中华流行病学杂志最新文献

{"title":"[Evaluation of performance of influenza trend prediction based on three time series models in Beijing].","authors":"X Xu, M Y Li, H Yao, J Li, Y Y Wang, J J Zhang, L Zhang, J X Ma, X L Wang, P Yang","doi":"10.3760/cma.j.cn112338-20250414-00245","DOIUrl":"https://doi.org/10.3760/cma.j.cn112338-20250414-00245","url":null,"abstract":"<p><p><b>Objective:</b> To explore the trend of influenza positive rate in Beijing by using classic autoregressive integrated moving average (ARIMA) model, autoregressive integrated moving average model with exogenous variables (ARIMAX) and vector autoregression model (VAR) to compare the performance of three models in influenza prediction and select the most suitable one for Beijing. <b>Methods:</b> The weekly positive rate of influenza virus nucleic acid test and meteorological data in Beijing from week 1 of 2013 to week 40 of 2024 were collected. The data were divided into four groups with expanding training sets and corresponding testing sets. The training set of the first group was from week 1 of 2013 to week 40 of 2016, and the testing set was from week 41 of 2016 to week 40 of 2017. Subsequent groups extended the training set by one year each time. Data from 2020 to 2023 were excluded due to COVID-19 pandemic. The fourth group used data from the week 1 of 2013 to week 40 of 2023 for training and from the week 41 of 2023 to week 40 of 2024 for testing. <b>Results:</b> The incidence of influenza had seasonality in Beijing with higher incidence in winter and spring. The positive rate of influenza virus was positively correlated with the weekly average atmospheric pressure (<i>r</i>=0.482, <i>P</i><0.001) and weekly average wind speed (<i>r</i>=0.003, <i>P</i>=0.034), and negatively correlated with the weekly average temperature (<i>r</i>=-0.541, <i>P</i><0.001). The ARIMAX model incorporating meteorological factors had the best prediction performance, with test set's root mean square error (<i>RMSE</i>) of 0.115 3 and mean absolute error (<i>MAE</i>) of 0.076 7 (the <i>RMSE</i> and <i>MAE</i> values for ARIMA and VAR models were 0.117 1 and 0.163 8, and 0.078 6 and 0.122 3, respectively). The prediction results of the optimal model showed that the positive rate of influenza virus would continue to rise in Beijing after October 2024 and reach peak in the second week of 2025, but the peak positive rate would be lower than that of previous influenza season. <b>Conclusions:</b> Compared with the ARIMA model and the VAR model,the ARIMAX model which used meteorological parameters is more suitable for prediction of long-term influenza trend in Beijing. The influenza trend peak was predicted to occur in the second week of 2025, but lower than that in previous influenza season.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1593-1599"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Etiological surveillance and antimicrobial resistance analysis of <i>Legionella pneumophila</i> in the aqueous environment of public places in Shanghai, 2011-2020].","authors":"J Feng, W Gao, Y Zhuang, L Y Yuan, Y X Chen, Z Xu, J Y Luo, Y Chen, H Y Wu, X Chen, J Zhang, M Chen","doi":"10.3760/cma.j.cn112338-20250207-00070","DOIUrl":"https://doi.org/10.3760/cma.j.cn112338-20250207-00070","url":null,"abstract":"<p><p><b>Objective:</b> To understand the etiological surveillance and drug resistance characteristics of <i>Legionella pneumophila</i> (LP) from the aqueous environment of public places in Shanghai, from 2011 to 2020, and provide evidence for surveillance of the disease. <b>Methods:</b> Environmental water samples were systematically collected from public venues in urban and suburban districts of Shanghai for LP surveillance. All the identified LP isolates underwent a series of testings including serotyping, pulsed field gel electrophoresis (PFGE), sequence-based typing, and antimicrobial susceptibility testing. <i>χ</i>² test or Cochran-Armitage trend tests were used for statistical analysis and for temporal resistance patterns. <b>Results:</b> Among 6 263 water samples, the LP-positive rate was 20.93% (1 311/6 263). The positivity rate decreased from 24.98% (287/1 149) in 2011-2012 to 20.02% (1 024/5 114) in 2013-2020 (<i>χ</i>²=13.92, <i>P</i><0.001), with the highest monthly positivity observed from June to August (23.79%, 745/3 132). A total of 1 365 LP strains were isolated, of which 912 were further characterized, including 10 serotypes, 149 PFGE patterns, and 33 sequence types (ST). The predominant serotype was Lp1 (86.84%, 792/912), and the dominant ST was ST752 (29.50%, 269/912). ST clustering revealed two major clonal groups CG1 and CG2, accounting for 91.12% (831/912) of the isolates. The 190 LPs involved in the drug sensitivity test showed three resistance profiles: azithromycin resistance (31.05%, 59/190), ciprofloxacin resistance (0.53%, 1/190) and azithromycin+ciprofloxacin resistance (0.53%, 