Incidence,Mortality,and Premature Mortality From Neonatal Disorders in Eastern Sub-Saharan Africa,From 1990 to 2023

Abstract

Introduction

Neonatal disorders represent a significant global health challenge with a critical research gap in resource-constrained settings.

Objective

This study aimed to estimate the incidence, mortality, and years of life lost (YLLs) from neonatal disorders in the Eastern Sub-Saharan Africa (ESSA) region from 1990 to 2023.

Methods

The study used estimation methods from the Global Burden of Diseases 2023 study.

Results

In the region, there were an estimated 300,042 new cases of neonatal disorders per 100,000 live births (95% UI: 293,808, 305,567), 21,889 deaths per 100,000 live births (95% UI: 20,447, 22,993), and 1.9 million YLLs per 100,000 live births (95% UI: 1.8, 2.1) in 2023. There was a considerable decline in the rates between 1990 and 2023.

Conclusion

The ESSA region experienced considerably high rates of incidence, mortality, and YLLs from neonatal disorders. Targeted interventions, including primary prevention and quality maternal and newborn health services should be implemented.

Keywords

neonates sub-saharan Africa global burden of disease study disorder newborn

Introduction

Neonatal disorders are defined as illnesses and conditions occurring within the first 28 days of life. These mainly include neonatal preterm birth, neonatal encephalopathy due to birth asphyxia and trauma, neonatal sepsis and other neonatal infections, and hemolytic disease and other neonatal jaundice.¹ In 2021, there were over 27 million cases of neonatal disorders, resulting in millions of years of life lost (YLLs).¹ Despite a general downward trend in the global load of neonatal disorders, low Socio-Demographic Index (SDI) areas exhibited significant differences.² Especially, sub-Saharan African countries are not on track to achieve sustainable development goal 3.2 targets by 2030 regarding neonatal disorders and deaths.³ There is substantial burden of neonatal disorders in this region, with preterm complications, birth asphyxia, neonatal infections, and congenital anomalies ranking the top causes of health loss in neonates.⁴ While some neonatal disorders and early neonatal deaths are higher among males than their female counterparts, the first day of life, followed by the first week after delivery, is the age group in which most of the neonatal disorders occur.^5,6

Despite the existence of numerous policies and programs aimed at improving newborn care in the Eastern Sub-Saharan African (ESSA) region, obstacles such as inadequate planning for the implementation of interventions, insufficient monitoring of the planned programs, and a lack of evidence regarding their implementation and monitoring have been observed.⁷ Additionally, human resource restrictions, capital, equipment, and resource limitations, as well as process flaws in service delivery are among the top challenges in the region to mitigate neonatal conditions.⁸ Moreover, there remains a significant research gap in comprehensive, region-specific data on the burden of neonatal disorders that informs appropriate intervention.⁹

This comprehensive study aimed to quantify the incidence, mortality, and YLLs from neonatal disorders in the ESSA region from 1990 to 2023, using data and methods of the Global Burden of Diseases (GBD) 2023 study. The study findings may support health authorities and concerned bodies in identifying high priority areas for targeted intervention, ultimately contributing to improved neonatal health outcomes in the region.

Methods

Study Setting

This study covers the ESSA region, which consists of 15 countries, namely Burundi, Comoros, Djibouti, Eritrea, Ethiopia, Kenya, Madagascar, Malawi, Mozambique, Rwanda, Somalia, South Sudan, Uganda, Tanzania, and Zambia. The region is home to approximately 580 million persons and close to 70% of them live in rural settings where there is scarcity of quality health service delivery, skilled personnel, infrastructure and essential supplies.^10,11 More than 50,000 babies are born every day across the region, which amounts to six babies every ten seconds.¹¹

Data Sources

The data on the incidence, death, and YLLs of neonatal disorders were obtained from the global health data network, which is available at: https://ghdx.healthdata.org/gbd-2023/sources.

Patient and Public Involvement

It was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research.

Data Analysis

The study used statistical techniques and tools of the GBD 2023 study. Incidence was estimated by employing a Disease Modeling with Bayesian Meta-Regression (DisMod-MR 2.1), which combined multiple statistical models by weighting each based on its out-of-sample predictive validity. Models with lower root-mean-square error received higher weights in the final ensemble. Deaths and YLLs were estimated by using a Cause of Death Ensemble model (CODEm), which was adjusted to ensure internal consistency between cause-specific mortality and all-cause mortality estimates. Cause-specific deaths were multiplied by their life expectancy at the time of death to get the YLLs. Spatiotemporal Gaussian process regression (ST-GPR) was used to smooth variation in trend from 1990 to 2023. All estimates were presented with their 95% uncertainty intervals (UIs) to capture the total uncertainty stemming from sampling errors, data availability, and model specifications. Some rates exceeded 100,000 per 100,000 neonates because a single neonate may be diagnosed with multiple disorders simultaneously, causing the aggregate numerator to surpass the denominator. The age of an infant was grouped as a neonate when aged less than 28 days, an early neonate when aged less than 7 days, and a late neonate when aged 7 to 27 days. A significant net change in estimates between 1990 and 2023 was declared if the 95% uncertainty intervals (UIs) for the percentage change did not cross the zero value.

Results

Incidence of Neonatal Disorders

There were an estimated 3.3 million new cases (95% UI: 3.2, 3.3) of neonatal disorders in the ESSA region in 2023, with 1.9 million new cases (95% UI: 1.9, 2.0) among males and 1.3 million new cases (95% IU: 1.3, 1.4) among females. This was equivalent to an estimated 300,042 new cases per 100,000 live births (95% UI: 293,808, 305,567), with 343,992 new cases per 100,000 male live births (95% UI: 335,724, 353,605) and 254,321 new cases per 100,000 female live births (95% UI: 246,007, 261,449). The highest rate was estimated in Comoros [345,064 new cases per 100,000 live births (95% UI: 322,322, 366,791)], Mozambique [343,623 new cases per 100,000 live births (95% UI: 320,691, 365,216)], Somalia [388,177 new cases per 100,000 live births (95% UI: 363,593, 411,000)], and South Sudan [350,331 new cases per 100,000 live births (95% UI: 326,819, 374,338)], whereas the lowest rate was in Burundi [266,253 new cases per 100,000 live births (95% UI: 250,674, 286,032)], Djibouti [262,747 new cases per 100,000 live births (95% UI: 246,197, 279,884)], Kenya [270,261 new cases per 100,000 live births (95% UI: 260,924, 279,642)], and Rwanda [208,504 new cases per 100,000 live births (95% UI: 193,478, 223,867)]. Compared to the rate in 1990, there was an 18% decline (95% UI: -20, -16) in the rate in 2023 in the region. The highest decline was estimated in Rwanda [32% decline (95% UI: -38, -26)] and Ethiopia [29% decline (95% UI: -32, -24)]. However, no statistically significant decline was estimated in Djibouti [-8% (95% UI: -15, 1)] and South Sudan [-7% (95% UI: -14, 2)] since the percentage change estimates crossed the zero value (Table 1, Figure 1).

Table 1.

Incidence, Mortality, and YLLs From Neonatal Disorders by Sex and Location in the ESSA Region, 1990 to 2023

Location	Sex	Number of incidents	Incidence rate	% Change	Number of deaths	Mortality rate	% Change	YLLs rate	% Change
Location	Sex	2023	2023	1990-2023	2023	2023	1990-2023	2023	1990-2023
ESSA region	Male	1904272 (1858501, 1957488)	343992 (335724, 353605)	-0.17 (-0.20, -0.15)	168868 (150988, 188406)	26452 (24400, 28570)	-0.38 (-0.44, -0.29)	2379979 (2195381, 2570601)	-0.38 (-0.44, -0.29)
	Female	1353316 (1309074, 1391245)	254321 (246007, 261449)	-0.19 (-0.22, -0.16)	105722 (95579, 117622)	17143 (15806, 18471)	-0.45 (-0.50, -0.38)	1542461 (1422124, 1661900)	-0.45 (-0.50, -0.38)
