Age-specific contact patterns by location.

<p>The age-specific contact patterns at home (panels a–c), at the workplace (panels d–f), in school (panels g–i) and at other locations (panels j–l) are projected from the model. The contact pattern at all locations (panels m–o) is the sum across the four locations (home, work, school and others). Contact matrices for Bolivia (DHS country; in panels b,e,h,k) and South Africa (ROW country; in panels c,f,i,l) were projected and the age-specific mean contact rates for Germany (part of the POLYMOD; in panels a,d,g,j) were estimated from the German contact data. A comparison between the German empirical and modelled estimates can be found in the <b><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005697#pcbi.1005697.s001" target="_blank">S1 Text</a></b>. Darker color intensities indicate higher proclivity of making the age-specific contact.</p

Cost effectiveness acceptability curves for vaccination of girls aged 12 years with a quadrivalent vaccine at different levels of three dose coverage, for different assumptions about duration of protection from vaccine

Incremental cost effectiveness of vaccination compared with no vaccination option is shown. Region of £20 000-£30 000 per QALY gained is shaded<p><b>Copyright information:</b></p><p>Taken from "Economic evaluation of human papillomavirus vaccination in the United Kingdom"</p><p></p><p>BMJ : British Medical Journal 2008;337():-.</p><p>Published online 31 Jul 2008</p><p>PMCID:PMC2500202.</p><p></p

Population and household age distribution, and age-specific contacts at home.

<p>The population pyramids by age and gender (panels a–c), household age matrices (panels d–f) and age-specific contact patterns (panels g–i) are presented for Germany (first column, as a representative of the POLYMOD countries), Bolivia (second column, as a representative of DHS) and South Africa (third column, as a representative of ROW). The population pyramids, panels a–c, and household age matrices (for only POLYMOD and DHS), panels d–e, are observed data. The age-specific contacts at home for Germany (g) is estimated from our hierarchical model. The household age matrix for South Africa (f) and the age-specific contacts at home for Bolivia (h) and South Africa (i) were projected using the described methods. Darker color intensities indicate more likely events i.e. greater tendency of having a household member of that age, higher proclivity of making the age-specific contact.</p

Inferred regional contact patterns at home.

<p>Countries of the world were group into 7 regions (East Asia & Pacific, Europe & Central Asia, Latin America & Caribbean, Middle East & North Africa, North America, South Asia and Sub-Saharan Africa). The regional mean age-specific contact patterns at home (inferred) of individuals aged 5–10 (first column), 25–30 (second column) and 55–60 (third column) years were represented as bars.</p

Methodology and data.

<p>Overview of the data sources and model framework in the manuscript is presented in this flow chart. The categories of the 152 countries are depicted on the world map (i.e. POLYMOD, Demographic and Health Survey (DHS), and Rest of the World (ROW) countries) and their data sources are listed in the table. A summary of the methodology is represented by the model framework: (A) POLYMOD model, (B) construction age-structured populations at home, work, and school in the 152 countries, and (C) projection of global estimates.</p

Age-specific final epidemic size and percentage reduction.

<p>The age-specific final epidemic size and percentage reduction of infection for Germany (first column), Bolivia (second column) and South Africa (third column) are shown for the three interventions: No intervention (sum of orange and pink/blue bars), School closure and social distancing of younger individuals (blue bars) and Workplace distancing (pink bars) for two epidemics with <i>R</i>₀ of 1.2 and 1.5. The percentage reduction of infection for the various intervention and <i>R</i>₀ values are represented by the black lines.</p

Cost effectiveness acceptability curves for base case vaccination programme (girls aged 12 years only, quadrivalent vaccine, 80% coverage) under different assumptions about duration of protection from vaccine

Incremental cost effectiveness of vaccination compared with no vaccination option is shown. Region of £20 000- £30 000 per QALY gained is shaded. Thick solid and dashed lines indicate cost effectiveness acceptability curves when considering vaccine type cervical cancers in a screened population, medium solid and dashed lines indicate curves assuming 80% coverage in screened and unscreened populations, and thin solid and dashed lines indicate curves assuming 80% coverage in screened and unscreened populations, protection against non-cervical cancers, and some cross protection against non-vaccine types<p><b>Copyright information:</b></p><p>Taken from "Economic evaluation of human papillomavirus vaccination in the United Kingdom"</p><p></p><p>BMJ : British Medical Journal 2008;337():-.</p><p>Published online 31 Jul 2008</p><p>PMCID:PMC2500202.</p><p></p

Distribution of severe pneumonia episodes and pneumonia deaths in children younger than 5 years in India.

<p>(A) Number of severe pneumonia episodes in children aged 0–59 months (B) Number of pneumonia deaths in children aged 0–59 months.</p

Selected Indian states with the highest number of pneumococcal pneumonia deaths in children younger than 5 years in 2010.

<p>Bubble size indicates the number of pneumococcal pneumonia deaths.</p

Fig 3 -

RSV cases, hospitalizations, and deaths per 1,000 person-years according to OM I and II. Number and 95% confidence intervals of hospitalizations and deaths per 1,000 person-years according to OM I and II, detailed in Fig 1 and Section S1.4 in S1 Text. The green bands arise from OM I, calculated by taking the splines of community-based incidence (Spline I), probability of hospitalization (Spline III), and probability of death among hospitalized cases (Spline IV). The orange bands arise from OM II, calculated by taking the splines of hospital-based incidence (Spline II), probability of hospitalization (Spline III) to back-calculate cases in the community, and probability of death among hospitalized cases (Spline IV). LIC, low-income countries; LMIC, lower-middle-income countries; OM, outcomes model; RSV, respiratory syncytial virus; UMIC, upper middle-income countries.</p