1/190). Azithromycin-resistant strains were predominantly ST1 (64.41%, 38/59). The antimicrobial resistance rate showed a significant decline, from 48.65% (18/37) in 2011-2012 to 28.10% (43/153) in 2013-2020 (<i>χ</i>²=9.38, <i>P=</i>0.002). <b>Conclusions:</b> Compared to from 2011 to 2012, both the positivity rate and antimicrobial resistance prevalence of LP in public aqueous environments of Shanghai exhibited an overall decline from 2013 to 2020. The predominant types of LP were serotype Lp1 and sequence type ST752, with notable high-level resistance to azithromycin. Measures as enhancing the enforcement of water safety regulations and prioritizing surveillance of azithromycin resistance in LP were recommended to mitigate public health risks.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1600-1609"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Epidemiological characteristics of chronic hepatitis B and establishment of prediction model based on socio-demographic index in Shenzhen, 2005-2023].","authors":"H W Xiong, L M Cao, Y P Chen, Q Y Lyu, Z G Chen, J Ren, Y Lu, Z Zhang","doi":"10.3760/cma.j.cn112338-20250218-00096","DOIUrl":"https://doi.org/10.3760/cma.j.cn112338-20250218-00096","url":null,"abstract":"<p><p><b>Objectives:</b> To analyze the epidemiological characteristics and incidence trends of chronic hepatitis B in Shenzhen from 2005 to 2023, develop a prediction models with performance evaluation, explore its associations with social demographic index (SDI) and inform targeted prevention strategy development. <b>Methods:</b> Based on surveillance data of infectious diseases, descriptive epidemiological methods were applied to analyze the spatiotemporal and population distribution characteristics. A multifactorial prediction model integrating the SDI was established, and its predictive performance was evaluated by using data from 2020-2023. Model accuracy was evaluated by using root mean square error and mean absolute percentage error (<i>MAPE</i>). The association between SDI and incidence rates was assessed through generalized linear models. <b>Results:</b> A total of 235 703 chronic hepatitis B cases were reported cumulatively in Shenzhen from 2005-2023, with an annual average incidence rate of 98.84/100 000. Long-term trends revealed a significant increase in the incidence from 2005 to 2019. The incidence rate was 2.48 times higher in men than in women, and the majority of cases occurred in age group 20-50 years. The cases were mainly workers in manufacturing and services. Seasonal incidence peaks were observed in March and during May to November. The overall SDI exhibited a consistent upward trend, and the positive correlation between SDI and incidence rate was observed in central urban districts (Futian and Nanshan). In contrast, industrial zones (Guangming and Bao'an) saw a significant decline in incidence rates due to intensified prevention interventions despite the increase of SDI level. Model predictions indicated that the multivariate long short-term memory (LSTM) deep learning model integrating SDI parameters outperformed both the spatiotemporal covariate- enhanced model and the augmented Bayesian structural time series model, with <i>MAPE</i> of 4.71%, 7.66% and 10.30%, respectively. <b>Conclusion:</b> SDI is a key social determinant associated with hepatitis B transmission risks, and dynamic thresholds can be established to develop tiered early warning mechanisms. It is suggested to integrate multisource SDI data into the LSTM framework, implement targeted interventions such as \"rapid antibody screening in key areas + vaccination boosters for high-risk populations\" and improve the timeliness of epidemic response through hybrid models to reduce disease burden level.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1623-1631"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Analysis and prediction of prevalence, disease burden of type 2 diabetes mellitus and risk factors in China from 1990 to 2021 in a global context].","authors":"A B Qu, F Y Wen, X Huang, L Zhang","doi":"10.3760/cma.j.cn112338-20250307-00144","DOIUrl":"https://doi.org/10.3760/cma.j.cn112338-20250307-00144","url":null,"abstract":"<p><p><b>Objective:</b> To analyze the prevalence, disease burden of type 2 diabetes mellitus (T2DM) and risk factors in China from 1990 to 2021 predict future trends and provide evidence for the development of precise prevention and control policies. <b>Methods:</b> Based on the Global Burden of Disease Study 2021 database, the data on disease burden and risk factors of T2DM in China and in the world from 1990 to 2021 were extracted. Age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), age-standardized mortality rate (ASMR), and age-standardized disability adjusted life year rate (ASDR) were used to evaluate the prevalence and disease burden of T2DM. Joinpoint regression models were used to calculate the average annual percentage