Fevers of unknown origin complicate treatment and prevention of infectious diseases and are a global health burden. We examined risk factors of self-reported fever—categorized as “malarial” and “nonmalarial”—in households adjacent to national parks across the Ugandan Albertine Rift, a biodiversity and emerging infectious disease hotspot. Statistical models fitted to these data suggest that perceived nonmalarial fevers of unknown origin were associated with more frequent direct contact with wildlife and with increased distance from parks where wildlife habitat is limited to small forest fragments. Perceived malarial fevers were associated with close proximity to parks but were not associated with direct wildlife contact. Self-reported fevers of any kind were not associated with livestock ownership. These results suggest a hypothesis that nonmalarial fevers in this area are associated with wildlife contact, and further investigation of zoonoses from wildlife is warranted. More generally, our findings of land use–disease relationships aid in hypothesis development for future research in this social-ecological system where emerging infectious diseases specifically, and rural public health provisioning generally, are important issues.
Bibliographical noteFunding Information:
This research was supported by the US National Science Foundation (CNH-EX 1114977). We are grateful to the respondents for their time and contribution and to Ogwang Jimmy, Ahabyona Peter, and Kamuli Elizabeth for their assistance with data collection. We also thank Makerere University Biological Field Station, Uganda Wildlife Authority, Uganda National Council for Science and Technology, and many local officials for providing assistance and granting permission for this research. Mark Grote, Colin Chapman, and Tom Butynski provided valuable insights. The paper was improved substantially based on comments from two anonymous reviewers.
© 2017, EcoHealth Alliance.
- Central Africa
- Fevers of unknown origin
- Human–wildlife interactions
- Protected areas