Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.3K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.3K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

411
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
411
Introduction to Epidemiology01:26

Introduction to Epidemiology

1.5K
Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
1.5K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

797
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
797
Principles of Disease Surveillance01:26

Principles of Disease Surveillance

391
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
391
Systematic Sampling Method01:17

Systematic Sampling Method

12.3K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
12.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

[A prospective cohort and Mendelian randomization study of association of snoring and adiposity with chronic obstructive pulmonary disease].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same author

[Non-invasive and high-precision identification of gastric precancerous lesions based on SERS and machine learning].

Zhonghua zhong liu za zhi [Chinese journal of oncology]·2026
Same author

[Associations of waist-to-hip ratio with mortality in older adults in 10 areas of China].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same author

[Association of non-invasive atherosclerotic indicators with cardiovascular disease risk in adults in 10 areas of China].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same author

[Observational and genetic epidemiological study on the association of alcohol consumption and chronic obstructive pulmonary disease in adults in 10 areas of China].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same author

Genetic engineering of dinoflagellate algae and the lethality of an introduced plastid terminal oxidase.

Protist·2026
Same journal

[Research progress on the impact of the digital information environment on the health of children and adolescents].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Exploration and practice of ideological and political education integration in the "One Core, Two Integrations" curriculum model for epidemiology].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Progress in research of visualization of ideology and politics elements in curriculum and its importance for <i>Epidemiology</i> curriculum].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Operation of WeChat official accounts of <i>Chinese Journal of Epidemiology</i>].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Study on the risk factors of development for mild cognitive impairment to Alzheimer's disease based on the competitive risk joint model].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Mendelian randomization study on related factors for esophageal adenocarcinoma and Barrett's esophagus].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
See all related articles

Related Experiment Video

Updated: Dec 17, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.1K

[Application of Python web crawler technology in infodemiology].

J J Zhou1, S F Wang1, L M Li1

  • 1Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.

Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|June 23, 2020
PubMed
Summary
This summary is machine-generated.

Python web crawler technology aids Infodemiology by collecting internet data. This technique offers simple syntax, flexibility, and low costs for public health surveillance and smart doctor seeking.

Keywords:
Health interventionInfodemiologyPublic health surveillancePython web crawler technologySmart doctor seeking

More Related Videos

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

33.2K
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.7K

Related Experiment Videos

Last Updated: Dec 17, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.1K
Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

33.2K
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.7K

Area of Science:

  • Infodemiology
  • Data Science
  • Public Health Informatics

Background:

  • Python web crawling is crucial for extracting and integrating multi-source heterogeneous data.
  • The technology mimics user browsing behavior for automated, large-scale information gathering.
  • It supports various applications within public health and healthcare informatics.

Purpose of the Study:

  • To highlight the utility and advantages of Python web crawler technology in Infodemiology.
  • To discuss current and future applications of this technology in public health.
  • To suggest improvements in education and innovation for its effective use.

Main Methods:

  • Utilizing simple and massive-scale Python web crawlers for simultaneous data collection.
  • Analyzing the inherent advantages: simple syntax, high flexibility, and low learning/maintenance costs.
  • Examining current application scenarios in public health surveillance and doctor seeking.

Main Results:

  • Python web crawlers provide an efficient method for data acquisition in Infodemiology.
  • The technology is characterized by ease of use, adaptability, and cost-effectiveness.
  • Existing applications demonstrate its value in health intervention programs and smart healthcare solutions.

Conclusions:

  • Python web crawler technology is a fundamental tool for Infodemiology, enabling effective data integration.
  • Its application scope is expanding due to government initiatives promoting data utilization.
  • Enhancing talent cultivation and technical innovation is recommended for future advancements in public health informatics.