Abstract

To use Google Insights search volume and publicly available economic indicators to test the hypothesis that sperm, egg, and blood donations increase during economic downturns and to demonstrate the feasibility of using Google search volume data to predict national trends in actual sperm, egg, and blood donations rates.Cross-correlation statistical analysis comparing Google search data for terms relating to blood, egg, and sperm donations with various economic indicators including the S&P 500 closing values, gross domestic product (GDP), the U.S. Index of Leading Indicators (U.S. Leading Index), gross savings rate, mortgage interest rates, unemployment rate, and consumer price index (CPI) from 2004-2011. A secondary analysis determined the Pearson correlation coefficient between Google search data with actual sperm, egg, and blood donation volume in the U.S. as measured by California Cryobank, the National Assisted Reproductive Technology Surveillance System, and the National Blood Collection and Utilization Survey, respectively. Significance of cross-correlation and Pearson correlation analysis as indicated by p value.There were several highly significant cross-correlation relationships between search volume and various economic indicators. Correlation between Google search volume for the term 'sperm donation,' 'egg donation,' and 'blood donation' with actual number of sperm, egg and blood donations in the United States demonstrated Pearson correlation coefficients of 0.2 (p > 0.10), -0.1 (p > 0.10), and 0.07 (p > 0.10), respectively. Temporal analysis showed an improved correlation coefficient of 0.9 (p < 0.05) for blood donation when shifted 12 months later relative to Google search volume.Google search volume data for search terms relating to sperm, egg, and blood donation increase during economic downturns. This finding suggests gamete and bodily fluid donations are influenced by market forces like other commodities. Google search may be useful for predicting blood donation trends but is more limited in predicting actual semen and oocyte donation patterns.

View details for PubMedID 26432967