Health Science Data Research Articles

Spatial-temporal distribution of neglected tropical diseases burdens in China from 2005 to 2020

BackgroundOut of the 21 neglected tropical diseases (NTDs) listed by the World Health Organization, 15 affect the People’s Republic of China. Despite significant achievements in controlling NTDs, comprehensive assessments of the disease burden based on actual case data and detailed information on spatial and temporal dynamics are still lacking. This study aims to assess the disease burden and spatial–temporal distribution of NTDs in China from 2005 to 2020, to provide a reference for the formulation of national health agendas in line with the global health agenda, and guide resource allocation.MethodsThe number of cases and deaths of major NTDs in China from 2005 to 2020 were downloaded from the China Public Health Science Data Center (https://www.phsciencedata.cn/Share/index.jsp) of the Chinese Center for Disease Control and Prevention and relevant literatures. Simplified formulas for disability-adjusted life years (DALYs) helped estimate the years of life lost (YLLs), years lived with disability (YLDs), and total DALYs. Spatial autocorrelation analysis of the average NTDs burden data for the years 2005 to 2020 was evaluated using Moran's I statistic.ResultsChina's overall NTDs burden decreased significantly, from 245,444.53 DALYs in 2005 to 18,984.34 DALYs in 2020, marking a reduction of 92.27%. In 2005, the DALYs caused by schistosomiasis and rabies represent a substantial proportion of the total disease burden, accounting for 65.37% and 34.43% respectively. In 2015, Hunan and Sichuan provinces had the highest diversity of NTDs, with 9 and 8 number of different NTDs reported respectively. And the highest disease burden was observed in Sichuan (242,683.46 DALYs), Xizang Zizhiqu (178,318.99 DALYs) and Guangdong (154,228.31 DALYs). The “high-high” clustering areas of NTDs were mainly in China's central and southern regions, as identified by spatial autocorrelation analysis.ConclusionsChina has made unremitting efforts in the prevention and control of NTDs, and the disease burden of major NTDs in China has decreased significantly. Using the One Health concept to guide disease prevention and control in the field to effectively save medical resources and achieve precise intervention.Graphical abstract

The spatial-temporal distribution of hepatitis B virus infection in China,2006–2018

ObjectivesHepatitis B is a liver disease caused by Hepatitis B virus (HBV) infection and is highly prevalent in China. To better understand the epidemiological characteristics of hepatitis B in China and develop effective disease control strategies, we employed temporal and spatial statistical methods.MethodsWe obtained HBV incidence data from the Public Health Science Data Center of the Chinese Center for Disease Control and Prevention for the years 2006 to 2018. Using Geographic Information System (GIS) and SaTScan scanning technology, we conducted spatial autocorrelation analysis and spatiotemporal scan analysis to create a map and visualize the distribution of hepatitis B incidence.ResultsWhile hepatitis B incidence rebounded in 2011 and 2017, the overall incidence in China decreased.In the trend analysis by item, the incidence varies from high to low. The global spatial autocorrelation analysis revealed a clustered distribution, and the Moran index analysis of spatial autocorrelation within local regions identified five provinces as H-H clusters (hot spots), while one province was an L-L cluster (cold spot). Spatial scan analysis identified 11 significant spatial clusters.ConclusionsWe found significant clustering in the spatial distribution of hepatitis B incidence and positive spatial correlation of hepatitis B incidence in China. We also identified high-risk times and regional clusters of hepatitis B incidence.

Next-generation statistical methodology: Advances health science research

Accurately modeling health science data is crucial for advancing medical research and improving patient outcomes. Traditional statistical analysis methods face significant challenges due to the complexity and diversity of health sciences data. This article introduces a groundbreaking statistical framework designed to overcome these challenges by developing a next-generation family of distributions, with a special focus on the versatility of the Weibull distribution. The data used in this study has been thoroughly authenticated to ensure reliability and validity. Comprehensive Monte Carlo simulations revealed that the Maximum Product of Spacing Estimator is the most effective among seven-point estimation methods, according to standard metrics. Additionally, the study identifies optimal methods for analyzing various types of lifetime data, including the Maximum Product of Spacing Estimator for pharmaceutical efficacy (ED50), the Least Squares Estimator for psychiatric treatment durations, the Cramer-von Mises Estimator for data on 43 leukemia patients and for survival periods of 20 leukemia patients, and the Right Tail Anderson-Darling Estimator for remission times of 128 bladder cancer patients. The adaptability and flexibility of the next-generation Weibull distribution set it apart as the best match among its contemporaries.

