Animal Welfare and Policy Risk Index (AWPRI)

The AWPRI compares the volume of animal use a country carries against the governance capacity standing over that use. Layer 1 measures animal-use exposure, Layer 2 measures the stock of binding welfare law and the institutional conditions under which welfare law is enforced, and Layer 3 measures how national research effort divides between automating animal agriculture and studying animal welfare. The index covers 12 indicators over 24 countries and the years 2010 to 2022, with every value traceable to a named public source.

World Map

Index Year

Point at a country to see the profile card, and click the country to open the full country page. On a touch screen, one tap shows the card and a second tap opens the page. A darker shade means a higher score. Every variable is coded so that a higher number means more animals exposed, weaker welfare law, worse institutional conditions for enforcing welfare law, or research effort tilted further towards automating animal agriculture. Scores are relative to the other 23 countries in the same year, so they say where a country sits in this panel, not how much welfare harm occurs in absolute terms.

Layer Score Breakdown

L1. Animal-use exposure (four variables)L2. Governance capacity (five variables)L3. AI amplification (three variables)

Each country's three layer scores in the selected year, ordered by overall AWPRI. Each layer is the mean of its own variables, and the composite is the mean of the three layers, so a variable in the three-variable layer carries more weight than one in the five-variable layer. The exact weights are on the methodology page.

Change since 2010

Highest AWPRI Scores, 2022

Rank	Country	AWPRI	Group
#1	China	0.703	higher risk
#2	Vietnam	0.663	higher risk
#3	Thailand	0.612	higher risk
#4	India	0.578	higher risk
#5	South Korea	0.545	lower risk
#6	United States	0.504	lower risk
#7	Brazil	0.492	lower risk
#8	Canada	0.480	lower risk
#9	Australia	0.479	lower risk
#10	Mexico	0.474	lower risk

Full rankings with all three layers →