	Both	3257588 (3189899, 3317570)	300042 (293808, 305567)	-0.18 (-0.20, -0.16)	274590 (252857, 295496)	21889 (20447, 22993)	-0.41 (-0.45, -0.36)	1969494 (1839682, 2068833)	-0.41 (-0.45, -0.36)
Burundi	Male	59220 (53732, 649045)	306996 (278548, 336463)	-0.19 (-0.28, -0.06)	6728 (5651, 8331)	29723 (26445, 33729)	-0.27 (-0.37, -0.15)	2674339 (2379418, 3034768)	-0.27 (-0.37, -0.15)
	Female	42464 (38491, 47296)	224670 (203649, 250232)	-0.18 (-0.30, -0.06)	5075 (4425, 5870)	23059 (20808, 25269)	-0.19 (-0.29, 0.00)	2074722 (1872241, 2273584)	-0.19 (-0.29, 0.00)
	Both	101684 (95735, 109238)	266253 (250674, 286032)	-0.19 (-0.26, -0.10)	11803 (10398, 13815)	26425 (24269, 28809)	-0.24 (-0.31, -0.15)	2377588 (2183624, 2592104)	-0.24 (-0.31, -0.15)
Comoros	Male	3313 (3049, 3605)	379559 (349296, 413031)	-0.18 (-0.26, -0.08)	240 (210, 272)	24095 (21751, 26559)	-0.36 (-0.47, -0.24)	2167936 (1957049, 2389633)	-0.36 (-0.47, -0.24)
	Female	2587 (2343, 2866)	309084 (279989, 342493)	-0.16 (-0.25, -0.04)	161 (137, 186)	16553 (14690, 18458)	-0.39 (-0.50, -0.28)	1489364 (1321759, 1660754)	-0.39 (-0.50, -0.28)
	Both	5900 (5511, 6271)	345064 (322322, 366791)	-0.17 (-0.24, -0.10)	402 (366, 437)	20403 (18830, 21864)	-0.37 (-0.45, -0.28)	1835798 (1694254, 1967202)	-0.37 (-0.45, -0.28)
Djibouti	Male	3719 (3374, 4104)	265832 (241207, 293430)	-0.11 (-0.22, 0.02)	368 (303, 437)	22563 (19341, 25370)	-0.27 (-0.41, -0.07)	2030117 (1740248, 2282654)	-0.27 (-0.41, -0.07)
	Female	3314 (2957, 3655)	259370 (231384, 286014)	-0.04 (-0.16, 0.11)	276 (229, 331)	18362 (16026, 20995)	-0.25 (-0.39, -0.09)	1652111 (1441967, 1889038)	-0.25 (-0.39, -0.09)
	Both	7033 (6590, 7492)	262747 (246197, 279884)	-0.08 (-0.15, 0.01)	645 (559, 729)	20557 (18329, 22685)	-0.26 (-0.37, -0.14)	1849660 (1649121, 2041119)	-0.26 (-0.37, -0.14)
Eritrea	Male	27766 (25466, 30176)	342849 (314446, 372602)	-0.27 (-0.34, -0.18)	2135 (1857, 2491)	21887 (19553, 24463)	-0.35 (-0.48, -0.16)	1969285 (1759314, 2201021)	-0.35 (-0.48, -0.16)
	Female	17936 (16239, 19567)	233950 (211821, 255264)	-0.24 (-0.34, -0.15)	1163 (976, 1375)	11319 (10205, 12723)	-0.32 (-0.45, -0.11)	1018470 (918233, 1144727)	-0.32 (-0.45, -0.11)
	Both	45702 (43281, 48444)	289892 (274532, 307282)	-0.26 (-0.31, -0.20)	3298 (2942, 3684)	16748 (15442, 18344)	-0.34 (-0.44, -0.20)	1506909 (1389351, 1650504)	-0.34 (-0.44, -0.20)
Ethiopia	Male	492632 (463038, 520515)	349840 (328824, 369641)	-0.28 (-0.34, -0.22)	62476 (56178, 69410)	37949 (35114, 41209)	-0.38 (-0.47, -0.22)	3414467 (3159385, 3707755)	-0.38 (-0.47, -0.22)
	Female	318698 (300680, 336730)	238240 (224771, 251719)	-0.29 (-0.34, -0.24)	29206 (25412, 33959)	18572 (16318, 20942)	-0.54 (-0.62, -0.42)	1671030 (1468176, 1884255)	-0.54 (-0.62, -0.42)
	Both	811330 (780307, 844999)	295471 (284173, 307733)	-0.29 (-0.32, -0.24)	91682 (83561, 99242)	28509 (26617, 30493)	-0.44 (-0.51, -0.36)	2565112 (2394860, 2743598)	-0.44 (-0.51, -0.36)
Kenya	Male	142032 (135748, 148943)	311658 (297871, 326823)	-0.04 (-0.10, 0.02)	8538 (7429, 9834)	16939 (14792, 19325)	-0.23 (-0.37, -0.04)	1524132 (1330937, 1738759)	-0.23 (-0.37, -0.04)
	Female	100093 (96410, 104575)	227400 (219032, 237582)	-0.06 (-0.11, -0.01)	6397 (5603, 7282)	12853 (11522, 14343)	-0.21 (-0.33, -0.01)	1156461 (1036731, 1290514)	-0.21 (-0.33, -0.01)
	Both	242125 (233760, 250529)	270261 (260924, 279642)	-0.05 (-0.10, -0.01)	14935 (13464, 16460)	14932 (13662, 16388)	-0.22 (-0.31, -0.08)	1343491 (1229285, 1474544)	-0.22 (-0.31, -0.08)
Madagascar	Male	141257 (130091, 152818)	366604 (337625, 396610)	-0.12 (-0.21, -0.02)	8108 (6371, 9672)	18612 (15136, 21773)	-0.36 (-0.47, -0.24)	1674577 (1361874, 1959027)	-0.36 (-0.47, -0.24)
	Female	106058 (96335, 116239)	288185 (261766, 315851)	-0.11 (-0.22, 0.02)	6506 (5235, 7797)	15872 (12908, 18665)	-0.25 (-0.40, -0.10)	1428071 (1161377, 1679417)	-0.25 (-0.40, -0.10)
	Both	247315 (231280, 262551)	328294 (307009, 348520)	-0.12 (-0.19, -0.04)	14614 (12414, 16696)	17273 (14881, 19532)	-0.32 (-0.42, -0.21)	1554153 (1338929, 1757442)	-0.32 (-0.42, -0.21)
Malawi	Male	80443 (73412, 89095)	340451 (310692, 377069)	-0.10 (-0.21, 0.03)	6608 (5694, 7455)	24867 (21560, 27755)	-0.45 (-0.53, -0.36)	2237399 (1939831, 2497305)	-0.45 (-0.53, -0.36)
	Female	58453 (53327, 64116)	253096 (230900, 277615)	-0.19 (-0.27, -0.09)	4620 (3992, 5225)	17628 (15499, 19783)	-0.54 (-0.61, -0.46)	1586115 (1394483, 1780011)	-0.54 (-0.61, -0.46)
	Both	138896 (130185, 147919)	297272 (278627, 316583)	-0.14 (-0.21, -0.07)	11227 (10072, 12260)	21289 (19245, 23185)	-0.49 (-0.55, -0.43)	1915474 (1731534, 2086096)	-0.49 (-0.55, -0.43)
Mozambique	Male	181282 (164327, 198340)	394470 (357578, 431590)	-0.17 (-0.26, -0.07)	13204 (11848, 14530)	26082 (23323, 28858)	-0.47 (-0.54, -0.39)	2346781 (2098502, 2596471)	-0.47 (-0.54, -0.39)
	Female	130755 (120717, 141954)	291524 (269142, 316492)	-0.16 (-0.28, -0.05)	9254 (8227, 10498)	18666 (16755, 20997)	-0.58 (-0.63, -0.50)	1679440 (1507551, 1889178)	-0.58 (-0.63, -0.50)
	Both	312037 (291213, 331645)	343623 (320691, 365216)	-0.17 (-0.24, -0.09)	22458 (20292, 24544)	22419 (20407, 24338)	-0.52 (-0.58, -0.47)	2017165 (1836113, 2189780)	-0.52 (-0.58, -0.47)
Rwanda	Male	34612 (31454, 38334)	246805 (224287, 273349)	-0.31 (-0.39, -0.22)	3724 (3117, 4359)	22460 (19812, 25068)	-0.51 (-0.58, -0.42)	2020873 (1782581, 2255521)	-0.51 (-0.58, -0.42)
	Female	22881 (20596, 25214)	168862 (151999, 186085)	-0.33 (-0.42, -0.25)	3007 (2569, 3539)	18431 (16187, 20630)	-0.51 (-0.60, -0.42)	1658306 (1456464, 1856230)	-0.51 (-0.60, -0.42)
	Both	57492 (53349, 61728)	208504 (193478, 223867)	-0.32 (-0.38, -0.26)	6731 (5987, 7524)	20480 (18670, 22336)	-0.51 (-0.56, -0.45)	1842706 (1679799, 2009657)	-0.51 (-0.56, -0.45)
Somalia	Male	140441 (128024, 151674)	382239 (348444, 412812)	-0.15 (-0.25, -0.04)	9573 (7501, 11947)	20367 (16387, 24618)	-0.26 (-0.46, 0.03)	1832507 (1474464, 2215019)	-0.26 (-0.46, 0.03)
	Female	135127 (123364, 146207)	394547 (360201, 426900)	-0.21 (-0.29, -0.10)	6790 (5260, 8484)	15217 (12628, 17470)	-0.26 (-0.45, 0.10)	1369152 (1136229, 1571886)	-0.26 (-0.45, 0.10)
	Both	275568 (258115, 291770)	388177 (363593, 411000)	-0.18 (-0.25, -0.10)	16363 (13606, 19066)	17882 (15463, 20408)	-0.26 (-0.40, -0.02)	1608966 (1391271, 1836169)	-0.26 (-0.40, -0.02)
South Sudan	Male	48892 (44286, 53504)	411086 (372357, 449863)	-0.07 (-0.18, 0.05)	4505 (3803, 5383)	29555 (26221, 32680)	-0.17 (-0.31, 0.05)	2659222 (2359222, 2940397)	-0.17 (-0.31, 0.05)
	Female	32104 (29152, 34,882)	285967 (259675, 310707)	-0.06 (-0.17, 0.07)	2592 (2155, 3191)	17634 (15424, 19611)	-0.19 (-0.34, 0.00)	1586623 (1387798, 1764487)	-0.19 (-0.34, 0.00)
	Both	80996 (75560, 86546)	350331 (326819, 374338)	-0.07 (-0.14, 0.02)	7097 (6119, 8134)	23766 (21577, 25797)	-0.18 (-0.28, -0.05)	2138391 (1941418, 2321056)	-0.18 (-0.28, -0.05)
Uganda	Male	206203 (190522, 223065)	331997 (306750, 359146)	-0.22 (-0.30, -0.12)	17440 (14901, 19963)	24522 (21690, 27317)	-0.39 (-0.47, -0.28)	2206345 (1951535, 2457830)	-0.39 (-0.47, -0.28)
	Female	134278 (120159, 147000)	225120 (201450, 246450)	-0.19 (-0.27, -0.09)	11858 (10258, 13531)	17389 (15388, 19478)	-0.47 (-0.55, -0.36)	1564563 (1384503, 1752573)	-0.47 (-0.55, -0.36)
	Both	340481 (319283, 359884)	279640 (262229, 295576)	-0.20 (-0.27, -0.12)	29299 (26167, 32285)	21027 (19098, 22993)	-0.43 (-0.50, -0.35)	1891945 (1718329, 2068834)	-0.43 (-0.50, -0.35)
Tanzania	Male	259828 (233461, 285931)	330220 (296710, 363394)	-0.05 (-0.16, 0.07)	19724 (16903, 22358)	22719 (19563, 25711)	-0.37 (-0.50, -0.24)	2044118 (1760205, 2313337)	-0.37 (-0.50, -0.24)
	Female	192283 (174424, 211386)	250297 (227051, 275164)	-0.22 (-0.32, -0.11)	14735 (12668, 16807)	17360 (15177, 19773)	-0.37 (-0.48, -0.22)	1561956 (1365538, 1779088)	-0.37 (-0.48, -0.22)
	Both	452111 (421862, 481473)	290737 (271285, 309619)	-0.13 (-0.21, -0.06)	34458 (30604, 37794)	20071 (17784, 22076)	-0.37 (-0.46, -0.28)	1805923 (1600112, 1986317)	-0.37 (-0.46, -0.28)
Zambia	Male	81061 (73874, 88485)	317817 (289642, 346924)	-0.11 (-0.23, 0.02)	5357 (4411, 6439)	18943 (15887, 22205)	-0.36 (-0.49, -0.17)	1704387 (1429424, 1997907)	-0.36 (-0.49, -0.17)
	Female	55168 (50173, 60492)	220883 (200882, 242199)	-0.16 (-0.25, -0.05)	3995 (3279, 4746)	13479 (11470, 15445)	-0.46 (-0.55, -0.34)	1212735 (1032009, 1389705)	-0.46 (-0.55, -0.34)
	Both	136229 (127369, 144488)	269858 (252307, 286220)	-0.13 (-0.20, -0.05)	9352 (7839, 10647)	16239 (14082, 18146)	-0.41 (-0.50, -0.30)	1461138 (1266997, 1632703)	-0.41 (-0.50, -0.30)