Typhoid and paratyphoid fever epidemiological indicators and spatiotemporal analysis in China from 2004 to 2019

Typhoid and paratyphoid fever are systemic infections caused by Salmonella Typhi and Salmonella Paratyphi. These diseases are endemic in many parts of China, occurring periodically throughout the year. Epidemiological features, temporal trends, and spatial distribution of these fevers were analyzed using GraphPad Prism 9 with data collected by China's Public Health Science Data Center from 2004 to 2019. Charts were generated to depict their incidence across provinces, years, age groups, and occupations. Spatial clustering was assessed using ArcGIS 10.5 and Moran's I index. SaTScan 9.5 was employed to analyze their spatiotemporal distribution. From 2004 to 2019, China reported 197,623 cases of typhoid fever, resulting in 72 deaths, and 84,583 cases of paratyphoid fever, with 17 fatalities, showing a yearly reduction. Epidemic zones for these diseases are primarily in Yunnan, Guangxi, Guizhou, and other southwestern regions, affecting predominantly peasants and students. Children and adolescents are particularly vulnerable. Due to the epidemic nature of these diseases, they can occur year-round, with peaks in the summer months. This study provides a comprehensive understanding of their epidemiological characteristics and geographic distribution in China, emphasizing the need for authorities to improve living conditions, implement preventive measures, and develop effective treatments and vaccines in these high-risk areas.

Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China

BackgroundChina is confronted with the significant menace posed by hemorrhagic fever with renal syndrome (HFRS). Nevertheless, the long-term spatial-temporal variations, regional prevalence patterns, and fundamental determinants' mechanisms for HFRS remain inadequately elucidated. MethodsNewly diagnosed cases of HFRS from January 2004 to December 2019 were acquired from the China Public Health Science Data repository. We used Age-period-cohort and Bayesian Spacetime Hierarchy models to identify high-risk populations and regions in mainland China. Additionally, the Geographical Detector model was employed to quantify the determinant powers of significant driver factors to the disease. ResultsA total of 199,799 cases of HFRS were reported in mainland China during 2004–2019. The incidence of HFRS declined from 1.93 per 100,000 in 2004 to 0.69 per 100,000 in 2019. The incidence demonstrated an inverted U-shaped trend with advancing age, peaking in the 50–54 age group, with higher incidences observed among individuals aged 20–74 years. Hyperendemic areas were mainly concentrated in the northeastern regions of China, while some western provinces exhibited a potential upward trend. Geographical detector model identified that the spatial variations of HFRS were significantly associated with the relative humidity (Q = 0.36), forest cover (Q = 0.26), rainfall (Q = 0.18), temperature (Q = 0.16), and the surface water resources (Q = 0.14). ConclusionsThis study offered comprehensive examinations of epidemic patterns, identified high-risk areas quantitatively, and analyzed factors influencing HFRS transmission in China. The findings may contribute to the necessary implementations for the effective prevention and control of HFRS.

A new hybrid model SARIMA-ETS-SVR for seasonal influenza incidence prediction in mainland China.

Seasonal influenza is a serious public health issue in China. This study aimed to develop a new hybrid model for seasonal influenza incidence prediction and provide reference information for early warning management before outbreaks. Data on the monthly incidence of seasonal influenza between 2004 and 2018 were obtained from the China Public Health Science Data Center website. A single seasonal autoregressive integrated moving average (SARIMA) model and a single error trend and seasonality (ETS) model were built. On this basis, we constructed SARIMA, ETS, and support vector regression (SARIMA-ETS-SVR) hybrid model. The prediction performance was determined by comparing mean absolute error (MAE), mean square error (MSE), mean absolute percentage error (MAPE), and root mean square error (RMSE) indices. The optimum SARIMA model was SARIMA (0,1,0) (0,0,1)12. Error trend and seasonality (ETS) (M,A,M) was the SARIMA optimal model. For the fitting performance, the SARIMA-ETS-SVR hybrid model achieved the lowest values of MAE, MSE, and RMSE, in addition to the MAPE. In terms of predictive performance, the SARIMA-ETS-SVR hybrid model had the lowest MAE, MSE, MAPE, and RMSE values among the three models. The study demonstrated that the SARIMA-ETS-SVR hybrid model provides better generalization ability than a single SARIMA model and a single ETS model, and the predictions will provide a useful tool for preventing this infectious disease.

