Background
Methods
Analytic overview
Model
Simulation model of the natural history of rotavirus infection
Excel-based companion model
Model input and assumptions
Intervention: vaccine types and vaccination schedule
Vaccine efficacy
Countrya
| GNI per capita (2008 US$) | GAVI grouping for co-financingb
| DTP3 coverage (2008) | Under 5 child mortality (per 1,000 live births) (2006) | Under 5 rotavirus mortality (per 100000 children <5) (2004) | Percentage of death due to diarrhea among children under 5 (2000) |
---|---|---|---|---|---|---|
AFR D | ||||||
Angola | 3,450 | 4 | 81% | 260 | 389 | 19.1 |
Benin | 690 | 1 | 93% | 148 | 182 | 17.1 |
Burkina Faso | 480 | 1 | 99% | 204 | 256 | 18.8 |
Cameroon | 1,150 | 3 | 84% | 149 | 179 | 17.3 |
Chad | 530 | 1 | 43% | 209 | 266 | 18.1 |
Comoros | 750 | 1 | 81% | 68 | 64 | 13.6 |
Ghana | 670 | 2 | 87% | 120 | 92 | 12.2 |
Guinea | 390 | 1 | 70% | 161 | 188 | 16.5 |
Guinea-Bissau | 250 | 1 | 79% | 200 | 283 | 18.6 |
Liberia | 170 | 4 | 92% | 235 | 331 | 17.3 |
Madagascar | 410 | 1 | 88% | 115 | 141 | 16.9 |
Mali | 580 | 1 | 99% | 217 | 307 | 18.3 |
Mauritania | 840 | 1 | 74% | 125 | 153 | 16.2 |
Niger | 330 | 1 | 89% | 253 | 392 | 19.8 |
Nigeria | 1,160 | 2 | 57% | 191 | 228 | 15.7 |
Sao Thome | 1,020 | 1 | 99% | 96 | 129 | 16.0 |
Senegal | 970 | 1 | 88% | 116 | 158 | 17.1 |
Sierra Leone | 320 | 4 | 87% | 269 | 439 | 19.7 |
The Gambia | 390 | 1 | 96% | 114 | 107 | 12.2 |
Togo | 400 | 1 | 89% | 107 | 134 | 13.8 |
AFR E | ||||||
Burundi | 140 | 4 | 92% | 181 | 255 | 18.2 |
Central African Republic | 410 | 4 | 51% | 174 | 210 | 14.7 |
Congo | 1,970 | 4 | 89% | 126 | 86 | 11.2 |
Cote d'Ivoire | 980 | 4 | 74% | 127 | 223 | 14.8 |
Democratic Republic of the Congo | 150 | 4 | 83% | 205 | 281 | 18.1 |
Eritrea | 300 | 4 | 85% | 74 | 84 | 15.6 |
Ethiopia | 280 | 1 | 81% | 123 | 213 | 17.3 |
Kenya | 770 | 2 | 85% | 121 | 135 | 16.5 |
Lesotho | 1,080 | 1 | 91% | 132 | 25 | 3.9 |
Malawi | 290 | 1 | 91% | 120 | 225 | 18.1 |
Mozambique | 370 | 1 | 80% | 138 | 183 | 16.5 |
Rwanda | 410 | 1 | 97% | 160 | 272 | 18.5 |
Tanzania | 430 | 1 | 84% | 118 | 147 | 16.8 |
Uganda | 420 | 1 | 79% | 134 | 165 | 17.2 |
Zambia | 950 | 1 | 95% | 182 | 227 | 17.5 |
Zimbabwe |
c
| 2 | 75% | 85 | 106 | 12.1 |
AMR A, B & D | ||||||
Cuba |
c
| 2 | 99% | 7 | 1 | 1.3 |
Guyana | 1,420 | 3 | 93% | 62 | 119 | 21.4 |
Honduras | 1,800 | 3 | 93% | 27 | 43 | 12.2 |
Bolivia | 1,460 | 3 | 83% | 61 | 66 | 14.3 |
Haiti | 660 | 4 | 53% | 80 | 133 | 16.5 |
Nicaragua | 1,080 | 2 | 96% | 26 | 30 | 12.2 |
EMR D | ||||||
Afghanistan |
c
| 4 | 85% | 257 | 338 | 18.9 |
Djibouti | 1,130 | 3 | 89% | 130 | 145 | 16.6 |
