Coupling Vector-host Dynamics with Weather Geography and Mitigation Measures to Model Rift Valley Fever in Africa

¹ Los Alamos National Laboratory, Theoretical Biology and Biophysics, Los Alamos, NM 87545
² Department of Mathematics, Tulane University, New Orleans, LA 70118
³ Center for Computational Science, Tulane University, New Orleans, LA 70118
⁴ Lawrence Livermore National Laboratory , Applied Statistics Group - Computational Engineering Division, Mailstop L-174, 7000 East Ave. Livermore, CA 94550
⁵ Los Alamos National Laboratory, Environmental Stewardship, K404, Los Alamos, NM 87545

^⋆ Corresponding author. E-mail: jmfair@lanl.gov

Abstract

We present and characterize a multi-host epidemic model of Rift Valley fever (RVF) virus in East Africa with geographic spread on a network, rule-based mitigation measures, and mosquito infection and population dynamics. Susceptible populations are depleted by disease and vaccination and are replenished with the birth of new animals. We observe that the severity of the epidemics is strongly correlated with the duration of the rainy season and that even severe epidemics are abruptly terminated when the rain stops. Because naturally acquired herd immunity is established, total mortality across 25 years is relatively insensitive to many mitigation approaches. Strong reductions in cattle mortality are expected, however, with sufficient reduction in population densities of either vectors or susceptible (ie. unvaccinated) hosts. A better understanding of RVF epidemiology would result from serology surveys to quantify the importance of herd immunity in epidemic control, and sequencing of virus from representative animals to quantify the realative importance of transportation and local reservoirs in nucleating yearly epidemics. Our results suggest that an effective multi-layered mitigation strategy would include vector control, movement control, and vaccination of young animals yearly, even in the absence of expected rainfall.