Epidemiologic changes of infectious diseases in the post-SARS era in China, 2004–2018

ObjectivesTo outline 44 major infectious diseases in the post-SARS (severe acute respiratory syndrome) in China and describe their long-term trends and changes by age, sex, epidemic season, and province.BackgroundAfter the outbreak of severe acute respiratory syndrome (SARS) in 2003, with the change of infectious disease prevention and control system and the improvement of residents’ quality of life, the incidence and mortality of infectious diseases have undergone major changes.MethodsThe data of 44 major infectious diseases in China from 2004 to 2018 were obtained from the monthly analysis report of the China Information System for Disease Control and Prevention (CISDCP) and the Public Health Science Data Center. Joinpoint r regression models were used to examine trends in incidence and mortality for 44 major and important infectious diseases from 2004 to 2018.ResultsFrom 2004 to 2018, 20,105, 500, 772 patients (10, 306, 546, 523 males and 9, 798, 954, 249 females) were diagnosed with 44 major infectious diseases. The overall incidence of 44 infectious diseases increased significantly from 294.6 per 100,000 people in 2004 to 479.1 per 100,000 people in 2010, with 7.9% APC (95% CI 5.2% -10.7%, P < 0.001), then slowed, and then increased to 561.2 per 100,000 people in 2018, with 1.5% APC (-0.1%—3.2%, P = 0.070). The overall mortality rose significantly, from 0.49 to 1.13 per 100,000 people between 2004 and 2011, with an APC increase of 11.6% (7.7% -15.6%, P < 0.001), and then remained stable until 2018. Among these, the prevalence of vaccine-preventable diseases and gastrointestinal & enteroviral diseases remained high and increased year by year. Patients with zoonotic diseases have the greatest risk of death, while patients with sexually transmitted and blood-borne diseases have the greatest number of deaths. Incidence rates vary considerably across geographic regions. Western China has a disproportionate burden of infectious diseases compared with eastern regions.ConclusionsAfter the event of SARS in 2003, infectious disease preventing and controlling model has undergone major changes in China, and certain achievements have been made in this field. Although overall morbidity and case fatality rates are still rising, they have leveled off. In reducing the disproportionate disease burden in the western region, expanding vaccination programs, preventing further increases in rates of sexually transmitted diseases, renewing efforts for emerging and persistent infectious diseases, and addressing seasonal and unpredictable outbreaks (such as the COVID-19 pandemic), there are still remain many challenges.

A hybrid model for tuberculosis forecasting based on empirical mode decomposition in China

BackgroundPulmonary Tuberculosis is a major public health problem endangering people's health, a scientifically accurate predictive model is of great practical significance for the prevention and treatment of pulmonary tuberculosis.MethodsThe reported incidence data of pulmonary tuberculosis were from the National Public Health Science Data Center (https://www.phsciencedata.cn/). The ARIMA, LSTM, EMD-SARIMA, EMD-LSTM, EMD-ARMA-LSTM models were established using the reported monthly incidence of tuberculosis reported in China from January 2008 to December 2018. The MSE, MAE, RMSE and MAPE were used to evaluate the performance of the models to determine the best model.ResultsComparing decomposition-based single model with undecomposed single model, it was found that: when predicting the incidence trend in the next year, compared with SARIMA model, the MSE, MAE, RMSE and MAPE of EMD-SARIMA decreased by 39.3%, 19.0%, 22.1% and 19.8%, respectively. The MSE, MAE, RMSE and MAPE of EMD-LSTM were reduced by 40.5%, 12.8%, 22.9% and 12.7%, respectively, compared with the LSTM model; Comparing the decomposition-based hybrid model with the decomposition-based single model, it was found that: when predicting the incidence trend in the next year, compared with EMD-SARIMA model, the MSE, MAE, RMSE and MAPE of EMD-ARMA-LSTM model decreased by 21.7%, 10.6%, 11.5% and 11.2%, respectively. The MSE, MAE, RMSE and MAPE of EMD-ARMA-LSTM were reduced by 16.7%, 9.6%, 8.7% and 12.3%, respectively, compared with EMD-LSTM model. Furthermore, the performance of the model were consistent when predicting the incidence trend in the next 3 months, 6 months and 9 months.ConclusionThe prediction performance of the decomposition-based single model is better than that of the undecomposed single model, and the prediction performance of the combined model using the advantages of different models is better than that of the decomposition-based single model, so the EMD-ARMA-LSTM combination model can improve the prediction accuracy better than other models, which can provide a theoretical basis for predicting the epidemic trend of pulmonary tuberculosis and formulating prevention and control policies.

