Name Benjamin McMahonName Benjamin McMahon

Title Scientist at Los Alamos National LaboratoryTitle Scientist at Los Alamos National Laboratory

Country USACountry USA

Modeling tool to support rinderpest outbreak preparedness

Benjamin McMahon, Paul Fenimore, Judy Mourant, Nick Hengartner, Carrie Manore, Mira

Dimitrijevic, Paul Rossiter, Samia MetwallyLos Alamos National Laboratory, FAO

Past rinderpest outbreaks

• Ethiopia, 1890, 90% cattle mortality• Zimbabwe 1896, 90% mortality• South Africa 1895-1896, 66.6% of 1.6 million cattle died or

slaughtered• Nigeria and Chad basin 1982-84, 2 million deaths?• Tanzania and Kenya, 1964-1968. Wildebeest population

increases from 250,000 to >1million after eradication of rinderpest from cattle

• Pakistan, 1992, 40,000-50,000 cattle

Our motivation for modeling tool

- Quantify potential impact and motivate virus destruction & sequestration

- Significant stocks of rinderpest virus are maintained under laboratory conditions for responding to contingencies (outbreaks) and research.

- These stocks create a potential risk for re-initiation of rinderpest infections. - Historical outbreaks in cattle need to be considered carefully when

predicting the course of potential future outbreaks because of changes in:- The level of pre-existing immunity- The density and type (dairy, range, transported) of cattle- The availability of surveillance and mitigations, such as:

- Vaccination- Short range movement controls and hygiene- Long range movement controls- Culling

A rinderpest outbreak could be devastating: Simulated spread of rinderpest in 101 days after point introduction to USA

Manore, McMahon, Fair, Hyman, Brown, & Labute, “Disease properties, geography, and mitigation strategies in a simulation spread of rinderpest across the United States” Vet. Res., 42:1 (2011).

What modeling can and cannot do

• Modeling can:– Translate historical events to contemporary situations, using best

available understanding of how diseases progress– Provide specific numbers and their dependencies, to guide planning

• Modeling cannot:– Predict the future. The actual course of the epidemic depends on

preparedness measures, responses, the particular viral strain, and random events

Determinants of disease spread Frequency of long and short range cattle movement

IS

SS

S

S

FAO modeled cattle density

5 km spatial resolution, from http://www.fao.org/3/a-a1259e.pdf

Comparing types of mitigation

Num

ber of Counties Infected

General impact of three types of mitigation

Time (days)

No Control

Movement Control

Vaccination

Culling

Disease progression rates determine required timescale of intervention (a couple of weeks).

S = SusceptibleE = Exposed (incubating)I = InfectiousH = Seriously diseasedD = DeadR = Recovered (Immune)VS= Vaccinated, still susceptibleV = Vaccinated, immune

S E I H D

RVVS

Disease progression scheme

The planning tool http://bsvepi.lanl.gov/rinderpest (password protected)

Phases of epidemic1. Exponential growth (R0=5)2. Short-range movement

controls and hygiene measures

3. Plus vaccination4. Long-range spread5. Control6. Eradication

Eradication

Control

MitigationsInfectivity

( * 5 days = R0 ~ 5)Number of sick cattle when epidemic is identified

(25 cows)Further delay and effectiveness of short-range movement restrictions & hygiene

(7 days, cut in half)Further delay and rate of vaccination

(4 weeks, 10,000 cattle / day)Extent of long-range cattle trade occurring, and screening by illness

(0.15% cattle not seriously ill moved per day)

Total dead cattle = 885 cowsVaccine doses given = 315,000 doses

Area affected by epidemic = 17,000 km2

Time to epidemic peak = 10 weeksTime to eradication = 17 weeks

Consequence metrics

An example epidemic:

Short-range movement controls are immediate

upon epidemic identification

Further observations• Long-range transport of animals has been added to model, with user-selected

destination and number of healthy animals moved. Infectious animals can be selected from Incubating, Ill, and seriously ill fractions.

• Mixing lengths in model can account for differences between, for example, dairy and range cattle.

• Virulent strains of rinderpest have a mortality rate of 80% and R0 ~ 5.• Less virulent strains of rinderpest have lower mortality rate and R0.• It is possible that naïve populations of cattle select for virulent strains as an

epidemic progresses.

• Studies of the 2001 FMD epidemic in Britain suggest short range movement controls and hygiene measures can decrease R0 by a factor two.

• The calculations here were for cattle densities of ~150 cattle / km2.

How to use this tool for planning

• Account for local variations in transmissibility, vaccination rate, distance range of spread, long-range transmission, escape from laboratory, movement controls.

• Convert estimates of dead and vaccinated cattle, duration and geographic extent of epidemic and nature of control measures into costs.

• Estimate required attributes of surveillance system to rapidly identify epidemic, and the corresponding needed size of vaccine stockpile.

• Balance cost of preparedness against acceptance of risk.

Conclusions & Acknowledgement• We have provided a planning tool which provides

considerable flexibility in simulating a rinderpest outbreak and mitigations

• It needs to be developed and validated in a country-specific manner, in a collaboration between each country and FAO

• The earlier an outbreak is halted, the better.

Questions & Answers