Pakistan | 980 | 2 | 73% | 97 | 95 | 14.0 |
Somalia |
c
| 4 | 31% | 145 | 315 | 18.7 |
Sudan | 1,130 | 4 | 93% | 89 | 79 | 12.9 |
Yemen | 950 | 1 | 87% | 100 | 108 | 16.1 |
EUR B & C | ||||||
Armenia | 3,350 | 3 | 89% | 24 | 29 | 10.5 |
Azerbaijan | 3,830 | 3 | 95% | 89 | 125 | 15.3 |
Georgia | 2,470 | 3 | 92% | 32 | 42 | 11.5 |
Kyrgyzstan | 740 | 2 | 95% | 41 | 86 | 14.1 |
Tajikistan | 600 | 2 | 86% | 68 | 177 | 16.4 |
Uzbekistan | 910 | 2 | 98% | 44 | 88 | 14.8 |
Moldova | 1,470 | 2 | 95% | 19 | 5 | 2.0 |
Ukraine | 3,210 | 3 | 90% | 24 | 2 | 1.2 |
SEAR B & D | ||||||
Indonesia | 2,010 | 3 | 77% | 34 | 60 | 18.3 |
Korea, Democratic Republic |
c
| 2 | 92% | 55 | 56 | 18.9 |
Sri Lanka | 1,790 | 3 | 98% | 13 | 16 | 13.5 |
Timor Leste | 2,460 | 4 | 79% | 55 | 115 | 21.9 |
Bangladesh | 520 | 1 | 87% | 69 | 89 | 20.0 |
Bhutan | 1,900 | 1 | 96% | 70 | 98 | 20.9 |
India | 1,070 | 2 | 84% | 76 | 102 | 20.3 |
Myanmar |
c
| 1 | 85% | 104 | 128 | 21.1 |
Nepal | 400 | 1 | 82% | 59 | 91 | 20.5 |
WPR B | ||||||
Cambodia | 600 | 1 | 91% | 82 | 226 | 16.6 |
Kiribati | 2,000 | 3 | 82% | 64 | 127 | 21.9 |
Lao People Democratic Republic | 750 | 1 | 61% | 75 | 122 | 15.6 |
Mongolia | 1,680 | 2 | 96% | 42 | 67 | 14.5 |
Papua New Guinea | 1,010 | 2 | 52% | 73 | 128 | 15.3 |
Solomon Islands | 1,180 | 1 | 78% | 72 | 45 | 8.8 |
Viet Nam | 890 | 2 | 93% | 17 | 21 | 10.4 |
Demographic data and assumptions
Incidence of rotavirus disease events
Costs
Cost-effectiveness analysis
Sensitivity analysis
Budget impact analysis and scale-up scenarios
Country | Categorya
| Year 1 | Year 2 | Year 3 | Year 4 | Year 5 | Year 6 | Year 7 | Year 8 | Year 9 | Year 10 |
---|---|---|---|---|---|---|---|---|---|---|---|
2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | ||
AFR D | |||||||||||
Angola | 10 | 31.0 | |||||||||
Benin | 5 | 15.0 | 30.6 | 46.2 | 61.8 | 77.4 | 93.0 | ||||
Burkina Faso | 5 | 57.0 | 65.4 | 73.8 | 82.2 | 90.6 | 99.0 | ||||
Cameroon | 3 | 53.0 | 60.8 | 68.5 | 76.3 | 84.0 | 84.0 | 84.0 | 84.0 | ||
Chad | 8 | 28.0 | 30.5 | 33.0 | |||||||
Comoros | 7 | 27.0 | 36.0 | 45.0 | 54.0 | ||||||
Ghana | 6 | 80.0 | 81.4 | 82.8 | 84.2 | 85.6 | |||||
Guinea | 8 | 57.0 | 59.2 | 61.3 | |||||||
Guinea-Bissau | 9 | 47.0 | 51.6 | ||||||||
Liberia | 5 | 48.0 | 56.8 | 65.6 | 74.4 | 83.2 | 92.0 | ||||
Madagascar | 6 | 61.0 | 66.4 | 71.8 | 77.2 | 82.6 | |||||
Mali | 5 | 54.0 | 63.0 | 72.0 | 81.0 | 90.0 | 99.0 | ||||
Mauritania | 8 | 31.0 | 38.2 | 45.3 | |||||||
Niger | 9 | 25.0 | 34.1 | ||||||||
Nigeria | 4 | 41.0 | 44.2 | 47.4 | 50.6 | 53.8 | 57.0 | 57.0 | |||
Sao Tome | 3 | 43.0 | 57.0 | 71.0 | 85.0 | 99.0 | 99.0 | 99.0 | 99.0 | ||
