Using social media to estimate Zika's impact on tourism: #babymoon, 2014-2017

• Published in: PloS one Vol. 14; no. 2; p. e0212507
• Main Authors: Gallivan, Mark, Oppenheim, Ben, Madhav, Nita K
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 21.02.2019; Public Library of Science (PLoS)
• Subjects: Anopheles; Behavior; Beliefs, opinions and attitudes; Biology and life sciences; Birth defects; Brazil; Computer and Information Sciences; Congenital defects; Content analysis; Digital media; Epidemics; Epidemiology; Female; Humans; Infant, Newborn; Infection; Influence; Latin America - epidemiology; Male; Medicine and Health Sciences; Microcephaly - epidemiology; Microcephaly - prevention & control; Microencephaly; Parents; Pregnancy; Pregnancy Complications, Infectious - epidemiology; Pregnancy Complications, Infectious - prevention & control; Pregnant women; Risk Reduction Behavior; Social Media; Social networks; Social Sciences; Tourism; Travel - statistics & numerical data; Travelers; Trends; Vector-borne diseases; Viruses; Womens health; Zika virus; Zika virus infection; Zika Virus Infection - complications; Zika Virus Infection - epidemiology; Zika Virus Infection - prevention & control; Latin America; Brazil; San Francisco California; Western Hemisphere; California; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0212507

Zika virus infection during pregnancy can cause microcephaly and other birth defects. We hypothesized that the Latin America Zika epidemic resulted in pregnant women and their partners adopting behavioral changes to limit risk, leading them to forego travel to Zika-affected locations. We evaluated this hypothesis by studying travelers' intent and behavior through Twitter data related to babymoon: a holiday taken by parents-to-be before their baby is born. We found the odds of mentioning representative Zika-affected locations in #babymoon tweets dropped significantly (Odds ratio: 0.29, 95% CI: 0.20-0.40) after the Zika-microcephaly association became well-known. This result was further corroborated through a content analysis of #babymoon tweets mentioning Zika-affected locations, which identified if the Twitter user was physically present in the Zika-affected locations. Conversely, we found a small but statistically insignificant increase in the odds of mentioning Zika-free locations from #babymoon tweets (Odds Ratio: 1.11, 95% CI: 0.97-1.27) after the Zika-microcephaly association became well-known.