A household-structured SIR transmission model reveals that agricultural workers face peak disease prevalence 1.41–1.69 times higher than the general U.S. population during a baseline R₀ = 2.0 respiratory outbreak, with final outbreak sizes 1.29–1.42 times larger. Critically, household crowding alone accounts for 54–68% of this disparity. For California's orange, lettuce, and strawberry harvests, peak productivity losses reach 0.50–0.63%, scaling to 2.4× worse under higher transmissibility (R₀ = 3) with fully symptomatic infections.
This modeling work quantifies what farmworker health advocates have long argued qualitatively: structural living conditions — not just individual health behaviors — are the primary disease amplifier in this workforce. The finding that crowding explains the majority of excess burden shifts the intervention conversation away from individual-level messaging toward housing policy and worksite infrastructure. It also connects food system fragility directly to public health equity, a linkage underexplored in pandemic preparedness literature.
Limitations are meaningful: this is a compartmental model with simplified assumptions about household size distributions, regional heterogeneity, and labor substitutability. Productivity loss estimates apply only to three California crops, limiting generalizability to other states or commodity types. Vaccination and obesity disparities are acknowledged but modeled parametrically rather than mechanistically. As a preprint posted on medRxiv and not yet peer-reviewed, the specific quantitative estimates should be treated as preliminary. Still, the framework is a valuable and actionable contribution to agricultural pandemic preparedness planning.