Senegal | 6 | 54.0 | 60.8 | 67.6 | 74.4 | 81.2 | |||||
Sierra Leone | 6 | 24.0 | 36.6 | 49.2 | 61.8 | 74.4 | |||||
The Gambia | 5 | 84.0 | 86.4 | 88.8 | 91.2 | 93.6 | 96.0 | ||||
Togo | 6 | 50.0 | 57.8 | 65.6 | 73.4 | 81.2 | |||||
AFR E | |||||||||||
Burundi | 10 | 74.0 | |||||||||
Central African Republic | 10 | 29.0 | |||||||||
Congo | 10 | 33.0 | |||||||||
Cote d'Ivoire | 4 | 10.0 | 22.8 | 35.6 | 48.4 | 61.2 | 74.0 | 74.0 | |||
Democratic Republic of the Congo | 10 | 40.0 | |||||||||
Eritrea | 6 | 52.0 | 58.6 | 65.2 | 71.8 | 78.4 | |||||
Ethiopia | 6 | 42.0 | 49.8 | 57.6 | 65.4 | 73.2 | |||||
Kenya | 6 | 72.0 | 74.6 | 77.2 | 79.8 | 82.4 | |||||
Lesotho | 3 | 14.0 | 33.3 | 52.5 | 71.8 | 91.0 | 91.0 | 91.0 | 91.0 | ||
Malawi | 5 | 64.0 | 69.4 | 74.8 | 80.2 | 85.6 | 91.0 | ||||
Mozambique | 8 | 25.0 | 34.2 | 43.3 | |||||||
Rwanda | 5 | 88.0 | 89.8 | 91.6 | 93.4 | 95.2 | 97.0 | ||||
Tanzania | 7 | 79.0 | 79.8 | 80.7 | 81.5 | ||||||
Uganda | 8 | 29.0 | 37.3 | 45.7 | |||||||
Zambia | 5 | 80.0 | 83.0 | 86.0 | 89.0 | 92.0 | 95.0 | ||||
Zimbabwe | 8 | 9.0 | 20.0 | 31.0 | |||||||
AMR A, B & D | |||||||||||
Cuba | 1 | 93.0 | 95.0 | 97.0 | 99.0 | 99.0 | 99.0 | 99.0 | 99.0 | 99.0 | 99.0 |
Guyana | 1 | 89.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 |
Honduras | 1 | 84.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 | 93.0 |
Bolivia | 1 | 82.0 | 83.0 | 83.0 | 83.0 | 83.0 | 83.0 | 83.0 | 83.0 | 83.0 | 83.0 |
Haiti | 10 | 39.0 | |||||||||
Nicaragua | 1b
| 96.0 | 96.0 | 96.0 | 96.0 | 96.0 | 96.0 | 96.0 | 96.0 | 96.0 | 96.0 |
EMR D | |||||||||||
Afghanistan | 10 | 31.0 | |||||||||
Djibouti | 2 | 46.0 | 56.8 | 67.5 | 78.3 | 89.0 | 89.0 | 89.0 | 89.0 | 89.0 | |
Pakistan | 4 | 63.0 | 65.0 | 67.0 | 69.0 | 71.0 | 73.0 | 73.0 | |||
Somalia | 9 | 33.0 | 32.7 | ||||||||
Sudan | 3 | 22.0 | 39.8 | 57.5 | 75.3 | 93.0 | 93.0 | 93.0 | 93.0 | ||
Yemen | 6 | 9.0 | 24.6 | 40.2 | 55.8 | 71.4 | |||||
EUR B & C | |||||||||||
Armenia | 1 | 55.0 | 66.3 | 77.7 | 89.0 | 89.0 | 89.0 | 89.0 | 89.0 | 89.0 | 89.0 |
Azerbaijan | 1 | 95.0 | 95.0 | 95.0 | 95.0 | 95.0 | 95.0 | 95.0 | 95.0 | 95.0 | 95.0 |
Georgia | 1 | 55.0 | 67.3 | 79.7 | 92.0 | 92.0 | 92.0 | 92.0 | 92.0 | 92.0 | 92.0 |
Kyrgyzstan | 1 | 10.0 | 38.3 | 66.7 | 95.0 | 95.0 | 95.0 | 95.0 | 95.0 | 95.0 | 95.0 |
Tajikistan | 1 | 39.0 | 54.7 | 70.3 | 86.0 | 86.0 | 86.0 | 86.0 | 86.0 | 86.0 | 86.0 |
Uzbekistan | 1 | 5.0 | 36.0 | 67.0 | 98.0 | 98.0 | 98.0 | 98.0 | 98.0 | 98.0 | 98.0 |
Moldova | 1 | 81.0 | 85.7 | 90.3 | 95.0 | 95.0 | 95.0 | 95.0 | 95. 0 | 95.0 | 95.0 |
Ukraine | 1 | 4.0 | 32.7 | 61.3 | 90.0 | 90.0 | 90.0 | 90.0 | 90.0 | 90.0 | 90.0 |