change (AAPC) to evaluate change trends. Bayesian age-period-cohort analysis models were constructed to predict the prevalence and disease burden of T2DM from 2022 to 2046. <b>Results:</b> In 2021, the ASIR, ASPR, and ASDR of T2DM in China were 308.37/100 000, 10 626.04/100 000, and 1 050.47/100 000, which increased by 12.92% (AAPC=0.388%, <i>P</i>=0.009), 61.60% (AAPC=1.546%, <i>P</i><0.001), and 25.26% (AAPC=0.756%, <i>P</i><0.001) compared with 1990, respectively. However, the ASMR dropped to 15.84/100 000, a decrease of 4.75% (AAPC=0.122%, <i>P</i>=0.154). The prediction results showed that the ASPR and ASDR of T2DM in China would continue to increase steadily from 2022 to 2046 , which would increase to 19 732.71/100 000 and 1 941.25/100 000 in 2046, while the ASIR and ASMR would decrease to 258.35/100 000 and 11.49/100 000 in 2046. It is predicted that the annual ASIR, ASPR, ASMR, and ASDR of T2DM in China would remain lower than the global levels from 2022 to 2046. The disease burden level of T2DM was higher in men and the elderly in China. Based on data from China and the world, metabolic factors (high FPG glucose and high BMI) are consistently the main risk factors leading to the disease burden of T2DM, and ambient particulate matter pollution is the main environmental factor. While the global disease burden of T2DM attributed to smoking has become stabilized, China still maintains a relatively high level and the level is predicted to keep rising in the future. <b>Conclusions:</b> The disease burden of T2DM continues to increase in China, posing significant challenges for prevention and treatment. The prevention and intervention strategies should focus on the key modifiable risk factors.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1570-1579"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Analysis of the trend changes in the burden of cardiovascular disease mortality in China from 2010 to 2021].","authors":"W P Fan, X H Yu, J L Qi, J L You, Y N Liu, J M Liu, L J Wang","doi":"10.3760/cma.j.cn112338-20250109-00024","DOIUrl":"https://doi.org/10.3760/cma.j.cn112338-20250109-00024","url":null,"abstract":"<p><p><b>Objective:</b> To analyze the current status and trend of the mortality burden of cardiovascular disease in China from 2010 to 2021. <b>Methods:</b> Data related to cardiovascular disease mortality and disability-adjusted life year (DALY) were extracted from the Global Burden of Disease Study 2021 (GBD2021) database. The age-standardized mortality rate and DALY rate were calculated, using the 2021 world standard population estimated by GBD2021. Joinpoint 5.2.0 software was used to calculate the mortality rate, standardized mortality rate, DALY rate, standardized DALY rate, annual percent change (APC), average annual percent change (AAPC), and 95%<i>CI</i> of cardiovascular disease in China from 2010 to 2021. <b>Results:</b> The mortality rate of cardiovascular disease was 357.44/100 000, and the age-standardized mortality rate was 280.11/100 000 in China in 2021. The DALY rate was 7 043.33/100 000, and the age-standardized DALY rate was 5 120.06/100 000. From 2010 to 2021, the mortality rate and DALY rate of cardiovascular disease in China showed an upward trend (AAPC was 1.58% and 0.83%, respectively, both <i>P</i><0.05), and the standardized mortality rate and standardized DALY rate showed a downward trend (AAPC was -2.13% and -2.02%, respectively, both <i>P</i><0.05). The mortality burden of cardiovascular disease was higher in males (mortality rate 392.80/100 000, DALY rate 8 156.19/100 000) than in females (mortality rate 320.38/100 000, DALY rate 5 876.87/100 000). With the increase older in age, the mortality burden of cardiovascular disease in China decreased first and then increased. China ranked high in the mortality burden of cardiovascular disease among G20 member countries. <b>Conclusions:</b> The death burden of cardiovascular disease is serious in China. The mortality rate and DALY rate of cardiovascular disease in China showed an increasing trend from 2010 to 2021, and the standardized mortality rate and standardized DALY rate of cardiovascular disease ranked high in G20 member countries. The death burden of cardiovascular disease was more serious in men and the elderly. It is necessary to develop more comprehensive prevention, treatment, and rehabilitation measures for men and the elderly to reduce mortality and disability rates, decrease the disease burden, and improve the quality of life.