bioRxivEcology
Role of monkeys in the sylvatic cycle of chikungunya virus in Senegal
B. M. Althouse, M. Guerbois, D. A. T. Cummings, O. Diop, O. Faye, A. Faye, D. Diallo, B. D. Sadio, A. Sow, O. Faye, A. A. Sall, M. Diallo, B. Benefit, E. Simmons, D. M. Watts, S. C. Weaver, K. A. Hanley
Abstract
Athropod-borne viruses (arboviruses) pose the greatest risk of spillover into humans of any class of pathogens. Such spillover may occur as a one-step jump from a reservoir host species into humans or as a two-step jump from the reservoir to a different amplification host species and thence to humans. Despite the widespread havoc wreaked by emerging arboviruses, little is known about their transmission dynamics in reservoir and amplification hosts. Here we used serosurveillance and mathematical modeling to elucidate the role of monkeys in the sylvatic, enzootic cycle of chikungunya virus (CHIKV). Over three years, 219 African green monkeys, 78 patas monkeys, and 440 Guinea baboons were captured in the region surrounding Kedougou, Senegal. The age of each animal was determined by anthropometry and dentition, and exposure to CHIKV was determined by detection of neutralizing antibodies. We estimate age-specific CHIKV seroprevalence, force of infection (FoI), and basic reproductive number (R0) in each species. Among the different species, CHIKV Fol ranged from 0.13 to 1.12 (95% CI, 0.81-2.28) and R0 ranged from 1.5 (95% CI, 1.3-1.9) to 6.6 (95% CI, 5.1-10.4). CHIKV infection of infant monkeys was detected even when the virus was not detected in a concurrent survey of primatophilic mosquitoes and when population seropositivity, and therefore immunity, was too high for monkeys themselves to support continuous CHIKV transmission. We therefore conclude that monkeys in this region serve primarily as amplification rather than reservoir hosts of CHIKV. Additional efforts are needed to identify other vertebrate hosts capable of supporting continuous circulation.
- organism: non-human primate
- research focus: host-pathogen & immune response
- approach: statistical model
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