Analysis and prediction of the incidence and prevalence trends of gonorrhea in China

ABSTRACT To understand the epidemiological trend of gonorrhea in China from 2004 to 2021, predict the prevalence of the disease, and provide basic theory and data support for monitoring and managing gonorrhea. Gonorrhea incidence data in China from 2004 to 2021 were collected through the China Public Health Science Data Center and National Administration of Disease Prevention and Control, and the incidence and epidemiological characteristics were analyzed. Statistical analysis was performed using Joinpoint and autoregressive integrated moving average (ARIMA) models. A linear correlation model was used to analyze the correlation between gross domestic product (GDP) and the incidence rate. From 2004 to 2021, a total of 2,289,435 cases of gonorrhea were reported in China, with an average reported incidence rate of 9.46/100,000 people and a downward followed by an upward trend. Individuals with gonorrhea were primarily 20–30 y of age, with 1,034,847 cases (53.38%) from 2004 to 2018. The trend of increasing incidence was most obvious in the 10–20 age group (5,811 cases in 2004 to 12,752 cases in 2018, AAPC = 6.1, P < .001). The incidence of gonorrhea in China was negatively correlated with GDP from 2004 to 2021 (r = -0.547, P = .019). The correlation coefficient between the average incidence growth rate of each region from 2012 to 2018 and the average growth rate of regional GDP was 0.673 (P < .01). The root mean square error (RMSE) of the ARIMA model was 4.89%, showing powerful performance. There would be 97,910 gonorrhea cases in 2023 as predicted by the model.

Impact of urbanization on morbidity of hepatitis A: a national panel study in China during 2005–2018

BackgroundThe effect of urbanization on the morbidity of hepatitis A remains unclear. We aimed to estimate the association between various urbanization-related indices and hepatitis A morbidity in China.MethodsData on the annual morbidity of hepatitis A, urbanization-related measures (i.e., gross domestic product per capita, the number of hospitalization beds per 1000 persons, illiteracy rate, tap water coverage, motor vehicles per 100 persons, population density, and the proportion of arable land), and meteorological factors in 31 provincial-level administrative divisions of Chinese mainland during 2005–2018 were collected from the National Population and Health Science Data Sharing Platform, China Statistical Yearbooks, and the China Meteorological Data Sharing Service System, respectively. Generalized linear mixed models were applied to quantify the impacts of different urbanization-related indices on the morbidity of hepatitis A in China after adjusting for covariates.ResultsA total of 537,466 hepatitis A cases were reported in China during 2005–2018. The annual morbidity had a decline of 79.4% from 5.64 cases to 1.16 cases per 100,000 people. There were obvious spatial variations with higher morbidity in western China. Nationally, gross domestic product per capita and the number of hospitalization beds per 1000 persons increased from 14,040 to 64,644 CNY and from 2.45 to 6.03 during 2005–2018, respectively. The illiteracy rate decreased from 11.0 to 4.9%. Gross domestic product per capita [relative risk (RR) = 0.96, 95% confidence interval (CI): 0.92–0.99], and the number of hospitalization beds per 1000 persons (RR = 0.79, 95% CI: 0.75–0.83) were associated with the declined morbidity of hepatitis A. By contrast, the increased morbidity of hepatitis A was linked to the illiteracy rate (RR = 1.04, 95% CI: 1.02–1.06). Similar influential factors were detected for children and adults, with greater effects witnessed for children.ConclusionsPeople in the western region suffered the heaviest burden of hepatitis A in Chinese mainland. Nationally, there was a sharp decline in the morbidity of hepatitis A. The urbanization process was associated with the reduction of hepatitis A morbidity in China during 2005–2018.Graphical

