sowc_child_mortality <- structure(list(countries_and_areas = c("Afghanistan", "Albania", "Algeria", "Andorra", "Angola", "Antigua and Barbuda", "Argentina", "Armenia", "Australia", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium", "Belize", "Benin", "Bhutan", "Bolivia (Plurinational State of)", "Bosnia and Herzegovina", "Botswana", "Brazil", "Brunei Darussalam", "Bulgaria", "Burkina Faso", "Burundi", "Cabo Verde", "Cambodia", "Cameroon", "Canada", "Central African Republic", "Chad", "Chile", "China", "Colombia", "Comoros", "Congo", "Cook Islands", "Costa Rica", "Cote d'Ivoire", "Croatia", "Cuba", "Cyprus", "Czechia", "Democratic People's Republic of Korea", "Democratic Republic of the Congo", "Denmark", "Djibouti", "Dominica", "Dominican Republic", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Eritrea", "Estonia", "Eswatini", "Ethiopia", "Fiji", "Finland", "France", "Gabon", "Gambia", "Georgia", "Germany", "Ghana", "Greece", "Grenada", "Guatemala", "Guinea", "Guinea-Bissau", "Guyana", "Haiti", "Honduras", "Hungary", "Iceland", "India", "Indonesia", "Iran (Islamic Republic of)", "Iraq", "Ireland", "Israel", "Italy", "Jamaica", "Japan", "Jordan", "Kazakhstan", "Kenya", "Kiribati", "Kuwait", "Kyrgyzstan", "Lao People's Democratic Republic", "Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Lithuania", "Luxembourg", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta", "Marshall Islands", "Mauritania", "Mauritius", "Mexico", "Micronesia (Federated States of)", "Monaco", "Mongolia", "Montenegro", "Morocco", "Mozambique", "Myanmar", "Namibia", "Nauru", "Nepal", "Netherlands", "New Zealand", "Nicaragua", "Niger", "Nigeria", "Niue", "North Macedonia", "Norway", "Oman", "Pakistan", "Palau", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Poland", "Portugal", "Qatar", "Republic of Korea", "Republic of Moldova", "Romania", "Russian Federation", "Rwanda", "Saint Kitts and Nevis", "Saint Lucia", "Saint Vincent and the Grenadines", "Samoa", "San Marino", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Seychelles", "Sierra Leone", "Singapore", "Slovakia", "Slovenia", "Solomon Islands", "Somalia", "South Africa", "South Sudan", "Spain", "Sri Lanka", "State of Palestine", "Sudan", "Suriname", "Sweden", "Switzerland", "Syrian Arab Republic", "Tajikistan", "Thailand", "Timor-Leste", "Togo", "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Tuvalu", "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom", "United Republic of Tanzania", "United States", "Uruguay", "Uzbekistan", "Vanuatu", "Venezuela (Bolivarian Republic of)", "Viet Nam", "Yemen", "Zambia", "Zimbabwe"), under5_mortality_1990 = c(179L, 41L, 50L, 11L, 223L, 28L, 29L, 49L, 9L, 10L, 96L, 24L, 23L, 144L, 18L, 15L, 10L, 38L, 175L, 127L, 121L, 18L, 51L, 63L, 13L, 18L, 199L, 174L, 61L, 116L, 137L, 8L, 180L, 212L, 19L, 54L, 35L, 125L, 90L, 24L, 17L, 155L, 13L, 13L, 11L, 12L, 43L, 186L, 9L, 118L, 16L, 60L, 54L, 86L, 60L, 179L, 153L, 18L, 71L, 202L, 29L, 7L, 9L, 93L, 167L, 48L, 9L, 127L, 10L, 22L, 80L, 236L, 223L, 60L, 144L, 58L, 17L, 6L, 126L, 84L, 56L, 54L, 9L, 12L, 10L, 30L, 6L, 36L, 52L, 107L, 95L, 18L, 65L, 153L, 17L, 32L, 90L, 262L, 42L, 15L, 9L, 159L, 239L, 17L, 86L, 230L, 11L, 49L, 117L, 23L, 45L, 55L, 8L, 108L, 17L, 79L, 241L, 115L, 74L, 60L, 140L, 8L, 11L, 66L, 329L, 211L, 13L, 36L, 9L, 39L, 139L, 35L, 31L, 87L, 45L, 81L, 57L, 17L, 15L, 21L, 15L, 33L, 31L, 22L, 154L, 31L, 22L, 24L, 30L, 13L, 108L, 45L, 139L, 28L, 17L, 263L, 8L, 15L, 10L, 39L, 179L, 59L, 254L, 9L, 22L, 44L, 132L, 48L, 7L, 8L, 37L, 102L, 37L, 174L, 145L, 22L, 30L, 55L, 74L, 85L, 53L, 185L, 19L, 17L, 9L, 166L, 11L, 23L, 72L, 36L, 30L, 51L, 126L, 186L, 80L), under5_mortality_2000 = c(129L, 26L, 40L, 6L, 206L, 16L, 20L, 31L, 6L, 6L, 75L, 16L, 13L, 87L, 15L, 13L, 6L, 24L, 139L, 78L, 75L, 10L, 87L, 35L, 10L, 18L, 179L, 156L, 36L, 107L, 149L, 6L, 172L, 186L, 11L, 37L, 25L, 102L, 114L, 18L, 13L, 145L, 8L, 9L, 7L, 5L, 60L, 161L, 5L, 101L, 15L, 41L, 29L, 47L, 33L, 157L, 86L, 11L, 126L, 142L, 23L, 4L, 5L, 85L, 115L, 37L, 5L, 99L, 6L, 16L, 52L, 166L, 175L, 47L, 103L, 37L, 10L, 4L, 92L, 52L, 34L, 44L, 7L, 7L, 6L, 22L, 5L, 27L, 43L, 106L, 71L, 12L, 49L, 107L, 14L, 20L, 118L, 187L, 28L, 11L, 5L, 107L, 173L, 10L, 39L, 188L, 8L, 41L, 114L, 19L, 26L, 54L, 5L, 64L, 14L, 49L, 171L, 89L, 77L, 42L, 81L, 6L, 7L, 37L, 226L, 185L, 24L, 16L, 5L, 16L, 112L, 29L, 26L, 72L, 34L, 39L, 38L, 9L, 7L, 12L, 7L, 31L, 22L, 19L, 183L, 23L, 18L, 23L, 21L, 6L, 85L, 22L, 131L, 13L, 14L, 234L, 4L, 10L, 6L, 30L, 172L, 74L, 183L, 5L, 17L, 30L, 104L, 34L, 4L, 6L, 23L, 84L, 22L, 108L, 120L, 18L, 29L, 30L, 38L, 81L, 41L, 148L, 18L, 11L, 7L, 130L, 8L, 17L, 63L, 29L, 22L, 30L, 95L, 162L, 105L), under5_mortality_2018 = c(62L, 9L, 23L, 3L, 77L, 6L, 10L, 12L, 4L, 4L, 22L, 10L, 7L, 30L, 12L, 3L, 4L, 13L, 93L, 30L, 27L, 6L, 36L, 14L, 12L, 7L, 76L, 58L, 19L, 28L, 76L, 5L, 116L, 119L, 7L, 9L, 14L, 67L, 50L, 8L, 9L, 81L, 5L, 5L, 2L, 3L, 18L, 88L, 4L, 59L, 36L, 29L, 14L, 21L, 14L, 85L, 42L, 3L, 54L, 55L, 26L, 2L, 4L, 45L, 58L, 10L, 4L, 48L, 4L, 15L, 26L, 101L, 81L, 30L, 65L, 18L, 4L, 2L, 37L, 25L, 14L, 27L, 4L, 4L, 3L, 14L, 2L, 16L, 10L, 41L, 53L, 8L, 19L, 47L, 4L, 7L, 81L, 71L, 12L, 4L, 2L, 54L, 50L, 8L, 9L, 98L, 7L, 33L, 76L, 16L, 13L, 31L, 3L, 16L, 3L, 22L, 73L, 46L, 40L, 32L, 32L, 4L, 6L, 18L, 84L, 120L, 24L, 