Datasets:

electricsheepafrica
/

africa-synth-neonatal-birth-outcomes-comoros

id int64 1 10k	sex stringclasses 2 values	gestational_age_weeks float64 24.1 42	birth_weight_g int64 590 4.97k	head_circumference_cm float64 18 42	maternal_age_years int64 14 47	parity int64 0 14	delivery_mode stringclasses 2 values	apgar_1min int64 0 10	apgar_5min int64 0 10	temperature_c float64 34.2 39.5	heart_rate_bpm int64 61 192	respiratory_rate_bpm int64 27 100	spo2_percent int64 73 100	bw_category stringclasses 5 values	preterm_category stringclasses 4 values	primary_outcome stringclasses 6 values
1	F	35.4	2,690	26.6	24	2	vaginal	6	3	37.2	154	53	97	Normal_BW	Late_preterm	healthy
2	M	37.1	2,830	38.5	15	0	vaginal	4	4	36.9	93	44	83	Normal_BW	Term	birth_asphyxia
3	F	37.1	2,600	36.3	27	1	vaginal	10	8	36.8	120	51	94	Normal_BW	Term	healthy
4	F	39.3	3,280	34.9	31	4	vaginal	9	7	37.1	141	54	95	Normal_BW	Term	healthy
5	M	38.5	3,540	42	27	0	vaginal	8	9	37	157	49	99	Normal_BW	Term	healthy
6	F	38.5	2,990	27.2	14	0	vaginal	7	6	36.9	123	49	96	Normal_BW	Term	healthy
7	F	35.9	2,680	36.7	32	4	vaginal	7	7	37.2	123	40	96	Normal_BW	Late_preterm	healthy
8	F	39.2	2,970	27.7	22	1	vaginal	7	6	36.6	147	47	97	Normal_BW	Term	healthy
9	M	34.4	2,210	42	32	4	caesarean	8	6	35.2	143	51	98	LBW	Late_preterm	healthy
10	M	37.8	2,470	26.6	15	1	vaginal	8	7	36.5	154	45	95	LBW	Term	healthy
11	M	41.4	3,650	42	26	5	vaginal	10	10	36.8	128	46	98	Normal_BW	Term	healthy
12	F	39.7	2,980	32	26	6	vaginal	7	6	37	137	51	98	Normal_BW	Term	healthy
13	F	39.2	2,600	27.8	37	9	vaginal	7	8	36.1	145	50	96	Normal_BW	Term	healthy
14	F	40.8	2,420	34.4	26	0	vaginal	7	9	36.9	138	51	94	LBW	Term	low_birth_weight_term
15	M	34.5	2,440	20.8	18	1	caesarean	9	7	36.4	145	39	98	LBW	Late_preterm	healthy
16	M	38.8	3,420	25.5	30	2	vaginal	9	9	37.2	151	51	97	Normal_BW	Term	healthy
17	F	37.4	1,990	42	21	1	vaginal	9	8	36.3	146	38	97	LBW	Term	low_birth_weight_term
18	M	38.9	3,580	39.3	24	4	vaginal	8	9	36.7	151	46	95	Normal_BW	Term	healthy
19	F	38.1	3,460	42	31	5	vaginal	9	10	37	140	60	100	Normal_BW	Term	healthy
20	F	37.6	2,790	28.9	17	0	vaginal	7	6	35.2	120	51	95	Normal_BW	Term	neonatal_sepsis
21	F	36.3	2,890	39.7	27	3	vaginal	4	3	36.6	137	50	96	Normal_BW	Late_preterm	healthy
22	M	38.8	2,910	36.1	36	6	vaginal	9	9	37	132	43	98	Normal_BW	Term	healthy
23	F	37.8	2,400	26.5	33	6	vaginal	9	9	37.3	111	57	97	LBW	Term	healthy
24	F	36.9	2,370	42	21	2	vaginal	9	9	36.7	143	50	97	LBW	Late_preterm	healthy
25	F	37.4	3,380	19.5	28	4	vaginal	1	3	36.9	135	34	83	Normal_BW	Term	birth_asphyxia
26	M	39.9	3,160	35.9	29	2	vaginal	8	7	37.2	132	44	95	Normal_BW	Term	healthy
27	M	31.9	2,320	35.6	19	4	vaginal	3	4	36.5	157	68	94	LBW	Very_preterm	preterm_complications
28	M	37.5	2,750	37.1	19	0	vaginal	9	10	37.3	130	47	96	Normal_BW	Term	healthy
29	M	35.2	1,770	28.2	27	4	vaginal	7	6	38.8	145	54	100	LBW	Late_preterm	neonatal_sepsis
