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Fig 1.

Input data of the model.

A: presence (red) or absence (white) of any yellow fever report between 1984 and 2013. B: Location, sample size and study years 12 serological surveys covering 31 provinces. C: estimated population-level vaccination coverage for 2017. Maps were produced from GADM version 2.0.

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Fig 1 Expand

Table 1.

Parameter estimates and outcomes for both model variants.

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Table 1 Expand

Fig 2.

Estimates of transmission intensity in the FOI (A) versus the R0 (B) model variants.

A: median estimates of the force of infection (FOI), in %; B: median estimates of R0. Maps were produced from GADM version 2.0.

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Fig 2 Expand

Fig 3.

Comparison of directly estimated versus model-predicted transmission parameters for three external serological studies.

Black: direct estimate; blue: prediction of the FOI model; green: prediction of the R0 model. Lines show 95% credibility intervals.

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Fig 4.

Estimated 2017 incidence of severe yellow fever infection per 100,000 persons across 34 African countries.

A: FOI model, B: R0 model. For the R0 model, provinces with no incidence are those for which the estimated vaccination coverage in 2017 was larger than the Critical Vaccination Coverage implied by R0. Maps were produced from GADM version 2.0.

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Fig 5.

Estimates of the effective reproductive number (Reff) and categorization for different preventive mass vaccination (PMVCs) strategies.

A: estimates of the effective reproductive number (Reff) based on 2018 vaccination coverage estimates; B: categorization for vaccination strategies. Each vaccination strategy includes all provinces from upper prioritization levels (ie the strategy B consists in vaccinating provinces corresponding to categories A and B). Light yellow provinces (Reff<0.85) are not considered for PMVCs under any strategy. Maps were produced from GADM version 2.0.

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Fig 5 Expand

Table 2.

Impact estimates of different preventive mass vaccination (PMVCs) strategies.

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Table 2 Expand