SEAR B & D | |||||||||||
Indonesia | 4 | 42.0 | 49.0 | 56.0 | 63.0 | 70.0 | 77.0 | 77.0 | |||
Korea, Democratic Republic | 10 | 27.0 | |||||||||
Sri Lanka | 3 | 62.0 | 71.0 | 80.0 | 89.0 | 98.0 | 98.0 | 98.0 | 98.0 | ||
Timor Leste | 4 | 57.0 | 61.4 | 65.8 | 70.2 | 74.6 | 79.0 | 79.0 | |||
Bangladesh | 7 | 5.0 | 18.7 | 32.3 | 46.0 | ||||||
Bhutan | 3 | 90.0 | 91.5 | 93.0 | 94.5 | 96.0 | 96.0 | 96.0 | 96.0 | ||
India | 3 | 6.0 | 25.5 | 45.0 | 64.5 | 84.0 | 84.0 | 84.0 | 84.0 | ||
Myanmar | 7 | 8.0 | 20.8 | 33.7 | 46.5 | ||||||
Nepal | 7 | 2.0 | 15.3 | 28.7 | 42. 0 | ||||||
WPR B | |||||||||||
Cambodia | 5 | 50.0 | 58.2 | 66.4 | 74.6 | 82.8 | 91.0 | ||||
Kiribati | 2 | 36.0 | 47.5 | 59.0 | 70.5 | 82.0 | 82.0 | 82.0 | 82.0 | 82.0 | |
Lao People Democratic Republic | 8 | 50.0 | 51.8 | 53.7 | |||||||
Mongolia | 2 | 95.0 | 95.3 | 95.5 | 95.8 | 96.0 | 96.0 | 96.0 | 96.0 | 96.0 | |
Papua New Guinea | 4 | 60.0 | 58.4 | 56.8 | 55.2 | 53.6 | 52.0 | 52.0 | |||
Solomon Islands | 2 | 53.0 | 59.3 | 65.5 | 71.8 | 78.0 | 78.0 | 78.0 | 78.0 | 78.0 | |
Viet Nam | 5 | 78.0 | 81.0 | 84.0 | 87.0 | 90.0 | 93.0 |
Results
Model validation
Health outcomes
Country | Base-case vaccine efficacy (adjusted for serotype distribution) | Vaccine efficacy based on SAGE recommendation | ||||
---|---|---|---|---|---|---|
Reduction in risk of severe rotavirus disease events | Rotavirus deaths averted (per 1000 vaccinated children) | DALYs averted | Reduction in risk of severe rotavirus disease events | Rotavirus deaths averted (per 1000 vaccinated children) | DALYs averted | |
AFR D | ||||||
Angola | 55% | 14.2 | 176,385 | 35% | 9.0 | 111,341 |
Benin | 55% | 6.7 | 42,644 | 35% | 4.2 | 26,918 |
Burkina Faso | 50% | 8.6 | 92,836 | 35% | 5.9 | 63,999 |
Cameroon | 54% | 6.6 | 67,042 | 35% | 4.2 | 42,761 |
Chad | 55% | 9.8 | 76,358 | 35% | 6.2 | 48,200 |
Comoros | 55% | 2.4 | 1,245 | 54% | 2.3 | 1,221 |
Ghana | 59% | 3.7 | 44,965 | 35% | 2.2 | 26,291 |
Guinea | 55% | 6.9 | 43,736 | 35% | 4.3 | 27,608 |
Guinea-Bissau | 50% | 9.5 | 13,602 | 35% | 6.5 | 9,366 |
Liberia | 55% | 12.1 | 38,173 | 35% | 7.6 | 24,096 |
Madagascar | 55% | 5.2 | 68,520 | 35% | 3.3 | 43,252 |
Mali | 55% | 11.1 | 110,369 | 35% | 7.0 | 69,669 |
Mauritania | 55% | 5.7 | 10,359 | 35% | 3.6 | 6,539 |
Niger | 55% | 14.4 | 160,612 | 35% | 9.1 | 101,384 |
Nigeria | 51% | 7.7 | 733,421 | 35% | 5.3 | 498,170 |
Sao Thome | 55% | 4.7 | 430 | 35% | 3.0 | 272 |
Senegal | 55% | 5.8 | 45,473 | 35% | 3.7 | 28,704 |
Sierra Leone | 55% | 15.9 | 62,305 | 35% | 10.1 | 39,329 |
The Gambia | 55% | 4.0 | 4,250 | 35% | 2.5 | 2,682 |
Togo | 55% | 5.0 | 21,192 | 35% | 3.1 | 13,377 |