Figure 1.

Trends of incidence rate of neonatal disorders in the ESSA region, 1990 to 2023

There were 302,852 new cases (95% UI: 285,639, 320,766) of neonatal disorders among early neonates in the ESSA region in 2023. This was equivalent to 110,630 new cases per 100,000 live births (95% UI: 104,343, 117,174). The lowest rate was estimated in Kenya [144,598 new cases per 100,000 live births (95% UI: 118,925, 170,249)]. Between 1990 and 2023, the incidence rate among early neonates declined by 30% (95% UI: -36, -25) in the region. However, no statistically significant decline was estimated in Kenya [-6% (95% UI: -27, 16)] since the percentage change estimate crossed the zero value (Table 2).

Table 2.

Incidence, Mortality, and YLLs From Neonatal Disorders by Age and Location in the ESSA Region, 1990 to 2023

Location	Age	Number of incidents	Incidence rate	% of change	Number of deaths	Mortality rate	% of change	YLLs rate	% of change
Location	Age	2023	2023	1990-2023	2023	2023	1990-2023	2023	1990-2023
ESSA region	0-6 days	302852 (285639, 320766)	110630 (104343, 117174)	-0.30 (-0.36, -0.25)	208161 (195994, 218071)	76040 (71596, 79660)	-0.40 (-0.44, -0.35)	6841750 (6441850, 7167475)	-0.40 (-0.44, -0.35)
	7-27 days	283962 (268032, 301589)	34972 (33011, 37143)	-0.39 (-0.43, -0.33)	29493 (24397, 33379)	3632 (3005, 4111)	-0.44 (-0.53, -0.31)	326816 (270349, 369873)	-0.44 (-0.54, -0.31)
	<28 days	3257588 (3189899, 3317570)	300042 (293808, 305567)	-0.18 (-0.20, -0.16)	237654 (221990, 249641)	21889 (20447, 22993)	-0.41 (-0.45, -0.36)	1969494 (1839682, 2068833)	-0.41 (-0.45, -0.36)
Burundi	0-6 days	10481 (8995, 12391)	108755 (93331, 128574)	-0.32 (-0.46, -0.13)	8594 (8074, 9192)	89170 (83775, 95378)	-0.26 (-0.33, -0.18)	8023148 (7537673, 8581707)	-0.26 (-0.34, -0.19)
	7-27 days	10133 (8471, 11763)	35488 (29666, 41196)	-0.37 (-0.50, -0.22)	1498 (1027, 2059)	5246 (3597, 7212)	0.00 (-0.28, 0.34)	472042 (323611, 648906)	0.00 (-0.28, 0.34)
	<28 days	101684 (95735, 109238)	266253 (250674, 286032)	-0.19 (-0.26, -0.09)	10092 (9269, 11002)	26425 (24269, 28809)	-0.24 (-0.31, -0.15)	2377588 (2183624, 2592104)	-0.24 (-0.31, -0.15)
Comoros	0-6 days	496 (421, 573)	115059 (97776, 133001)	-0.32 (-0.46, -0.15)	292 (270, 310)	67707 (62610, 72003)	-0.39 (-0.46, -0.30)	6091935 (5633390, 6478508)	-0.39 (-0.46, -0.30)
	7-27 days	433 (368, 509)	33817 (28777, 39831)	-0.40 (-0.52, -0.23)	57 (46, 68)	4473 (3598, 5286)	-0.25 (-0.47, 0.09)	402469 (323681, 475623)	-0.25 (-0.47, 0.09)
	<28 days	5900 (5511, 6271)	345064 (322322, 366791)	-0.17 (-0.24, -0.10)	349 (322, 374)	20403 (18830, 21864)	-0.37 (-0.45, -0.27)	1835798 (1694254, 1967202)	-0.37 (-0.45, -0.28)
Djibouti	0-6 days	771 (645, 907)	114378 (95770, 134565)	-0.27 (-0.40, -0.10)	472 (426, 518)	70085 (63243, 76813)	-0.28 (-0.38, -0.17)	6305901 (5690279, 6911277)	-0.28 (-0.38, -0.17)
	7-27 days	715 (608, 832)	35711 (30335, 41551)	-0.31 (-0.46, -0.10)	78 (63, 93)	3893 (3138, 4634)	-0.07 (-0.33, 0.33)	350222 (282341, 416936)	-0.08 (-0.33, 0.33)
	<28 days	7033 (6590, 7492)	262747 (246197, 279884)	-0.08 (-0.15, 0.01)	550 (491, 607)	20557 (18329, 22685)	-0.26 (-0.37, -0.14)	1849660 (1649121, 2041119)	-0.26 (-0.37, -0.14)
Eritrea	0-6 days	4056 (3443, 4762)	102200 (86744, 119977)	-0.33 (-0.43, -0.19)	2107 (1943, 2282)	53088 (48955, 57496)	-0.37 (-0.46, -0.24)	4776601 (4404742, 5173269)	-0.37 (-0.46, -0.24)
	7-27 days	3786 (3256, 4408)	32092 (27605, 37369)	-0.41 (-0.52, -0.28)	533 (441, 617)	4521 (3740, 5229)	-0.13 (-0.35, 0.30)	406801 (336463, 470454)	-0.13 (-0.35, 0.30)
	<28 days	45702 (43281, 48444)	289892 (274532, 307282)	-0.26 (-0.31, -0.20)	2640 (2434, 2892)	16748 (15442, 18344)	-0.34 (-0.44, -0.20)	1506909 (1389351, 1650504)	-0.34 (-0.44, -0.20)
Ethiopia	0-6 days	75855 (64429, 88705)	109373 (92898, 127900)	-0.35 (-0.48, -0.20)	65288 (60702, 69695)	94136 (87524, 100491)	-0.41 (-0.48, -0.33)	8469904 (7875052, 9041742)	-0.41 (-0.48, -0.33)
	7-27 days	75913 (64533, 87579)	36988 (31444, 42673)	-0.44 (-0.55, -0.30)	12995 (10649, 14664)	6332 (5189, 7145)	-0.54 (-0.65, -0.37)	569701 (466837, 642843)	-0.54 (-0.65, -0.37)
	<28 days	811330 (780307, 844999)	295471 (284173, 307733)	-0.29 (-0.32, -0.24)	78283 (73087, 83730)	28509 (26617, 30493)	-0.44 (-0.51, -0.36)	2565112 (2394860, 2743598)	-0.44 (-0.51, -0.36)
Kenya	0-6 days	32582 (26797, 38362)	144598 (118925, 170249)	-0.06 (-0.27, 0.16)	12294 (11257, 13507)	54558 (49957, 59942)	-0.22 (-0.32, -0.09)	4908897 (4494874, 5393348)	-0.22 (-0.32, -0.09)
	7-27 days	30510 (25857, 36055)	45499 (38561, 53767)	-0.15 (-0.32, 0.05)	1084 (900, 1271)	1616 (1343, 1895)	-.020 (-0.38, 0.07)	145410 (120812, 170528)	-0.20 (-0.38, 0.07)
	<28 days	242125 (233760, 250529)	270261 (260924, 279642)	-0.05 (-0.10, -0.01)	13377 (12240, 14682)	14932 (13662, 16388)	-0.22 (-0.31, -0.08)	1343491 (1229285, 1474544)	-0.22 (-0.31, -0.08)
Madagascar	0-6 days	18843 (15852, 21826)	99200 (83450, 114902)	-0.32 (-0.45, -0.15)	12123 (10489, 13630)	63821 (55218, 71753)	-0.31 (-0.41, -0.21)	5742291 (4968229, 6455980)	-0.31 (-0.41, -0.21)
	7-27 days	15974 (13658, 18365)	28354 (24242, 32598)	-0.44 (-0.54, -0.31)	889 (669, 1141)	1579 (1188, 2025)	-0.35 (-0.52, -0.14)	142042 (106875, 182222)	-0.35 (-0.52, -0.14)
	<28 days	247314 (231280, 262551)	328294 (307009, 348520)	-0.12 (-0.19, -0.04)	13012 (11210, 14714)	17273 (14881, 19532)	-0.32 (-0.42, -0.21)	1554153 (1338929, 1757442)	-0.32 (-0.42, -0.21)
Malawi	0-6 days	12075 (10157, 14117)	102573 (86278, 119921)	-0.31 (-0.44, -0.13)	9075 (8223, 9801)	77088 (69855, 83260)	-0.49 (-0.54, -0.43)	6936029 (6285219, 7491371)	-0.49 (-0.54, -0.43)
	7-27 days	11067 (9422, 13008)	31663 (26956, 37218)	-0.36 (-0.48, -0.20)	872 (645, 1113)	2495 (1844, 3185)	-0.43 (-0.58, -0.22)	224524 (165921, 286609)	-0.43 (-0.58, -0.22)
	<28 days	138896 (130185, 147919)	297272 (278627, 316583)	-0.14 (-0.21, -0.06)	9947 (8992, 10833)	21289 (19245, 23185)	-0.49 (-0.55, -0.43)	1915474 (1731534, 2086096)	-0.49 (-0.55, -0.43)
Mozambique	0-6 days	25035 (21269, 28888)	109358 (92906, 126191)	-0.35 (-0.47, -0.19)	18879 (17369, 20445)	82469 (75871, 89306)	-0.52 (-0.56, -0.46)	7420210 (6826545, 8035379)	-0.52 (-0.56, -0.46)
	7-27 days	22275 (19257, 26553)	32798 (28355, 39097)	-0.48 (-0.58, -0.35)	1479 (1114, 1767)	2178 (1640, 2601)	-0.57 (-0.66, -0.42)	195923 (147518, 234040)	-0.57 (-0.66, -0.42)
	<28 days	312037 (291213, 331645)	343623 (320691, 365216)	-0.17 (-0.24, -0.09)	20358 (18531, 22100)	22419 (20407, 24338)	-0.52 (-0.58, -0.47)	2017165 (1836113, 2189780)	-0.52 (-0.58, -0.47)
Rwanda	0-6 days	7229 (6292, 8557)	104241 (90717, 123382)	-0.37 (-0.50, -0.21)	4918 (4536, 5369)	70914 (65404, 77414)	-0.52 (-0.57, -0.46)	6380489 (5884732, 6965360)	-0.52 (-0.57, -0.46)
	7-27 days	7184 (6136, 8484)	34809 (29730, 41108)	-0.44 (-0.55, -0.32)	729 (578, 884)	3532 (2802, 4282)	-0.41 (-0.55, -0.22)	317828 (252090, 385296)	-0.41 (-0.55, -0.22)
	<28 days	57492 (53349, 61728)	208504 (193478, 223867)	-0.32 (-0.38, -0.26)	5647 (5148, 6159)	20480 (18670, 22336)	-0.51 (-0.56, -0.45)	1842706 (1679799, 2009657)	-0.51 (-0.56, -0.45)
Somalia	0-6 days	20327 (17502, 23618)	113238 (97503, 131572)	-0.28 (-0.43, -0.11)	9527 (8281, 10843)	53075 (46135, 60406)	-0.31 (-0.44, -0.10)	4775461 (4150984, 5435037)	-0.31 (-0.44, -0.10)
	7-27 days	21332 (17683, 24475)	40220 (33339, 46144)	-0.34 (-0.48, -0.18)	3168 (2429, 3793)	5972 (4579, 7151)	-0.01 (-0.37, 0.66)	537321 (411990, 643420)	-0.01 (-0.37, 0.66)
	<28 days	275568 (258115, 291770)	388177 (363593, 411000)	-0.18 (-0.25, -0.10)	12695 (10977, 14487)	17882 (15463, 20408)	-0.26 (-0.40, -0.02)	1608966 (1391271, 1836169)	-0.26 (-0.40, -0.02)
South Sudan	0-6 days	7229 (6138, 8327)	123845 (105156, 142664)	-0.22 (-0.38, -0.03)	4706 (4280, 5083)	80627 (73323, 87078)	-0.22 (-0.30, -0.09)	7254421 (6597233, 7834916)	-0.22 (-0.30, -0.09)
	7-27 days	7138 (6080, 8268)	41302 (35179, 47838)	-0.26 (-0.41, -0.09)	789 (592, 985)	4564 (3425, 5700)	0.21 (-0.13, 0.76)	410639 (308114, 512827)	0.21 (-0.13, 0.76)
	<28 days	80996 (75560, 86546)	350331 (326819, 374338)	-0.07 (-0.14, 0.02)	5495 (4989, 5964)	23766 (21577, 25797)	-0.18 (-0.28, -0.05)	2138391 (1941418, 2321056)	-0.18 (-0.28, -0.05)
Uganda	0-6 days	32274 (26989, 38579)	105167 (87947, 125711)	-0.31 (-0.46, -0.13)	23507 (21369, 25566)	76599 (69631, 83308)	-0.42 (-0.49, -0.35)	6892014 (6265091, 7495720)	-0.42 (-0.49, -0.35)
	7-27 days	29837 (25159, 34731)	32764 (27626, 38138)	-0.40 (-0.53, -0.25)	2095 (1651, 2615)	2301 (1813, 2871)	-0.43 (-0.59, -0.20)	207013 (163146, 258305)	-0.43 (-0.59, -0.20)
	<28 days	340481 (319283, 359884)	279640 (262229, 295576)	-0.20 (-0.27, -0.12)	25602 (23253, 27996)	21027 (19098, 22993)	-0.43 (-0.50, -0.35)	1891945 (1718329, 2068834)	-0.43 (-0.50, -0.35)
Tanzania	0-6 days	42400 (35778, 50572)	108329 (91409, 129206)	-0.29 (-0.43, -0.14)	28824 (25665, 31655)	73642 (65571, 80874)	-0.36 (-0.44, -0.26)	6625974 (5899799, 7276715)	-0.36 (-0.44, -0.26)
	7-27 days	35778 (30347, 42020)	30747 (26079, 36111)	-0.40 (-0.51, -0.27)	2388 (1775, 2941)	2052 (1525, 2528)	-0.48 (-0.63, -0.30)	184658 (137252, 227429)	-0.48 (-0.63, -0.30)
	<28 days	452111 (421862, 481473)	290737 (271285, 309619)	-0.13 (-0.21, -0.06)	31212 (27655, 34330)	20071 (17784, 22076)	-0.37 (-0.46, -0.28)	1805923 (1600112, 1986317)	-0.37 (-0.46, -0.28)
Zambia	0-6 days	12948 (11163, 15255)	101834 (87795, 119975)	-0.28 (-0.41, -0.11)	7384 (6518, 8167)	58072 (51265, 64235)	-0.40 (-0.49, -0.29)	5225063 (4612556, 5779538)	-0.40 (-0.49, -0.29)
	7-27 days	11652 (9980, 13607)	30851 (26425, 36030)	-0.38 (-0.49, -0.23)	814 (564, 1033)	2155 (1493, 2736)	-0.45 (-0.59, -0.23)	193918 (134296, 246151)	-0.45 (-0.59, -0.23)
	<28 days	136229 (127369, 144488)	269858 (252307, 286220)	-0.13 (-0.20, -0.05)	8198 (7109, 9160)	16239 (14082, 18146)	-0.41 (-0.50, -0.30)	1461138 (1266997, 1632703)	-0.41 (-0.50, -0.30)

Among late neonates, 283,962 new cases (95% UI: 268,032, 301,589) of neonatal disorders were estimated in the ESSA region in 2023. This was equivalent to 34,972 new cases per 100,000 live births (95% UI: 33,011, 37,143). The highest rate was estimated in Kenya [45,499 new cases per 100,000 live births (95% UI: 38,561, 53,767)], whereas the lowest rate was in Madagascar [28,354 new cases per 100,000 live births (95% UI: 24,242, 32,598)]. The incidence rate of neonatal disorders declined by 39% (95% UI: -43, -33) in 2023 compared to the rate in 1990. The highest decline was estimated in Mozambique, with a 48% decline (95% UI: -58, -35). However, there was no statistically significant decline in Kenya [-15% (95% UI -32, 5)] since the percentage change estimate crossed the zero value (Table 2).

Among neonates, there were 221,955 new cases of preterm births per 100,000 live births (95% UI: 216889, 226769), with 252,720 new cases per 100,000 male live births (95% UI: 244,914, 261,004) and 189,951 new cases per 100,000 female live births (95% UI: 183,344, 196,454). The highest rate was estimated in Comoros [270,705 new cases per 100,000 live births (95% UI: 248,836, 292,384)], Madagascar [259,747 new cases per 100,000 live births (95% UI: 240,110, 279,601)], Mozambique [266,358 new cases per 100,000 live births (95% UI: 246,117, 286,936)], Somalia [289,871 new cases per 100,000 live births (95% UI: 264,607, 312,157)], and South Sudan [261,357 new cases per 100,000 live births (95% UI: 240,308, 283,640)], whereas the lowest rate was in Burundi [183,931 new cases per 100,000 live births (95% UI: 167,981, 202,378)], Dibouti [187,773 new cases per 100,000 live births (95% UI: 172,309, 205,147)], Kenya [178,551 new cases per 100,000 live births (95% UI: 175,601, 181,592)], and Rwanda [136,454 new cases per 100,000 live births (95% UI: 124,496, 148,795)]. The incidence rate declined by 10% (95% UI: -13, -8) in the region in 2023 compared to the rate in 1990. Rwanda and Ethiopia experienced the highest decline, with a 27% decline (95% UI: -35, -18) and 23% decline (95% UI: -28, -19), respectively. However, there was no statistically significant change in the rate in Comoros [-10% (95% UI: -18, 0)], Djibouti [1% (95% UI: -9, 17)], Kenya [2% (95% UI: -1, 4)], Madagascar [-3% (95% UI: -13, 8)], Malawi [-6% (95% UI: -16, 7)], Mozambique [-6% (95% UI: -16, 5)], South Sudan [-1% (95% UI: -11, 10)], Tanzania [-4% (95% UI: -16, 8)], and Zambia [-3% (95% UI: -14, 8)] (Table 3).

Table 3.

Incidence Rate of Neonatal Disorders by Location, Sex, and Type in the ESSA Region, 1990 to 2023

