Datasets:

electricsheepafrica
/

laboratory-workforce-training

id int64	age int64	sex string	facility_level string	location string	cadre string	qualified_for_role int64	highest_qualification string	years_experience int64	registered_professional_body int64	cpd_last_year int64	cpd_hours_year int64	slmta_trained int64	biosafety_trained int64	eqa_trained int64	competency_assessed int64	position_filled int64	supervision_regular int64	workload_manageable int64	salary_adequate int64	salary_on_time int64	housing_provided int64	transport_allowance int64	intend_to_stay_5yr int64	emigration_intention int64	transfer_request int64	job_satisfaction_score int64	mentorship_available int64	career_pathway_clear int64	promotion_last_5yr int64	tests_per_day int64	overtime_hours_week int64	year int64
1	41	male	private	rural	lab_technologist	0	certificate	24	0	1	15	0	0	0	0	1	1	0	1	0	0	0	1	0	0	3	0	0	1	98	3	2,022
2	33	male	district	peri_urban	lab_technologist	1	certificate	7	0	0	0	0	0	0	0	1	0	0	0	1	0	0	1	0	0	5	0	0	0	58	1	2,019
3	29	male	health_centre	rural	lab_assistant	0	certificate	4	0	1	14	0	0	0	1	0	0	0	0	0	0	0	1	0	0	3	1	0	0	63	4	2,020
4	42	male	district	peri_urban	lab_assistant	0	degree	4	0	0	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0	4	0	0	0	82	7	2,021
5	38	female	health_centre	urban	lab_technician	1	certificate	7	1	1	40	0	0	0	0	1	1	0	0	0	0	1	1	0	0	4	0	0	0	53	2	2,021
6	36	female	private	urban	lab_technician	1	certificate	2	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	1	0	3	0	0	0	63	5	2,023
7	39	female	private	remote	lab_technician	0	certificate	22	0	0	0	1	0	0	0	0	1	0	1	1	0	0	1	0	0	3	0	1	1	161	0	2,022
8	20	female	health_centre	rural	lab_technologist	0	certificate	13	0	1	4	0	0	0	0	1	0	0	0	1	0	0	1	1	0	9	0	0	0	38	21	2,019
9	50	female	health_centre	urban	lab_technician	0	on_job_training	16	0	0	0	0	0	0	0	1	1	1	0	0	0	1	1	0	0	4	0	0	0	118	1	2,020
10	36	male	national_reference	urban	lab_technologist	1	certificate	2	1	0	0	0	0	0	1	0	1	1	0	0	0	1	1	0	0	1	0	1	0	33	1	2,023
11	26	female	health_centre	rural	lab_assistant	1	certificate	1	0	0	0	0	0	0	1	1	0	1	0	0	0	0	0	1	0	5	0	0	0	191	10	2,023
12	35	female	district	rural	lab_technologist	0	on_job_training	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	1	4	0	0	0	93	10	2,023
13	54	female	private	urban	lab_technologist	1	certificate	1	0	0	0	0	0	0	0	1	0	1	1	0	0	0	1	0	0	2	0	0	0	80	5	2,022
14	46	male	private	rural	lab_technologist	0	certificate	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	1	0	2	0	1	0	104	1	2,020
15	39	male	private	rural	lab_scientist	1	degree	7	0	0	0	0	1	0	0	1	0	0	1	1	1	0	0	0	0	2	0	0	0	119	5	2,022
16	41	female	national_reference	remote	lab_assistant	1	degree	5	0	0	0	0	0	0	1	1	0	0	0	0	0	1	1	0	0	8	0	0	0	52	5	2,022
17	41	male	district	rural	lab_technician	1	certificate	2	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	3	0	0	0	52	3	2,019
18	44	female	regional	urban	lab_technician	1	diploma	5	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	1	0	95	1	2,020
19	46	female	health_centre	remote	other	1	certificate	5	1	0	0	0	0	0	1	1	1	1	0	0	0	0	1	1	0	4	0	0	0	88	1	2,022
20	44	female	district	rural	phlebotomist	0	on_job_training	10	0	0	0	0	0	0	1	1	0	0	1	0	1	1	0	0	0	1	1	0	0	87	7	2,022
21	50	female	private	rural	other	0	on_job_training	0	0	0	0	0	0	0	0	1	0	0	0	0	1	1	0	0	0	4	0	0	0	151	11	2,023
22	43	female	national_reference	peri_urban	lab_scientist	1	certificate	4	0	0	0	0	0	1	1	1	0	1	0	0	0	1	1	0	0	6	0	0	0	286	3	2,022
23	34	male	private	urban	lab_technologist	0	certificate	12	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	1	0	1	0	87	1	2,021
24	21	female	health_centre	urban	phlebotomist	1	diploma	23	0	0	0	0	0	0	1	1	1	0	0	0	0	0	0	0	0	5	0	0	0	62	17	2,020
25	45	male	health_centre	remote	lab_technician	0	degree	59	0	1	22	1	0	0	0	0	1	0	1	0	0	0	1	0	1	5	0	1	0	43	1	2,021
26	34	female	district	peri_urban	lab_technologist	0	certificate	5	0	0	0	0	1	0	0	0	1	1	0	1	0	0	1	1	0	1	0	0	0	31	0	2,023
27	55	male	health_centre	remote	lab_technologist	0	certificate	6	0	0	0	0	0	0	0	1	1	0	0	1	1	0	1	1	0	7	0	0	0	157	0	2,020
28	27	male	health_centre	remote	lab_scientist	1	on_job_training	1	1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	2	0	0	0	152	5	2,023
