Fertility choices are linked to the different preferences and constraints of individuals and couples, and vary importantly by socio-economic status, as well by cultural and institutional context. The meaning of childbearing and child-rearing, therefore, differs between individuals and across groups. In this paper, we combine data from Google Correlate and Google Trends for the U.S. with ground truth data from the American Community Survey to derive new insights into fertility and its meaning. First, we show that Google Correlate can be used to illustrate socio-economic differences on the circumstances around pregnancy and birth: e.g., searches for "flying while pregnant" are linked to high income fertility, and "paternity test" are linked to non-marital fertility. Second, we combine several search queries to build predictive models of regional variation in fertility, explaining about 75 of the variance. Third, we explore if aggregated web search data can also be used to model fertility trends.
@cite_10: Background: Internet search patterns have emerged as a novel data source for monitoring infectious disease trends. We propose that these data can also be used more broadly to study the impact of health policies across different regions in a more efficient and timely manner. Methods: As a test use case, we studied the relationships between abortion-related search volume, local abortion rates, and local abortion policies available for study. Results: Our initial integrative analysis found that, both in the US and internationally, the volume of Internet searches for abortion is inversely proportional to local abortion rates and directly proportional to local restrictions on abortion. Conclusion: These findings are consistent with published evidence that local restrictions on abortion lead individuals to seek abortion services outside of their area. Further validation of these methods has the potential to produce a timely, complementary data source for studying the effects of health policies.
Also related to fertility, Reis and Brownstein @cite_10 show that the volume of Internet searches for abortion is proportional to local abortion rates and directly proportional to local restrictions on abortion.