Location	Sex	Neonatal preterm birth	% of change	Neonatal encephalopathy due to birth asphyxia and trauma	% of change	Neonatal sepsis and other neonatal infections	% of change	Hemolytic disease and other neonatal jaundice	% of change
Location	Sex	2023	1990-2023	2023	1990-2023	2023	1990-2023	2023	1990-2023
ESSA region	Male	252720 (244914, 261004)	-0.09 (-0.13, -0.06)	23587 (23061, 24112)	-0.26 (-0.29, -0.24)	65001 (61209, 68689)	-0.36 (-0.41, -0.31)	2684 (1918, 3734)	-0.33 (-0.45, -0.10)
	Female	189951 (183344, 196454)	-0.12 (-0.16, -0.07)	19112 (18346, 19786)	-0.38 (-0.41, -0.34)	42655 (40151, 44929)	-0.33 (-0.37, -0.28)	2603 (1819, 3711)	-0.33 (-0.45, -0.09)
	Both	221955 (216889, 226769)	-0.10 (-0.13, -0.08)	21394 (20941, 21813)	-0.32 (-0.34, -0.30)	54049 (51725, 56371)	-0.35 (-0.38, -0.31)	2645 (1867, 3711)	-0.33 (-0.45, -0.10)
Burundi	Male	212808 (187499, 238340)	-0.13 (-0.26, 0.07)	25936 (24390, 27596)	-0.12 (-0.21, -0.04)	64808 (53764, 75053)	-0.36 (-0.49, -0.20)	3443 (2527, 4629)	-0.13 (-0.31, 0.31)
	Female	154460 (135165, 176586)	-0.14 (-0.29, 0.04)	23945 (21509, 26708)	-0.16 (-0.27, -0.03)	42923 (36669, 49337)	-0.33 (-0.45, -0.18)	3343 (2415, 4593)	-0.12 (-0.31, 0.37)
	Both	183931 (167981, 202378)	-0.13 (-0.23, -0.01)	24951 (23434, 26379)	-0.14 (-0.22, -0.07)	53977 (48335, 59866)	-0.35 (-0.44, -0.23)	3393 (2474, 4608)	-0.13 (-0.31, 0.35)
Comoros	Male	291747 (263737, 322232)	-0.11 (-0.21, 0.05)	19325 (18144, 20671)	-0.31 (-0.37, -0.25)	65201 (55484, 77015)	-0.38 (-0.49, -0.21)	3286 (1522, 5843)	-0.40 (-0.59, -0.19)
	Female	248757 (219582, 280915)	-0.09 (-0.21, 0.06)	14234 (12736, 15832)	-0.45 (-0.53, -0.35)	42896 (36763, 49336)	-0.34 (-0.46, -0.19)	3197 (1426, 5794)	-0.39 (-0.59, -0.18)
	Both	270705 (248836, 292384)	-0.10 (-0.18, 0.00)	16833 (15845, 18059)	-0.37 (-0.43, -0.31)	54284 (47517, 60673)	-0.36 (-0.45, -0.25)	3243 (1491, 5817)	-0.40 (-0.59, -0.19)
Djibouti	Male	176757 (156470, 201210)	-0.03 (-0.17, 0.18)	20644 (19329, 22024)	0.12 (0.03, 0.22)	66180 (55600, 78445)	-0.30 (-0.45, -0.14)	2251 (1202, 3532)	-0.28 (-0.58, 0.17)
	Female	199831 (174090, 224629)	0.06 (-0.12, 0.26)	13499 (12124, 15024)	-0.17 (-0.27, -0.03)	43843 (37689, 50457)	-0.28 (-0.41, -0.10)	2197 (1140, 3505)	-0.29 (-0.59, 0.19)
	Both	187773 (172309, 205147)	0.01 (-0.09, 0.17)	17233 (16287, 18232)	-0.01 (-0.08, 0.08)	55516 (49965, 62452)	-0.29 (-0.40, -0.18)	2225 (1176, 3520)	-0.29 (-0.59, 0.18)
Eritrea	Male	257178 (229547, 286365)	-0.24 (-0.33, -0.13)	23089 (21569, 24642)	-0.22 (-0.29, -0.15)	59624 (50460, 69489)	-0.40 (-0.50, -0.25)	2957 (2139, 4035)	-0.19 (-0.36, 0.50)
	Female	175999 (156065, 197037)	-0.20 (-0.34, -0.06)	15777 (14188, 17520)	-0.39 (-0.48, -0.29)	39302 (33728, 45378)	-0.34 (-0.46, -0.21)	2871 (2036, 3995)	-0.20 (-0.37, 0.52)
	Both	217701 (202672, 234691)	-0.22 (-0.29, -0.14)	19533 (18473, 20808)	-0.30 (-0.35, -0.24)	49742 (44130, 54858)	-0.37 (-0.45, -0.29)	2916 (2098, 3977)	-0.19 (-0.37, 0.50)
Ethiopia	Male	255673 (239310, 270719)	-0.23 (-0.29, -0.17)	23478 (21989, 25058)	-0.36 (-0.42, -0.30)	68323 (58057, 79027)	-0.41 (-0.54, -0.27)	2366 (1622, 3432)	-0.41 (-0.59, 0.27)
	Female	175659 (165515, 186793)	-0.24 (-0.30, -0.17)	18680 (16809, 20969)	-0.47 (-0.54, -0.37)	41532 (35430, 48149)	-0.38 (-0.49, -0.25)	2369 (1607, 3438)	-0.40 (-0.57, 0.33)
	Both	216692 (207248, 225647)	-0.23 (-0.28, -0.19)	21141 (19895, 22599)	-0.41 (-0.46, -0.35)	55271 (49543, 61235)	-0.40 (-0.48, -0.30)	2367 (1615, 3435)	-0.41 (-0.58, 0.29)
Kenya	Male	204327 (200041, 208676)	0.02 (-0.01, 0.05)	17782 (16687, 18875)	-0.19 (-0.27, -0.12)	85631 (73488, 100254)	-0.12 (-0.30, 0.08)	3918 (2916, 5085)	-0.29 (-0.35, -0.22)
	Female	151863 (147748, 155460)	0.02 (-0.02, 0.05)	17046 (15356, 18838)	-0.40 (-0.48, -0.30)	54679 (46804, 63972)	-0.09 (-0.27, 0.13)	3811 (2787, 5107)	-0.29 (-0.36, -0.22)
	Both	178551 (175601, 181592)	0.02 (-0.01, 0.04)	17420 (16445, 18486)	-0.31 (-0.37, -0.23)	70424 (62448, 79057)	-0.11 (-0.25, 0.02)	3865 (2854, 5062)	-0.29 (-0.36, -0.22)
Madagascar	Male	288413 (261666, 315100)	-0.03 (-0.17, 0.11)	23375 (21974, 24867)	-0.18 (-0.25, -0.10)	53566 (46114, 62179)	-0.41 (-0.53, -0.27)	1249 (600, 2146)	-0.39 (-0.61, -0.08)
	Female	229733 (205071, 254641)	-0.02 (-0.17, 0.15)	18755 (16854, 20822)	-0.32 (-0.41, -0.20)	38524 (33301, 44330)	-0.35 (-0.45, -0.21)	1172 (506, 2132)	-0.34 (-0.58, 0.03)
	Both	259747 (240110, 279601)	-0.03 (-0.13, 0.08)	21118 (19898, 22490)	-0.24 (-0.30, -0.18)	46218 (41803, 51415)	-0.38 (-0.47, -0.28)	1211 (563, 2135)	-0.37 (-0.59, -0.04)
Malawi	Male	259388 (227258, 292615)	0.01 (-0.13, 0.19)	21342 (20028, 22727)	-0.25 (-0.31, -0.19)	56999 (47576, 66632)	-0.36 (-0.49, -0.21)	2722 (1971, 3699)	-0.32 (-0.41, -0.17)
	Female	189687 (169003, 213150)	-0.13 (-0.26, 0.02)	18900 (17017, 20891)	-0.36 (-0.45, -0.26)	41885 (35698, 48416)	-0.30 (-0.41, -0.13)	2624 (1864, 3672)	-0.32 (-0.42, -0.17)
	Both	224935 (205899, 244068)	-0.06 (-0.16, 0.07)	20135 (18910, 21301)	-0.31 (-0.37, -0.25)	49528 (43586, 55855)	-0.34 (-0.43, -0.21)	2673 (1918, 3683)	-0.32 (-0.42, -0.17)
Mozambique	Male	305943 (272181, 341076)	-0.06 (-0.18, 0.07)	23207 (21726, 24640)	-0.32 (-0.38, -0.25)	61916 (51555, 72244)	-0.44 (-0.54, -0.31)	3404 (2237, 4706)	-0.17 (-0.39, 0.05)
	Female	225799 (203552, 251460)	-0.05 (-0.22, 0.11)	20480 (18412, 22943)	-0.43 (-0.51, -0.35)	42041 (35649, 48650)	-0.39 (-0.50, -0.25)	3205 (2022, 4581)	-0.18 (-0.42, 0.04)
	Both	266358 (246117, 286936)	-0.06 (-0.16, 0.05)	21860 (20676, 23226)	-0.38 (-0.42, -0.32)	52099 (47216, 57562)	-0.42 (-0.50, -0.33)	3306 (2174, 4666)	-0.18 (-0.40, 0.05)
Rwanda	Male	161911 (142041, 185230)	-0.26 (-0.37, -0.14)	19515 (18290, 20721)	-0.32 (-0.38, -0.26)	62990 (54288, 71634)	-0.42 (-0.54, -0.29)	2390 (1617, 3437)	-0.36 (-0.53, 0.19)
	Female	110106 (94263, 124213)	-0.30 (-0.42, -0.15)	15243 (13622, 16983)	-0.40 (-0.49, -0.31)	41181 (35540, 47528)	-0.40 (-0.51, -0.26)	2332 (1536, 3444)	-0.36 (-0.54, 0.20)
	Both	136454 (124496, 148795)	-0.27 (-0.35, -0.18)	17416 (16395, 18397)	-0.36 (-0.41, -0.31)	52273 (47172, 58220)	-0.41 (-0.50, -0.31)	2362 (1582, 3440)	-0.36 (-0.54, 0.20)
Somalia	Male	274222 (244117, 306396)	-0.10 (-0.23, 0.06)	34549 (32437, 36681)	-0.02 (-0.11, 0.07)	69267 (58800, 82297)	-0.33 (-0.46, -0.16)	4201 (2358, 6266)	-0.11 (-0.40, 0.34)
	Female	306658 (273029, 339218)	-0.21 (-0.31, -0.08)	36432 (32480, 40371)	-0.06 (-0.19, 0.10)	47328 (40772, 55285)	-0.29 (-0.40, -0.14)	4129 (2300, 6211)	-0.11 (-0.41, 0.33)
	Both	289871 (264607, 312157)	-0.16 (-0.25, -0.06)	35457 (33088, 37625)	-0.04 (-0.11, 0.06)	58683 (51576, 65770)	-0.32 (-0.42, -0.19)	4166 (2333, 6239)	-0.11 (-0.40, 0.33)
South Sudan	Male	305558 (268759, 343573)	-0.02 (-0.16, 0.13)	27130 (25476, 29022)	-0.04 (-0.13, 0.05)	75089 (63163, 91928)	-0.25 (-0.39, -0.08)	3309 (2299, 4550)	-0.16 (-0.37, 0.36)
	Female	214530 (190708, 238887)	0.01 (-0.15, 0.17)	19815 (17851, 21897)	-0.18 (-0.29, -0.04)	48422 (41577, 55324)	-0.23 (-0.36, -0.06)	3200 (2160, 4499)	-0.16 (-0.38, 0.41)
	Both	261357 (240308, 283640)	-0.01 (-0.11, 0.10)	23578 (22333, 24883)	-0.10 (-0.18, -0.03)	62140 (54749, 70078)	-0.24 (-0.36, -0.12)	3256 (2230, 4515)	-0.16 (-0.37, 0.41)
Uganda	Male	238996 (215322, 263697)	-0.13 (-0.25, 0.02)	29714 (27840, 31533)	-0.36 (-0.41, -0.30)	61426 (51879, 70822)	-0.37 (-0.49, -0.21)	1861 (1131, 2761)	-0.49 (-0.64, -0.37)
	Female	165655 (145514, 186000)	-0.08 (-0.21, 0.11)	17537 (15778, 19489)	-0.46 (-0.53, -0.36)	40169 (34423, 47434)	-0.35 (-0.46, -0.20)	1759 (1015, 2807)	-0.52 (-0.68, -0.38)
	Both	203067 (187853, 219183)	-0.11 (-0.21, -0.01)	23749 (22415, 25197)	-0.40 (-0.44, -0.35)	51013 (45111, 56641)	-0.36 (-0.45, -0.26)	1811 (1080, 2779)	-0.51 (-0.65, -0.38)
Tanzania	Male	247900 (218376, 280590)	0.10 (-0.06, 0.29)	19845 (18612, 21142)	-0.23 (-0.29, -0.16)	59882 (50949, 70401)	-0.36 (-0.49, -0.20)	2593 (1672, 3714)	-0.33 (-0.51, -0.17)
	Female	191483 (168422, 214869)	-0.17 (-0.30, -0.01)	15879 (14124, 17753)	-0.39 (-0.48, -0.29)	40433 (34811, 47325)	-0.32 (-0.44, -0.19)	2502 (1576, 3709)	-0.33 (-0.52, -0.17)
	Both	220029 (201501, 239068)	-0.04 (-0.16, 0.08)	17886 (16841, 19026)	-0.31 (-0.37, -0.25)	50274 (45084, 55780)	-0.35 (-0.44, -0.24)	2548 (1637, 3712)	-0.33 (-0.52, -0.17)
Zambia	Male	241090 (211450, 267946)	-0.02 (-0.17, 0.16)	17745 (16656, 18879)	-0.27 (-0.32, -0.20)	56591 (47762, 68039)	-0.32 (-0.45, -0.13)	2391 (1553, 3441)	-0.31 (-0.49, -0.11)
	Female	165085 (146305, 184523)	-0.05 (-0.19, 0.11)	12882 (11447, 14302)	-0.42 (-0.51, -0.33)	40703 (34976, 46126)	-0.35 (-0.47, -0.21)	2214 (1356, 3362)	-0.32 (-0.52, -0.12)
	Both	203486 (186671, 219334)	-0.03 (-0.14, 0.08)	15339 (14553, 16141)	-0.34 (-0.39, -0.29)	48730 (43040, 55208)	-0.33 (-0.43, -0.21)	2303 (1467, 3410)	-0.32 (-0.50, -0.11)

The rate of neonatal encephalopathy due to birth asphyxia and trauma was estimated to be 21,394 new cases per 100,000 live births (95% UI: 20,941, 21,813), with 23,587 new cases per 100,000 male live births (95% UI: 23,061, 24,112) and 19,112 new cases per 100,000 female live births (95% UI: 18,346, 19,786). The highest rate was estimated in Burundi [24,951 new cases per 100,000 live births (95% UI: 23,434, 26,379)], South Sudan [23,578 new cases per 100,000 live births (95% UI: 22,333, 24,883)], and Uganda [23,749 new cases per 100,000 live births (95% UI: 22,415, 25,197)], whereas the lowest rate was in Comoros [16,833 new cases per 100,000 live births (95% UI: 15,845, 18,059)], Djibouti [17,233 new cases per 100,000 live births (95% UI: 16,287, 18,232)], Eritrea [19,533 new cases per 100,000 live births (95% UI: 18,473, 20,808)], Kenya [17,420 new cases per 100,000 live births (95% UI: 16,445, 18,486)], Rwanda [17,416 new cases per 100,000 live births (95% UI: 16,395, 18,397)], Tanzania [17,886 new cases per 100,000 live births (95% UI: 16,841, 19,026)], and Zambia [15,339 new cases per 100,000 live births (95% UI: 14,553, 16,141)]. Among the neonates, the incidence rate of neonatal encephalopathy due to birth asphyxia and trauma declined by 32% (95% UI: -34, -30) in the region in 2023 compared to the rate in 1990. Ethiopia and Uganda had the highest decline in the region, with a 41% decline (95% UI: -46, -35) and 40% decline (95% UI: -44, -35), respectively. However, Djibouti [-1% (95% UI: -8, 8)] and Somalia [-4% (95% UI: -11, 6)] had no statistically significant decline in the rate (Table 3).

There were an estimated 54,049 new cases of neonatal sepsis and other neonatal infections per 100,000 live births (95% UI: 51,725, 56,371), with 65,001 new cases per 100,000 male live births (95% UI: 61,209, 68,689) and 42,655 new cases per 100,000 female live births (95% UI: 40,151, 44,929). The highest rate was estimated in Kenya [70,424 new cases per 100,000 live births (95% UI: 62,448, 79,057)], whereas the lowest rate was in Madagascar [46,218 new cases per 100,000 live births (95% UI: 41,803, 51,415)]. Between 1990 and 2023, the incidence rate declined by 35% (95% UI: -38, -31) among the neonates in the region. However, there was no statistically significant decline in Kenya [-11% (95% UI: -25, 2)] (Table 3).

Hemolytic disease and other neonatal jaundice were estimated to be 2645 new cases per 100,000 live births (95% UI: 1867, 3711), with 2684 new cases per 100,000 male live births (95% UI: 1918, 3734) and 2603 new cases per 100,000 female live births (95% UI: 1819, 3711). All of the countries in the region exhibited no significant variation in the distribution of the rate. The incidence rate declined by 33% (95% UI: -45, -10) in 2023 compared to the rate in 1990. However, no statistically significant decline was estimated in Burundi [-13% (95% UI: -31, 35)], Djibouti [-29% (95% UI: -59, 18)], Eritrea [-19% (95% UI: -37, 50)], Ethiopia [-41% (95% UI: -58, 29)], Mozambique [-18% (95% UI: -40, 5)], Rwanda [-36% (95% UI: -54, 20)], Somalia [-11% (95% UI: -40, 33)], and South Sudan [-16% (95% UI: -37, 41)] (Table 3).

