Table 1. Populations requiring interventions against neglected tropical diseases (NTDs) and living in poverty.
To predict the percentage and the total number of people requiring interventions against NTDs and living below US$3.10 purchasing power parity (PPP) per day and person, 2 extreme scenarios were considered. The “optimistic” scenario assumes that the percentage of people living in severe poverty is the same among those who do and those who do not require NTD interventions. However, the proportion of people living in severe poverty is likely to be higher in those requiring NTD interventions than the national average as NTDs are usually most prevalent among the poor. The “pessimistic” scenario assumes that those who require NTD interventions are first of all those who live in severe poverty.
| Country | Total population estimates, 2014a | Total number of people requiring NTD interventions, 2014b | Percentage of total population requiring interventions against NTDs, 2014 | Percentage of total population living below US$3.10 PPP per dayc | Percentage of people requiring interventions against NTDs living below US$3.10 PPP per day | Total number of people requiring interventions against NTDs living below US$3.10 PPP per day | ||
|---|---|---|---|---|---|---|---|---|
| Optimistic scenario | Pessimistic scenario | Optimistic scenario | Pessimistic scenario | |||||
| China | 1,368,930,561 | 26,227,888 | 2 | 11 | 11 | 100 | 2,885,068 | 26,227,888 |
| India | 1,294,737,310 | 577,240,673 | 45 | 58 | 58 | 100 | 334,799,590 | 577,240,673 |
| Indonesia | 254,308,847 | 127,979,175 | 50 | 36 | 36 | 72 | 46,072,503 | 92,145,006 |
| Brazil | 205,973,640 | 18,680,873 | 9 | 8 | 8 | 88 | 1,494,470 | 16,439,168 |
| Pakistan | 185,021,056 | 47,386,262 | 26 | 37 | 37 | 100 | 17,532,917 | 47,386,262 |
| Nigeria | 177,463,719 | 140,381,164 | 79 | 77 | 77 | 97 | 108,093,496 | 136,169,729 |
| Bangladesh | 159,086,957 | 49,873,889 | 31 | 57 | 57 | 100 | 28,428,117 | 49,873,889 |
| Philippines | 99,132,703 | 44,803,112 | 45 | 38 | 38 | 84 | 17,025,183 | 37,634,614 |
| Ethiopia | 96,938,457 | 67,843,988 | 70 | 71 | 71 | 100 | 48,169,231 | 67,843,988 |
| Democratic Republic of the Congo | 74,892,895 | 57,568,918 | 77 | 91 | 91 | 100 | 52,387,715 | 57,568,918 |
| Myanmar | 53,458,639 | 40,777,860 | 76 | NA | NA | NA | NA | NA |
| Tanzania | 51,832,105 | 33,868,257 | 65 | 76 | 76 | 100 | 25,739,875 | 33,868,257 |
| Sudan: North | 39,384,299 | 28,468,689 | 72 | 39 | 39 | NA | NA | NA |
| Sudan: South | 64 | 64 | NA | NA | NA | |||
| Uganda | 37,796,069 | 25,344,345 | 67 | 65 | 65 | 97 | 16,473,824 | 24,584,015 |
| Nepal | 28,181,459 | 21,352,583 | 76 | 48 | 48 | 63 | 10,249,240 | 13,452,127 |
| Mozambique | 27,215,953 | 22,815,820 | 84 | 88 | 88 | 100 | 20,077,922 | 22,815,820 |
| Ghana | 26,770,192 | 18,697,745 | 70 | 49 | 49 | 70 | 9,161,895 | 13,088,422 |
| Madagascar | 23,577,196 | 20,491,358 | 87 | 91 | 91 | 100 | 18,647,136 | 20,491,358 |
| Cameroon | 22,772,412 | 19,449,659 | 85 | 44 | 44 | 52 | 8,557,850 | 10,113,823 |
| Mali | 17,090,697 | 19,462,713 | ND (>100%) | 78 | 78 | NA | NA | NA |
a Data on country-specific total numbers of population and annual rates of population change are from the United Nations Population Prospects (see https://esa.un.org/unpd/wpp/). Total population estimates for 2015 and average annual rates of population change from 2010 to 2015 were used to calculate total population estimates for 2014.
b Data on country-specific total number of people requiring interventions against NTDs in 2014 are from the World Health Organization Global Health Observatory (see http://apps.who.int/gho/data/node.sdg.3-3-map-5?lang=en).
c Data on country-specific proportions of people living in severe poverty are from the World Bank Open Data Database (see http://data.worldbank.org/indicator/). To define severe poverty, the recently updated international poverty line of US$3.10 purchasing power parity per day and person was applied.
NA, not available; ND, not determined; PPP, purchasing power parity.