10L, 3L, 11L, 69L, 18L, 15L, 48L, 20L, 14L, 28L, 4L, 4L, 7L, 3L, 16L, 7L, 7L, 35L, 12L, 17L, 16L, 16L, 2L, 31L, 7L, 44L, 6L, 14L, 105L, 3L, 6L, 2L, 20L, 122L, 34L, 99L, 3L, 7L, 20L, 60L, 19L, 3L, 4L, 17L, 35L, 9L, 46L, 70L, 16L, 18L, 17L, 11L, 46L, 24L, 46L, 9L, 8L, 4L, 53L, 7L, 8L, 21L, 26L, 25L, 21L, 55L, 58L, 46L), under5_reduction = c(4.0999999999999996, 6, 2.8999999999999999, 4.4000000000000004, 5.4000000000000004, 5, 3.7999999999999998, 5.0999999999999996, 2.8999999999999999, 2.5, 6.9000000000000004, 2.3999999999999999, 3.2000000000000002, 5.9000000000000004, 1.2, 7.2999999999999998, 2.6000000000000001, 3.2999999999999998, 2.2000000000000002, 5.2999999999999998, 5.7000000000000002, 2.8999999999999999, 4.7999999999999998, 4.9000000000000004, -0.59999999999999998, 5, 4.7000000000000002, 5.5, 3.2999999999999998, 7.4000000000000004, 3.7999999999999998, 1.2, 2.2000000000000002, 2.5, 2.2999999999999998, 8.0999999999999996, 3.1000000000000001, 2.2999999999999998, 4.5999999999999996, 4.5999999999999996, 2.2000000000000002, 3.2000000000000002, 3.2000000000000002, 3, 5.7000000000000002, 2.7000000000000002, 6.5999999999999996, 3.2999999999999998, 1.5, 3, -4.9000000000000004, 1.8999999999999999, 4, 4.4000000000000004, 4.9000000000000004, 3.3999999999999999, 4, 7.9000000000000004, 4.7000000000000002, 5.2000000000000002, -0.69999999999999996, 5.0999999999999996, 1.6000000000000001, 3.5, 3.7999999999999998, 7.2999999999999998, 2.1000000000000001, 4.0999999999999996, 2, 0.10000000000000001, 3.7999999999999998, 2.7999999999999998, 4.2000000000000002, 2.3999999999999999, 2.6000000000000001, 4.0999999999999996, 4.7999999999999998, 4, 5.0999999999999996, 4.0999999999999996, 4.7999999999999998, 2.7999999999999998, 3.7000000000000002, 3.3999999999999999, 3.3999999999999999, 2.3999999999999999, 3.2999999999999998, 2.8999999999999999, 8.0999999999999996, 5.2999999999999998, 1.7, 2.5, 5.2999999999999998, 4.5, 7.2000000000000002, 5.5, 2.1000000000000001, 5.4000000000000004, 4.7999999999999998, 5.4000000000000004, 3.7999999999999998, 3.8999999999999999, 6.9000000000000004, 1.5, 8.4000000000000004, 3.6000000000000001, 0.40000000000000002, 1.1000000000000001, 2.2999999999999998, 1, 4, 3.1000000000000001, 2.6000000000000001, 7.5999999999999996, 9.5, 4.4000000000000004, 4.7000000000000002, 3.6000000000000001, 3.7000000000000002, 1.5, 5.0999999999999996, 2.6000000000000001, 1.3999999999999999, 3.7999999999999998, 5.5, 2.3999999999999999, 0, 2.6000000000000001, 3.6000000000000001, 2, 2.7000000000000002, 2.6000000000000001, 2.8999999999999999, 2.2999999999999998, 2.8999999999999999, 5.5, 1.6000000000000001, 4.0999999999999996, 