30	F	39.4	3,190	27.9	31	3	vaginal	8	10	36.9	154	41	95	Normal_BW	Term	healthy
31	F	41.9	2,810	38.4	27	4	vaginal	10	7	37	152	49	96	Normal_BW	Term	healthy
32	F	38.3	3,010	26.5	18	0	vaginal	8	10	37.2	140	44	97	Normal_BW	Term	healthy
33	M	40.1	3,620	42	23	1	vaginal	9	10	37.1	155	49	96	Normal_BW	Term	healthy
34	M	36.5	3,230	35.8	25	1	vaginal	6	7	37.2	132	45	96	Normal_BW	Late_preterm	healthy
35	M	39.2	3,730	33.1	26	1	vaginal	9	10	36.7	129	48	97	Normal_BW	Term	healthy
36	M	36.8	2,920	34.9	24	1	caesarean	9	9	37.3	151	57	100	Normal_BW	Late_preterm	healthy
37	M	40.6	3,320	40.6	26	2	vaginal	8	10	36.8	164	39	96	Normal_BW	Term	healthy
38	M	35.8	2,560	42	27	3	vaginal	7	8	37.2	141	60	95	Normal_BW	Late_preterm	healthy
39	M	37.3	3,040	38	20	2	vaginal	9	10	36.9	151	69	98	Normal_BW	Term	healthy
40	F	36.1	2,520	34.7	32	1	vaginal	7	9	36.7	137	45	96	Normal_BW	Late_preterm	healthy
41	M	36.9	2,780	42	23	2	vaginal	6	8	36.3	147	56	95	Normal_BW	Late_preterm	healthy
42	F	39.1	2,720	20	21	2	vaginal	7	7	36.8	163	53	98	Normal_BW	Term	healthy
43	F	39.6	3,420	29	21	0	vaginal	8	10	36.5	130	53	98	Normal_BW	Term	healthy
44	M	38.1	3,160	32.9	29	4	vaginal	9	9	36.6	137	43	96	Normal_BW	Term	healthy
45	F	37.6	2,560	24.8	31	3	vaginal	9	8	37.1	149	42	94	Normal_BW	Term	healthy
46	F	36.4	3,080	40.1	29	3	vaginal	6	8	36.4	148	45	98	Normal_BW	Late_preterm	healthy
47	M	41.2	3,540	35.7	34	5	caesarean	9	9	37.3	140	45	96	Normal_BW	Term	healthy
48	M	39.5	2,400	23.7	22	2	vaginal	8	9	36.8	140	41	97	LBW	Term	low_birth_weight_term
49	F	40.5	3,660	22.3	25	3	vaginal	9	10	37.3	137	43	97	Normal_BW	Term	healthy
50	M	35.5	2,340	32.8	21	0	vaginal	5	8	37	145	54	98	LBW	Late_preterm	healthy
51	M	32.5	1,900	37.2	24	1	caesarean	5	6	37.8	112	57	89	LBW	Late_preterm	birth_asphyxia
52	M	40.8	3,350	36.2	36	6	vaginal	8	9	36.8	119	43	99	Normal_BW	Term	healthy
53	F	40.2	3,590	42	18	0	caesarean	9	10	37	152	63	98	Normal_BW	Term	healthy
54	F	39.4	3,100	32.4	24	0	vaginal	8	10	36.8	125	39	94	Normal_BW	Term	healthy
55	F	36.5	2,360	27	39	5	vaginal	6	6	38.2	146	41	96	LBW	Late_preterm	neonatal_sepsis
56	F	37.4	2,240	42	28	2	vaginal	9	7	35.4	144	37	97	LBW	Term	healthy
57	M	37.7	2,590	37.4	19	1	vaginal	8	9	37	148	37	96	Normal_BW	Term	healthy
58	F	27.6	1,020	38.7	25	5	vaginal	2	4	35.3	143	76	97	VLBW	Extremely_preterm	preterm_complications
59	M	39.2	2,950	42	30	4	vaginal	9	10	36.8	150	45	98	Normal_BW	Term	healthy
60	M	24.7	790	19.5	27	2	caesarean	8	9	36.7	141	70	80	ELBW	Extremely_preterm	respiratory_distress
61	F	38.7	2,180	28.2	28	1	vaginal	7	7	37.2	143	46	96	LBW	Term	low_birth_weight_term
62	M	37.3	2,620	41.2	23	3	vaginal	9	10	36.9	153	40	97	Normal_BW	Term	healthy
63	F	37.5	2,550	25.3	25	0	vaginal	8	10	37.1	116	37	96	Normal_BW	Term	healthy
64	F	36.6	2,660	28.2	24	0	vaginal	6	6	36.8	139	34	98	Normal_BW	Late_preterm	healthy