Spatial clustering analysis of scarlet fever incidence in China from 2016 to 2020

To investigate the incidence trend and spatial clustering characteristics of scarlet fever in China from 2016 to 2020 to provide evidence for development of regional disease prevention and control strategies. The incidence data of scarlet fever in 31 provinces and municipalities in mainland China from 2016 to 2020 were obtained from the Chinese Health Statistics Yearbook and the Public Health Science Data Center led by the Chinese Center for Disease Control and Prevention.The three-dimensional spatial trend map of scarlet fever incidence in China was drawn using ArcGIS to determine the regional trend of scarlet fever incidence.GeoDa spatial autocorrelation analysis was used to explore the spatial aggregation of scarlet fever in China in recent years. From 2016 to 2020, a total of 310 816 cases of scarlet fever were reported in 31 provinces, municipalities directly under the central government and autonomous regions, with an average annual incidence of 4.48/100 000.The reported incidence decreased from 4.32/100 000 in 2016 to 1.18/100 000 in 2020(Z=103.47, P < 0.001).The incidence of scarlet fever in China showed an obvious regional clustering from 2016 to 2019(Moran's I>0, P < 0.05), but was randomly distributed in 2020(Moran's I>0, P=0.16).The incidence of scarlet fever showed a U-shaped distribution in eastern and western regions of China, and increased gradually from the southern to northern regions.Inner Mongolia Autonomous Region and Hebei and Gansu provinces had the High-high (H-H) clusters of scarlet fever in China. Scarlet fever still has a high incidence in China with an obvious spatial clustering.For the northern regions of China with H-H clusters of scarlet fever, the allocation of health resources and public health education dynamics should be strengthened, and local scarlet fever prevention and control policies should be made to contain the hotspots of scarlet fever.

PD24-11 HOT CLEAR CELL RENAL CELL CARCINOMA IMMUNE STATUS: ILLUSION OR REALITY?

You have accessJournal of UrologyCME1 Apr 2023PD24-11 HOT CLEAR CELL RENAL CELL CARCINOMA IMMUNE STATUS: ILLUSION OR REALITY? Yi Lu and Hongjun Li Yi LuYi Lu More articles by this author and Hongjun LiHongjun Li More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003302.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The drivers and resistors of the anti-tumor response remain incompletely elucidated. High tumor mutation burden (TMB) and increased infiltration by T cells are associated with the answer to immune checkpoint inhibitors ICIs. We conducted the bioinfomatic study to better understand immunotherapy resistance in clear cell renal cell carcinoma (ccRCC). METHODS: The patients and sequencing data were selected from The Cancer Genome Atlas KIRC (TCGA-KIRC), and a clinical trial dataset. To classify worse-survival ccRCC resistant to immunotherapy, immune prognosis model (IPM) risk score classifier was constructed with prognostic costimulatory molecule genes through survival analysis and validated as well. For function analysis, ESTIMATE, ImmuCellAI, TIDE, and Gene Oncology (GO) were used. RESULTS: The 366 Co-expressed genes (CEGs) correlated with IPM risk score were enriched with p<0.05 and correlation |R-value|>0.5. GO analysis indicated CEGs were enriched within immune-associated gene sets, such as T cell homeostasis. TIDE algorithm predicted all the patients' response to ICIs, and non-responders were enriched in higher IPM risk scores and a real-world ICIs-treated ccRCC cohort validated it with a consistent finding with p=0.028 in chi-square test. ESTIMATE algorithm showed the ESTIMATE, and immune scores of high-risk patients, markedly increased compared with low-risk patients. Nevertheless, tumor purity was thinner than low-risk patients. Besides, TMB and cytolytic activity were higher in high-risk patients. ImmuCellAI algorithm revealed the levels of CD8+ T cells, CD4+ T cells, dendritic cells, and MAIT, together with macrophages, increased in the tumor microenvironment of high-risk patients. The TIDE T cell function estimate was used to test the T cell dysfunction of high-risk patients, which was markedly worse compared with low-risk patients. Meanwhile, immune inhibiting cells, namely exhausted T cells, nTreg cells, iTreg cells, and cancer associated fibroblast (CAF), had an increased fraction in high-risk ccRCC. Remarkably, the microsatellite instability (MSI) score was lower in high-risk ccRCC. Interestingly, IPM risk level was independent from MSI level in prognostic influence. CONCLUSIONS: We found a subtype of refractory ccRCC (IPM high risk), and subsequent function analysis indicated the reason for its insensitivity to immune blockades was T cell dysfunction. In IPM high-risk ccRCC, T cells' high infiltration, hot immune status, is an illusion. The reality is the increased infiltration of dysfunctional CD8+ and CD4+ T cells, immunosuppressive cells (i.e., iT-regs, nT-regs, and CAFs) as well as low MSI. Source of Funding: This work is supported by the grant from National Population Health Science Data Sharing Service Platform Clinical Medical Science Data Center (NCMI-ABD02-201906) to Hongjun Li © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e727 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Yi Lu More articles by this author Hongjun Li More articles by this author Expand All Advertisement PDF downloadLoading ...