AFR E | ||||||
Burundi | 55% | 9.3 | 67,442 | 35% | 5.8 | 42,572 |
Central African Republic | 55% | 7.7 | 19,559 | 35% | 4.8 | 12,346 |
Congo | 55% | 3.2 | 7,180 | 35% | 2.0 | 4,532 |
Cote d'Ivoire | 51% | 7.6 | 85,210 | 35% | 5.2 | 57,935 |
Democratic Republic of the Congo | 55% | 10.3 | 541,455 | 35% | 6.5 | 341,786 |
Eritrea | 55% | 3.1 | 11,263 | 54% | 3.0 | 11,045 |
Ethiopia | 55% | 7.8 | 443,905 | 35% | 4.9 | 280,209 |
Kenya | 55% | 5.0 | 132,053 | 35% | 3.1 | 83,357 |
Lesotho | 55% | 0.9 | 838 | 35% | 0.6 | 529 |
Malawi | 57% | 8.6 | 81,905 | 35% | 5.2 | 50,027 |
Mozambique | 55% | 6.8 | 90,101 | 35% | 4.3 | 56,875 |
Rwanda | 55% | 9.9 | 75,890 | 35% | 6.2 | 47,905 |
Tanzania | 57% | 5.5 | 146,305 | 35% | 3.4 | 89,138 |
Uganda | 55% | 6.0 | 153,907 | 35% | 3.8 | 97,151 |
Zambia | 51% | 7.8 | 56,160 | 35% | 5.3 | 37,952 |
Zimbabwe | 52% | 3.6 | 21,407 | 35% | 2.4 | 14,392 |
AMR A, B & D | ||||||
Cuba | 57% | 0.0 | 63 | 54% | 0.0 | 60 |
Guyana | 57% | 4.8 | 969 | 54% | 4.6 | 923 |
Honduras | 57% | 1.7 | 6,710 | 54% | 1.6 | 6,386 |
Bolivia | 57% | 2.6 | 12,692 | 54% | 2.5 | 12,080 |
Haiti | 57% | 5.2 | 26,275 | 35% | 3.2 | 16,098 |
Nicaragua | 57% | 1.2 | 3,384 | 54% | 1.1 | 3,195 |
EMR D | ||||||
Afghanistan | 53% | 12.5 | 254,469 | 35% | 8.2 | 166,606 |
Djibouti | 53% | 5.4 | 2,234 | 35% | 3.5 | 1,463 |
Pakistan | 53% | 3.5 | 315,915 | 35% | 2.3 | 206,836 |
Somalia | 55% | 12.1 | 78,642 | 35% | 7.7 | 49,641 |
Sudan | 53% | 2.9 | 65,913 | 35% | 1.9 | 43,155 |
Yemen | 53% | 4.0 | 67,530 | 35% | 2.6 | 44,213 |
EUR B & C | ||||||
Armenia | 59% | 1.1 | 907 | 54% | 1.0 | 834 |
Azerbaijan | 59% | 4.7 | 14,086 | 35% | 2.8 | 8,329 |
Georgia | 59% | 1.7 | 1,471 | 54% | 1.6 | 1,352 |
Kyrgyzstan | 59% | 3.3 | 7,922 | 54% | 3.1 | 7,277 |
Tajikistan | 59% | 7.1 | 24,217 | 54% | 6.5 | 22,246 |
Uzbekistan | 59% | 3.6 | 41,188 | 54% | 3.3 | 37,836 |
Moldova | 59% | 0.2 | 159 | 54% | 0.2 | 146 |
Ukraine | 59% | 0.1 | 590 | 54% | 0.1 | 542 |
SEAR B & D | ||||||
Indonesia | 57% | 2.3 | 187,993 | 54% | 2.2 | 176,588 |
Korea, Democratic Republic | 57% | 2.1 | 12,982 | 54% | 2.0 | 12,194 |
Sri Lanka | 57% | 0.6 | 3,424 | 54% | 0.6 | 3,216 |
Timor Leste | 57% | 4.3 | 4,470 | 54% | 4.1 | 4,199 |
Bangladesh | 55% | 3.4 | 231,585 | 54% | 3.3 | 225,739 |
Bhutan | 57% | 3.8 | 858 | 54% | 3.6 | 806 |
India | 53% | 3.6 | 1,777,110 | 54% | 3.7 | 1,802,809 |
Myanmar | 57% | 4.9 | 79,028 | 35% | 3.0 | 47,784 |
Nepal | 58% | 3.5 | 52,750 | 54% | 3.2 | 48,998 |
WPR B | ||||||
Cambodia | 57% | 8.6 | 63,250 | 35% | 5.2 | 38,244 |
Kiribati | 57% | 4.9 | 118 | 54% | 4.6 | 111 |
Lao People Democratic Republic | 57% | 4.6 | 14,067 | 54% | 4.3 | 13,213 |
