Arenavirus Dynamics in Experimentally and Naturally Infected Rodents

• Published in: EcoHealth 2017-09, Vol.14 (3), p.463-473
• Main Authors: Mariën, Joachim, Borremans, Benny, Gryseels, Sophie, Broecke, Bram Vanden, Becker-Ziaja, Beate, Makundi, Rhodes, Massawe, Apia, Reijniers, Jonas, Leirs, Herwig
• Format: Article
• Language: English
• Subjects: Animal Ecology; Animals; Animals, Wild - immunology; Animals, Wild - virology; Antibodies; Arenaviridae Infections - immunology; Arenaviridae Infections - pathology; Arenavirus - immunology; Arenavirus - pathogenicity; Bayesian analysis; Disease Reservoirs - virology; Ecosystems; Environmental Health; Experimental infection; Immune response; Immune system; Infectious diseases; Medicine; Medicine & Public Health; Mice - virology; Microbiology; Original Contribution; Pathogens; Public Health; Ribonucleic acid; RNA; Rodent Diseases - immunology; Rodent Diseases - pathology; Rodent Diseases - virology; Rodents; Tanzania; Viral infections; Water and Health; Wildlife
• ISSN: 1612-9202; 1612-9210
• DOI: 10.1007/s10393-017-1256-7

Infectious diseases of wildlife are typically studied using data on antibody and pathogen levels. In order to interpret these data, it is necessary to know the course of antibodies and pathogen levels after infection. Such data are typically collected using experimental infection studies in which host individuals are inoculated in the laboratory and sampled over an extended period, but because laboratory conditions are controlled and much less variable than natural conditions, the immune response and pathogen dynamics may differ. Here, we compared Morogoro arenavirus infection patterns between naturally and experimentally infected multimammate mice ( Mastomys natalensis ). Longitudinal samples were collected during three months of bi-weekly trapping in Morogoro, Tanzania, and antibody titer and viral RNA presence were determined. The time of infection was estimated from these data using a recently developed Bayesian approach, which allowed us to assess whether the natural temporal patterns match the previously observed patterns in the laboratory. A good match was found for 52% of naturally infected individuals, while most of the mismatches can be explained by the presence of chronically infected individuals (35%), maternal antibodies (10%), and an antibody detection limit (25%). These results suggest that while laboratory data are useful for interpreting field samples, there can still be differences due to conditions that were not tested in the laboratory.