil selenium levels and the risk of diabetes in Chinese adults aged 35-74 years. METHODS: Data for this study were derived from the China Chronic Diseases and Behavioral Risk Factors Surveillance 2010 survey. Selenium concentrations in soil were obtained from the Atlas of Soil Environmental Background Values in China. A two-level binary logistic regression model was used to determine the association between soil selenium concentrations and the risk of diabetes, with participants nested within districts/counties. RESULTS: A total of 69,332 participants aged 35-74 years, from 158 districts/counties were included in the analysis. Concentrations of selenium in soil varied greatly across the 158 districts/counties, with a median concentration of 0.219 mg/kg ( IQR: 0.185-0.248). The results showed that both Quartile 1 (0.119-0.185 mg/kg) and Quartile 4 (0.249-0.344 mg/kg) groups were positively associated with diabetes compared to a soil selenium concentration of 0.186-0.219 mg/kg (Quartile 2), crude odds ratios ( ORs) (95% CI) were 1.227 (1.003-1.502) and 1.280 (1.048-1.563). The P values were 0.045 and 0.013, for Quartile 1 and Quartile 4 groups, respectively. After adjusting for all confounding factors of interest, the Quartile 1 group became non-significant, and the Quartile 4 group had an adjusted OR (95% CI) of 1.203 (1.018-1.421) relative to the reference group (Quartile 2), the P values was 0.030. No significant results were seen for the Quartile 3 group (0.220-0.248 mg/kg) compared to the reference group. CONCLUSION: Excessive selenium concentrations in soil could increase the risk of diabetes among Chinese adults aged 35-74 years.

Pyrimidine Nucleosides from Streptomyces sp. SSA28.

Eleven new pyrimidine nucleosides (1-11) and 12 known analogues (12-23) were isolated from the marine-derived Streptomyces sp. SSA28. All of the new structures were elucidated by extensive NMR spectroscopic analysis and HRESIMS data. The absolute configurations of compound 1 were determined by X-ray diffraction. The configurations of 2-16 were investigated by ECD calculations. Compounds 11-16 showed cytotoxicity against HCT-116 human colon cancer cell lines with IC50 values from 0.39 ± 0.03 to 6.63 ± 0.47 µM.

Medermycin-Type Naphthoquinones from the Marine-Derived Streptomyces sp. XMA39.

Four new medermycin-type naphthoquinones, strepoxepinmycins A-D (1-4), and one known compound, medermycin (5), were identified from Streptomyces sp. XMA39. Their structures were elucidated by analysis of HRESIMS, 1D and 2D NMR spectroscopic data, and ECD calculations. Among these compounds, strepoxepinmycin A (1) represents a rare 5,10-oxepindione ring system typically formed by a Baeyer-Villiger oxidation, and strepoxepinmycin B (2) is an isolation artifact derived from 1. Bioactivity evaluations of these compounds showed that compounds 3 and 4 exhibited cytotoxicity against HCT-116 and PC-3 cancer cell lines and 4 exhibited moderate inhibition of ROCK 2 protein kinase. In addition, all of the new compounds showed antibacterial activity against Escherichia coli and methicillin-resistant Staphylococcus aureus and antifungal activity against Candida albicans.

Quantifying the influences of various ecological factors on land surface temperature of urban forests.

Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST.

Towards Identifying and Reducing the Bias of Disease Information Extracted from Search Engine Data.

The estimation of disease prevalence in online search engine data (e.g., Google Flu Trends (GFT)) has received a considerable amount of scholarly and public attention in recent years. While the utility of search engine data for disease surveillance has been demonstrated, the scientific community still seeks ways to identify and reduce biases that are embedded in search engine data. The primary goal of this study is to explore new ways of improving the accuracy of disease prevalence estimations by combining traditional disease data with search engine data. A novel method, Biased Sentinel Hospital-based Area Disease Estimation (B-SHADE), is introduced to reduce search engine data bias from a geographical perspective. To monitor search trends on Hand, Foot and Mouth Disease (HFMD) in Guangdong Province, China, we tested our approach by selecting 11 keywords from the Baidu index platform, a Chinese big data analyst similar to GFT. The correlation between the number of real cases and the composite index was 0.8. After decomposing the composite index at the city level, we found that only 10 cities presented a correlation of close to 0.8 or higher. These cities were found to be more stable with respect to search volume, and they were selected as sample cities in order to estimate the search volume of the entire province. After the estimation, the correlation improved from 0.8 to 0.864. After fitting the revised search volume with historical cases, the mean absolute error was 11.19% lower than it was when the original search volume and historical cases were combined. To our knowledge, this is the first study to reduce search engine data bias levels through the use of rigorous spatial sampling strategies.

Spatial dynamic patterns of hand-foot-mouth disease in the People's Republic of China.

Hand-foot-mouth disease (HFMD) is the most common and widespread infectious disease in the People's Republic of China. Although there has been a substantial increase of HFMD in many parts of the country in recent years, its spatial dynamics and determinants remain unclear. When we collected and analysed weekly data on HFMD cases from 1,456 counties and the corresponding meteorological factors from 1 May 2008 to 27 March 2009, it was found that HFMD was spatially dispersed across the country in the summer and winter, while clustered in the spring and autumn. The spatial variation of HFMD was found to be affected by a combination of climate variables, while its spatio-temporal transmission was largely driven by temperature variations with a 7-week lag implying that (i) the dispersal of the disease can be anticipated based on the variation of the temperature and other climate variables; and (ii) the spatial dynamics of HFMD can be robustly predicted 7 weeks ahead of time using temperature data only. The findings reported allow prompt preparation and implementation of appropriate public health interventions to control and prevent disease outbreaks.

Estimation of citywide air pollution in Beijing.

There has been discrepancies between the daily air quality reports of the Beijing municipal government, observations recorded at the U.S. Embassy in Beijing, and Beijing residents' perceptions of air quality. This study estimates Beijing's daily area PM(2.5) mass concentration by means of a novel technique SPA (Single Point Areal Estimation) that uses data from the single PM(2.5) observation station of the U.S Embassy and the 18 PM(10) observation stations of the Beijing Municipal Environmental Protection Bureau. The proposed technique accounts for empirical relationships between different types of observations, and generates best linear unbiased pollution estimates (in a statistical sense). The technique extends the daily PM(2.5) mass concentrations obtained at a single station (U.S. Embassy) to a citywide scale using physical relations between pollutant concentrations at the embassy PM(2.5) monitoring station and at the 18 official PM(10) stations that are evenly distributed across the city. Insight about the technique's spatial estimation accuracy (uncertainty) is gained by means of theoretical considerations and numerical validations involving real data. The technique was used to study citywide PM(2.5) pollution during the 423-day period of interest (May 10, 2010 to December 6, 2011). Finally, a freely downloadable software library is provided that performs all relevant calculations of pollution estimation.

[The influences of shoulder porcelain length on the stress distribution of metal-ceramic crowns].

OBJECTIVE: To analyze the stress distribution induced by simulated intra-oral loads on ceramometal crowns with different length of shoulder porcelain in labial margins. METHODS: Eighteen two-dimensional finite element models of the maxillary central incisor restored with ceramometal crowns were constructed which were designed with different labial terminal locations of metal coping. Different coping alloys and marginal designs were employed in the crown models. The stresses of porcelain veneers and adhesive layers in all models were estimated with different loading locations and angles. RESULTS: Although coping alloys and marginal designs were different, the labial terminal locations of metal coping had no influence on the stress distribution of porcelain veneers and adhesive layers. CONCLUSION: The coping design of short labial margin to add the length of shoulder porcelain of ceramometal restorations can be used clinically.