Mongolia | 57% | 2.6 | 2,316 | 54% | 2.5 | 2,176 |
Papua New Guinea | 57% | 5.0 | 16,493 | 54% | 4.7 | 15,492 |
Solomon Islands | 57% | 1.7 | 493 | 54% | 1.6 | 463 |
Viet Nam | 58% | 0.8 | 26,089 | 54% | 0.8 | 24,032 |
Cost-effectiveness
Country | Base-case vaccine efficacy (adjusted for serotype distribution) | Vaccine efficacy based on SAGE recommendation | ||||
---|---|---|---|---|---|---|
ICERa(I$/DALY averted) I$10 per vaccinated child | ICERa(I$/DALY averted) I$25 per vaccinated child | ICERb(I$/DALY averted) based on GAVI's co-financing scheme | ICERa(I$/DALY averted) I$10 per vaccinated child | ICERa(I$/DALY averted) I$25 per vaccinated child | ICERb(I$/DALY averted) based on GAVI's co-financing scheme | |
AFR D | ||||||
Angola | saving | 26 | 4 | 0.2 | 68 | 22 |
Benin | 25 | 108 | 52 | 57 | 190 | 87 |
Burkina Faso | 22 | 90 | 37 | 42 | 141 | 59 |
Cameroon | 22 | 108 | 57 | 54 | 190 | 93 |
Chad | saving | 54 | 33 | 17 | 113 | 59 |
Comoros | 119 | 341 | 150 | 122 | 348 | 153 |
Ghana | 71 | 221 | 100 | 142 | 398 | 176 |
Guinea | 18 | 99 | 54 | 49 | 178 | 88 |
Guinea-Bissau | 7 | 68 | 37 | 26 | 113 | 57 |
Liberia | 17 | 67 | 32 | 37 | 114 | 53 |
Madagascar | 20 | 124 | 65 | 60 | 225 | 108 |
Mali | 5 | 58 | 29 | 26 | 109 | 51 |
Mauritania | 21 | 116 | 52 | 58 | 209 | 92 |
Niger | saving | 36 | 23 | 10 | 78 | 42 |
Nigeria | 27 | 102 | 48 | 51 | 162 | 74 |
Sao Thome | 40 | 152 | 65 | 83 | 262 | 112 |
Senegal | 32 | 125 | 56 | 68 | 215 | 95 |
Sierra Leone | 2 | 41 | 21 | 17 | 79 | 37 |
The Gambia | 59 | 196 | 87 | 112 | 328 | 145 |
Togo | 46 | 155 | 75 | 88 | 262 | 121 |
AFR E | ||||||
Burundi | 22 | 84 | 44 | 46 | 145 | 70 |
Central African Republic | 20 | 96 | 46 | 50 | 171 | 78 |
Congo | 74 | 250 | 111 | 143 | 422 | 185 |
Cote d'Ivoire | 21 | 95 | 47 | 44 | 153 | 72 |
Democratic Republic of the Congo | 19 | 76 | 39 | 41 | 131 | 62 |
Eritrea | 95 | 266 | 117 | 97 | 272 | 120 |
Ethiopia | 28 | 98 | 45 | 55 | 166 | 74 |
Kenya | 37 | 150 | 68 | 81 | 260 | 115 |
Lesotho | 397 | 1,061 | 459 | 655 | 1,707 | 737 |
Malawi | 26 | 93 | 40 | 55 | 165 | 71 |
Mozambique | 31 | 115 | 48 | 64 | 198 | 83 |
Rwanda | 1 | 58 | 30 | 23 | 114 | 54 |
Tanzania | 42 | 147 | 66 | 87 | 258 | 114 |
Uganda | 31 | 127 | 62 | 68 | 220 | 102 |
Zambia | 23 | 103 | 45 | 49 | 166 | 72 |
Zimbabwe | 78 | 251 | 110 | 134 | 391 | 170 |
AMR A, B & D | ||||||
Cuba | 11,332 | 28,443 | 12,240 | 11,909 | 29,888 | 12,862 |
Guyana | 4 | 113 | 40 | 7 | 122 | 44 |
Honduras | 85 | 386 | 190 | 95 | 411 | 201 |
Bolivia | 47 | 246 | 120 | 53 | 262 | 128 |
Haiti | 4 | 105 | 56 | 46 | 212 | 102 |