3.6000000000000001, 3.2999999999999998, 4.7000000000000002, 3.7999999999999998, 6.0999999999999996, 5.5, 9.0999999999999996, 3.7000000000000002, 0.40000000000000002, 1.8, 1.6000000000000001, 6.2999999999999998, 5.5, 6.4000000000000004, 6.0999999999999996, 4.5999999999999996, -0.29999999999999999, 4.4000000000000004, 1.8, 3.1000000000000001, 5.2000000000000002, 2.2999999999999998, 1.8999999999999999, 4.2999999999999998, 3.3999999999999999, 3.2000000000000002, 4.4000000000000004, 2.2000000000000002, 3, 3.2999999999999998, 2.2999999999999998, 1.7, 1.8999999999999999, 4.9000000000000004, 4.9000000000000004, 4.7999999999999998, 3, 0.59999999999999998, 2.5, 3.2000000000000002, 7.0999999999999996, 3.2000000000000002, 2.8999999999999999, 6.4000000000000004, 4.0999999999999996, 2.2000000000000002, 2.3999999999999999, 5, 1.3999999999999999, 4.5, 6, 0.5, -0.69999999999999996, 2, 3, 5.7000000000000002, 4.5), under5_mortality_2018_male = c(66L, 9L, 25L, 3L, 83L, 7L, 11L, 14L, 4L, 4L, 24L, 11L, 7L, 32L, 13L, 4L, 4L, 14L, 99L, 32L, 29L, 6L, 40L, 16L, 12L, 8L, 81L, 63L, 21L, 31L, 81L, 5L, 123L, 125L, 8L, 9L, 16L, 73L, 54L, 9L, 10L, 89L, 5L, 5L, 3L, 4L, 20L, 95L, 5L, 64L, 38L, 32L, 16L, 22L, 15L, 91L, 47L, 3L, 59L, 61L, 28L, 2L, 4L, 49L, 63L, 11L, 4L, 52L, 5L, 17L, 29L, 105L, 88L, 34L, 70L, 19L, 5L, 2L, 36L, 28L, 15L, 29L, 4L, 4L, 3L, 16L, 3L, 18L, 11L, 45L, 57L, 9L, 21L, 52L, 4L, 8L, 88L, 76L, 13L, 4L, 3L, 58L, 54L, 8L, 9L, 103L, 8L, 37L, 81L, 17L, 14L, 34L, 4L, 19L, 3L, 25L, 78L, 51L, 43L, 35L, 34L, 4L, 6L, 20L, 87L, 127L, 26L, 11L, 3L, 12L, 74L, 20L, 17L, 52L, 22L, 16L, 31L, 5L, 4L, 7L, 3L, 18L, 8L, 8L, 38L, 13L, 18L, 18L, 17L, 2L, 34L, 7L, 48L, 6L, 16L, 111L, 3L, 6L, 2L, 22L, 127L, 37L, 103L, 3L, 8L, 22L, 65L, 21L, 3L, 4L, 17L, 39L, 10L, 50L, 75L, 14L, 20L, 18L, 11L, 52L, 27L, 51L, 10L, 8L, 5L, 57L, 7L, 8L, 24L, 28L, 26L, 24L, 59L, 63L, 51L), under5_mortality_2018_female = c(59L, 8L, 22L, 3L, 71L, 6L, 9L, 11L, 3L, 3L, 19L, 9L, 7L, 28L, 11L, 3L, 3L, 12L, 87L, 27L, 24L, 5L, 33L, 13L, 11L, 6L, 72L, 54L, 18L, 25L, 71L, 5L, 110L, 112L, 7L, 8L, 13L, 62L, 46L, 7L, 8L, 73L, 4L, 4L, 2L, 3L, 16L, 81L, 4L, 54L, 33L, 26L, 13L, 20L, 12L, 79L, 36L, 2L, 49L, 49L, 23L, 2L, 4L, 40L, 54L, 9L, 3L, 43L, 4L, 14L, 23L, 96L, 75L, 26L, 59L, 16L, 4L, 2L, 37L, 22L, 14L, 24L, 3L, 3L, 3L, 13L, 2L, 15L, 9L, 37L, 48L, 7L, 17L, 42L, 4L, 7L, 74L, 65L, 11L, 4L, 2L, 49L, 45L, 7L, 8L, 92L, 6L, 29L, 70L, 14L, 11L, 27L, 3L, 13L, 2L, 20L, 68L, 42L, 36L, 29L, 30L, 3L, 5L, 16L, 80L, 113L, 21L, 9L, 2L, 10L, 65L, 16L, 14L, 44L, 18L, 13L, 25L, 4L, 3L, 6L, 3L, 14L, 7L, 6L, 32L, 11L, 15L, 15L, 14L, 2L, 28L, 7L, 39L, 5L, 13L, 99L, 3L, 5L, 2L, 18L, 115L, 31L, 93L, 