Date of Award


Document Type


Degree Name

Bachelor of Arts


Biochemistry & Molecular Biol.

First Advisor

Jonathan Richardson



Global rat populations are increasing at an alarming rate across the world. In turn, this increases the risk of human-rat interactions and the potential spread of zoonotic pathogens and parasites. Rats are the second most common host of disease and can have detrimental effects in urban ecosystems. Rattus rattus and R. norvegicus are the two most abundantly distributed species of rats and are the target organism for this study. The aim of this study is to understand the connection between environmental and socioeconomic factors that influence the rate of zoonotic disease in rats. We developed two hypotheses to gain a better understanding: (1) there will be a higher prevalence of disease in rats in areas of lower biodiversity, as explained by the dilution effect, and (2) there will be a higher prevalence of disease in rats in countries of lower sanitation scores, GDP, and Gini Index. To test these hypotheses, we performed a meta-analysis on a global scale. We extracted our data from papers in the Web of Science database and collected the environmental and socioeconomic datasets from additional databases. All statistical analyses were performed in RStudio.


Our initial search returned 636 studies that we assessed for eligibility. From those, 242 studies are included in our final dataset, and 903 data points were extracted for analysis. Our dataset includes data from 64 countries and 205 pathogen or parasite species. The top pathogen represented was Leptospira spp., Bartonella spp., Toxoplasma gondii, Capillaria hepatica, and Leishmania spp. The pathogen/parasite that was tested for the most was Leptospira spp., and the pathogen/parasite that had the highest overall percent positivity was C. hepatica, a common nematode. We found a negative relationship between 3 of the 4 socioeconomic variables and rodent disease burden. The analyses point to the value of knowledge we can gain from looking at environmental and social factors in predicting disease prevalence. There is clearly a public health interest in understanding the disease ecology of commensal rodents and the pathogens they transmit. But our study also provides a baseline understanding of the environmental predictors of infection risk, and how to use global data on rat disease ecology to make predictions in unstudied areas.

Available for download on Wednesday, May 28, 2025