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1562-1569"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Temporal distribution characteristics of other infectious diarrhea in Shenzhen, 2011-2023].","authors":"L X Song, W H Lu, Z Zhang, Y P Cheng, H W Xiong, Y Lu, Q Y Lyu, Z G Chen","doi":"10.3760/cma.j.cn112338-20250103-00005","DOIUrl":"https://doi.org/10.3760/cma.j.cn112338-20250103-00005","url":null,"abstract":"<p><p><b>Objective:</b> To analyze the temporal distribution of other infectious diarrhea (OID) in Shenzhen and provide evidence for the prevention and control of OID. <b>Methods:</b> The incidence data of OID in Shenzhen from 2011 to 2023 were collected. The seasonal and trend decomposition using loess (STL), seasonal index method, concentration degree and circular distribution method were used to analyze the incidence trend and temporal distribution of OID. <b>Results:</b> A total of 477 611 cases of OID were reported in Shenzhen from 2011 to 2023, with an average annual incidence rate of 260.19/100 000 showing a fluctuating upward trend. The seasonal index method indicated that October-January was period with high incidence of OID in Shenzhen and the seasonal intensity began to decrease in 2020. STL revealed an obvious incidence peak in winter. The concentration method showed that OID had a certain seasonality before 2018 except 2016, but the seasonality was not obvious after 2018. The circular distribution results showed that <i>r</i> was 0.05, mean angle <i>ā</i> was 1.92° and angular standard deviation <i>s</i> was 141.93° (<i>Z</i>=1 033.37, <i>P</i><0.001), with the peak on January 1^st and the high incidence period from August 11^th to May 25^th. <b>Conclusions:</b> OID had a certain degree of seasonality in Shenzhen, with an obvious incidence peak in winter. Since the seasonal intensity of OID decreased after 2018, the surveillance, early warning and risk assessment of OID should be continued, and prevention and control measures should be adjusted timely according to the change in the characteristics of the epidemic.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1610-1616"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Development and application of diphtheria-tetanus-pertussis containing combined vaccines].","authors":"S Zhang, L Li, R Y Hu, L Cao, X Liu, J K Ye, Y F Song, Z N Zhang, W Z Yu","doi":"10.3760/cma.j.cn112338-20241224-00822","DOIUrl":"10.3760/cma.j.cn112338-20241224-00822","url":null,"abstract":"<p><p>Combined vaccines can simplify the vaccination process, improve coverage rates, reduce the risk of adverse events following immunization, lower social costs, and improve the timeliness of childhood vaccination. This article focuses on multi-component vaccines based on the diphtheria-tetanus-pertussis containing vaccine. Globally, multiple combined vaccines have been developed and marketed, but the development of combined vaccine is still in its infancy stage in China, with limited vaccine types and doses available. The research, development, and application of combined vaccines still face numerous challenges in China, including technical challenges in research and development, as well as insufficient motivation for research and development. Additionally, the high cost of existing combined vaccines, coupled with low public awareness and weak vaccination intentions, significantly hinders their widespread application, China should continue to rigorously implement the Vaccine Administration Law of the People's Republic of China, promote innovative development of combined vaccines, increase public awareness, strengthen child guardians' confidence in vaccination, and improve the accessibility and affordability of combined vaccines to protect public health across all life stages.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1667-1672"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Analysis on epidemiological characteristics and changing trends of fatal injury in residents in Qingdao, 2014 - 2023].","authors":"W W Gui, J Chen, Y Y Xu, Z C Jin, H P Duan, H Zhang","doi":"10.3760/cma.j.cn112338-20241208-00779","DOIUrl":"https://doi.org/10.3760/cma.j.cn112338-20241208-00779","url":null,"abstract":"<p><p><b>Objective:</b> To understand the epidemiological characteristics and changing trends of injury-related deaths in local residents in Qingdao from 2014 to 2023, and provide evidence for development of injury prevention and control measures. <b>Methods:</b> The incidence data on fatal injury in residents of Qingdao from 2014 to 2023 were used to describe the epidemiological characteristics of fatal injury by using fatal injury rate, standardized fatal injury rate, proportion, and death order. The average annual percentage change (AAPC) was used to describe the annual change in fatal injury rates, and the trend of fatal injury was analyzed. <b>Results:</b> From 2014 to 2023, a total of 23 533 residents died of injury in Qingdao, with a crude fatal injury rate of 28.74/100 000 and a standardized fatal injury rate of 27.64/100 000. The total fatal injury rate showed a downward trend (AAPC: -5.06%, <i>P</i><0.05). The top three causes of fatal injury in the residents were road traffic accident (40.85%), suicide (15.80%), and accidental falls (12.92%). In terms of gender specific fatal injury cause, the top one in both men and women was road traffic accident injury. In terms of age specific fatal injury cause, the top one was road traffic accident in the all age groups, except age group 5-14 years with top cause of drowning. From 2014 to 2023, the fatal injury rates of road traffic accident, suicide, and accidental poisoning in the top five fatal injury causes showed a downward trend year by year (AAPC:-7.42%, -6.54%, -13.95%, <i>P</i><0.05). <b>Conclusions:</b> The fatal injury rate showed a downward trend in the residents in Qingdao from 2014 to 2023. It is necessary to strengthen the prevention and control of road traffic accident injury, suicide, falls in the elderly, and drowning in adolescents.