Spatial patterns on the edge of stability: measles in the Sahel.
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Transcript of Spatial patterns on the edge of stability: measles in the Sahel.
![Page 1: Spatial patterns on the edge of stability: measles in the Sahel.](https://reader035.fdocuments.us/reader035/viewer/2022062518/56649e605503460f94b5b51c/html5/thumbnails/1.jpg)
Spatial patterns on the edge of stability: measles in the
Sahel
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• 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
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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
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Measles Dynamics in Niger
measlesAll Niger
Measles epidemic begin in the dry season
Aggregate measures can obscure local complexity
measles
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• Timing is consistent with the national pattern
• High variability in outbreaks size
• Frequent local extinction
Local Dynamics: Niamey
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€
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
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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
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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 (!)
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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
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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.
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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
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Timing is Everything
Spatially implicit model showed that campaign was unlikely to have had a great impact on the course of the epidemic
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Within Niamey Model
• > 9000 case records
• 26 health districts
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Within Niamey Model
• > 9000 case records
• 26 health districtsQuickTime™ and a
MPEG-4 Video decompressorare needed to see this picture.
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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
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• 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
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• Predict timescale for vaccination response
• Prioritize spatial surveillance
Within Niamey Model
rainfallβ
= Epidemic size | index case
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Regional Dynamics
Given that measles tends to go extinct locally, even in the largest cities, regional persistence must rely on metapopulation dynamics.
Nita Bharti
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5 years
Weekly reporting
County scale health centers
Spatial and temporal variation in incidence
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5 years
Weekly reporting
County scale health centers
Spatial and temporal variation in incidence
QuickTime™ and aAnimation decompressor
are needed to see this picture.
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Measles Persistence
• Measles persistence scales with population size
• Nowhere is measles endemic
• Even above the classic CCS
Population size
Mea
sles
cas
es
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Regional PatternPopulation size
Mea
sles
cas
es
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Spatial Metapopulation Model
Mea
sles
cas
es
€
E[It+1, j ] = β tSt , j It, j + di, j−θ It,i
i≠ j
∑ ⎛
⎝ ⎜ ⎜
⎞
⎠ ⎟ ⎟
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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
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Guilt by association
• Predict that “well connected” locations have frequent immigrants
• Districts with many neighbors have short periods of measles extinction
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Guilt by association
Districts with more frequent reintroductions than expected are along the southern road network
Trans-national immigration
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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
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Isolating Reintroductions
2005 (1 yr) 2008 (8 wks)
2005 & 2008
Locations with > average cases per capita
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Measles in Chad 2005
2005 2004
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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)
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A regional perspective
• Suggests that understanding measles persistence (and conversely eradication), requires broadening the regional perspective beyond national borders.
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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
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Acknowledgements
Ministry of Health Niger Ali Djibo
Rebecca Grais, Phillippe Guerin
Nita Bharti, Ottar Bjornstad,Bryan Grenfell Andrew Conlan