3L, 7L, 18L, 55L, 17L, 2L, 4L, 15L, 31L, 8L, 42L, 64L, 17L, 17L, 15L, 10L, 40L, 22L, 42L, 8L, 7L, 4L, 49L, 6L, 7L, 18L, 24L, 23L, 17L, 51L, 53L, 42L), infant_mortality_1990 = c(121L, 35L, 42L, 9L, 132L, 24L, 25L, 42L, 8L, 8L, 76L, 20L, 20L, 100L, 16L, 12L, 8L, 31L, 106L, 89L, 84L, 16L, 39L, 53L, 10L, 15L, 99L, 105L, 47L, 85L, 85L, 7L, 117L, 112L, 16L, 42L, 29L, 88L, 59L, 20L, 14L, 105L, 11L, 11L, 10L, 10L, 33L, 119L, 7L, 92L, 13L, 46L, 42L, 63L, 46L, 121L, 94L, 14L, 54L, 120L, 24L, 6L, 7L, 60L, 82L, 41L, 7L, 80L, 9L, 18L, 59L, 139L, 132L, 47L, 100L, 45L, 15L, 5L, 89L, 62L, 44L, 42L, 8L, 10L, 8L, 25L, 5L, 30L, 44L, 68L, 69L, 15L, 54L, 105L, 13L, 27L, 72L, 175L, 35L, 12L, 7L, 97L, 139L, 14L, 63L, 120L, 10L, 39L, 71L, 20L, 36L, 43L, 6L, 77L, 15L, 62L, 161L, 82L, 50L, 46L, 97L, 7L, 9L, 51L, 133L, 125L, 12L, 33L, 7L, 32L, 106L, 30L, 26L, 64L, 36L, 57L, 40L, 15L, 12L, 18L, 13L, 28L, 24L, 18L, 94L, 25L, 19L, 20L, 25L, 12L, 69L, 36L, 71L, 24L, 14L, 156L, 6L, 13L, 9L, 31L, 108L, 46L, 150L, 7L, 19L, 36L, 82L, 41L, 6L, 7L, 30L, 81L, 30L, 131L, 90L, 19L, 27L, 43L, 55L, 68L, 42L, 109L, 17L, 14L, 8L, 101L, 9L, 20L, 60L, 29L, 25L, 37L, 88L, 111L, 52L), infant_mortality_2018 = c(48L, 8L, 20L, 3L, 52L, 5L, 9L, 11L, 3L, 3L, 19L, 8L, 6L, 25L, 11L, 3L, 3L, 11L, 61L, 25L, 22L, 5L, 30L, 13L, 10L, 6L, 49L, 41L, 17L, 24L, 51L, 4L, 84L, 71L, 6L, 7L, 12L, 51L, 36L, 7L, 8L, 59L, 4L, 4L, 2L, 3L, 14L, 68L, 4L, 50L, 33L, 24L, 12L, 18L, 12L, 63L, 31L, 2L, 43L, 39L, 22L, 1L, 3L, 33L, 39L, 9L, 3L, 35L, 4L, 14L, 22L, 65L, 54L, 25L, 49L, 15L, 4L, 2L, 30L, 21L, 12L, 22L, 3L, 3L, 3L, 12L, 2L, 14L, 9L, 31L, 41L, 7L, 17L, 38L, 3L, 6L, 66L, 53L, 10L, 3L, 2L, 38L, 35L, 7L, 7L, 62L, 6L, 27L, 52L, 14L, 11L, 26L, 3L, 14L, 2L, 19L, 54L, 37L, 29L, 26L, 27L, 3L, 5L, 16L, 48L, 76L, 20L, 9L, 2L, 10L, 57L, 17L, 13L, 38L, 17L, 11L, 22L, 4L, 3L, 6L, 3L, 14L, 6L, 6L, 27L, 10L, 15L, 15L, 14L, 2L, 24L, 6L, 32L, 5L, 12L, 78L, 2L, 5L, 2L, 17L, 77L, 28L, 64L, 3L, 6L, 17L, 42L, 17L, 2L, 4L, 14L, 30L, 8L, 39L, 47L, 13L, 16L, 15L, 9L, 39L, 21L, 34L, 7L, 6L, 4L, 38L, 6L, 6L, 19L, 22L, 21L, 16L, 43L, 40L, 34L), neonatal_mortality_1990 = c(75L, 13L, 23L, 6L, 54L, 15L, 15L, 23L, 5L, 5L, 33L, 13L, 15L, 64L, 12L, 8L, 5L, 19L, 46L, 43L, 41L, 11L, 25L, 25L, 6L, 8L, 46L, 40L, 20L, 40L, 40L, 4L, 52L, 52L, 9L, 29L, 18L, 50L, 27L, 13L, 9L, 49L, 8L, 7L, 6L, 7L, 22L, 42L, 4L, 50L, 10L, 24L, 23L, 33L, 23L, 48L, 35L, 10L, 21L, 59L, 12L, 4L, 4L, 31L, 49L, 25L, 3L, 42L, 6L, 12L, 28L, 62L, 64L, 31L, 39L, 22L, 11L, 3L, 57L, 31L, 26L, 26L, 5L, 6L, 6L, 20L, 3L, 20L, 22L, 28L, 36L, 10L, 24L, 47L, 8L, 20L, 39L, 59L, 21L, 8L, 4L, 39L, 50L, 8L, 39L, 67L, 8L, 20L, 46L, 15L, 22L, 26L, 4L, 