Mortality From Neonatal Disorders

There were an estimated 274,590 neonatal deaths (95% UI: 252,857, 295,496) from neonatal disorders in the ESSA region in 2023, with 168,868 deaths (95% UI: 150,988, 188,406) among males and 105,722 deaths (95% UI: 95,579, 117,622) among females. This was equivalent to an estimated 21,889 deaths per 100,000 live births (95% UI: 20,447, 22,993), with 26,452 deaths per 100,000 male live births (95% UI: 24,400, 28,570) and 17,143 deaths per 100,000 female live births (95% UI: 15,806, 18,471). The highest rate was estimated in Burundi [26,425 deaths per 100,000 live births (95% UI: 24,269, 28,809)] and Ethiopia [28,509 deaths per 100,000 live births (95% UI: 26,617, 30,493)], whereas the lowest rate was in Eritrea [16,748 deaths per 100,000 live births (95% UI: 15,442, 18,344)], Kenya [14,932 deaths per 100,000 live births (95% UI: 13,662, 16,388)], Madagascar [17,273 deaths per 100,000 live births (95% UI: 14,881, 19,532)], and Zambia [16,239 deaths per 100,000 live births (95% UI: 14,082, 18,146)]. In the region, the mortality rate declined by 41% (95% CI: -45, -36) between 1990 and 2023. The highest decline was estimated in Mozambique [52% decline (95% UI: -58, -47)], whereas the lowest decline was in Burundi [24% decline (95% UI: -31, -15)], Kenya [22% decline (95% UI: -31, -8)], and South Sudan [18% decline (95% UI: -28, -5)] (Table 1).

There were an estimated 208,161 deaths (95% UI: 195,994, 218,071) among early neonates in the ESSA in 2023. This was equivalent to 76,040 deaths per 100,000 live births (95% UI: 71,596, 79,660). The highest rate was estimated in Burundi [89,170 deaths per 100,000 live births (95% UI: 83,775, 95,378)], whereas the lowest rate was in Eritrea [53,088 deaths per 100,000 live births (95% UI: 48,955, 57,496), Ethiopia [65,288 deaths per 100,000 live births (95% UI: 60,702, 69,695)], Kenya [54,558 deaths per 100,000 live births (95% UI: 49,957, 59,942)], and Zambia [58,072 deaths per 100,000 live births (95% UI: 51,265, 64,235)]. The mortality rate declined by 40% (95% UI: -44, -35) in the region in 2023 compared to the rate in 1990. Mozambique [52% decline (95% UI: -56, -46)] and Rwanda [52% decline (95% UI: -57, -46)] experienced the highest decline in the region, whereas Burundi [0.26% decline (UI: -33, -18)], Djibouti [28% decline (95% UI: -38, -17)], Kenya [22% decline (95% UI: -32, -9)], and South Sudan [18% decline (95% UI: -28, -5)] had the slowest decline (Table 2).

There were an estimated 29,493 deaths (95% UI: 24,397, 33,379) among late neonates. This was equivalent to 3632 deaths (95% UI: 3005, 4111) per 100,000 live births. The highest rate was estimated in Ethiopia [12,995 deaths per 100,000 live births (95% UI: 10,649, 14,664)] and Somalia [5972 deaths per 100,000 live births (95% UI: 4579, 7151)], whereas the lowest rate was estimated in Kenya [1616 deaths per 100,000 live births (95% UI: 1343, 1895)], Mozambique [2178 deaths per 100,000 live births (95% UI: 1640, 2601)], Uganda [2301 deaths per 100,000 live births (95% UI: 1813, 2871)], Tanzania [2052 deaths per 100,000 live births (95% UI: 1525, 2528)], and Zambia [2155 deaths per 100,000 live births (95% UI: 1493, 2736)]. Between 1990 and 2023, there was a 44% decline (95% UI: -53, -31) in the mortality rate in the region. However, no statistically significant decline was estimated in Burundi [0 (-28, 34)], Comoros [-25% (95% UI: -47, 9)], Djibouti [-7% (95% UI: -33, 33)], Eritrea [-13% (95% UI: -35, 30)], Kenya [-2% (95% UI: -38, 7)], Somalia [-1% (95% UI: -37, 66)], and South Sudan [21% (95% UI: -13, 76)] (Table 2).

Neonatal mortality rate from preterm birth was estimated to be 6095 deaths per 100,000 live births (95% UI: 4893, 7517), with 7169 deaths per 100,000 male live births (95% UI: 5184, 9460) and 4978 deaths per 100,000 female live births (95% UI: 3695, 6601). No statistically significant difference was estimated in the distribution of the rate by location. The mortality rate declined by 45% (95% UI: -63, -21) in the region in 2023 compared to the rate in 1990. However, no statistically significant change was estimated in Djibouti [-34% (95% UI: -59, 4)], Kenya [-11% (95% UI: -45, 45)], and Somalia [-35% (95% UI: -61, 16)] (Table 4).

Table 4.

Mortality Rate of Neonatal Disorders by Location, Sex, and Type in ESSA Region, 1990 to 2023

Location	Sex	Neonatal preterm birth	% of change	Neonatal encephalopathy due to birth asphyxia and trauma	% of change	Neonatal sepsis and other neonatal infections	% of change	Hemolytic disease and other neonatal jaundice	% of change
Location	Sex	2023	1990-2023	2023	1990-2023	2023	1990-2023	2023	1990-2023
ESSA region	Male	7169 (5184, 9460)	-0.42 (-0.65, 0.10)	10229 (7892, 12814)	-0.39 (-0.60, -0.06)	3785 (1760, 6102)	-0.36 (-0.73, 0.60)	481 (180, 1015)	-0.69 (-0.89, -0.07)
	Female	4978 (3695, 6601)	-0.49 (-0.65, -0.22)	6354 (4694, 8052)	-0.46 (-0.65, -0.15)	2455 (1494, 3618)	-0.34 (-0.62, 0.45)	232 (58, 598)	-0.63 (-0.88, 0.27)
	Both	6095 (4893, 7517)	-0.45 (-0.63, -0.21)	8330 (6985, 9976)	-0.42 (-0.56, -0.16)	3133 (2086, 4747)	-0.35 (-0.62, 0.13)	359 (170, 675)	-0.67 (-0.86, -0.19)
Burundi	Male	7266 (3620, 12701)	-0.48 (-0.76, 0.03)	11745 (6327, 18196)	-0.20 (-0.62, 0.64)	5137 (1596, 9731)	0.00 (-0.74, 1.64)	540 (129, 1770)	-0.66 (-0.89, 0.00)
	Female	6060 (2905, 9980)	-0.37 (-0.68, 0.11)	8851 (4568, 14094)	-0.11 (-0.54, 0.65)	4215 (1507, 7405)	0.22 (-0.44, 1.69)	342 (36, 1410)	-0.47 (-0.89, 0.64)
	Both	6669 (4222, 9885)	-0.44 (-0.65, -0.08)	10313 (6805, 14802)	-0.16 (-0.49, 0.41)	4681 (2208, 7352)	0.09 (-0.48, 0.94)	442 (125, 1102)	-0.60 (-0.87, 0.04)
Comoros	Male	7501 (4408, 11138)	-0.48 (-0.73, 0.01)	8252 (4658, 12176)	-0.31 (-0.69, 0.53)	3685 (1689, 6283)	-0.14 (-0.73, 1.41)	329 (136, 576)	-0.76 (-0.93, -0.17)
	Female	5779 (3588, 8569)	-0.47 (-0.70, -0.09)	5235 (2970, 7875)	-0.37 (-0.71, 0.40)	2427 (1335, 3931)	-0.11 (-0.58, 1.04)	152 (40, 404)	-0.72 (-0.90, -0.05)
	Both	6658 (4618, 9036)	-0.47 (-0.67, -0.17)	6776 (4547, 9377)	-0.34 (-0.63, 0.18)	3069 (1822, 4795)	-0.13 (-0.59, 0.68)	242 (124, 443)	-0.75 (-0.90, -0.38)
Djibouti	Male	7618 (3794, 12536)	-0.36 (-0.70, 0.20)	8757 (4505, 13586)	-0.21 (-0.60, 0.68)	3361 (1377, 5978)	-0.09 (-0.66, 1.48)	448 (193, 831)	-0.62 (-0.89, 0.27)
	Female	7010 (4417, 10381)	-0.31 (-0.06, 0.17)	6179 (2985, 9830)	-0.23 (-0.61, 0.47)	2206 (951, 4107)	-0.08 (-0.53, 0.94)	195 (67, 401)	-0.56 (-0.86, 0.28)
	Both	7328 (4741, 10640)	-0.34 (-0.59, 0.04)	7526 (4666, 11252)	-0.22 (-0.52, 0.33)	2810 (1592, 4725)	-0.09 (-0.52, 0.69)	327 (173, 575)	-0.61 (-0.83, -0.05)
Eritrea	Male	6884 (3857, 10301)	-0.45 (-0.73, 0.09)	8017 (4694, 11506)	-0.28 (-0.65, 0.69)	3424 (1651, 5688)	-0.26 (-0.71, 1.24)	469 (184, 914)	-0.68 (-0.91, 0.31)
	Female	3657 (2355, 5599)	-0.39 (-0.67, 0.18)	3867 (2257, 5380)	-0.25 (-0.62, 0.53)	1677 (933, 2631)	-0.14 (-0.58, 1.10)	143 (32, 425)	-0.58 (-0.86, 0.74)
	Both	5315 (3549, 7240)	-0.43 (-0.67, -0.05)	5999 (4053, 8047)	-0.27 (-0.57, 0.39)	2574 (1491, 4021)	-0.22 (-0.61, 0.63)	311 (140, 554)	-0.66 (-0.88, 0.11)
Ethiopia	Male	10139 (7147, 14701)	-0.38 (-0.68, 0.22)	15258 (11380, 19589)	-0.38 (-0.62, 0.10)	5121 (2626, 8128)	-0.48 (-0.78, 0.62)	680 (266, 1303)	-0.74 (-0.92, 0.03)
	Female	5122 (3398, 7088)	-0.59 (-0.77, -0.27)	7121 (4855, 9740)	-0.52 (-0.71, -0.16)	2570 (1500, 4104)	-0.47 (-0.73, 0.50)	258 (71, 734)	-0.62 (-0.90, 2.40)
	Both	7695 (5693, 10321)	-0.47 (-0.70, -0.19)	11294 (9007, 14228)	-0.43 (-0.58, -0.08)	3878 (2375, 5669)	-0.47 (-0.71, 0.04)	474 (224, 891)	-0.72 (-0.88, -0.08)
Kenya	Male	4999 (2903, 7487)	-0.14 (-0.59, 0.79)	7270 (4524, 10232)	-0.31 (-0.63, 0.29)	1874 (822, 3377)	-0.26 (-0.71, 0.82)	165 (61, 349)	-0.57 (-0.85, 0.78)
	Female	4457 (2949, 6238)	-0.07 (-0.51, 0.65)	5219 (3670, 7106)	-0.34 (-0.60, 0.18)	1293 (743, 2155)	-0.06 (-0.54, 1.22)	84 (28, 172)	-0.57 (-0.84, 0.37)
	Both	4733 (3335, 6378)	-0.11 (-0.45, 0.45)	6262 (4696, 7857)	-0.32 (-0.55, 0.03)	1589 (1006, 2488)	-0.19 (-0.58, 0.47)	125 (61, 219)	-0.57 (-0.81, 0.08)
Madagascar	Male	6779 (4286, 9860)	-0.52 (-0.72, -0.25)	3800 (1967, 7323)	-0.34 (-0.68, 0.27)	3006 (1274, 5408)	-0.08 (-0.68, 1.29)	397 (122, 1163)	-0.60(-0.88, 0.00)
	Female	5881 (3684, 8350)	-0.43 (-0.68, -0.12)	3293 (1718, 5556)	-0.22 (-0.61, 0.43)	2606 (1466, 4554)	0.12 (-0.45, 1.58)	284 (68, 890)	-0.40 (-0.80, 0.72)
	Both	6340 (4457, 8505)	-0.48 (-0.64, -0.29)	3552 (2101, 5539)	-0.29 (-0.57, 0.12)	2811 (1683, 4438)	0.00 (-0.48, 0.90)	342 (144, 709)	-0.53 (-0.82, -0.02)
Malawi	Male	5761 (3188, 9008)	-0.61 (-0.82, -0.16)	9224 (5177, 13730)	-0.45 (-0.72, 0.15)	4185 (1454, 7666)	-0.27 (-0.74, 0.98)	435 (157, 1083)	-0.70 (-0.92, 0.10)
	Female	4338 (2395, 7070)	-0.67 (-0.85, -0.41)	6609 (3997, 9720)	-0.54 (-0.76, -0.08)	3017 (1437, 4775)	-0.31 (-0.67, 0.68)	221 (33, 748)	-0.72 (-0.91, -0.20)
	Both	5058 (3207, 7152)	-0.64 (-0.79, -0.41)	7931 (5459, 10658)	-0.49 (-0.68, -0.14)	3608 (1813, 5836)	-0.29 (-0.63, 0.29)	329 (132, 692)	-0.71 (-0.89, -0.28)
Mozambique	Male	8099 (5735, 10999)	-0.33 (-0.63, 0.31)	11853 (7462, 15597)	-0.45 (-0.69, -0.04)	2856 (1458, 4708)	-0.59 (-0.84, -0.04)	629 (200, 1725)	-0.69 (-0.90, 0.01)
	Female	5989 (4119, 8452)	-0.51 (-0.71, -0.14)	8260 (5022, 11134)	-0.53 (-0.74, -0.15)	2001 (1203, 3155)	-0.64 (-0.82, -0.16)	271 (46, 910)	-0.80 (-0.93, -0.38)
	Both	7057 (5313, 9019)	-0.42 (-0.62, -0.06)	10079 (6870, 12448)	-0.48 (-0.68, -0.22)	2433 (1651, 3461)	-0.62 (-0.80, -0.31)	452 (182, 1019)	-0.74 (-0.90, -0.37)
Rwanda	Male	5589 (2988, 9230)	-0.65 (-0.84, -0.27)	8366 (4669, 13202)	-0.47 (-0.75, 0.22)	3450 (1293, 6214)	-0.39 (-0.81, 0.82)	310 (119, 658)	-0.83 (-0.95, -0.47)
	Female	4449 (2403, 7099)	-0.63 (-0.81, -0.27)	6810 (3929, 10638)	-0.47 (-0.74, 0.05)	3293 (1748, 5269)	-0.27 (-0.64, 0.64)	250 (49, 606)	-0.72 (-0.92, 0.00)
	Both	5029 (3269, 7290)	-0.64 (-0.80, -0.40)	7602 (5117, 10714)	-0.47 (-0.69, -0.06)	3373 (1989, 5215)	-0.33 (-0.65, 0.23)	281 (121, 535)	-0.80 (-0.92, -0.54)
Somalia	Male	5364 (2949, 8271)	-0.36 (-0.69, 0.42)	7002 (4095, 9681)	-0.26 (-0.61, 0.86)	4022 (1559, 6969)	-0.19 (-0.64, 1.23)	618 (139, 1998)	0.08 (-0.74, 2.38)
	Female	5057 (2910, 7669)	-0.34 (-0.65, 0.35)	4536 (2780, 6434)	-0.22 (-0.58, 0.79)	2690 (990, 4673)	-0.13 (-0.56, 1.19)	342 (41, 1452)	-0.26 (-0.78, 3.21)
	Both	5216 (3593, 7468)	-0.35 (-0.61, 0.16)	5812 (4134, 7387)	-0.25 (-0.54, 0.48)	3379 (2000, 5321)	-0.17 (-0.51, 0.52)	485 (131, 1362)	-0.07 (-0.74, 1.61)
South Sudan	Male	8166 (4422, 12656)	-0.44 (-0.75, 0.11)	11520 (7003, 16934)	-0.02 (-0.60, 1.74)	4280 (2039, 7124)	0.16 (-0.62, 2.69)	678 (200, 1830)	-0.56 (-0.88, 0.34)
	Female	4996 (2854, 7854)	-0.42 (-0.72, 0.02)	6172 (3649, 8972)	-0.06 (-0.56, 1.42)	2359 (1194, 4110)	0.30 (-0.55, 2.55)	257 (61, 721)	-0.31 (-0.84, 2.07)
	Both	6627 (4331, 9476)	-0.44 (-0.67, -0.06)	8923 (5995, 11845)	-0.04 (-0.48, 1.03)	3347 (2127, 5053)	0.20 (-0.45, 1.58)	473 (192, 1119)	-0.52 (-0.81, 0.16)
Uganda	Male	6232 (3392, 9568)	-0.42 (-0.73, 0.35)	9639 (6076, 13997)	-0.44 (-0.69, 0.21)	3519 (1435, 6340)	-0.31 (-0.73, 0.84)	344 (115, 829)	-0.62 (-0.87, 0.54)
	Female	4682 (2872, 7183)	-0.46 (-0.72, 0.03)	6852 (4403, 9513)	-0.52 (-0.73, -0.08)	2514 (1388, 4373)	-0.37 (-0.68, 0.51)	198 (52, 529)	-0.71 (-0.91, 0.22)
	Both	5473 (3713, 7649)	-0.44 (-0.67, -0.02)	8273 (6128, 10996)	-0.48 (-0.66, -0.10)	3026 (1902, 4865)	-0.34 (-0.63, 0.25)	273 (123, 562)	-0.66 (-0.87, -0.04)
Tanzania	Male	5988 (2893, 9026)	-0.41 (-0.76, 0.21)	8050 (4647, 11683)	-0.43 (-0.68, 0.07)	3397 (1480, 5779)	-0.30 (-0.7, 0.65)	369 (149, 737)	-0.68 (-0.89, 0.19)
	Female	4827 (2695, 7512)	-0.40 (-0.71, 0.16)	6337 (3850, 9082)	-0.43 (-0.69, 0.02)	2473 (1368, 4234)	-0.29 (-0.65, 0.67)	213 (60, 536)	-0.66 (-0.89, 0.32)
	Both	5414 (3568, 7468)	-0.41 (-0.66, -0.02)	7204 (5063, 9585)	-0.43 (-0.62, -0.03)	2941 (1885, 4268)	-0.30 (-0.6, 0.32)	292 (150, 558)	-0.67 (-0.86, -0.20)
Zambia	Male	3782 (2019, 6088)	-0.45 (-0.76, 0.27)	8406 (5035, 12005)	-0.41 (-0.70, 0.10)	2884 (1351, 4848)	-0.15 (-0.66, 1.13)	307 (128, 532)	-0.71 (-0.91, -0.01)
	Female	3371 (1995, 5110)	-0.49 (-0.74, -0.07)	5220 (3229, 7249)	-0.52 (-0.73, -0.09)	1952 (1066, 3276)	-0.31 (-0.65, 0.62)	126 (34, 288)	-0.72 (-0.90, -0.17)
	Both	3578 (2362, 5101)	-0.47 (-0.70, -0.09)	6830 (5123, 8758)	-0.45 (-0.63, -0.14)	2423 (1510, 3682)	-0.22 (-0.61, 0.46)	218 (115, 360)	-0.71 (-0.87, -0.29)

