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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.

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measles vaccination in epidemic contexts

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
Background

Cases

Place

Year

Length (months)

1

12+

6

Kinshasa, DRC

17624

2002

Kinshasa, DRC

40857

2005

Niamey, Niger

10880

2003

Adamawa, Nigeria

2505

2004

Ndjamena, Chad

8015

2005

rationale
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
Objectives
  • Measure the impact of vaccination interventions
  • Examine:
      • Timing of interventions in course of epidemic
      • Age range to vaccinate
      • Intervention vaccination coverage
  • Generalize to other settings
overview of methodology
Overview of methodology
  • Estimate effective reproductive ratio
      • Chain-Binomial/MLE
      • Ferrari, et al, 2005, Math Biosc, 98(1), 14-26
  • Recreate epidemic & simulate interventions
      • Individual-based model
      • Niamey, Niger 2003-2004 as a case study
  • Generalize results
      • Standard epidemic model with vaccination
slide6

1) Estimating the Effective Reproductive Ratio (R)

  • Niamey, Niger (2003-2004): 2.8
  • Kinshasa, DRC (2005-6): 1.9
  • Ndjamena, Chad (2005): 2.5

I

I

NI

I

NI

I

R= avg number secondary cases generated by one case in a partially immune population

2 recreating an epidemic niamey niger 2003 2004 key assumptions
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
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 niger1
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 niger2
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 niger3
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 niger4
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 proportion cases prevented by intervention coverage and time 6 to 59m niamey niger
2) Proportion cases prevented by intervention coverage and time: 6 to 59m, Niamey, Niger

100

2 months

3 months

90

4 months

+ 6 months

80

70

60

Proportion of Cases Prevented (%)

50

40

30

20

10

0

30

40

50

60

70

80

90

100

Intervention Coverage (%)

2 proportion cases prevented by intervention coverage and time 6 to 15y niamey niger
2) Proportion cases prevented by intervention coverage and time: 6 to 15y, Niamey, Niger

100

90

80

70

60

Proportion of cases prevented(%)

50

40

2 months

3 months

30

4 months

20

10

0

30

40

50

60

70

80

90

100

Intervention Coverage (%)

slide15

3) Generalizing to different scenarios (ex.: 50% coverage, 10 days, 100 000 persons)

Proportion reduction in number of cases

R

Day of intervention

conclusions
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

Acknowledgements