Nicaragua | 217 | 646 | 289 | 234 | 688 | 307 |
EMR D | ||||||
Afghanistan | saving | 47 | 29 | 15 | 90 | 48 |
Djibouti | saving | 90 | 54 | 25 | 179 | 92 |
Pakistan | 42 | 192 | 102 | 95 | 325 | 159 |
Somalia | saving | 39 | 32 | 11 | 83 | 51 |
Sudan | 84 | 266 | 121 | 148 | 426 | 190 |
Yemen | 26 | 160 | 82 | 73 | 276 | 132 |
EUR B & C | ||||||
Armenia | 227 | 685 | 312 | 254 | 753 | 341 |
Azerbaijan | saving | 95 | 68 | 35 | 223 | 123 |
Georgia | 131 | 429 | 206 | 148 | 473 | 225 |
Kyrgyzstan | 59 | 215 | 99 | 68 | 239 | 109 |
Tajikistan | 6 | 80 | 48 | 10 | 91 | 53 |
Uzbekistan | saving | 122 | 58 | saving | 144 | 67 |
Moldova | 1,763 | 4,497 | 1,949 | 1,925 | 4,900 | 2,122 |
Ukraine | 4,816 | 12,161 | 5,243 | 5,249 | 13,245 | 5,710 |
SEAR B & D | ||||||
Indonesia | 80 | 302 | 136 | 90 | 326 | 146 |
Korea, Democratic Republic | 118 | 363 | 154 | 129 | 390 | 165 |
Sri Lanka | 487 | 1,303 | 565 | 522 | 1,391 | 603 |
Timor Leste | 41 | 161 | 67 | 46 | 174 | 73 |
Bangladesh | 50 | 209 | 104 | 52 | 216 | 106 |
Bhutan | 38 | 175 | 75 | 44 | 190 | 81 |
India | 54 | 201 | 97 | 53 | 198 | 96 |
Myanmar | 28 | 137 | 74 | 75 | 256 | 126 |
Nepal | 62 | 215 | 102 | 70 | 235 | 110 |
WPR B | ||||||
Cambodia | saving | 44 | 34 | 10 | 111 | 63 |
Kiribati | 4 | 111 | 50 | 9 | 122 | 54 |
Lao People Democratic Republic | 15 | 132 | 77 | 20 | 144 | 83 |
Mongolia | 77 | 274 | 114 | 85 | 296 | 123 |
Papua New Guinea | saving | 84 | 36 | saving | 95 | 41 |
Solomon Islands | 143 | 444 | 186 | 156 | 476 | 200 |
Viet Nam | 193 | 799 | 390 | 228 | 885 | 427 |
Sensitivity analyses
Budget impact: Forecasting disease burden reduction and financial costs
No | Scale-up scenarios | No. of children vaccinated (in million) | No. of outpatient visits averted (r = 0%) (in million) | No. of hospitalization averted (r = 0%) (in million) | No. of deaths averted (r = 0%) (in million) | YL saved (r = 3%) (in million) | DALYs averted (r = 3%) (in million) |
---|---|---|---|---|---|---|---|
1 | Base-case rollout scenario (Table 2) | ||||||
Vaccine efficacy based on the SAGE approach | |||||||
Vaccine immunity waning (14% annually) | 281.8 | 40.7 | 4.5 | 0.9 | 20.3 | 20.4 | |
2 | Base-case rollout scenario (Table 2) | ||||||
Vaccine efficacy based on the SAGE approach | |||||||
No vaccine immunity waning | 281.8 | 44.1 | 4.9 | 1.0 | 22.0 | 22.1 | |
3 | Base-case rollout scenario (Table 2) | ||||||
Vaccine efficacy adjusted for serotype distribution | |||||||
Vaccine immunity waning (14% annually) | 281.8 | 47.8 | 5.6 | 1.2 | 25.3 | 25.4 | |
4a
| Base-case rollout scenario (Table 2) | ||||||
Vaccine efficacy adjusted for serotype distribution | |||||||