Epidemiological characteristics of typhus in China, 1950-2021

Objective: To analyze the epidemiological characteristics of typhus in China from 1950 to 2021, and discuss the challenges in typhus prevention and control in China and suggest future prevention and control strategies. Methods: Based on the reported data of typhus from 1950 to 2021 in China from the Infectious Disease History Database of China Public Health Science Data Center and the National Notifiable Infectious Disease Reporting Information System of Chinese Center for Disease Control and Prevention, we conducted a descriptive statistical analysis. Mann-Kendall test and circular distribution method were used to analyze the incidence, mortality and case fatality of typhus to reveal the temporal, spatial and population distributions and diagnosis of typhus in China. Results: From 1950 to 2021, a total of 452 965 typhus cases and 7 339 typhus deaths were reported in China, with the cases numbers exceeding 10 000 in 14 years of the 1950s, 1960s and 1980s, respectively. Since 1990s, the reported cases and incidence rate of typhus have decreased dramatically and the most cases were sporadic. However, the reported typhus cases in Anhui, Hubei, Hunan Provinces showed significant uptrends. Although typhus could occur all the year round, but the seasonality was observed with the incidence mainly in summer and autumn. For different provinces from the north to the south, the peaks of typhus' monthly incidence tended to shift to earlier dates. The male to female ratio of the cases was 1.01∶1 (18 529∶18 366). However, more cases occurred in women in recent years. The cases aged ≤9 years accounted for the highest proportion (18.9%), but the number of cases aged ≥50 years showed an upward trend. Most cases were farmers with the proportion increasing year by year. Moreover, the cases in students and scattered-living children also accounted for relatively higher proportions. The median of the interval between onset and diagnosis of typhus was 6 days. Most cases were clinically diagnosed, while the proportion of laboratory-confirmed cases was low and most laboratory cases were confirmed by Well-Felix reaction. Conclusions: Although the incidence and mortality of typhus in China has decreased significantly, the risk for local typhus outbreaks still exists. The prevention and control of typhus still face many challenges. It is indispensable to strengthen the pathogen detection and surveillance for typhus in China.

Harnessing high-dimensional data in environmental health sciences

Harnessing high-dimensional data in environmental health sciences

How meteorological factors impacting on scrub typhus incidences in the main epidemic areas of 10 provinces, China, 2006-2018.