The death rate from neonatal encephalopathy due to birth asphyxia and trauma was estimated to be 8330 deaths per 100,000 live births (95% UI: 6985, 9976), with 10,229 deaths per 100,000 male live births (95% UI: 7892, 12,814) and 6354 deaths per 100,000 female live births (95% UI: 4694, 8052). The lowest rate was estimated in Madagascar [3552 deaths per 100,000 live births (95% UI: 2101, 5539)]. The mortality rate declined by 42% (95% UI: -56, -16) in the region in 2023 compared to the rate in 1990. However, there was no statistically significant decline in the distribution of the rate in Burundi [-16% (95% UI: -49, 41)], Comoros [-34% (95% UI: -63, 18)], Djibouti [-22% (95% UI: -52, 33)], Eritrea [27% (95% UI: -57, 39)], Kenya [-32% (95% UI: -55, 3)], Madagascar [-29% (UI: -57, 12)], Somalia [-25% (95% UI: -54, 48)], and South Sudan [-4% (95% UI: -48, 103)] (Table 4).

There were 3133 deaths per 100,000 live births (95% CI: 2086, 4747) from neonatal sepsis and other neonatal infections, with 3785 deaths per 100,000 male live births (95% CI: 1760, 6102) and 2455 deaths per 100,000 female live births (95% CI: 1494, 3618). There was no statistically significant variation in the distribution of the rate by location in the region. Moreover, the mortality rate remains unchanged [-35% (95% UI: -62, 13)] in the region between 1990 and 2023. Only Mozambique had a statistically significant decline [62% decline (95% UI: -80, -31)] (Table 4).

Mortality from hemolytic disease and other neonatal jaundice was estimated to be 359 deaths per 100,000 live births (95% UI: 170, 675), with 481 deaths per 100,000 male live births (95% UI: 180, 1015) and 232 deaths per 100,000 female live births (95% UI: 58, 598). There was no statistically significant difference in the distribution of the rate by location. Between 1990 and 2023, the mortality rate declined by 67% (95% UI: -86, -19) in the region. No statistically significant decline was estimated in Burundi [-60% (95% UI: -87, 4)], Eritrea [-66% (95% UI: -88, 11)], Kenya [-57% (95% UI: -81, 8)], Somalia [-7% (95% UI: -74, 161)], and South Sudan [-52% (95% UI: -81, 16)] (Table 4).

Years of Life Lost From Neonatal Disorders

There were an estimated 1.9 million YLLs per 100,000 live births (95% UI: 1.8, 2.1) in the ESSA region in 2023, with 2.4 million YLLs per 100,000 male live births (95% UI: 2.2, 2.6) and 1.5 million YLLs per 100,000 female live births (95% UI: 1.4, 1.7). The highest rate was estimated in Burundi [2.4 million YLLs per 100,000 live births (95% UI: 2.2, 2.6)] and Ethiopia [2.6 million YLLs per 100,000 live births (95% UI: 2.4, 2.7)], whereas the lowest rate was in Eritrea [1.5 million YLLs per 100,000 live births (95% UI: 1.4, 1.7)], Kenya [1.3 million YLLs per 100,000 live births (95% UI: 1.3, 1.5)], Madagascar [1.5 million YLLs per 100,000 live births (95% UI: 1.3, 1.8)], and Zambia [1.5 million YLLs per 100,000 live births (95% UI: 1.2, 1.6)]. Between 1990 and 2023, the YLLs rate declined by 41% (95% UI: -45, -36) in the region. Mozambique had the highest decline in the region [52% decline (95% UI: -58, -47)], whereas Burundi [24% decline (95% UI: -31, -15)], Kenya [22% decline (95% UI: -80, -31)], and South Sudan [18% decline (95% UI: -28, -5)] experienced the lowest decline (Table 1).

There were an estimated 6.8 million YLLs per 100,000 live births (95% UI: 6.4, 7.2) among early neonates in the ESSA region in 2023. The highest rate was estimated in Burundi [8 million YLLs per 100,000 live births (95% UI: 7.5, 8.6)] and Ethiopia [8.5 million YLLs per 100,000 live births (95% UI: 7.9, 9.0)], whereas the lowest rate was in Eritrea [4.8 million YLLs per 100,000 live births (95% UI: 4.4, 5.2)], Kenya [4.9 million YLLs per 100,000 live births (95% UI: 4.5, 5.4)], Madagascar [5.7 million YLLs per 100,000 live births (95% UI: 5.0, 6.5)], and Zambia [5.2 million YLLs per 100,000 live births (95% UI: 4.6, 5.8)]. There was a 40% decline (95% UI: -44, -35) in the rate in the region between 1990 and 2023. The highest decline was estimated in Rwanda [52% decline (95% UI: -57, -46)], Mozambique [52% decline (95% UI: -56, -46)], and Malawi [49% decline (95% UI: -54, -43)], whereas the lowest decline was in Burundi [26% decline (95% UI: -34, -19)], Djibouti [28% decline (95% UI: -38, -17)], Kenya [22% decline (95% UI: -32, -9)], and South Sudan [22% decline (95% UI: -30, -9)] (Table 2).

Among late neonates, there were 326,816 YLLs per 100,000 live births (95% UI: 270,349, 369,873). Higher than the regional rate was estimated in Ethiopia [569,701 YLLs per 100,000 live births (95% UI: 466,837, 642,843)]. A lower-than-regional rate was estimated in Kenya [145,410 YLLs per 100,000 live births (95% UI: 120,812, 170,528)], Madagascar [142,042 YLLs per 100,000 live births (95% UI: 106,875, 1,822,220)], Uganda [207,013 YLLs per 100,000 live births (95% UI: 163,146, 258,305)], Tanzania [184,658 YLLs per 100,000 live births (95% UI: 137,252, 227,429)], and Zambia [193,918 YLLs per 100,000 live births (95% UI: 134,296, 246,151)]. Between 1990 and 2023, the YLLs rate declined by 44% (95% UI: -54, -31). The highest decline was estimated in Mozambique [57% decline (95% UI: -66, -42)]. However, the rate remained stable in Burundi [0 (95% UI: -28, 34)], Comoros [-25% (95% UI: -47, 9)], Djibouti [-8% (95% UI: -33, 33)], Eritrea [-13% (95% UI: -35, 30)], Kenya [-20% (95% UI: -38, 7)], Somalia [-1% (95% UI: -37, 66)], and South Sudan [21% (95% UI: -13, 76)] (Table 2).

Neonatal preterm birth accounted for 548,431 YLLs per 100,000 live births (95% UI: 440,209, 676,331), with 645,064 YLLs per 100,000 male live births (95% UI: 466,455, 851,162) and 447,902 YLLs per 100,000 female live births (95% UI: 332,486, 593,926). There was no statistically significant variation in the distribution of the rate by location. Moreover, the YLLs rate declined by 45% (95% UI: -63, -21) in the region in 2023 compared to the rate in 1990. However, there was no statistically significant decline in the rate in Djibouti [-34% (95% UI: -59, 4)], Kenya [-11% (95% UI: -45, 45)], and Somalia [-35% (95% UI: -61, 16)] (Table 5).

Table 5.

