UNWTO World Tourism Barometer and Statistical Annex, March 2021
Bibliographic record
Abstract
International tourism further weakens in January 2021 with a drop of 87% After the unprecedented 73% drop in international tourism recorded in 2020 under the impact of the COVID-19 pandemic, demand for international travel remained very weak at the beginning of 2021. International tourist arrivals (overnight visitors) plunged by 87% in January 2021, amid new outbreaks and tighter travel restrictions. This follows a decline of 85% in the last quarter of 2020. By regions, Asia and the Pacific (-96%), the region which continues to have the highest level of travel restrictions in place, recorded the largest decrease in international arrivals in January. Europe and Africa both saw a decline of 85% in arrivals, while the Middle East recorded a drop of 84%. International arrivals in the Americas decreased by 77% in January, following somewhat better results in the last quarter of the year. Due to the worsening of the pandemic with a surge of cases and the emergence of new variants, many countries reintroduced stricter travel restrictions, including mandatory testing, quarantines and in some cases a complete closure of borders, on top of local lockdowns, all weighing on the resumption of international travel. In addition, the speed and distribution of the vaccination roll-out have been slower than expected and quite uneven across countries and regions. With 32% of destinations worldwide showing complete border closures in early February and another 34% with partial closure, UNWTO expects international tourist arrivals to be down about 85% in the first quarter of 2021 over the same period of 2019. This would represent a loss of some 260 million international arrivals when compared to pre-pandemic levels. Looking ahead, UNWTO has outlined two scenarios for 2021.The first scenario points to a rebound in July, which would result in a 66% increase in international arrivals for the year 2021 compared to the historic lows of 2020. In this case, arrivals would still be 55% below the levels recorded in 2019. The second scenario considers a potential rebound in September, leading to a 22% increase in arrivals compared to last year. Still, this would be 67% below the levels of 2019. The scenarios consider a number of factors such as a gradual improvement of the epidemiological situation, a continued roll-out of the COVID-19 vaccine, a significant improvement in traveller confidence and a major lifting of travel restrictions, in particular in Europe and the Americas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".