Estimation of Natural Mortality Coefficient from Fish Abundance and Catch Data Using Virtual Population Analysis(VPA)

Natural mortality coefficient (M) was estimated from fish abundance (N) and catch (C) data using a Virtual Population Analysis (VPA) model. Monte Carlo simulations were used to evaluate the impact of different error distributions for the simulated data on the estimates of M. Among the four error structures (normal, lognormal, Poisson and gamma), simulations of normally dis-tributed errors produced the most viable estimates for M, with the lowest relative estimation errors (REEs) and median mean absolute deviations (MADs) for the ratio of the true to the estimated Ms. In contrast, the lognormal distribution had the largest REE value. Errors with different coefficients of variation (CV) were added to N and C. In general, when CVs in the data were less than 10%, reliable estimates of M were obtained. For normal and lognormal distributions, the estimates of M were more sensitive to the CVs in N than in C; when only C had error the estimates were close to the true. For Poisson and gamma distributions, opposite results were obtained. For instance, the estimates were more sensitive to the CVs in C than in N, with the largest REE from the scenario of error only in C. Two scenarios of high and low fishing mortality coefficient (F) were generated, and the simulation results showed that the method performed better for the scenario with low F. This method was also applied to the published data for the anchovy (Engraulis japonicus) of the Yellow Sea. Viable estimates of M were obtained for young groups, which may be explained by the fact that the great uncertainties in N and C observed for older Yellow Sea anchovy introduced large variation in the corresponding estimates of M.

Does Missing Data in Studies of Hard-to-Reach Populations Bias Results? Not Necessarily

Missing data are always an issue in community-based longitudinal studies, calling into question the representativeness of samples and bias in conclusions, the research has generated. This may be due to the difficulty of implementing random sampling procedures in these studies and/or the inherent difficulty in sampling hard-to-reach segments of the population being studied. In fact, the ability to accurately study hard-to-reach populations in light of potential bias created by missing data remains an open question. In this study, missing data are defined as both failure to interview potential research participants identified in the sampling frame and failure to retain enrolled research participants longitudinally. Using the sample from the Mobile Youth Survey, a multiple-cohort, longitudinal study of adolescents living in highly impoverished neighborhoods in Mobile, Alabama, we examined sample representativeness and dropout to determine whether missing data led to a nonrepresentative, and therefore, biased sample. Results indicate that even though random procedures are not strictly used to draw the sample, (a) the sample appears to be largely representative of the population that was studied, and (b) attrition is largely uncorrelated with characteristics of those who dropped out. This suggests that it is possible to study with validity hard-to reach populations in community settings.

Analysis of Complex Correlated Interval-Censored HIV Data from Population Based Survey

In studies of HIV, interval-censored data occur naturally. HIV infection time is not usually known exactly, only that it occurred before the survey, within some time interval or has not occurred at the time of the survey. Infections are often clustered within geographical areas such as enumerator areas (EAs) and thus inducing unobserved frailty. In this paper we consider an approach for estimating parameters when infection time is unknown and assumed correlated within an EA where dependency is modeled as frailties assuming a normal distribution for frailties and a Weibull distribution for baseline hazards. The data was from a household based population survey that used a multi-stage stratified sample design to randomly select 23,275 interviewed individuals from 10,584 households of whom 15,851 interviewed individuals were further tested for HIV (crude prevalence = 9.1%). A further test conducted among those that tested HIV positive found 181 (12.5%) recently infected. Results show high degree of heterogeneity in HIV distribution between EAs translating to a modest correlation of 0.198. Intervention strategies should target geographical areas that contribute disproportionately to the epidemic of HIV. Further research needs to identify such hot spot areas and understand what factors make these areas prone to HIV.

Major Data of China's 1% National Population Sampling Survey,1995

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Real-Time Monitoring and Forecast of Active Population Density Using Mobile Phone Data

Real-time monitoring and forecast of large scale active population density is of great significance as it can warn and prevent possible public safety accident caused by abnormal population aggregation.Active population is defined as the number of people with their mobile phone powered on.Recently,an unfortunate deadly stampede occurred in Shanghai on December 31th 2014 causing the death of 39 people.We hope that our research can help avoid similar unfortunate accident from happening.In this paper we propose a method for active population density real-time monitoring and forecasting based on data from mobile network operators.Our method is based solely on mobile network operators existing infrastructure and barely requires extra investment,and mobile devices play a very limited role in the process of population locating.Four series forecasting methods,namely Simple Exponential Smoothing(SES),Double exponential smoothing(DES),Triple exponential smoothing(TES)and Autoregressive integrated moving average(ARIMA)are used in our experiments.Our experimental results suggest that we can achieve good forecast result for 135 min in future.