30L, 11L, 36L, 60L, 48L, 28L, 29L, 58L, 5L, 4L, 23L, 54L, 50L, 7L, 17L, 4L, 17L, 65L, 19L, 17L, 31L, 22L, 28L, 19L, 11L, 7L, 11L, 7L, 19L, 15L, 11L, 40L, 19L, 12L, 13L, 16L, 7L, 26L, 22L, 40L, 17L, 11L, 53L, 4L, 9L, 6L, 15L, 45L, 20L, 65L, 5L, 13L, 22L, 43L, 23L, 4L, 4L, 17L, 31L, 20L, 55L, 43L, 10L, 20L, 29L, 33L, 28L, 28L, 39L, 12L, 8L, 4L, 40L, 6L, 12L, 31L, 17L, 13L, 24L, 43L, 37L, 24L), neonatal_mortality_2000 = c(61L, 12L, 21L, 3L, 51L, 9L, 11L, 16L, 4L, 3L, 34L, 8L, 5L, 42L, 9L, 6L, 3L, 12L, 40L, 32L, 29L, 7L, 26L, 18L, 5L, 8L, 41L, 37L, 17L, 35L, 35L, 4L, 49L, 44L, 5L, 21L, 13L, 41L, 31L, 10L, 8L, 47L, 6L, 4L, 4L, 3L, 27L, 39L, 3L, 44L, 11L, 24L, 14L, 23L, 15L, 45L, 27L, 5L, 23L, 49L, 9L, 2L, 3L, 29L, 40L, 23L, 3L, 36L, 4L, 7L, 21L, 47L, 55L, 27L, 30L, 18L, 6L, 2L, 45L, 23L, 19L, 24L, 4L, 4L, 3L, 17L, 2L, 16L, 21L, 28L, 29L, 7L, 20L, 38L, 7L, 12L, 40L, 45L, 15L, 5L, 2L, 31L, 40L, 5L, 22L, 51L, 5L, 18L, 43L, 12L, 13L, 25L, 3L, 24L, 9L, 27L, 46L, 37L, 23L, 25L, 40L, 4L, 3L, 16L, 43L, 48L, 13L, 9L, 3L, 7L, 60L, 15L, 15L, 29L, 18L, 16L, 17L, 6L, 3L, 7L, 3L, 21L, 10L, 10L, 41L, 15L, 11L, 13L, 11L, 3L, 23L, 12L, 38L, 8L, 9L, 51L, 2L, 5L, 3L, 13L, 44L, 17L, 57L, 3L, 10L, 16L, 37L, 18L, 2L, 3L, 12L, 28L, 12L, 37L, 36L, 8L, 18L, 20L, 19L, 30L, 25L, 32L, 11L, 6L, 4L, 34L, 5L, 8L, 29L, 13L, 11L, 15L, 37L, 35L, 23L), neonatal_mortality_2018 = c(37L, 7L, 15L, 1L, 28L, 3L, 6L, 6L, 2L, 2L, 11L, 5L, 3L, 17L, 8L, 1L, 2L, 9L, 31L, 16L, 14L, 4L, 24L, 8L, 5L, 4L, 25L, 22L, 12L, 14L, 27L, 3L, 41L, 34L, 5L, 4L, 8L, 32L, 20L, 4L, 6L, 34L, 3L, 2L, 1L, 2L, 10L, 28L, 3L, 32L, 28L, 19L, 7L, 11L, 7L, 30L, 18L, 1L, 17L, 28L, 11L, 1L, 3L, 21L, 26L, 6L, 2L, 24L, 3L, 10L, 12L, 31L, 37L, 18L, 26L, 10L, 2L, 1L, 23L, 13L, 9L, 15L, 2L, 2L, 2L, 10L, 1L, 9L, 6L, 20L, 23L, 4L, 13L, 23L, 2L, 4L, 35L, 24L, 6L, 2L, 1L, 21L, 22L, 4L, 5L, 33L, 5L, 15L, 33L, 9L, 8L, 16L, 2L, 9L, 2L, 14L, 28L, 23L, 16L, 20L, 20L, 2L, 3L, 9L, 25L, 36L, 12L, 7L, 1L, 5L, 42L, 9L, 8L, 22L, 11L, 7L, 14L, 3L, 2L, 4L, 1L, 12L, 3L, 3L, 16L, 8L, 12L, 10L, 8L, 1L, 14L, 4L, 21L, 3L, 9L, 33L, 1L, 3L, 1L, 8L, 38L, 11L, 40L, 2L, 4L, 11L, 29L, 10L, 2L, 3L, 9L, 15L, 5L, 20L, 25L, 7L, 12L, 11L, 5L, 21L, 16L, 20L, 5L, 4L, 3L, 21L, 4L, 5L, 12L, 12L, 15L, 11L, 27L, 23L, 21L), prob_dying_age5to14_1990 = c(16L, 7L, 9L, 7L, 46L, 5L, 3L, 3L, 2L, 2L, 5L, 4L, 4L, 26L, 3L, 4L, 2L, 5L, 45L, 20L, 13L, 3L, 17L, 5L, 4L, 4L, 40L, 62L, 6L, 35L, 35L, 2L, 32L, 53L, 3L, 8L, 5L, 18L, 37L, 5L, 3L, 31L, 3L, 4L, 2L, 2L, 8L, 41L, 2L, 26L, 3L, 8L, 8L, 11L, 7L, 38L, 45L, 5L, 11L, 78L, 10L, 2L, 2L, 19L, 36L, 7L, 2L, 27L, 2L, 3L, 12L, 49L, 40L, 6L, 31L, 9L, 3L, 2L, 21L, 15L, 8L, 9L, 2L, 2L, 2L, 5L, 