65	F	40.8	2,430	18	32	8	vaginal	7	9	36.9	124	46	98	LBW	Term	healthy
66	F	39	3,450	32.7	23	0	vaginal	9	10	36.6	146	50	98	Normal_BW	Term	healthy
67	F	37	2,750	42	32	4	vaginal	8	10	36.8	132	42	98	Normal_BW	Term	healthy
68	M	36.4	2,750	33.7	16	0	vaginal	7	8	37.1	139	34	99	Normal_BW	Late_preterm	healthy
69	M	36.4	2,540	18	16	0	vaginal	2	8	37.4	150	53	98	Normal_BW	Late_preterm	healthy
70	M	40.4	3,670	42	24	2	vaginal	9	9	36.5	138	54	98	Normal_BW	Term	healthy
71	M	34.4	1,780	25.6	30	2	vaginal	6	6	36.9	95	39	88	LBW	Late_preterm	birth_asphyxia
72	M	36.9	3,230	34.2	28	2	vaginal	7	6	36.9	132	40	96	Normal_BW	Late_preterm	healthy
73	F	38.9	2,400	37.5	33	3	vaginal	8	8	36	148	52	100	LBW	Term	healthy
74	M	36.4	2,740	42	39	13	vaginal	8	8	36.8	152	35	98	Normal_BW	Late_preterm	healthy
75	M	36.6	2,770	38.2	18	0	vaginal	9	8	36.8	123	39	96	Normal_BW	Late_preterm	healthy
76	M	36.7	2,880	32.2	25	2	vaginal	9	7	37	153	56	97	Normal_BW	Late_preterm	healthy
77	M	39.1	3,750	34.7	14	0	caesarean	7	9	36.7	156	44	96	Normal_BW	Term	healthy
78	F	39.5	2,610	27.4	32	6	vaginal	10	8	36.7	128	47	98	Normal_BW	Term	healthy
79	F	39.8	2,630	24.1	20	0	vaginal	9	10	36.9	152	40	97	Normal_BW	Term	healthy
80	F	38.2	1,950	30.8	27	2	vaginal	5	9	36.6	144	54	95	LBW	Term	low_birth_weight_term
81	F	39	2,080	42	22	5	vaginal	4	9	36.9	151	47	98	LBW	Term	low_birth_weight_term
82	M	35.1	3,200	21.9	16	0	vaginal	5	7	37.3	168	53	96	Normal_BW	Late_preterm	healthy
83	F	38.6	3,350	20.8	14	0	vaginal	9	10	37	141	44	94	Normal_BW	Term	healthy
84	M	38.5	3,310	36.3	17	1	vaginal	8	9	36.6	148	40	98	Normal_BW	Term	healthy
85	M	41.3	3,790	42	19	0	vaginal	9	10	37.4	135	46	95	Normal_BW	Term	healthy
86	M	35	2,860	25.8	22	2	caesarean	7	5	36.7	136	42	96	Normal_BW	Late_preterm	healthy
87	F	39.6	2,920	24.6	20	0	vaginal	9	10	37.4	117	44	97	Normal_BW	Term	healthy
88	M	38.4	2,970	38.2	32	3	caesarean	9	9	36.9	143	42	97	Normal_BW	Term	healthy
89	M	37.8	2,260	35.9	32	7	vaginal	4	9	36.8	129	39	96	LBW	Term	low_birth_weight_term
90	M	36.3	2,530	42	34	3	vaginal	8	8	36.8	126	52	98	Normal_BW	Late_preterm	healthy
91	M	37.7	2,650	42	19	0	vaginal	8	8	37.3	140	50	98	Normal_BW	Term	healthy
92	F	35.7	2,570	19.7	15	0	caesarean	3	5	36.8	120	41	84	Normal_BW	Late_preterm	birth_asphyxia
93	M	38.8	3,310	24.4	34	9	vaginal	9	10	37.2	170	58	97	Normal_BW	Term	healthy
94	M	40.8	3,800	18	23	1	vaginal	9	10	36.9	132	42	97	Normal_BW	Term	healthy
95	M	38.3	2,620	36.4	26	1	vaginal	7	8	36.9	157	52	99	Normal_BW	Term	healthy
96	F	38.6	2,930	26.3	16	0	vaginal	7	10	37.1	139	31	97	Normal_BW	Term	healthy
97	M	37.4	2,900	42	32	5	vaginal	9	7	36.9	113	45	94	Normal_BW	Term	healthy
98	M	41.7	2,900	30.4	15	0	vaginal	9	10	36.7	150	36	100	Normal_BW	Term	healthy
99	M	35.7	2,740	29.6	21	0	vaginal	7	8	36.7	141	42	97	Normal_BW	Late_preterm	healthy
100	F	39.3	3,070	27.3	29	7	vaginal	9	9	37.1	132	49	97	Normal_BW	Term	healthy