The exploration of cell population data in clinical use: Beyond infectious diseases

Cell population data(CPD)is regarded as the fingerprint of a blood cell at a given moment.CPD parameters harbor information associated with cell morphology and can be automatically generated using modern hematological analyzers.Various studies have revealed many unique clinical applications for CPD,especially for infectious diseases,such as sepsis.For example,one monocyte-related CPD parameter is the monocyte distribution width(MDW),which can be generated using a Beckman Coulter hematological analyzer.MDW has received FDA and CE approval for aiding in sepsis diagnosis in adult patients in the emergency department.Additionally,MDW can serve as a diagnostic biomarker in patients infected with SARS-CoV-2.CPD has also been widely explored for possible clinical applications beyond infectious dis-eases,such as for predicting myelodysplastic syndromes,screening for he-matological malignancies,and detecting sterile inflammation.CPD parameter measurements are easily obtained and quite cost-effective,making them practical for clinical use.However,there are some potential drawbacks of CPD parameters.Some pre-analytical conditions can affect CPD values.Further-more,CPD are specific to certain hematological analyzers and the result cannot be transferred between different analyzers.The practical usefulness of CPD reference intervals is also still questionable.In this review,wesummarize the current studies related to CPD and its clinical applications.Additional well-designed clinical studies related to CPD are still expected.

Decreasing trend in prostate cancer with high serum prostate-specific antigen levels detected at first prostate-specific antigen-based population screening in Japan

To clarify the recent trends in prostate-specific antigen （PSA） distribution in men in Japan, we analyzed the PSA distributions of men undergoing PSA-based population screening. We summarized the annual individual data of PSA-based population screening in Kanazawa, Japan, from 2000 to 2011, and analyzed baseline serum PSA values of the participants at the first population screening. Serum PSA distributions were estimated in all participants and those excluding prostate cancer patients according to age. From 2000 to 2011, 19 620 men participated aged 54-69 years old in this screening program. Mean baseline serum PSA level of all participants at the first screening was 2.64 ng m1-1 in 2000, and gradually decreased to approximately 1.30 ng ml-I in 2006. That of participants excluding prostate cancer patients was 1.46 ng m1-1 in 2000, and there was no remarkable change during the study period. The 95t＂ percentiles in the participants excluding prostate cancer patients detected at the first population screening of men aged 54-59, 60-64, and 65-69 years old were 2.90, 3.60, and 4.50 ng m1-1, respectively. After the commencement of population screening, the proportion of prostate cancer patients with high serum PSA levels decreased. However, there were no changes in serum PSA levels in men without prostate cancer. Age-specific PSA reference level of men without prostate cancer in Japan was similar to that in China and Korea.

Spatio-temporal characteristics and influencing factors of urban floating population in China from 2011 to 2015

Although China’s urban floating population is mainly concentrated in developed cities,from the central and western cities to the eastern developed cities,but the characteristics of the floating population in different cities are significantly different.This paper systematically investigates the spatiotemporal characteristics and influencing factors of the floating population in different levels of cities.The results show that the regional imbalance to further strengthen,accumulation and dispersion trend has become increasingly obvious,liquidity is positively correlated and city level scale,and urban agglomeration and the core city is still polarization center of floating population.Flow range is closely related to urban hierarchy:the higher the intra-urban grade,the more tend to inter-provincial flow;the lower the city grade,the more tend to intra-urban mobility.Short-term(1-2 years)and long-term(more than 7 years)flow-time coexist.The short-term liquidity increases with the city grade,and the long-term liquidity decreases with the city level.Farmers are still the main body of the floating population.Younger age,lower education level,low-skilled,high gender ratio employees are the most basic demographic characteristics of the floating population,although there are differences between different cities.The main reason for affecting the floating population is seeking jobs and doing business.

Bayes Prediction of Future Observables from Exponentiated Populations with Fixed and Random Sample Size

Bayesian predictive probability density function is obtained when the underlying pop-ulation distribution is exponentiated and subjective prior is used. The corresponding predictive survival function is then obtained and used in constructing 100(1 – ?)% predictive interval, using one- and two- sample schemes when the size of the future sample is fixed and random. In the random case, the size of the future sample is assumed to follow the truncated Poisson distribution with parameter λ. Special attention is paid to the exponentiated Burr type XII population, from which the data are drawn. Two illustrative examples are given, one of which uses simulated data and the other uses data that represent the breaking strength of 64 single carbon fibers of length 10, found in Lawless [40].