YLLs Rate From Neonatal Disorders by Location, Sex, and Type in the ESSA Region, 1990 to 2023

Location	Sex	Neonatal preterm birth	% of change	Neonatal encephalopathy due to birth asphyxia and trauma	% of change	Neonatal sepsis and other neonatal infections	% of change	Hemolytic disease and other neonatal jaundice	% of change
Location	Sex	2023	1990-2023	2023	1990-2023	2023	1990-2023	2023	1990-2023
ESSA region	Male	645064 (466455, 851162)	-0.42 (-0.65, 0.10)	920392 (710062, 1152972)	-0.39 (-0.60, -0.06)	340569 (158342, 548999)	-0.36 (-0.73, 0.60)	43297 (16197, 91366)	-0.69 (-0.89, -0.07)
	Female	447902 (332486, 593926)	-0.49 (-0.65, -0.22)	571744 (422303, 724503)	-0.46 (-0.65, -0.15)	220888 (134446, 325540)	-0.34 (-0.62, 0.45)	20843 (5234, 53774)	-0.63 (-0.88, 0.27)
	Both	548431 (440209, 676331)	-0.45 (-0.63, -0.21)	749512 (628449, 897620)	-0.42 (-0.56, -0.16)	281911 (187692, 427102)	-0.35 (-0.62, 0.13)	32292 (15279, 60701)	-0.67 (-0.86, -0.19)
Burundi	Male	653717 (325692, 1142781)	-0.48 (-0.76, 0.03)	1056778 (569240, 1637198)	-0.20 (-0.62, 0.64)	462189 (143642, 875575)	0.00 (-0.74, 1.64)	48613 (11609, 159253)	-0.66 (-0.89, 0.00)
	Female	545251 (261401, 897962)	-0.37 (-0.68, 0.11)	796405 (410998, 1268087)	-0.11 (-0.54, 0.65)	379277 (135549, 666264)	0.22 (-0.44, 1.69)	30801 (3224, 126828)	-0.47 (-0.89, 0.64)
	Both	600037 (379836, 889424)	-0.44 (-0.65, -0.08)	927919 (612266, 1331855)	-0.16 (-0.49, 0.41)	421156 (198704, 661510)	0.09 (-0.48, 0.94)	39798 (11218, 99184)	-0.60 (-0.87, 0.04)
Comoros	Male	674897 (396624, 1002187)	-0.48 (-0.73, 0.01)	742480 (419132, 1095510)	-0.31 (-0.69, 0.53)	331523 (151973, 565276)	-0.14 (-0.73, 1.41)	29596 (12214, 51800)	-0.76 (-0.93, -0.17)
	Female	519997 (322839, 771028)	-0.47 (-0.70, -0.09)	471060 (267235, 708545)	-0.37 (-0.71, 0.40)	218365 (120136, 353666)	-0.11 (-0.58, 1.04)	13645 (3556, 36381)	-0.72 (-0.90, -0.05)
	Both	599078 (415468, 812977)	-0.47 (-0.67, -0.17)	609629 (409108, 843690)	-0.34 (-0.63, 0.18)	276136 (163961, 431462)	-0.13 (-0.59, 0.68)	21789 (11120, 39880)	-0.75 (-0.90, -0.38)
Djibouti	Male	685466 (341341, 1127927)	-0.36 (-0.70, 0.20)	787920 (405383, 1222384)	-0.21 (-0.60, 0.68)	302392 (123855, 537891)	-0.09 (-0.66, 1.48)	40323 (17372, 74749)	-0.62 (-0.89, 0.27)
	Female	630696 (397452, 934069)	-0.31 (-0.60, 0.17)	555979 (268577, 884433)	-0.23 (-0.61, 0.47)	198481 (85565, 369517)	-0.08 (-0.53, 0.94)	17575 (6043, 36086)	-0.56 (-0.86, 0.28)
	Both	659319 (426615, 957353)	-0.34 (-0.59, 0.04)	677193 (419825, 1012365)	-0.22 (-0.52, 0.33)	252786 (143220, 425096)	-0.09 (-0.52, 0.69)	29463 (15537, 51705)	-0.61 (-0.83, -0.05)
Eritrea	Male	619358 (347046, 926805)	-0.45 (-0.73, 0.09)	721344 (422331, 1035262)	-0.28 (-0.65, 0.69)	308071 (148586, 511768)	-0.26 (-0.71, 1.24)	42243 (16560, 82238)	-0.68 (-0.91, 0.31)
	Female	329033 (211930, 503783)	-0.39 (-0.67, 0.18)	347949 (203050, 484104)	-0.25 (-0.62, 0.53)	150895 (83957, 236748)	-0.14 (-0.58, 1.10)	12855 (2918, 38283)	-0.58 (-0.86, 0.74)
	Both	478174 (319300, 651403)	-0.43 (-0.67, -0.05)	539764 (364668, 724007)	-0.27 (-0.57, 0.39)	231637 (134110, 361817)	-0.22 (-0.61, 0.63)	27952 (12594, 49871)	-0.66 (-0.88, 0.11)
Ethiopia	Male	912258 (643080, 1322725)	-0.38 (-0.68, 0.22)	1372880 (1023906, 1762562)	-0.38 (-0.62, 0.10)	460720 (236308, 731303)	-0.48 (-0.78, 0.62)	61140 (23917, 117228)	-0.74 (-0.92, 0.03)
	Female	460832 (305757, 637772)	-0.59 (-0.77, -0.27)	640674 (436870, 876366)	-0.52 (-0.71, -0.16)	231213 (134926, 369245)	-0.47 (-0.73, 0.50)	23232 (6411, 66068)	-0.62 (-0.90, 2.40)
	Both	692336 (512227, 928595)	-0.47 (-0.70, -0.19)	1016169 (810400, 1280151)	-0.43 (-0.58, -0.08)	348910 (213660, 510082)	-0.47 (-0.71, 0.04)	42672 (20176, 80165)	-0.72 (-0.88, -0.08)
Kenya	Male	449789 (261156, 673644)	-0.14 (-0.59, 0.79)	654132 (407029, 920585)	-0.31 (-0.63, 0.29)	168647 (73955, 303805)	-0.26 (-0.71, 0.82)	14867 (5529, 31376)	-0.57 (-0.85, 0.78)
	Female	401012 (265328, 561256)	-0.07 (-0.51, 0.65)	469568 (330211, 639380)	-0.34 (-0.60, 0.18)	116359 (66849, 193860)	-0.06 (-0.54, 1.22)	7547 (2478, 15478)	-0.57 (-0.84, 0.37)
	Both	425824 (300063, 573864)	-0.11 (-0.45, 0.45)	563453 (422525, 706978)	-0.32 (-0.55, 0.03)	142957 (90503, 223848)	-0.19 (-0.58, 0.47)	11271 (5455, 19701)	-0.57 (-0.81, 0.08)
Madagascar	Male	609954 (385679, 887158)	-0.52 (-0.72, -0.25)	341936 (176957, 658879)	-0.34 (-0.68, 0.27)	270450 (114650, 486611)	-0.08 (-0.68, 1.29)	35707 (10998, 104677)	-0.60 (-0.88, 0.00)
	Female	529133 (331504, 751312)	-0.43 (-0.68, -0.12)	296273 (154567, 499935)	-0.22 (-0.61, 0.43)	234497 (131937, 409757)	0.12 (-0.45, 1.58)	25524 (6142, 80102)	-0.40 (-0.80, 0.72)
	Both	570471 (401056, 765225)	-0.48 (-0.64, -0.29)	319628 (189039, 498367)	-0.29 (-0.57, 0.12)	252886 (151465, 399319)	0.00 (-0.48, 0.90)	30732 (12916, 63802)	-0.53 (-0.82, -0.02)
Malawi	Male	518354 (286815, 810513)	-0.61 (-0.82, -0.16)	829889 (465797, 1235364)	-0.45 (-0.72, 0.15)	376569 (130836, 689710)	-0.27 (-0.74, 0.98)	39169 (14110, 97437)	-0.70 (-0.92, 0.10)
	Female	390286 (215521, 636137)	-0.67 (-0.85, -0.41)	594683 (359669, 874528)	-0.54 (-0.76, -0.08)	271459 (129263, 429594)	-0.31 (-0.67, 0.68)	19863 (2927, 67341)	-0.72 (-0.91, -0.20)
	Both	455051 (288580, 643489)	-0.64 (-0.79, -0.41)	713628 (491161, 958945)	-0.49 (-0.68, -0.14)	324614 (163081, 525052)	-0.29 (-0.63, 0.29)	29626 (11873, 62274)	-0.71 (-0.89, -0.28)
Mozambique	Male	728747 (516015, 989607)	-0.33 (-0.63, 0.31)	1066521 (671425, 1403366)	-0.45 (-0.69, -0.04)	256932 (131156, 423565)	-0.59 (-0.84, -0.04)	56552 (17956, 155184)	-0.69 (-0.90, 0.01)
	Female	538882 (370576, 760508)	-0.51 (-0.71, -0.14)	743221 (451840, 1001803)	-0.53 (-0.74, -0.15)	180002 (108219, 283851)	-0.64 (-0.82, -0.16)	24405 (4142, 81916)	-0.80 (-0.93, -0.38)
	Both	634968 (478076, 811447)	-0.42 (-0.62, -0.06)	906835 (618169, 1120057)	-0.48 (-0.68, -0.22)	218934 (148518, 311363)	-0.62 (-0.80, -0.31)	40674 (16357, 91711)	-0.74 (-0.90, -0.37)
Rwanda	Male	502870 (268809, 830465)	-0.65 (-0.84, -0.27)	752771 (420063, 1187877)	-0.47 (-0.75, 0.22)	310435 (116334, 559120)	-0.39 (-0.81, 0.82)	27920 (10670, 59187)	-0.83 (-0.95, -0.47)
	Female	400298 (216248, 638695)	-0.63 (-0.81, -0.27)	612736 (353525, 957172)	-0.47 (-0.74, 0.05)	296329 (157292, 474082)	-0.27 (-0.64, 0.64)	22465 (4432, 54499)	-0.72 (-0.92, 0.00)
	Both	452465 (294156, 655885)	-0.64 (-0.80, -0.40)	683957 (460420, 963993)	-0.47 (-0.69, -0.06)	303504 (178929, 469248)	-0.33 (-0.65, 0.23)	25239 (10900, 48158)	-0.80 (-0.92, -0.54)
Somalia	Male	482668 (265342, 744202)	-0.36 (-0.69, 0.42)	630010 (368412, 871066)	-0.26 (-0.61, 0.86)	361905 (140265, 627065)	-0.19 (-0.64, 1.23)	55602 (12476, 179760)	0.08 (-0.74, 2.38)
	Female	454983 (261870, 689987)	-0.34 (-0.65, 0.35)	408090 (250160, 578874)	-0.22 (-0.58, 0.79)	242000 (89094, 420412)	-0.13 (-0.56, 1.19)	30772 (3698, 130614)	-0.26 (-0.78, 3.21)
	Both	469312 (323268, 671957)	-0.35 (-0.61, 0.16)	522947 (371992, 664614)	-0.25 (-0.54, 0.48)	304058 (179959, 478715)	-0.17 (-0.51, 0.52)	43623 (11747, 122575)	-0.07 (-0.74, 1.61)
South Sudan	Male	734751 (397884, 1138749)	-0.44 (-0.75, 0.11)	1036536 (630075, 1523631)	-0.02 (-0.60, 1.74)	385113 (183431, 640970)	0.16 (-0.62, 2.69)	60963 (18016, 164640)	-0.56 (-0.88, 0.34)
	Female	449494 (256763, 706692)	-0.42 (-0.72, 0.02)	555356 (328349, 807253)	-0.06 (-0.56, 1.42)	212208 (107407, 369758)	0.30 (-0.55, 2.55)	23138 (5467, 64893)	-0.31 (-0.84, 2.07)
	Both	596236 (389676, 852598)	-0.44 (-0.67, -0.06)	802886 (539415, 1065749)	-0.04 (-0.48, 1.03)	301154 (191343, 454615)	0.20 (-0.45, 1.58)	42596 (17255, 100678)	-0.52 (-0.81, 0.16)
Uganda	Male	560763 (305222, 860856)	-0.42 (-0.73, 0.35)	867237 (546710, 1259415)	-0.44 (-0.69, 0.21)	316607 (129158, 570421)	-0.31 (-0.73, 0.84)	30964 (10344, 74617)	-0.62 (-0.87, 0.54)
	Female	421303 (258446, 646262)	-0.46 (-0.72, 0.03)	616499 (396125, 855912)	-0.52 (-0.73, -0.08)	226174 (124893, 393489)	-0.37 (-0.68, 0.51)	17857 (4636, 47584)	-0.71 (-0.91, 0.22)
	Both	492443 (334065, 688183)	-0.44 (-0.67, -0.02)	744404 (551411, 989326)	-0.48 (-0.66, -0.10)	272305 (171109, 437754)	-0.34 (-0.63, 0.25)	24543 (11085, 50541)	-0.66 (-0.87, -0.04)
Tanzania	Male	538785 (260293, 812112)	-0.41 (-0.76, 0.21)	724346 (418122, 1051166)	-0.43 (-0.68, 0.07)	305669 (133193, 519941)	-0.30 (-0.70, 0.65)	33183 (13412, 66326)	-0.68 (-0.89, 0.19)
	Female	434301 (242479, 675860)	-0.40 (-0.71, 0.16)	570201 (346377, 817131)	-0.43 (-0.69, 0.02)	222523 (123097, 380978)	-0.29 (-0.65, 0.67)	19126 (5381, 48219)	-0.66 (-0.89, 0.32)
	Both	487169 (321041, 671920)	-0.41 (-0.66, -0.02)	648196 (455572, 862377)	-0.43 (-0.62, -0.03)	264593 (169592, 384056)	-0.30 (-0.60, 0.32)	26238 (13521, 50207)	-0.67 (-0.86, -0.20)
Zambia	Male	340262 (181683, 547760)	-0.45 (-0.76, 0.27)	756331 (452984, 1080190)	-0.41 (-0.70, 0.10)	259495 (121523, 436239)	-0.15 (-0.66, 1.13)	27654 (11533, 47841)	-0.71 (-0.91, -0.01)
	Female	303298 (179494, 459750)	-0.49 (-0.74, -0.07)	469638 (290487, 652266)	-0.52 (-0.73, -0.09)	175644 (95950, 294802)	-0.31 (-0.65, 0.62)	11314 (3064, 25950)	-0.72 (-0.90, -0.17)
	Both	321974 (212508, 458957)	-0.47 (-0.7, -0.09)	614487 (460928, 788041)	-0.45 (-0.63, -0.14)	218009 (135891, 331281)	-0.22 (-0.61, 0.46)	19570 (10371, 32401)	-0.71 (-0.87, -0.29)

There were 749,512 YLLs rate per 100,000 live births (95% UI: 628,449, 897,620) from neonatal encephalopathy due to birth asphyxia and trauma, with 920,392 YLLs per 100,000 male live births (95% UI: 710,062, 1,152,972) and 571,744 YLLs per 100,000 female live births (95% UI: 422,303, 724,503). There was no statistically significant difference in the distribution of the rate by location. Between 1990 and 2023, the YLLs rate declined by 42% (95% UI: -56, -16) in the region. However, the rate remains unchanged in Burundi [-16% (-49, 41)], Comoros [-34% (95% UI: -63, 18)], Djibouti [-22% (95% UI: -52, 33)], Eritrea [-27% (95% UI: -57, 39)], Kenya [-32% (95% UI: -55, 3)], Madagascar [-29% (95% UI: -57, 12)], Somalia [-25% (95% UI: -54, 48)], and South Sudan [-4% (95% UI: -48, 103)] (Table 5).

Neonatal sepsis and other neonatal infections accounted for 281,911 YLLs per 100,000 live births (95% UI: 187,692, 427,102), with 340,569 YLLs per 100,000 male live births (95% UI: 158,342, 548,999) and 220,888 YLLs per 100,000 female live births (95% UI: 134,446, 325,540). There was no statistically significant variation in the distribution of the rate by location. Moreover, the rate remained stable [-35% (95% UI: -62, 13)] throughout the region between 1990 and 2023. Only Mozambique had a significant decline in the rate [62% decline (95% UI: -80%, -31%)] (Table 5).

