Spatial patterns on the edge of stability: measles in the

Sahel

• Great success in measles eradication

• Distribution of that success has not been equitable

Susceptible

Infected

Immune

• Poster child for non-linear dynamics and spatial epidemiology

Niger

Niamey

• Culturally and environmentally diverse

• Highest reported birthrate in the world (51 per 1000)

• Low vaccine coverage in Niger and surrounding countries

• Relatively high case fatality

http://patstoll.org

http://afrikafont.free.fr

Measles Dynamics in Niger

measlesAll Niger

Measles epidemic begin in the dry season

Aggregate measures can obscure local complexity

measles

• Timing is consistent with the national pattern

• High variability in outbreaks size

• Frequent local extinction

Local Dynamics: Niamey

€

λ =βtStItα

It+1 ~ neg binomial(It ,λ )

St+1 = St − It+1 + births

Estimating Seasonal Transmission

Seasonal TSIR Model

Susceptible

Infected

Immune

λ

Recovery rate

Births

Observational Model

€

Ot ~ binomial(It ,Pobs)Observed

Cases

Pobs

Fit state space model state using Bayesian MCMC methods

Estimated Seasonality

• Strong seasonality in Niamey

• Related to the rainy season

- Rural-urban migration due to agriculture?

• 3-fold greater seasonality than pre-vaccine London

Seasonality Generates Complex Epidemic Dynamics

Strength of seasonality

Birt

h ra

te p

er 1

000

London Niamey

• Stronger seasonality leads to more episodic dynamics at all birthrates

• Potential for deterministic chaos (!)

Deep Troughs Make Stochastic Extinction Likely

Strength of seasonality

Birt

h ra

te p

er 1

000

London Niamey

• Stronger seasonality leads to more episodic dynamics at all birthrates

• Potential for deterministic chaos

• Stochastic extinction is likely when there are few cases

Dynamics set the stage for spatial dynamics

Strong seasonality and high birth rates give rise to locally instable dynamics and erratic outbreaks that can vary in size over orders of magnitude . . .

. . . public health strategies need to be local and reactive.

2003-4 outbreak in Niamey

• Large outbreak (>11,000 cases) following 2 years of few cases.

• In response a collaborative effort between MOH, WHO, and MSF was mobilized to vaccinate

Timing is Everything

Spatially implicit model showed that campaign was unlikely to have had a great impact on the course of the epidemic

Within Niamey Model

• > 9000 case records

• 26 health districts

Within Niamey Model

• > 9000 case records

• 26 health districtsQuickTime™ and a

MPEG-4 Video decompressorare needed to see this picture.

Within Niamey Model

• Spatially explicit model of epidemic spread in Niamey

€

E cases at i on day t[ ] = β tSi,t−1 (dij +1)−θ I jj

∑dij = distance between location i and j

Susceptibles Infecteds

transmission rate

• Simulating the fitted model replicates the aggregate dynamics

• Seasonal transmission is necessary to replicate timing and extinction of outbreaks

• Weak spatial coupling is required to slow spread through entire city

Within Niamey Model

rainfallβ

data

simulation

• Predict timescale for vaccination response

• Prioritize spatial surveillance

Within Niamey Model

rainfallβ

= Epidemic size | index case

Regional Dynamics

Given that measles tends to go extinct locally, even in the largest cities, regional persistence must rely on metapopulation dynamics.

Nita Bharti

5 years

Weekly reporting

County scale health centers

Spatial and temporal variation in incidence

5 years

Weekly reporting

County scale health centers

Spatial and temporal variation in incidence

QuickTime™ and aAnimation decompressor

are needed to see this picture.

Measles Persistence

• Measles persistence scales with population size

• Nowhere is measles endemic

• Even above the classic CCS

Population size

Mea

sles

cas

es

Regional PatternPopulation size

Mea

sles

cas

es

Spatial Metapopulation Model

Mea

sles

cas

es

€

E[It+1, j ] = β tSt , j It, j + di, j−θ It,i

i≠ j

∑ ⎛

⎝ ⎜ ⎜

⎞

⎠ ⎟ ⎟

Predicts Regional Pattern

€

E[It+1, j ] = β tSt , j It, j + di, j−θ It,i

i≠ j

∑ ⎛

⎝ ⎜ ⎜

⎞

⎠ ⎟ ⎟

• Spatial model captures regional trend in persistence

• Effect of spatial arrangement

Guilt by association

• Predict that “well connected” locations have frequent immigrants

• Districts with many neighbors have short periods of measles extinction

Guilt by association

Districts with more frequent reintroductions than expected are along the southern road network

Trans-national immigration

A Natural Experiment• Pulsed vaccination (Unicef, The Measles Initiative)

– December 2004 > 80% coverage– January 2008 > 90% coverage

• We can assume most 2005 and 2008 cases are reintroductions – 52 weeks from 2005– 8 weeks from 2008

Isolating Reintroductions

2005 (1 yr) 2008 (8 wks)

2005 & 2008

Locations with > average cases per capita

Measles in Chad 2005

2005 2004

Measles in Nigeria

• Measles killed more than 500 children between January and mid-March in Nigeria (WHO 2005)

• Measles Outbreak Hits Northern Nigerian State, over 3,000 cases reported (VOA news March 2008)

A regional perspective

• Suggests that understanding measles persistence (and conversely eradication), requires broadening the regional perspective beyond national borders.

Goals at Multiple Scales

• Short term goals of reducing measles morbidity and mortality require local response and planning

• Long-term goals of measles eradication require large-scale coordination that reflects dynamics rather than national boundaries

Acknowledgements

Ministry of Health Niger Ali Djibo

Rebecca Grais, Phillippe Guerin

Nita Bharti, Ottar Bjornstad,Bryan Grenfell Andrew Conlan