Population Spatial Distribution Based on Luojia 1-01 Nighttime Light Image:A Case Study of Beijing

With the continuous development of urbanization in China,the country’s growing population brings great challenges to urban development.By mastering the refined population spatial distribution in administrative units,the quantity and agglomeration of population distribution can be estimated and visualized.It will provide a basis for a more rational urban planning.This paper takes Beijing as the research area and uses a new Luojia1-01 nighttime light image with high resolution,land use type data,Points of Interest(POI)data,and other data to construct the population spatial index system,establishing the index weight based on the principal component analysis.The comprehensive weight value of population distribution in the study area was then used to calculate the street population distribution of Beijing in 2018.Then the population spatial distribution was visualize using GIS technology.After accuracy assessments by comparing the result with the WorldPop data,the accuracy has reached 0.74.The proposed method was validated as a qualified method to generate population spatial maps.By contrast of local areas,Luojia 1-01 data is more suitable for population distribution estimation than the NPP/VIIRS(Net Primary Productivity/Visible infrared Imaging Radiometer)nighttime light data.More geospatial big data and mathematical models can be combined to create more accurate population maps in the future.

人口老龄化背景下体育消费的健康效应——基于全国消费大数据的实证证据

基于健康资本需求理论将体育消费视作一种健康投资,提出个体体育消费的增长可降低其医疗消费支出的假设;采用2018—2021年全国消费大数据,实证检验个体体育消费的健康效应。结果显示,体育消费占个体年度总消费的比例每提高1个单位,医疗消费占个体年度总消费的比例降低0.203个单位。新冠病毒感染疫情对体育消费的健康效应有所抑制但依然显著。进一步分析表明,体育消费的健康效应对35岁及以上人群的影响会随着年龄的增长明显增强,对65岁及以上老龄人口的影响效果最为突出。认为:在应对人口老龄化和医疗负担增加等重大挑战时,需要加快普及对体育消费的健康效应认知,大力促进全人群体育消费。

呼吸道传染病时空传播风险精细化评估系统构建与应用

目的开发多源城市大数据支持下的城市内部呼吸道传染病时空传播风险精细化评估系统,为城市内部实施更加精准的疾病防控提供决策支持。方法本研究面向流感等典型的呼吸道传染病,融合传染病、人群活动、地理环境等多源大数据,以500米网格为基本空间单元,通过德尔菲法构建高精度传播风险评估模型;通过构建基于人口流动网络的传播动力学模型,实现高精度的呼吸道传染病时空传播模拟,推演未来30天城市内部疾病发展的时空趋势;选取传染病传播高风险区域作为关键的空间防控节点,利用时空传播模拟模型精细化评估不同关键节点防控的效果。结果以深圳市为例,构建了呼吸道传染病时空传播风险精细化评估系统。结论本研究提供了一套面向大型城市内部区域的呼吸道传染病时空传播风险精细化评估系统,能够支持传染病时空扩散趋势的研判,并且能够在疫情发展的不同阶段快速预判高危风险区域防控措施的效果,为呼吸道传染病精准防控提供应急响应的技术和系统储备。

基于栅格数据的辽中南城市群人居环境自然适宜性测评

以辽中南城市群为研究对象,基于1km×1km栅格数据,建立了基于地形起伏度、植被、水文、温湿指数的人居环境自然适宜性综合评价模型,对人居环境自然适宜性进行了综合评价与合理分区。研究结果表明:①辽中南城市群人居环境自然适宜性受地形条件限制较小,受水文、植被、气候条件限制较大。②辽中南城市群人居环境自然适宜性指数范围为19.03~84.15,在空间上总体呈现出西高东低的态势。③中度适宜地区分布最广,高度适宜地区与不适宜地区面积最小。④辽中南城市群64.48%的人口分布在中高度适宜地区。

大数据智慧养老服务系统与发展机制建设策略

本文以现代社会养老服务供不应求的现状为研究背景,结合当前先进的大数据技术,对智慧养老服务系统的设置及其发展机制建设策略进行研究。研究主要包括我国当前的养老服务发展现状,大数据支持下的智慧养老服务系统应用需求,大数据智慧养老服务系统的建设策略,以及大数据智慧养老服务系统发展机制建设策略。希望通过本次的分析,可以为大数据技术的应用和智慧养老服务系统的设置及其发展提供科学参考。

