title: Predicting Rift Valley Fever Inter-epidemic Activities and Outbreak Patterns: Insights from a Stochastic Host-Vector Model.
abstract: Rift Valley fever (RVF) outbreaks are recurrent, occurring at irregular intervals of up to 15 years at least in East Africa. Between outbreaks disease inter-epidemic activities exist and occur at low levels and are maintained by female Aedes mcintoshi mosquitoes which transmit the virus to their eggs leading to disease persistence during unfavourable seasons. Here we formulate and analyse a full stochastic host-vector model with two routes of transmission: vertical and horizontal. By applying branching process theory we establish novel relationships between the basic reproduction number, R0, vertical transmission and the invasion and extinction probabilities. Optimum climatic conditions and presence of mosquitoes have not fully explained the irregular oscillatory behaviour of RVF outbreaks. Using our model without seasonality and applying van Kampen system-size expansion techniques, we provide an analytical expression for the spectrum of stochastic fluctuations, revealing how outbreaks multi-year periodicity varies with the vertical transmission. Our theory predicts complex fluctuations with a dominant period of 1 to 10 years which essentially depends on the efficiency of vertical transmission. Our predictions are then compared to temporal patterns of disease outbreaks in Tanzania, Kenya and South Africa. Our analyses show that interaction between nonlinearity, stochasticity and vertical transmission provides a simple but plausible explanation for the irregular oscillatory nature of RVF outbreaks. Therefore, we argue that while rainfall might be the major determinant for the onset and switch-off of an outbreak, the occurrence of a particular outbreak is also a result of a build up phenomena that is correlated to vertical transmission efficiency.
authors.affiliation: School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa.|Modelling Unit, International Center of Insect Physiology and Ecology, Nairobi, Kenya.|Departmento de Matemática e Informática, Universidade Eduardo Mondlane, Maputo, Mozambique.
authors.forename: Sansao A
authors.initials: SA
authors.lastname: Pedro
authors.affiliation: School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa.
authors.forename: Shirley
authors.initials: S
authors.lastname: Abelman
authors.affiliation: International Maize and Wheat Improvement Center (CIMMYT) ICRAF House, United Nation, Avenue, Gigiri, Nairobi, Kenya.
authors.forename: Henri E Z
authors.initials: HE
authors.lastname: Tonnang
mesh_terms: D000330:Aedes / Q000821:virology; D000351:Africa, Eastern / Q000453:epidemiology; D000818:Animals; D004196:Disease Outbreaks; D018562:Disease Transmission, Infectious; D058872:Epidemics; D006801:Humans; D018445:Infectious Disease Transmission, Vertical; D007630:Kenya / Q000453:epidemiology; D008954:Models, Biological; D008962:Models, Theoretical; D000072138:Mosquito Vectors / Q000821:virology*; D011891:Rain; D012295:Rift Valley Fever / Q000453:epidemiology* / Q000635:transmission* / Q000821:virology; D012296:Rift Valley fever virus / Q000302:isolation & purification; D012621:Seasons; D013019:South Africa; D013269:Stochastic Processes; D013636:Tanzania / Q000453:epidemiology