2L, 5L, 6L, 18L, 16L, 5L, 6L, 44L, 6L, 8L, 17L, 33L, 8L, 4L, 2L, 41L, 40L, 5L, 12L, 44L, 2L, 9L, 21L, 4L, 5L, 10L, 2L, 10L, 2L, 10L, 60L, 31L, 16L, 11L, 29L, 2L, 3L, 8L, 68L, 41L, 4L, 3L, 2L, 6L, 14L, 7L, 8L, 15L, 7L, 11L, 14L, 3L, 4L, 4L, 5L, 5L, 5L, 5L, 72L, 5L, 4L, 4L, 6L, 2L, 20L, 7L, 37L, 3L, 4L, 53L, 2L, 3L, 2L, 8L, 38L, 8L, 52L, 2L, 6L, 6L, 29L, 7L, 1L, 2L, 9L, 12L, 9L, 27L, 37L, 5L, 4L, 7L, 9L, 7L, 10L, 32L, 4L, 5L, 2L, 30L, 2L, 3L, 6L, 7L, 4L, 12L, 20L, 30L, 14L), prob_dying_age5to14_2018 = c(5L, 2L, 4L, 1L, 16L, 1L, 2L, 2L, 1L, 1L, 3L, 2L, 2L, 4L, 2L, 1L, 1L, 3L, 22L, 7L, 5L, 1L, 6L, 2L, 2L, 2L, 20L, 23L, 2L, 5L, 32L, 1L, 15L, 28L, 1L, 2L, 2L, 9L, 7L, 2L, 2L, 25L, 1L, 2L, 1L, 1L, 4L, 29L, 0L, 13L, 3L, 3L, 3L, 4L, 4L, 18L, 9L, 1L, 13L, 12L, 5L, 1L, 1L, 14L, 13L, 2L, 1L, 12L, 1L, 5L, 4L, 21L, 16L, 5L, 12L, 5L, 1L, 1L, 6L, 6L, 3L, 7L, 1L, 1L, 1L, 3L, 1L, 3L, 3L, 10L, 9L, 2L, 3L, 9L, 1L, 2L, 9L, 17L, 6L, 1L, 0L, 12L, 14L, 3L, 2L, 26L, 1L, 6L, 8L, 2L, 2L, 6L, 1L, 4L, 1L, 3L, 17L, 5L, 12L, 6L, 6L, 1L, 1L, 4L, 37L, 20L, 5L, 1L, 1L, 2L, 10L, 4L, 3L, 9L, 3L, 3L, 5L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 10L, 2L, 2L, 5L, 4L, 1L, 8L, 2L, 13L, 1L, 3L, 21L, 1L, 1L, 1L, 4L, 24L, 6L, 20L, 1L, 2L, 3L, 8L, 3L, 1L, 1L, 12L, 5L, 5L, 8L, 21L, 3L, 2L, 3L, 2L, 4L, 5L, 15L, 2L, 2L, 1L, 13L, 1L, 2L, 3L, 5L, 3L, 3L, 8L, 12L, 13L), under5_deaths_2018 = c(74L, 0L, 24L, 0L, 94L, 0L, 8L, 1L, 1L, 0L, 4L, 0L, 0L, 89L, 0L, 0L, 0L, 0L, 38L, 0L, 7L, 0L, 2L, 42L, 0L, 0L, 56L, 25L, 0L, 10L, 66L, 2L, 19L, 75L, 2L, 146L, 10L, 2L, 9L, 0L, 1L, 70L, 0L, 1L, 0L, 0L, 6L, 296L, 0L, 1L, 0L, 6L, 5L, 55L, 2L, 4L, 4L, 0L, 2L, 191L, 0L, 0L, 3L, 3L, 5L, 1L, 3L, 41L, 0L, 0L, 11L, 44L, 5L, 0L, 17L, 4L, 0L, 0L, 882L, 121L, 22L, 29L, 0L, 1L, 1L, 1L, 2L, 3L, 4L, 60L, 0L, 0L, 3L, 8L, 0L, 1L, 5L, 11L, 2L, 0L, 0L, 45L, 30L, 4L, 0L, 75L, 0L, 0L, 11L, 0L, 28L, 0L, 0L, 1L, 0L, 15L, 79L, 43L, 3L, 0L, 18L, 1L, 0L, 2L, 83L, 866L, 0L, 0L, 0L, 1L, 409L, 0L, 1L, 11L, 3L, 8L, 63L, 2L, 0L, 0L, 1L, 1L, 1L, 13L, 13L, 0L, 0L, 0L, 0L, 0L, 0L, 4L, 23L, 0L, 0L, 26L, 0L, 0L, 0L, 0L, 73L, 40L, 38L, 1L, 3L, 3L, 80L, 0L, 0L, 0L, 7L, 10L, 7L, 2L, 18L, 0L, 0L, 3L, 14L, 6L, 0L, 74L, 4L, 1L, 3L, 107L, 25L, 0L, 15L, 0L, 13L, 33L, 47L, 36L, 21L), neonatal_deaths_2018 = c(45L, 0L, 15L, 0L, 36L, 0L, 5L, 0L, 1L, 0L, 2L, 0L, 0L, 50L, 0L, 0L, 0L, 0L, 13L, 0L, 4L, 0L, 1L, 24L, 0L, 0L, 19L, 9L, 0L, 5L, 24L, 1L, 7L, 22L, 1L, 73L, 6L, 1L, 3L, 0L, 0L, 30L, 0L, 0L, 0L, 0L, 3L, 98L, 0L, 1L, 0L, 4L, 2L, 29L, 1L, 1L, 2L, 0L, 1L, 99L, 0L, 0L, 2L, 1L, 2L, 0L, 2L, 21L, 0L, 0L, 5L, 14L, 2L, 0L, 7L, 2L, 0L, 0L, 549L, 62L, 14L, 17L, 0L, 0L, 1L, 0L, 1L, 2L, 2L, 29L, 0L, 0L, 2L, 4L, 