Scrub typhus, caused by Orientia tsutsugamushi, is a serious public health problem in the Asia-Pacific region, threatening the health of more than one billion people. China is one of the countries with the most serious disease burden of scrub typhus. Previous epidemiological evidence indicated that meteorological factors may affect the incidence of scrub typhus, but there was limited evidence for the correlation between local natural environment factors dominated by meteorological factors and scrub typhus. This study aimed to evaluate the correlation between monthly scrub typhus incidence and meteorological factors in areas with high scrub typhus prevalence using a distributed lag non-linear model (DLNM). The monthly data on scrub typhus cases in ten provinces from 2006 to 2018 and meteorological parameters were obtained from the Public Health Science Data Center and the National Meteorological Data Sharing Center. The results of the single-variable and multiple-variable models showed a non-linear relationship between incidence and meteorological factors of mean temperature (Tmean), rainfall (RF), sunshine hours (SH), and relative humidity (RH). Taking the median of meteorological factors as the reference value, the relative risks (RRs) of monthly Tmean at 0°C, RH at 46%, and RF at 800 mm were most significant, with RRs of 2.28 (95% CI: 0.95-5.43), 1.71 (95% CI: 1.39-2.09), and 3.33 (95% CI: 1.89-5.86). In conclusion, relatively high temperature, high humidity, and favorable rainfall were associated with an increased risk of scrub typhus.

Evaluation of the impact of the Japanese encephalitis vaccine included in an expanded immunization program on the reported incidence rate of Japanese encephalitis in Gansu province-based on interrupted time series

Objective: To evaluate the impact of the Japanese encephalitis vaccine included in an expanded immunization program on the reported incidence rate of Japanese encephalitis in Gansu province. Methods: Information on the reported incidence rate of Japanese encephalitis in Gansu province from 1987 to 2019 was collected through the National Population Health Science Data Center and the China Disease Prevention and Control Information System. In addition, the trend of Japanese encephalitis reported incidence rate in Gansu province before and after the inclusion of the Japanese encephalitis vaccine in the expanded immunization program was analyzed using an interrupted time-series design. Results: The annual reported incidence rate of Japanese encephalitis in Gansu province from 1987 to 2019 was 0.448/per 100 000. However, after the inclusion of the Japanese encephalitis vaccine in the expanded immunization program in Gansu province in 2008, the amount of change in the level of Japanese encephalitis reported incidence rate was -2.223/per 100 000 (t=-2.90, P=0.007), the amount of change in the slope of Japanese encephalitis reported incidence rate was 0.082 (t=2.87, P=0.008) with the slope of Japanese encephalitis reported incidence rate as 0.071 (β1+β3=0.071). Conclusions: The Japanese encephalitis vaccine has achieved good prevention and control effects in Gansu province in the short term after its inclusion in the expanded immunization program, but outbreaks of Japanese encephalitis have still occurred. Therefore, in the future, Gansu province should promptly adjust the immunization strategy of the Japanese encephalitis vaccine, and strengthen the vaccination of the adult population, especially the rural adult population in the southeastern region of Gansu province, based on the continued focus on the works on Japanese encephalitis vaccination for children and adolescents.

Reframing the environment in data-intensive health sciences

In this paper, we analyse the relation between the use of environmental data in contemporary health sciences and related conceptualisations and operationalisations of the notion of environment. We consider three case studies that exemplify a different selection of environmental data and mode of data integration in data-intensive epidemiology. We argue that the diversification of data sources, their increase in scale and scope, and the application of novel analytic tools have brought about three significant conceptual shifts. First, we discuss the EXPOsOMICS project, an attempt to integrate genomic and environmental data which suggests a reframing of the boundaries between external and internal environments. Second, we explore the MEDMI platform, whose efforts to combine health, environmental and climate data instantiate a reframing and expansion of environmental exposure. Third, we illustrate how extracting epidemiological insights from extensive social data collected by the CIDACS institute yields innovative attributions of causal power to environmental factors. Identifying these shifts highlights the benefits and opportunities of new environmental data, as well as the challenges that such tools bring to understanding and fostering health. It also emphasises the constraints that data selection and accessibility pose to scientific imagination, including how researchers frame key concepts in health-related research.

