Related Experiment Video
Updated: Aug 18, 2025

12:00
Vaccinia Virus Infection & Temporal Analysis of Virus Gene Expression: Part 1
Published on: April 8, 2009
10.4K
Association between public attention and monkeypox epidemic: A global lag-correlation analysis
Wenxin Yan1, Min Du1, Chenyuan Qin1
1Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Journal of Medical Virology
|December 8, 2022
Summary
Google Trends Index (GTI) can help monitor monkeypox outbreaks. Public attention via GTI showed a significant correlation with daily monkeypox cases, particularly with a 13-day lead time.
Area of Science:
- Epidemiology
- Public Health Surveillance
- Infectious Disease Dynamics
Background:
- Human monkeypox emerged as a global public health concern.
- Google Trends Index (GTI) offers potential for real-time infectious disease surveillance by tracking public attention.
Approach:
- Lag-correlation analysis assessed Spearman correlation between GTI and monkeypox cases across 20 countries (-36 to +36 day lag).
- Meta-analyses pooled country-level correlation coefficients.
- Vector autoregression and Granger-causality tests explored GTI's forecasting significance.
Key Points:
- Strongest correlation found at a +13 day lag (r=0.53).
- Meta-analysis revealed significant positive correlations from -12 to +36 day lags, most notable at +3 days.
- GTI causality for daily cases was significant globally and in multiple countries.
Conclusions:
- A robust association exists between a 13-day lead time in GTI and worldwide daily monkeypox cases.
- GTI serves as a potential early warning and surveillance indicator for monkeypox outbreaks.
Related Concept Videos
Causality in Epidemiology
632
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
632
Correlation and Causation
38.0K
Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
38.0K
Steps in Outbreak Investigation
170
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:
170
Bias in Epidemiological Studies
493
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
493
Principles of Disease Surveillance
165
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...
165
Statistical Methods for Analyzing Epidemiological Data
478
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:
478