0L, 1L, 2L, 4L, 1L, 0L, 0L, 18L, 14L, 2L, 0L, 26L, 0L, 0L, 5L, 0L, 17L, 0L, 0L, 1L, 0L, 9L, 31L, 22L, 1L, 0L, 11L, 0L, 0L, 1L, 26L, 267L, 0L, 0L, 0L, 0L, 251L, 0L, 1L, 5L, 2L, 4L, 30L, 1L, 0L, 0L, 1L, 0L, 1L, 6L, 6L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 11L, 0L, 0L, 8L, 0L, 0L, 0L, 0L, 24L, 13L, 15L, 1L, 2L, 2L, 38L, 0L, 0L, 0L, 4L, 4L, 4L, 1L, 6L, 0L, 0L, 2L, 7L, 3L, 0L, 32L, 2L, 0L, 2L, 44L, 14L, 0L, 8L, 0L, 8L, 17L, 23L, 15L, 9L), neonatal_deaths_percent_under5 = c("60", "74", "62", "50", "38", "50", "64", "52", "62", "60", "51", "53", "43", "57", "65", "38", "56", "67", "35", "56", "54", "69", "67", "57", "47", "51", "33", "38", "59", "52", "36", "68", "36", "30", "67", "50", "55", "48", "41", "50", "67", "43", "55", "41", "57", "52", "53", "33", "74", "54", "79", "67", "51", "53", "49", "36", "44", "47", "32", "52", "42", "55", "62", "48", "46", "59", "60", "51", "56", "64", "47", "32", "46", "60", "40", "55", "53", "50", "62", "51", "62", "58", "61", "52", "64", "71", "33", "59", "56", "48", "44", "56", "69", "48", "51", "59", "43", "35", "52", "50", "60", "39", "46", "55", "55", "34", "67", "46", "45", "59", "59", "53", "50", "53", "63", "61", "39", "50", "40", "60", "62", "55", "61", "51", "32", "31", "0", "74", "59", "45", "62", "50", "56", "47", "53", "52", "47", "61", "54", "53", "46", "74", "46", "44", "46", "63", "75", "58", "53", "?", "45", "53", "48", "61", "61", "32", "38", "49", "55", "42", "32", "32", "41", "56", "60", "54", "48", "53", "56", "72", "51", "44", "55", "45", "36", "40", "63", "67", "52", "46", "71", "44", "58", "53", "60", "41", "54", "60", "54", "44", "61", "51", "50", "42", "45"), age5to14_deaths_2018 = c(5L, 0L, 3L, 0L, 15L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 12L, 0L, 0L, 0L, 0L, 7L, 0L, 1L, 0L, 0L, 7L, 0L, 0L, 11L, 8L, 0L, 2L, 22L, 0L, 2L, 13L, 0L, 40L, 2L, 0L, 1L, 0L, 0L, 17L, 0L, 0L, 0L, 0L, 1L, 70L, 0L, 0L, 0L, 1L, 1L, 9L, 0L, 1L, 1L, 0L, 0L, 34L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 9L, 0L, 0L, 2L, 8L, 1L, 0L, 3L, 1L, 0L, 0L, 143L, 28L, 3L, 7L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 14L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 2L, 1L, 0L, 0L, 8L, 7L, 1L, 0L, 15L, 0L, 0L, 1L, 0L, 6L, 0L, 0L, 0L, 0L, 2L, 14L, 5L, 1L, 0L, 3L, 0L, 0L, 1L, 26L, 110L, 0L, 0L, 0L, 0L, 46L, 0L, 0L, 2L, 0L, 2L, 12L, 0L, 0L, 0L, 0L, 0L, 0L, 4L, 3L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 6L, 0L, 0L, 4L, 0L, 0L, 0L, 0L, 11L, 6L, 6L, 0L, 1L, 0L, 9L, 0L, 0L, 0L, 4L, 1L, 4L, 0L, 4L, 0L, 0L, 1L, 3L, 0L, 0L, 19L, 1L, 0L, 1L, 20L, 6L, 0L, 2L, 0L, 2L, 4L, 6L, 6L, 5L)), class = "data.frame", row.names = c(NA, -195L))