No vaccine immunity waning | 281.8 | 51.7 | 6.0 | 1.3 | 27.3 | 27.4 | |
5 | (Modified) Wolfson et al. scenario [37] | ||||||
Vaccine efficacy based on the SAGE approach | |||||||
No vaccine immunity waning | 410.5 | 64.2 | 7.7 | 1.6 | 35.6 | 35.7 | |
6 | (Modified) Wolfson et al. scenario [37] | ||||||
Vaccine efficacy adjusted for serotype distribution | |||||||
No vaccine immunity waning | 410.5 | 81.4 | 10.4 | 2.2 | 48.1 | 48.3 | |
7 | A flat coverage of 70% | ||||||
Vaccine efficacy based on the SAGE approach | |||||||
No vaccine immunity waning | 537.0 | 85.9 | 10.1 | 2.1 | 48.9 | 49.1 | |
8 | A flat coverage of 70% | ||||||
Vaccine efficacy adjusted for serotype distribution | |||||||
No vaccine immunity waning | 537.0 | 106.6 | 13.3 | 2.8 | 64.5 | 64.7 |
Financial costsa
| ||||||
---|---|---|---|---|---|---|
No | Scale-up scenarios | No. of children vaccinated | Global society perspective (Total vaccination program costs) | GAVI Alliance perspective (Vaccine cost support) | Local government perspective (not including medical cost savings)b
| Local government perspective (including medical cost savings)b
|
(in million) | (US$, million) | (US$, million) | (US$, million) | (US$, million) | ||
1 | Base-case rollout scenario (Table 2) | |||||
Vaccine efficacy based on the SAGE approach | ||||||
Vaccine immunity waning (14% annually) | 281.8 | 5,879 | 4,079 | 1,800 | 1,714 | |
2 | Base-case rollout scenario (Table 2) | |||||
Vaccine efficacy based on the SAGE approach | ||||||
No vaccine immunity waning | 281.8 | 5,879 | 4,079 | 1,800 | 1,707 | |
3 | Base-case rollout scenario (Table 2) | |||||
Vaccine efficacy adjusted for serotype distribution | ||||||
Vaccine immunity waning (14% annually) | 281.8 | 5,879 | 4,079 | 1,800 | 1,695 | |
4c
| Base-case rollout scenario (Table 2) | |||||
Vaccine efficacy adjusted for serotype distribution | ||||||
No vaccine immunity waning | 281.8 | 5,879 | 4,079 | 1,800 | 1,686 | |
5 | (Modified) Wolfson et al. scenario [30] | |||||
Vaccine efficacy based on the SAGE approach | ||||||
No vaccine immunity waning | 410.5 | 8,573 | 5,943 | 2,630 | 2,472 | |
6 | (Modified) Wolfson et al. scenario [30] | |||||
Vaccine efficacy adjusted for serotype distribution | ||||||
No vaccine immunity waning | 410.5 | 8,573 | 5,943 | 2,630 | 2,414 | |
7 | A flat coverage of 70% | |||||
Vaccine efficacy based on the SAGE approach | ||||||
No vaccine immunity waning | 537.0 | 11,222 | 7,785 | 3,437 | 3,236 | |
8 | A flat coverage of 70% | |||||
Vaccine efficacy adjusted for serotype distribution | ||||||
No vaccine immunity waning | 537.0 | 11,222 | 7,785 | 3,437 | 3,170 |