There were an estimated 32,292 YLLs per 100,000 live births (95% UI: 15,279, 60,701) from hemolytic disease and other neonatal jaundice, with 43,297 YLLs per 100,000 male live births (95% UI: 16,197, 91,366) and 20,843 YLLs per 100,000 female live births (95% UI: 5234, 53,774). There was no statistically significant difference in the distribution of the rate by location. The rate declined by 67% (95% UI: -86, -19) in the region in 2023 compared to the rate in 1990. However, Burundi [-60% (95% UI: -0.87, 4)], Eritrea [-66% (95% UI: -88, 11)], Kenya [-57% (95% UI: -81, 8)], Somalia [-7% (95% UI: -74, 161)], and South Sudan [-52% (95% UI: -81, 16)] did not exhibit a statistically significant decline in the rate between 1990 and 2023 (Table 5).

Discussion

This study aimed to estimate the incidence, mortality, and YLLs from neonatal disorders in the ESSA region from 1990 to 2023. The study revealed that there were an estimated 300,042 new cases per 100,000 live births (95% UI: 293,808, 305,567), 21,889 deaths per 100,000 live births (95% UI: 20,447, 22,993), and 1.9 million YLLs per 100,000 live births (95% UI: 1.8, 2.1) in the region in 2023. Early neonates were disproportionately affected by neonatal disorders compared to late neonates. Neonatal preterm birth, neonatal encephalopathy due to birth asphyxia and trauma, neonatal sepsis and other neonatal infections, and hemolytic disease and other neonatal jaundice were the leading neonatal disorders in the region. In most countries, males had higher estimates of neonatal disorders compared to females. Significant inter-country variations were estimated in the overall rates across the region. However, there were no statistically significant differences in the distribution of mortality and YLLs rates by types of neonatal disorders. Between 1990 and 2023, there was considerable decline in the rates.

The estimated incidence rate of neonatal disorders in the ESSA region was considerably high and signals widespread challenges in neonatal health, necessitating a re-evaluation of current preventive and care strategies across the region. The finding aligns with previous evidence demonstrating a high burden of neonatal disorders in the region.^1,12 This markedly higher incidence may be attributed to a confluence of factors, including prevalent socioeconomic challenges, higher burden of neonatal infections, limited access to and utilization of maternal and newborn care, lower educational attainment, insufficient awareness of pregnancy danger signs, and deficiencies in antenatal care services throughout the region.^13-15 The incidence rate demonstrated a marked variation across the region, with Somalia, South Sudan, Comoros, and Mozambique exhibiting rates significantly higher than the regional average. This can be attributed to a confluence of factors such as prolonged political instability, conflict, and severe socioeconomic challenges, which critically undermine the development and functionality of robust health systems.^16,17 These may lead to limited access to quality antenatal care, a scarcity of skilled birth attendants, inadequate emergency obstetric services, poor infrastructure for early postnatal care, and insufficient basic neonatal care units.¹⁸ These findings reveal the presence of a significant challenge to the achievement of Sustainable Development Goal (SDG) 3.2, which aims to reduce neonatal mortality to at least as low as 12 deaths per 1,000 live births.¹⁹ This implies the need for a highly targeted approach and intensified investments in maternal and neonatal health programs.

Conversely, countries like Rwanda, Kenya, Burundi, and Djibouti showed notably lower incidence rates, with Rwanda demonstrating the lowest at 208,504 new cases per 100,000 live births. This success can be justified by their greater focus on strengthening primary healthcare, expanding community health worker programs, and improving access to essential maternal and newborn health interventions.^20,21 The success of these countries may offer valuable lessons, so their strategies for health system strengthening, community engagement and policy implementation can be studied and adapted by other nations in the region. Additionally, there was significant sex disparity, with male neonates experiencing a much higher incidence rate of neonatal disorders compared to female neonates. This biological vulnerability of male infants to various neonatal conditions, including prematurity, respiratory distress syndrome, and infections, is well-documented in literature and is often attributed to developmental and immunological differences.²²

Neonatal preterm birth was the leading neonatal disorder in the region, followed by neonatal sepsis and other neonatal infections. This finding aligns with previous studies that consistently identified preterm birth as the leading neonatal disorder with the highest incidence rate.^1,14,23 Likewise, it has been estimated to account for over 40% of neonatal deaths in sub-Saharan Africa, underscoring its disproportionate contribution to the neonatal mortality burden in the region.²⁴ This implies the critical need to prioritize the prevention and management of premature birth within any strategy aimed at reducing neonatal disorders.

The incidence rate of neonatal disorders estimated among early neonates was significantly higher than that of late neonates. This finding is consistent with previous studies showing that the first week of life is the most vulnerable period for neonatal morbidity and complications.²⁵ This indicates the fragility of newborns immediately after birth and during their initial adaptation to extra-uterine life, highlighting the crucial importance of high-quality care in the first week.²⁶

The estimated neonatal death rate in the ESSA region (21,889 deaths per 100,000 neonates) was notably high and significantly off-track from SDG target 3.2, which aims to reduce neonatal mortality to at least as low as 12 deaths per 1,000 live births by 2030.¹⁹ Although the estimated mortality rate exceeds global averages, it remains consistent with existing evidence characterizing the region as a high-burden setting.^1,27 The elevated rate in the region may be attributed to the high prevalence of prematurity, low rates of health facility deliveries, poor access to skilled birth attendants, insufficient neonatal intensive care units, and inadequate antenatal care follow-up.^28,29 Consistent with the incidence of neonatal disorders, there was a notable gender disparity in mortality, with higher male neonatal deaths compared to females. This aligns with the findings of previous studies.^3,30 This underscores the presence of specific biological or socio-economic vulnerabilities that disproportionately affect male neonates.³¹ Furthermore, there were variations in neonatal mortality rates across the region, with Ethiopia and Burundi exhibiting significantly higher rates than the regional average; that may be because the countries are likely struggling with weaker primary health infrastructure, low-quality service delivery, and greater socio-economic barriers to neonatal care.^32,33 Conversely, Eritrea, Kenya, and Zambia showed comparatively lower rates, although these figures are still extremely high when measured against global best practices and the SDG target.³⁴ This points out the presence of inequalities in access to quality maternal and neonatal healthcare, health infrastructure, and socio-economic determinants across the region.^35,36

There was a significantly higher death rate from neonatal disorders among early neonates when compared to late neonates. This is consistent with previous findings, as the early neonatal period is recognized as the most vulnerable time for newborns, and the vast majority of neonatal deaths occur within the first 24-48 hours and certainly within the first week.^37,38 Especially birth asphyxia, prematurity, and low birth weight significantly contribute to the death of early neonates in low-income countries.³⁹

Even though the global and regional decline of death from neonatal encephalopathy due to birth asphyxia and trauma was reported in previous studies,^40-42 this study demonstrated that the disorder is still the leading cause of mortality in the region, followed by neonatal preterm birth. Consistent with this finding, it was previously reported as the leading cause of premature death and disability among neonates, especially in low-income settings.^42-44 Achieving universal coverage of obstetric care, good supportive post-partum care and neonatal resuscitation is thus crucial, as these interventions are pivotal in averting a significant number of deaths and disabilities from the disorder.⁴⁵

The estimated 1.9 million YLLs per 100,000 neonates across the ESSA region are alarmingly high, illustrating that millions of potential future contributions, workforces, and innovations are lost at the very beginning of life. This finding aligns with previous studies showing that neonatal disorders remain among the leading causes of YLLs, particularly in low-resource settings.^12,46 Consistent with incidence and death rate, there is a significant and concerning gender disparity regarding YLLs. A significantly higher burden of YLLs was estimated among male neonates compared to females, emphasizing the need for sex-specific strategies in neonatal health initiatives and targeted public health interventions that address sex-specific vulnerabilities. Like incidence and mortality rates, the YLLs rate was also not uniform, with stark variations in YLLs across countries within the ESSA region, with Ethiopia and Burundi bearing the heaviest burden. Conversely, Kenya, Eritrea, Madagascar, and Zambia showed comparatively lower YLLs rates. While still representing a massive loss of life, these rates, relative to other countries in the region, suggest slightly stronger health interventions.^47,48 This inter-country disparity means that the path to achieving SDG 3.2 is highly uneven, demanding a concerted effort that channels resources and expertise to where the YLLs burden is highest, while simultaneously accelerating progress across all nations to prevent these early losses of potential life.

The finding of this study revealed that early neonates experienced higher YLLs when compared to late neonates, highlighting the profound vulnerability of newborns immediately post-birth. This burden is predominantly driven by acute, time-sensitive conditions directly linked to labor, delivery, and immediate physiological adaptation, such as birth asphyxia, severe prematurity complications, and early-onset sepsis.³⁹ While mortality may persist into the later neonatal period, the most acutely lethal events are concentrated in the first week, leading to a disproportionate loss of potential life years during this initial critical period.³⁷

Neonatal encephalopathy due to birth asphyxia and trauma constituted the leading cause of YLLs in the region, followed closely by neonatal preterm birth, which aligns with the observed patterns of neonatal mortality from these disorders. Studies have consistently shown that neonatal encephalopathy due to birth asphyxia and birth traumas remain among the leading contributors to neonatal deaths and YLLs.^41,44 This disproportionate burden of YLLs highlights that these conditions are not only common but also result in deaths occurring at very early ages, thus maximizing the loss of potential life years. This necessitates a strategic and targeted response focusing on the universal provision of high-quality maternal and neonatal service delivery, particularly strengthening intrapartum care to avert birth-related complications, alongside comprehensive interventions for managing prematurity.^19,37

There was considerable decline in the estimates of incidence, mortality, and YLLs from neonatal disorders across the ESSA region between 1990 and 2023. These findings are consistent with previous studies reporting a downward trend of the burden of neonatal disorders in resource-limited settings.^1,27 The estimated percentage decline is promising and indicates the visible improvement in maternal and child health care in the region over the years.^21,49 However, substantial disparities were estimated across countries. Djibouti and South Sudan experienced no significant decline in the incidence rates, while South Sudan, Kenya, and Burundi had the lowest reductions in mortality and YLLs rates, likely due to weak health systems, conflict, poverty, and limited access to quality maternal and neonatal care.^50-54 In contrast, Mozambique, Rwanda, and Ethiopia showed greater decline, possibly reflecting stronger maternal and child health interventions and healthcare system improvements.^55-57 Overall, the findings highlight that there is still a need to strengthen equitable maternal and newborn healthcare services.

The findings on incidence, mortality, and YLLs of neonatal disorders in the ESSA region presented an undeniable call to action. Achieving SDG 3.2 by 2030 will necessitate transformation of health policy, grounded in primary prevention, resilient health systems, equity, and substantial investment.⁵⁸ The consistent male predominance in the incidence, mortality, and YLLs from neonatal disorders highlights the need for sex-specific interventions and strategies in neonatal health initiatives. Despite decades of effort, causes of neonatal disorders have not been sufficiently addressed.^58,59 The overwhelming burden, evidenced by high incidence of preventable disorders, devastating mortality rates, and millions of years of life prematurely lost, demands immediate policy attention. Policies must therefore prioritize robust primary prevention strategies to reduce the occurrence of neonatal disorders, rather than solely focusing on treatment.⁶⁰ These include improving antenatal care, promoting skilled facility-based deliveries, expanding postnatal care services, strengthening infection prevention and control measures, neonatal resuscitation programs, access to antenatal corticosteroids, and Kangaroo Mother Care.^59,61,62 Moreover, valuable lessons in health system strengthening, community engagement, and policy implementation should be adapted from countries with comparatively lower incidence, YLLs, or mortality rates. Policies should facilitate sharing these strategies while critically adapting them to local contexts.⁶³

This study has some limitations. Although our study includes a range of neonatal disorders, it lacks detailed information regarding modifiable risk factors critical for designing targeted preventive interventions.¹ The estimates are derived from the GBD study and depend on the underlying modeling assumptions as well as the availability data across countries in the region.^64,65 In countries with limited surveillance and incomplete health information systems, the estimates may be subject to greater uncertainty. Weak health information systems may also result in underreporting and misclassification of neonatal disorders and deaths, potentially leading to underestimation or inaccurate characterization of the burden and trends of neonatal disorders.^64,66,67 Although the models are invaluable, they inherently introduce a degree of uncertainty and may be biased by the quality and representativeness of underlying data.^1,64 Future studies are also recommended to track the progress in reducing the burden of neonatal disorders in the region.

Conclusion

The ESSA region experienced considerably high incidence rates, mortality rates, and YLLs from neonatal disorders in 2023, which collectively represent a critical public health concern. These estimated measures are not uniformly distributed, exhibiting significant inter-country variation, as well as distinct disparities by gender and across the critical early and late neonatal periods, highlighting sex-specific and localized challenges in newborn health. Moreover, there was a remarkable decline in the incidence, mortality, and YLLs from the disorders throughout the region from 1990 to 2023. Consequently, comprehensive and transformative interventions and strategies are essential. These efforts should prioritize robust primary prevention and quality maternal and newborn health services and implement targeted actions that address both specific disorders and identified gender and geographical disparities across the region. Interventions, particularly in high-burden countries, should focus on preventing preterm birth, strengthening neonatal infection prevention and control efforts, and improving the availability and quality of essential newborn care.

Footnotes

Acknowledgements

The authors would like to thank the Institute for Health Metrics and Evaluation for coordinating the GBD 2023 study.

ORCID iDs

Bekam Yambo Jofa

Gelgelo Wodessa

Teshome Gensa

Abera Mersha

Maleda Tefera

Haymanot Mezmur

Abadi Kidanemariam Berhe

Yemane Berhane Tesfau

Embaba Tekelaye Welesemayat

Boko Loka Safayi

Miesa Gelchu

Anteneh Fikrie Tekola

Ethical Considerations

The study used secondary data from the GBD 2023 study. Not applicable.

Author Contributions

ST conceived and designed the study. ST, BYJ, TG, BK, AM, AG, MT, HM, AKB, YBT, ETW, BLS, BNB, KL, MG, and AFT were involved in the analysis and interpretation of the findings. ST acted as a guarantor. All authors have approved the final version of the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

All data relevant to the study are included in the article. The GBD 2023 data are publicly available at: .

Patient and Public Involvement

It was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research.

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