Turns Out USAID Funding May Have Caused a Lot of Death and Destruction

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After Ro Khanna accused Elon Musk of killing 4.5 million children with DOGE-led USAID cuts, only to fold like a cheap shirt after Musk threatened a defamation suit, someone decided to use the study Khanna cited as his source to see how many deaths USAID funding caused.

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Guess what. It's a lot.

The entire post reads:

The USAID Mortality Multiplier: A Counterfactual Analysis of Regime-Enabled Excess Deaths, 2001–2025

We apply fixed-effects Poisson regression to panel data from the 133 countries in the original Lancet study. Our key independent variable is annual USAID disbursements per capita. We control for the usual suspects — GDP, literacy, doctors per thousand — but add one critical covariate the original paper omitted: an index of left-wing governance strength, scored from 0 to 1 based on the proportion of cabinet positions held by self-identified socialists, communists, or Peronists during each year.

The model reveals a robust positive association: each additional dollar of USAID per capita is associated with 47.3 excess deaths per 100,000 population under left-wing administrations. Using the same microsimulation framework as the Lancet paper, we project that USAID’s total spending from 2001 to 2025 enabled approximately 187 million excess deaths, of which 68 million were children under five.

Our counterfactual — what if USAID had never existed? — shows that 68 million kids would still be alive today.

The confidence intervals are wide, the causal assumptions are heroic, and the governance index is completely made up. But hey, it matches their methods exactly.

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Excellent work.

Even Musk took note.

Their own logic.

Yes, it is all complete BS. But it helps advance the narrative, so they run with it.

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Looking at you, Ro Khanna.

See, this is a two-way street. One study can claim DOGE cuts led to 4.5 million deaths, but applying that same methodology shows that USAID funding may have led to ten times as many deaths. For some reason, we doubt the same people citing the first study will be eager to talk about the second set of numbers.

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