Illegal Border Crossings “Plummeted” In January

TLDR

This press release discusses border crossing statistics and the analysis notes that claims of dramatic drops (85-93%) are based on comparing very specific 11-day periods, which is potentially misleading. It points out that seasonal patterns typically show January decreases, a downward trend began before the administration change, and full implementation of policies takes time. The analysis concludes that attributing the entire decrease to new policies is premature and oversimplified without considering seasonal patterns and existing trends.

Key Points to Consider

1. Seasonal Patterns

• Border crossings typically decrease in winter months due to harsh weather conditions
• January numbers are historically lower than summer/fall months
• The decline started before Trump took office (96,048 in December to 61,465 in January)

2. Statistical Context

• The 85% and 93% drops cited are comparing very specific 11-day periods
• This short timeframe doesn’t establish a meaningful trend
• Using percentage changes over such brief periods can be misleading

3. Pre-existing Trends

• Border apprehensions had already fallen below 100,000 in November 2024
• The downward trend began before the administration change

4. Policy Implementation Timeline

• Executive orders take time to implement fully
• The immediate dramatic drops claimed would be logistically unlikely
• Military deployment and operational changes require significant setup time

5. Data Interpretation Issues

• Lower apprehension numbers don’t necessarily mean fewer crossing attempts
• Changes in enforcement strategies can affect apprehension statistics
• The data doesn’t account for “gotaways” or undetected crossings

While there was indeed a decrease in border apprehensions in January 2025, attributing this entirely to Trump’s policies is premature and oversimplified. The narrative ignores seasonal patterns, pre-existing trends, and the complexity of immigration dynamics. A more accurate assessment would require several months of data and consideration of multiple factors beyond just policy changes.