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1617-1622"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Artificial intelligence in epidemiology: a decade-long bibliometric analysis].","authors":"C H Wang, Z M Yang, W Shi, C W Xi, S C Si, L L Wu, J Du, S F Wang, S Y Zhan","doi":"10.3760/cma.j.cn112338-20250118-00049","DOIUrl":"https://doi.org/10.3760/cma.j.cn112338-20250118-00049","url":null,"abstract":"<p><p><b>Objective:</b> To describe the hotspots and application trends of artificial intelligence (AI) in epidemiology in the past decade and analyze its advantages and challenges. <b>Methods:</b> The literatures with AI and epidemiology related keywords were systematically retrieved from Web of Science and China National Knowledge Infrastructure from 2014 to 2024. CiteSpace was used for bibliometric analysis of publication volume, keyword co-occurrence, clustering, emergence and cited literature co-occurrence analysis. <b>Results:</b> A total of 5 389 English papers and 1 659 Chinese papers were included, showing an increasing publication trend. High-frequency Chinese keywords included prediction, influencing factor, and machine learning, while English keywords frequently used were machine learning, prediction, and artificial intelligence. The Chinese keywords formed 14 clusters such as epidemiological characteristic, dietary pattern, and elderly individual, and the English keywords formed 21 clusters including prediction model, risk factor, and adult. In international studies, health policy, COVID-19, and digital health were the emerging frontier keywords. Eleven core papers were selected, covering key areas like traffic accident risk assessment, public health big data application, and deep learning in medical diagnosis. <b>Conclusions:</b> This study systematically summarized the research hotspots and development trends of AI applications in epidemiology over the past decade by using bibliometric methods, which indicated that current AI-based epidemiological studies are still in the exploratory phase, with the coexisting of both advantages and challenges. Continued attention should be paid to the future development of this field.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1650-1659"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Study of β-amyloid protein deposition in brain regions on progression from mild cognitive impairment to Alzheimer's disease].","authors":"Y X Wang, Y H Ma, X Y Yang, G Y Guo, W C Song, A M Wang, S Z Wang, F Y Shi","doi":"10.3760/cma.j.cn112338-20250201-00066","DOIUrl":"https://doi.org/10.3760/cma.j.cn112338-20250201-00066","url":null,"abstract":"<p><p><b>Objective:</b> To analyze the key β-amyloid protein (Aβ) deposition in brain regions affecting the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). <b>Methods:</b> Based on the positron emission tomography data of Aβ in the Alzheimer's disease neuroimaging initiative database, the penalized generalized estimating equation (PGEE) and the mixed effects regression forest algorithm (MERF) were used to conduct dimensionality reduction analysis on 164 brain regions with Aβ deposition. Additionally, a multivariate longitudinal data joint model was used to screen the key Aβ deposition brain regions that influence the progression from MCI to AD. <b>Results:</b> Five key brain regions were commonly screened out by the PGEE and MERF models, they were the right prefrontal orbital cortex, the left superior temporal sulcus shore cortex, the right medial orbitofrontal cortex, the left putamen, and the right transverse temporal cortex, respectively. The results of the multivariate longitudinal data joint model based on these 5 Aβ deposition brain regions showed that, except the left superior temporal sulcus shore cortex, the longitudinal change trajectories of the other 4 Aβ deposition brain regions all affected the progression from MCI to AD (<i>P</i><0.05). <b>Conclusion:</b> The Aβ deposition in the right prefrontal orbital cortex, right medial orbitofrontal cortex, left putamen and right transverse temporal cortex affect the progression from MCI to AD.</p>","PeriodicalId":23968,"journal":{"name":"中华流行病学杂志","volume":"46 9","pages":"1660-1666"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}