Analysis on incidence trend of liver cancer in China, 2005-2016

Objective: To understand the incidence trend of liver cancer in China from 2005 to 2016, and explore the correlation between the incidence trend of liver cancer and the incidence trend of hepatitis B. Methods: The incidence data of liver cancer in China from 2005 to 2016 were collected from the Annual Report of Cancer Registry in China. The incidence data of hepatitis B were collected from China Public Health Science Data Center. World standardized incidence rate (WSR) was calculated according to the World Segi's population. Joinpoint regression model was used to analyze the trend of WSR of liver cancer [measured by average annual percentage change (AAPC)]. The age-period-cohort model was fitted to analyze the age, period and cohort effects in people aged 20- years and above. Pearson correlation coefficient was used to explore the correlation between the incidence of liver cancer and the incidence of hepatitis B. Results: The crude incidence of liver cancer in China showed a trend of first increase before 2009 and then relatively stable. The world standardized morbidity rate of liver cancer in China decreased from 19.11 per 100 000 in 2005 to 17.74 per 100 000 in 2016 (AAPC=-0.5%, 95%CI: -1.3%-0.3%, P=0.240). The incidence of liver cancer in male decreased significantly (AAPC=-1.0%, 95%CI: -1.5%--0.5%, P=0.001). The incidence of liver cancer in women increased from 2005 to 2010 [annual percentage change (APC)=1.7%, 95%CI: -0.1%-3.4%, P=0.059] but showed a significant decrease trend from 2010 to 2016 (APC=-1.6%, 95%CI: -2.3%--1.0%, P=0.001). From 2005 to 2016, the incidence of liver cancer showed a decreasing trend in urban areas (AAPC=-0.3%, 95%CI: -0.8%-0.3%, P=0.316) and rural areas (AAPC=-3.9%, 95%CI: -4.4%--3.3%, P<0.001). Risk for liver cancer increased with age, while the period effect showed a trend of first increase then decrease and cohort effect showed a decrease trend. The morbidity rates of both hepatitis B and liver cancer showed decrease trends from 2009 to 2016, and there was a significant correlation (r=0.71, 95%CI: 0.01-0.94, P=0.048). Conclusions: From 2005 to 2016, the morbidity rate of liver cancer in China showed a decrease trend, and there were significant gender and urban-rural area specific differences. Age effect had a great impact on the risk for liver cancer. With the progress of population aging in China, liver cancer is still a public health problem, to which close attention needs to be paid.

Changing trend in reported hepatitis B incidence among Chinese residents, 2004 – 2017

Objective To analyze the trend of reported incidence of hepatitis B (HB) in China from 2004 to 2017 to provide evidences for developing strategies on HB prevention and control. Methods From National Public Health Science Data Center, we extracted the data on HB incidence in 31 provincial-level administrative divisions (not including Chinese Taiwan, Hong Kong Special Administrative Region and Macao Special Administrative Region) reported from March 2004 through March 2017. The average annual percentage change (AAPC) in region-, gender- and age group-specific HB incidence were calculated to assess variation trend of HB incidence during the period. Results From 2004 to 2017, the average reported incidence (per 100 000 population) of HB for the 31 divisions were 70.50, 75.57, 84.82, 89.00, 88.52, 88.82, 79.46, 81.54, 80.68, 71.12, 69.05, 68.57, 68.74 and 72.61, with no significant variation in the reported incidence as a whole (AAPC = 0.2%, P > 0.05); while, the increased HB incidences were reported in 9 of the divisions, with the APPCs of 5.80% for Shanxi, 4.20% for Anhui, 1.50% for Jiangxi, 1.70% for Hubei, 11.30% for Hunan, 6.70% for Guangdong, 3.50% for Guangxi Zhuang Autonomous Region, 3.10% for Hainan, 14.50% for Tibet Autonomous Region, and 4.40% for Xinjiang Production and Construction Corps, respectively (all P 0.05). The age group-specific HB incidences (per 100 000 population) were 12.78, 17.64, 80.21, 211.00, 181.62 and 163.11 for the population aged 0 – 4, 5 – 9, 10 – 19, 20 – 39, 40 – 59, and 60 years and above, respectively; the age group-specific HB incidence decreased for the groups less than 20 years (AAPC = – 7.7%, – 13.6%, and – 11.6% for groups of 0 – 4, 5 – 9, 10 – 19 years, all P Conclusion During 2004 – 2017 in China, the reported incidence of hepatitis B was not significantly changed generally but the incidence showed an increasing trend in some regions and the residents aged 60 years and above is the key population for hepatitis B prevention.

Introduction of Nonlinear Principal Component Analysis with an Application in Health Science Data

Introduction of Nonlinear Principal Component Analysis with an Application in Health Science Data