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⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.

Synthetic Neonatal Birth Outcomes & Vital Signs Dataset (0–28 days)

Abstract

This dataset provides 30,000 synthetic neonatal records (10,000 per scenario) representing live-born neonates in low- and middle-income country (LMIC) facility settings. Each record contains 15 clinically relevant variables including gestational age, birth weight, Apgar scores, vital signs (temperature, heart rate, respiratory rate, SpO2), head circumference, maternal demographics, and delivery mode. All distributions are parameterized from peer-reviewed epidemiological literature, WHO/UNICEF normative standards, and Intergrowth-21st reference curves. Three burden scenarios (low, moderate, high) reflect the spectrum of neonatal health contexts encountered across LMICs. The dataset is designed for training and benchmarking machine learning models for neonatal risk prediction, triage, and outcome classification, where real patient data is unavailable or restricted.

1. Introduction

Neonatal mortality accounts for approximately 47% of all under-five deaths globally, with 98% occurring in low- and middle-income countries (Lawn et al., 2014). Birth asphyxia, prematurity-related complications, and neonatal sepsis are the three leading causes. Despite this burden, open-access tabular datasets of neonatal clinical data from LMIC contexts are virtually nonexistent due to ethical constraints, fragmented health information systems, and data governance barriers.

This synthetic dataset addresses this gap by generating realistic neonatal records grounded in published epidemiological evidence. It is intended for:

Training ML models for neonatal outcome prediction
Benchmarking classification algorithms on realistic class distributions
Educational use in global health and clinical data science curricula
Prototyping clinical decision support tools for neonatal care

This dataset is entirely synthetic. It must not be used for clinical decision-making.

2. Methodology

2.1 Target Population

Live-born neonates (0–28 days of life) presenting at facility-based delivery settings in LMICs. The age range corresponds to the WHO neonatal period definition.

2.2 Causal Structure (DAG)

Variables are sampled following a directed acyclic graph that respects clinical causal relationships:

Sex, Maternal Age (roots)
    → Parity (conditional on maternal age)
    → Primary Outcome (from scenario prevalence)
        → Gestational Age (conditional on outcome)
            → Birth Weight (conditional on GA, sex, outcome)
            → Head Circumference (conditional on GA, sex)
        → Apgar Scores (conditional on outcome, GA)
        → Vital Signs: Temp, HR, RR, SpO2 (conditional on outcome, GA, BW)
    → Delivery Mode (conditional on outcome, GA, scenario)
    → Classifications (derived from measurements)

2.3 Epidemiological Parameterization

All distributions are grounded in the following primary sources:

Parameter	Value	Source
Global preterm rate	10.6% (range 5–18%)	Blencowe et al., Lancet 2012
LBW prevalence (LMIC)	14.6% global; up to 28% South Asia	UNICEF/WHO Low Birthweight Estimates 2019
Birth asphyxia incidence	2–8% of facility births	WHO Basic Newborn Resuscitation 2012
Neonatal sepsis incidence	1–6% depending on setting	Lawn et al., Lancet 2014
Birth weight by GA	Intergrowth-21st reference curves	Intergrowth-21st Consortium, Lancet 2014
Sex ratio at birth	1.05:1 (M:F)	WHO Global Health Observatory
C-section rates (LMIC)	3–25% by setting	DHS Program, multiple countries

Birth weight and head circumference are generated via cubic spline interpolation of Intergrowth-21st reference curves, with sex-specific offsets (~130g for BW, ~0.6cm for HC).

2.4 Scenario Design

Scenario	Context	Healthy	Preterm Comp.	Asphyxia	Sepsis	RDS	LBW Term	C-section
Low burden	Urban LMIC facility	88.6%	3.1%	2.5%	1.5%	0.7%	3.5%	19.1%
Moderate burden	District hospital	80.0%	4.8%	4.2%	3.5%	2.6%	4.9%	13.7%
High burden	Under-resourced/conflict	70.0%	6.7%	7.1%	5.1%	4.0%	7.0%	7.4%

2.5 Generation Process

Outcome-first sampling: Primary outcome assigned from scenario-specific prevalence to ensure epidemiological fidelity
Conditional GA sampling: Gestational age sampled from outcome-specific truncated normal distributions (e.g., preterm complications → GA 24–36.9 weeks)
Spline-interpolated anthropometry: Birth weight and head circumference derived from Intergrowth-21st reference curves via cubic spline interpolation, with sex offsets and outcome-specific z-score shifts
Outcome-conditional vitals: Apgar scores (scaled Beta distribution), temperature, HR, RR, SpO2 all conditioned on primary outcome and GA
Biological clipping: All values constrained to physiologically possible ranges

3. Dataset Description

3.1 Schema

Column	Type	Units	Range	Description
id	int	—	1–10000	Unique identifier
sex	categorical	—	M, F	Biological sex at birth
gestational_age_weeks	float	weeks	24.0–42.0	Gestational age at delivery
birth_weight_g	int	grams	400–5500	Birth weight
head_circumference_cm	float	cm	18.0–42.0	Head circumference at birth
maternal_age_years	int	years	14–48	Maternal age at delivery
parity	int	—	0–14	Number of previous deliveries
delivery_mode	categorical	—	vaginal, caesarean	Mode of delivery
apgar_1min	int	score	0–10	Apgar score at 1 minute
apgar_5min	int	score	0–10	Apgar score at 5 minutes
temperature_c	float	°C	32.0–41.0	Axillary temperature
heart_rate_bpm	int	bpm	80–200	Heart rate
respiratory_rate_bpm	int	breaths/min	15–110	Respiratory rate
spo2_percent	int	%	40–100	Peripheral oxygen saturation
bw_category	categorical	—	ELBW, VLBW, LBW, Normal_BW, Macrosomia	WHO birth weight classification
preterm_category	categorical	—	Extremely_preterm, Very_preterm, Late_preterm, Term, Post_term	WHO preterm classification
primary_outcome	categorical	—	6 classes	Primary neonatal outcome

3.2 Classification Criteria

Classification	Criteria	Source
ELBW	Birth weight < 1000g	WHO ICD-10 P07.0
VLBW	Birth weight 1000–1499g	WHO ICD-10 P07.1
LBW	Birth weight 1500–2499g	WHO/UNICEF
Extremely preterm	GA < 28 weeks	WHO Born Too Soon 2012
Very preterm	GA 28–31 weeks	WHO Born Too Soon 2012
Late preterm	GA 32–36 weeks	WHO Born Too Soon 2012

3.3 Primary Outcome Categories

Outcome	Description
healthy	No significant complications
preterm_complications	Prematurity-related complications (apnoea, feeding difficulty, hypothermia)
birth_asphyxia	Perinatal asphyxia (failure to establish breathing at birth)
neonatal_sepsis	Early or late-onset neonatal sepsis
respiratory_distress	Respiratory distress syndrome or transient tachypnoea
low_birth_weight_term	Term neonate with low birth weight (small for gestational age)

4. Validation

4.1 Prevalence Fidelity

Cross-scenario monotonicity confirmed: all adverse outcome rates increase from low → moderate → high burden, consistent with epidemiological expectations.