县域耕地非农化、非粮化与乡村人口空心化的耦合协调关系——以长江经济带为例

耕地非农化、非粮化的不断扩大严重影响了我国的粮食安全,亟需研究其演变机制和管控措施。基于1990、2000、2010和2020年四期土地覆盖数据和农业劳动力数据,利用耦合协调度模型和探索性时空数据分析(ESTDA)方法,分析了长江经济带县域耕地非农化、非粮化和乡村人口空心化的时空演化特征及其耦合协调关系。结果表明:(1)非农化呈现东高西低的格局,且存在围绕中心城市高值集聚的态势。非粮化则大致呈现出西高东低的倾向,远离大城市的边远县域非粮化程度较高。研究期内非农化和非粮化呈整体加剧趋势,乡村人口空心化程度显著提升。(2)非农化、非粮化和乡村人口空心化之间呈现较强耦合作用,失调区域逐渐扩大。(3)非农化、非粮化和乡村人口空心化耦合协调度存在明显的空间集聚现象并逐渐增强。高值集聚区主要分布在上游地区且数量逐渐减少,低值集聚区分布相对分散。(4)非农化、非粮化和乡村人口空心化耦合协调度具有较强时空动态特征,但县域及其邻域协同变动的比例较高,表明具有较强的局域整合性。

数字时代人口监测中的多源数据应用——现状及展望

人口监测是开展人口规划、统计、预测及预警等的基础性工作,是政府科学决策的基石。我国人口监测的传统数据仍存在漏报重报、质量不高、时效不强、属性不全、融合不深等问题,难以实施有效的人口精细化管理,也限制了监测数据在人口学研究中的广泛应用。随着信息技术的快速发展及移动终端的进一步普及,手机信令、互联网、遥感信息等一系列可直接或间接捕捉“人口行为”的新型数据大量涌现并应用于人口监测,与人口普查、调查等传统数据采集手段互为补充,有望通过交叉协同形成更加全面、更为实用的人口监测多源大数据基础。从人口监测的传统数据、新型数据及新老数据融合三方面入手,系统梳理了数字时代用于人口监测的多源数据。首先,通过梳理传统人口监测的分类及相关应用研究,总结了传统数据的主要优势、瓶颈与不足,进而明确了融合新型数据的需求靶点和必要性。其次,从数据分类及优缺点对比、应用研究等角度对新型数据的相关文献进行梳理,重点分析现阶段应用新型数据的机会和挑战。最后,通过总结传统数据与新型数据融合应用的优势,提炼了有待进一步研究的议题,为应用多源数据实现人口动态监测,推进流动人口统计信息化、规范化和精细化,支撑政府政策制定和人口学研究建立了理论基础。

南京地区健康成人白细胞群落参数参考区间的建立

目的旨在建立南京地区不同年龄和性别表观健康成年人白细胞群落参数的参考区间。方法选择2024年1月至4月于南京大学医学院附属鼓楼医院进行体检的1262名健康成人作为研究对象。采用Sysmex XN全自动血细胞分析仪进行血常规检测,同时记录仪器WDF通道提供的中性粒、淋巴和单核细胞相关的细胞群落参数(cell population data,CPD),统称为白细胞CPD,包括它们的平均侧向散射光强度(NE-SSC、LY-X、MO-X)和分布宽度(NE-WX、LY-WX、MO-WY);平均荧光强度(NE-SFL、LY-Y、MO-Y)和分布宽度(NE-WY、LY-WY、MO-WY);平均前向散射光强度(NE-FSC、LY-Z、MO-Z)和分布宽度(NE-WZ、LY-WZ、MO-WZ)。参照中华人民共和国卫生行业标准(WS/T405-2012)《血细胞分析参考区间》中的推荐方法,分析各项指标在不同年龄及性别间的差异,并得出南京健康成人白细胞CPD的参考区间。结果在男女两性别组内按年龄分组比较发现,LY-WZ、MO-WZ、NE-FCS、NE-WZ不显示年龄和性别上的差异;MO-Z只显示性别差异;LY-Y、LY-Z、MO-X、NE-SSC、NE-WY只在女性组内存在年龄差异;MO-WY、MO-Y、NE-SFL、NE-WX只在男性内存在年龄差异;LY-X、LY-WX、LY-WY、MO-WX在两性别组内均存在年龄差异。以此为依据划分参考区间。结论建立了南京地区白细胞CPD在不同性别和年龄段健康成年人中的参考区间,为疾病的诊断、治疗和预后判断提供重要的实验室参考依据。

人口老龄化与城市创新:理论逻辑与中国经验

当前我国正处于人口老龄化程度不断加深的阶段,如何有效应对人口老龄化对城市创新所造成的影响已成为推进我国高质量发展进程中迫切需要解决的问题。本文分析了人口老龄化影响城市创新的理论机制,采用全国人口普查数据和人口抽样调查数据实证检验了人口老龄化对城市创新的影响。研究发现,人口老龄化程度的加深会显著抑制城市的创新能力,并且这一效应在中西部地区城市和经济发展水平较低的城市表现得尤为明显,其主要原因在于人口老龄化通过技术抑制效应和要素成本效应对城市创新产生影响。本文的研究结论对推动高水平城市创新和积极应对人口老龄化的政策协同具有一定借鉴意义。