ArticlePloS one2019
Using social media to estimate Zika's impact on tourism: #babymoon, 2014-2017.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- From bites to ripple effects: Unraveling the health, economic, and social effects of arboviral epidemics in Mainland France.IJID regions · 2026Article
- Artificial intelligence in public health: the potential of epidemic early warning systems.The Journal of international medical research · 2023Review
- Exploring the experiences of pregnant women in the U.S. during the first year of the Covid-19 pandemic.The Journal of social issues · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.