4.2 Key Statistics (Moderate Burden)

Metric	Observed	Literature Target	Source
LBW rate	25.9%	15–28%	UNICEF/WHO 2019
Preterm rate	29.6%	12–18% overall	Blencowe 2012
Asphyxia rate	4.2%	3–5%	WHO 2012
Sepsis rate	3.5%	2–4%	Lawn 2014
C-section rate	13.7%	8–15%	DHS
Mean birth weight	2845g	2800–3100g	Intergrowth-21st
GA-BW correlation	~0.85	0.80–0.90	Clinical expectation

4.3 Diagnostic Plots

Validation Report

5. Usage

5.1 Loading with HuggingFace `datasets`

from datasets import load_dataset

# Load default (moderate burden) configuration
dataset = load_dataset("electricsheepafrica/synthetic-neonatal-birth-outcomes-vitals-WHO-0-28days", "moderate_burden")

# Load high burden scenario
high = load_dataset("electricsheepafrica/synthetic-neonatal-birth-outcomes-vitals-WHO-0-28days", "high_burden")

# Access as pandas DataFrame
df = dataset["train"].to_pandas()

5.2 Loading directly from CSV

import pandas as pd

df = pd.read_csv("data/neonatal_moderate_burden.csv")
asphyxia = df[df['primary_outcome'] == 'birth_asphyxia']
print(f"Asphyxia prevalence: {len(asphyxia)/len(df)*100:.1f}%")
print(f"Mean Apgar-1 in asphyxia: {asphyxia['apgar_1min'].mean():.1f}")

5.3 Regenerating with custom parameters

pip install numpy pandas scipy matplotlib
python generate_dataset.py --all-scenarios --n 10000 --seed 42
python validate_dataset.py

6. Limitations & Ethical Considerations

Synthetic data: All records are computationally generated. No real patient data was used. The dataset must NOT be used for clinical decision-making.
Simplified causal structure: Real neonatal outcomes involve complex interactions (e.g., maternal HIV, malaria in pregnancy, intrapartum events) not fully modelled here.
LMIC focus: Distributions are parameterized for LMIC facility contexts and may not represent high-income country populations.
No longitudinal component: Each record is a snapshot at birth; neonatal trajectory (e.g., NICU course) is not modelled.
Outcome exclusivity: Each neonate has one primary outcome; in reality, comorbidities are common (e.g., preterm + sepsis).
Missing data: No missing values are simulated; real clinical datasets have substantial missingness.

7. References

Blencowe H, et al. (2012). National, regional, and worldwide estimates of preterm birth rates in 2010. Lancet, 379(9832):2162-2172.
UNICEF/WHO (2019). UNICEF-WHO Low Birthweight Estimates. New York.
Lee AC, et al. (2013). National and regional estimates of term and preterm babies born small for gestational age. Lancet Global Health, 1(1):e26-36.
WHO (2012). Guidelines on Basic Newborn Resuscitation. Geneva.
Lawn JE, et al. (2014). Every Newborn: progress, priorities, and potential beyond survival. Lancet, 384(9938):189-205.
Mwaniki MK, et al. (2012). Long-term neurodevelopmental outcomes after intrauterine and neonatal insults. Lancet, 379(9814):445-452.
WHO (2022). Born Too Soon: Decade of Action on Preterm Birth. Geneva.
Intergrowth-21st Consortium (2014). International standards for newborn weight, length, and head circumference. Lancet, 384(9946):857-868.
Demographic and Health Surveys (DHS) Program. Maternal and newborn health indicators, multiple countries 2015-2023.
WHO (2015). Pregnancy, Childbirth, Postpartum and Newborn Care: A guide for essential practice (3rd ed). Geneva.

Citation

If you use this dataset in your research, please cite:

@dataset{esa_neonatal_2025,
  title={Synthetic Neonatal Birth Outcomes and Vital Signs Dataset (0-28 days)},
  author={Electric Sheep Africa},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/electricsheepafrica/synthetic-neonatal-birth-outcomes-vitals-WHO-0-28days}
}

License

This dataset is released under the Creative Commons Attribution 4.0 International (CC-BY-4.0) license.

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