Comparison of weighted deming regression of force of infection estimates by country from cumulative incidence data and seroprevalence data.

<p>Each point is weighted depending on the error in both serology and incidence estimates, represented by the size of circles (larger circles indicating greater weight, i.e. smaller error).</p

Posterior median estimates of the total force of infection from the model fitted to incidence data (model 1) and model A (as described in [13]) to age-stratified seroprevalence data (serology) from Thailand where incidence and serology data were available from the same year and location.

<p>Posterior median estimates of the total force of infection from the model fitted to incidence data (model 1) and model A (as described in [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0004833#pntd.0004833.ref013" target="_blank">13</a>]) to age-stratified seroprevalence data (serology) from Thailand where incidence and serology data were available from the same year and location.</p

Flowchart describing the literature search process for age-stratified incidence data.

<p>Flowchart describing the literature search process for age-stratified incidence data.</p

Estimated time-varying A) serotype-specific force of infection in individuals under the threshold age and B) <i>R</i>0_<i>i</i> derived by fitting Model C to Nicaraguan data (2001–2007).

<p>Posterior median and 95% credible intervals shown.</p

Flowchart describing the literature search process for dengue seroprevalence surveys.

<p>Flowchart describing the literature search process for dengue seroprevalence surveys.</p

Summary of PRNT surveys identified and associated demographics.

<p><i>^Number of serotypes known to have been in circulation</i>.</p><p>Summary of PRNT surveys identified and associated demographics.</p

Summary of cross-sectional non-serotype specific datasets identified and associated demographics.

<p>^ Survey date not given, noted as ‘pre-year of publication’. ⁺All assays were IgG or HI ELISAs. ^-Cross-sectional surveys from multiple years (2001–2007).</p><p>Summary of cross-sectional non-serotype specific datasets identified and associated demographics.</p

Total force of infection and corresponding R₀ estimates from the model fitted to the incidence data grouped by country.

<p>Each dot represents the posterior median estimate and the error bars show the 95% CrI for each dataset. The box represents the country-specific central estimate calculated by taking the mean values of the MCMC output for each country (the line and limits of the box represents the posterior median and the 95% CrI respectively). R₀ assumption one: complete protection acquired upon quaternary infection, assumption two: complete protection reached after secondary infection.</p

Summary of cross-sectional incidence datasets identified and associated demographics.

<p>Summary of cross-sectional incidence datasets identified and associated demographics.</p

Summary of estimated reporting rates showing the baseline reporting rate or probability of detecting a secondary infection (ρ), the probability of detecting a primary infection (γ1) relative to a secondary infection, and the probability of detecting a tertiary/quaternary infection (γ3) relative to a primary infection.

<p>Each point represents the posterior median estimate and the error bars show the 95% CrI for each dataset. The box represents the country-specific central estimate calculated by taking the mean values of the MCMC output for each country (the line and limits of the box represents the posterior median and the 95% CrI respectively). A single overall value of γ1 and γ3 were estimated per country.</p