measles vaccination in epidemic contexts
DESCRIPTION
Measles Vaccination in Epidemic Contexts. RF Grais, ACK Conlan, MJ Ferrari, C Dubray, A Djibo, F Fermon, M-E Burny, KP Alberti, I Jeanne, BS Hersh, PJ Guerin, ON Bjornstad, BT Grenfell June 1 , 2006. Background. Cases. Place. Year. Length (months). 1. 12+. 6. Kinshasa, DRC. - PowerPoint PPT PresentationTRANSCRIPT
Measles Vaccination in Epidemic Contexts
RF Grais, ACK Conlan, MJ Ferrari, C Dubray, A Djibo,
F Fermon, M-E Burny, KP Alberti, I Jeanne, BS Hersh, PJ Guerin, ON Bjornstad, BT Grenfell
June 1, 2006
Background
2005
2004
2003
2005
2002
8015
2505
10880
40857
17624
Ndjamena, Chad
Adamawa, Nigeria
Niamey, Niger
Kinshasa, DRC
Kinshasa, DRC
CasesLength (months)YearPlace
1 6 12+
Rationale
Operational guidance for MSF WHO guidelines (1999)
– Spread so fast its always too late– Scarce resources best invested
elsewhere– Based on literature review and
mathematical models of epidemics in non-African settings
Objectives
1. Measure the impact of vaccination interventions
2. Examine:• Timing of interventions in course of epidemic• Age range to vaccinate• Intervention vaccination coverage
3. Generalize to other settings
Overview of methodology
1. Estimate effective reproductive ratio• Chain-Binomial/MLE • Ferrari, et al, 2005, Math Biosc, 98(1), 14-26
2. Recreate epidemic & simulate interventions • Individual-based model• Niamey, Niger 2003-2004 as a case study
3. Generalize results• Standard epidemic model with vaccination
Niamey, Niger (2003-2004): 2.8
Kinshasa, DRC (2005-6): 1.9
Ndjamena, Chad (2005): 2.5
I
NI
NI
I
I
I
R= avg number secondary cases generated by one case in a partially immune population
1) Estimating the Effective Reproductive Ratio (R)
2) Recreating an epidemic, Niamey, Niger 2003-2004: Key Assumptions
Constant– 15 day delay between decision and delivery– 10 day intervention– Vaccine efficiency = 85%
Variable– 2 age ranges for vaccination (standard):
• 6m to 59m• 6m to <15y
– Interventions: • 2, 3 or 4 months after epidemic starts• vaccination coverage: 30% – 100%
2) Model Overview: Niamey, Niger
Probability of infection:• age• immune status• vaccination status• location in the city• status of other children• contact decreases with distance• time
2) Model Overview: Niamey, Niger
Probability of infection:• age• immune status• vaccination status• location in the city• status of other children• contact decreases with distance• time
2) Model Overview: Niamey, Niger
Probability of infection:• age• immune status• vaccination status• location in the city• status of other children• contact decreases with distance• time
2) Model Overview: Niamey, Niger
Probability of infection:• age• immune status• vaccination status• location in the city• status of other children• contact decreases with distance• time
2) Model Overview: Niamey, Niger
Probability of infection:• age• immune status• vaccination status• location in the city• status of other children• contact decreases with distance• time
city
citycity
commune
communecommune
CSI
CSICSI
quartier
quartierquartierat,i
NIβ+
NIβ+
NIβ+
NIβ=,P exp1
2) Proportion cases prevented by intervention coverage and time: 6 to 59m, Niamey, Niger
0
10
20
30
40
50
60
70
80
90
100
30 40 50 60 70 80 90 100
Intervention Coverage (%)
Pro
po
rtio
n o
f C
ases
Pre
ven
ted
(%
) 2 months 3 months
4 months + 6 months
2) Proportion cases prevented by intervention coverage and time: 6 to 15y, Niamey, Niger
0
10
20
30
40
50
60
70
80
90
100
30 40 50 60 70 80 90 100Intervention Coverage (%)
Pro
po
rtio
n o
f c
ases
pre
ven
ted
(%
)
2 months 3 months
4 months
3) Generalizing to different scenarios (ex.: 50% coverage, 10 days, 100 000 persons)
Pro
port
ion
redu
ctio
n in
num
ber
of c
ases
RDay of intervention
Conclusions
More time than we thought to intervene 3 Key Factors
– Timing– Age range for vaccination– Vaccination coverage objective
Benefit even when late– Up to 8% = 800 cases
Revision of WHO guidelines
Acknowledgements
Ministries of Health, Niger, Nigeria, Chad, DRC MSF-F and MSF-B in field and Paris WHO Survey teams Study participants Center for Infectious Disease Dynamics CERMES EPIET