Schematic of sub-populations in the metapopulation, for a 2 region example.

<p>Note homogeneous mixing occurs within each side of the border.</p

The (local) disease model. S = Susceptible, L = Latently infected, N = non-infectious clinically apparent TB, I = infectious clinically apparent TB, D = Detected but not yet treated, T = undergoing Treatment but still infectious.

<p>The parameters are described in the text and summarised in the table in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034411#pone.0034411.s001" target="_blank">File S1</a>. Here .</p

Sensitivity analysis of the model parameters, comparing the relative monotonicity of the cumulative number with active TB (I+N+D+T) for all sub-populations with various parameters.

<p>‘PNG’ refers to sub-population (1,1) parameters.</p

The relative sensitivities of the intervention parameters at ‘2032’.

<p>The relative sensitivities of the intervention parameters at ‘2032’.</p

Effect of improved health care system capacity.

<p>Starting with a baseline case ascertainment of 80% and a small health care system (0.1% of population are HCWs, 1:15 and 1:50 ratio of bed and contact-tracing capacities to HCWs, as above), this figure shows the effect of doubling both the health care capacity and the health care workforce at different times after the first detected case. This increase in capacity represents the transition from a small health care system to a medium health care system, as defined in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0005018#pntd.0005018.g005" target="_blank">Fig 5</a>. This clearly shows the importance of early detection; the time delay in delivering the additional capacity is less important over this timescale of 0–8 weeks, because the existing health care system is capable of accommodating patients in the early stage of the outbreak.</p

Population and health care system diversity in Southeast Asia and the Western Pacific.

<p><b>(A)</b> Population density ranges from less than 1 person per square kilometre in parts of Papua New Guinea and Indonesia to over 6,800 people per square kilometre in Singapore. Data obtained from Center for International Earth Science Information Network (CIESIN), Columbia University (<a href="http://sedac.ciesin.columbia.edu/gpw" target="_blank">http://sedac.ciesin.columbia.edu/gpw</a>). <b>(B)</b> Number of health care workers per thousand population ranges from 1.2 in Cambodia to 11.5 in Brunei Darussalam. Data obtained from Global Health Observatory data repository (<a href="http://apps.who.int/gho/data/" target="_blank">http://apps.who.int/gho/data/</a>).</p

Effect of increased case ascertainment.

<p>Starting with a baseline case ascertainment of 20%, this figure shows the effect of boosting ascertainment to 100% (i.e., perfect detection) at different times after the first detected case. This clearly shows the simultaneous importance of early detection and high ascertainment; provision of one is not a substitute for lack of the other.</p

Effect of behavioural interventions in Southern region.

<p>The effect of reducing the force of infection in the community and/or from dead bodies by 25%, in the rural population of the Southern region where community transmission is low. When transmission is reduced in both settings, the overall force of infection is sufficiently low that uncontrolled outbreaks never occur.</p

Effect of behavioural interventions in Port Moresby region.

<p>The effect of reducing the force of infection in the community and/or from dead bodies by 25%, in the urban population of Port Moresby where community transmission is high. When case ascertainment is 40% or higher, reducing transmission in both settings has a synergistic effect on outbreak control.</p

The Ebola model.

<p>The natural history of infection comprises susceptibility (S), exposure (E) at a rate determined by the force of infection β and the current prevalence of infectious individuals and unburied dead bodies. Exposed individuals progress to mild infectiousness prior to developing symptoms (I0) at rate σ, and symptomatic infection (I) at rate γ₀, followed by either death (D) or recovery (R) at rate γ₁. The proportion of infections leading to death or recovery is informed by estimates of the case fatality ratio (CFR). Dead bodies remain infectious prior to burial (B) at rate τ. Ascertainment of cases (with probability p_asc) allows symptomatic individuals to be hospitalised in isolation wards (H), which reduces their contribution to transmission and increases their probability of recovery. Full equations describing the model are provided in Model description in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0005018#pntd.0005018.s001" target="_blank">S1 Methods</a>.</p