Ecologies of Risk: Malaria and Settler Landscape Transformation in 19th-Century Ontario.

OBJECTIVES

This study examines how settler-driven environmental change shaped malaria transmission and mortality in 19th-century southern Ontario. It aimed to understand the biosocial and ecological conditions that sustained endemic malaria in a temperate, colonial context.

MATERIALS AND

METHODS

We analyzed 2702 deaths attributed to probable malaria from 1831 to 1900 using civil, cemetery, parish, and municipal records. Each record was coded for age, sex, occupation, region, and season of death. To assess environmental influences, we incorporated monthly temperature and rainfall data from Toronto as a regional climate proxy. We examined demographic and spatial patterns at multiple scales, including towns, settlement type (urban/rural), and regional groupings, alongside temporal and seasonal variation. Statistical comparisons were used to explore associations, including nonlinear modeling of rainfall and malaria mortality.

RESULTS

Probable malaria mortality declined over time but persisted throughout the century. Children under 5 accounted for over half of recorded deaths, while adults in agricultural occupations were also disproportionately affected. Rural areas, particularly in western Ontario, experienced the highest mortality. Generalized additive model (GAM) results indicated a strong nonlinear association between rainfall and malaria deaths (p < 0.001), while temperature was not a significant predictor.

CONCLUSIONS

Malaria's persistence in 19th-century Ontario reflected a structural embedding of disease risk within settler-transformed landscapes. Deforestation, altered hydrology, and agricultural intensification created ecologies conducive to mosquito breeding. Vulnerability was not evenly distributed but shaped by age, labor, and proximity to altered environments. These findings underscore the importance of integrating environmental and historical data to reconstruct past disease ecologies and illustrate how evolutionary mismatch can drive vulnerability even in short-lived endemic contexts.