Computational Modeling of Interventions and Protective Thresholds to Prevent Disease Transmission in Deploying Populations

Abstract

Military personnel are deployed abroad for missions ranging from humanitarian relief efforts to combat actions; delay or interruption in these activities due to disease transmission can cause operational disruptions, significant economic loss, and stressed or exceeded military medical resources. Deployed troops function in environments favorable to the rapid and efficient transmission of many viruses particularly when levels of protection are suboptimal. When immunity among deployed military populations is low, the risk of vaccine-preventable disease outbreaks increases, impacting troop readiness and achievement of mission objectives. However, targeted vaccination and the optimization of preexisting immunity among deployed populations can decrease the threat of outbreaks among deployed troops. Here we describe methods for the computational modeling of disease transmission to explore how preexisting immunity compares with vaccination at the time of deployment as a means of preventing outbreaks and protecting troops and mission objectives during extended military deployment actions. These methods are illustrated with five modeling case studies for separate diseases common in many parts of the world, to show different approaches required in varying epidemiological settings.

Evolution and Use of Dynamic Transmission Models for Measles and Rubella Risk and Policy Analysis

“…One model of a hypothetical outbreak in South Africa assumed that measles treatment impacts transmission (without providing any support for this assumption, which appears inconsistent with other models and the evidence), and suggested that saturation of treatment may support sustained transmission. Based on current rates of immunization among U.S. troops, a recent study found limited benefit associated with predeployment boosting immunization with MRCV for troops going to Afghanistan, although the model did not explicitly consider the impact of individual importations that could lead to limited local transmission and associated costs …”

Modelling Risk to US Military Populations from Stopping Blanket Mandatory Polio Vaccination

“…The military population structure for this study was built upon previous analyses [ 23 ]. The simulated deployed population consisted of 4 subpopulations defined by interaction with the local population, ranging from negligible to high levels of daily contact.…”

“…In- and outbound rotation rates ( b IN and b OUT ) varied over the 10-year period to allow for force increase and decrease (see Figure 1 ) and a daily casualty rate ( μ ) accounted for removal of individuals for reasons other than rotation or polio-related disease. See Burgess et al [ 23 ] for additional population details.…”