29	25	male	health_centre	urban	lab_assistant	0	certificate	1	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	4	0	0	0	97	1	2,019
30	34	female	health_centre	urban	lab_technologist	0	degree	15	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	4	0	0	0	30	1	2,019
31	37	female	district	urban	lab_technologist	0	certificate	7	0	1	5	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	22	3	2,022
32	32	male	district	urban	phlebotomist	0	certificate	4	0	0	0	0	0	0	1	1	1	0	1	1	0	0	1	0	0	5	0	0	0	164	3	2,020
33	20	male	private	remote	lab_assistant	0	certificate	2	0	0	0	0	1	0	0	1	0	1	0	1	0	1	1	0	0	4	0	0	0	94	7	2,021
34	42	female	district	urban	lab_technician	0	certificate	3	0	0	0	0	0	0	0	0	0	0	1	0	0	1	1	0	0	4	0	0	0	138	2	2,022
35	42	female	district	urban	lab_assistant	0	degree	5	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	4	0	0	0	65	0	2,020
36	41	female	health_centre	rural	lab_scientist	0	diploma	9	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	3	0	0	0	62	0	2,021
37	37	female	district	remote	phlebotomist	0	certificate	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	4	0	0	0	63	4	2,020
38	37	male	health_centre	remote	lab_technologist	0	diploma	4	0	0	0	0	1	0	0	1	0	1	1	0	0	0	0	1	0	5	0	0	0	119	3	2,023
39	50	male	health_centre	remote	lab_technician	0	certificate	1	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	1	0	4	1	1	1	54	8	2,019
40	35	female	regional	urban	phlebotomist	0	diploma	14	0	1	23	0	0	0	0	1	0	0	0	1	0	0	1	1	0	3	0	0	0	129	0	2,022
41	44	male	private	remote	phlebotomist	1	diploma	22	1	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	4	0	0	0	53	0	2,019
42	24	female	health_centre	urban	phlebotomist	0	certificate	27	0	1	1	0	0	0	1	0	1	0	1	1	0	0	1	0	0	2	0	0	0	62	21	2,023
43	20	male	regional	rural	lab_technologist	0	certificate	13	0	0	0	0	1	0	0	1	0	0	1	0	0	0	0	0	0	2	0	0	0	173	1	2,022
44	54	male	district	rural	phlebotomist	0	certificate	2	0	0	0	0	0	0	0	1	0	0	1	1	0	0	1	0	0	3	0	0	0	107	0	2,023
45	34	female	health_centre	urban	lab_scientist	0	certificate	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	1	0	0	1	0	0	0	57	5	2,022
46	38	male	regional	remote	lab_technician	1	on_job_training	3	1	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0	0	36	2	2,020
47	20	male	private	peri_urban	lab_assistant	0	degree	6	0	0	0	0	0	0	1	1	0	0	1	0	0	0	0	1	0	5	0	1	1	208	1	2,022
48	32	female	district	peri_urban	lab_scientist	0	diploma	0	0	0	0	0	1	0	0	1	0	0	0	1	0	0	1	0	0	4	0	0	0	68	9	2,021
49	38	male	regional	rural	lab_technician	0	certificate	0	0	1	2	0	0	0	0	1	1	1	1	1	1	0	0	0	0	5	0	0	0	150	3	2,019
50	60	male	private	peri_urban	lab_assistant	0	diploma	8	0	0	0	0	0	0	0	0	0	1	1	0	0	0	1	0	0	1	0	0	0	95	14	2,020
51	36	male	private	peri_urban	phlebotomist	0	degree	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	4	0	0	0	33	0	2,020
52	37	female	private	urban	lab_technologist	0	diploma	2	0	0	0	0	0	0	0	0	0	0	1	1	0	0	1	0	0	1	1	0	0	45	7	2,021
53	32	male	district	urban	lab_technician	0	diploma	9	0	0	0	0	1	0	0	1	1	0	0	0	0	0	0	0	0	1	0	0	0	137	0	2,019
54	20	female	district	rural	lab_technician	0	diploma	7	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	1	0	2	0	0	0	58	0	2,020
55	46	male	private	urban	lab_assistant	0	diploma	2	0	0	0	0	0	0	0	1	0	0	0	1	0	1	1	0	0	4	0	0	0	56	4	2,022
56	20	male	regional	peri_urban	lab_technician	0	certificate	7	0	0	0	0	0	0	1	1	0	1	0	1	0	0	1	1	0	4	0	0	0	70	1	2,020
57	31	male	district	remote	lab_technician	1	diploma	8	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	4	0	0	0	23	0	2,020
58	38	female	health_centre	peri_urban	lab_assistant	0	diploma	9	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	4	0	0	0	76	4	2,023
59	42	female	district	rural	lab_assistant	0	degree	9	0	0	0	0	0	1	0	1	1	0	0	1	0	0	0	0	0	1	0	0	0	33	0	2,023
60	33	female	health_centre	rural	lab_technician	0	certificate	0	0	0	0	0	0	0	1	1	0	0	0	1	0	1	1	1	0	6	0	0	0	82	8	2,023
61	37	female	health_centre	peri_urban	lab_technician	0	diploma	10	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	2	0	0	0	188	3	2,022
62	38	female	health_centre	rural	lab_scientist	0	certificate	3	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	5	0	0	0	112	4	2,023
63	22	male	district	urban	lab_scientist	0	certificate	5	0	1	5	0	0	0	0	1	0	0	0	1	0	0	1	0	0	5	0	0	0	79	1	2,022
64	44	female	health_centre	rural	phlebotomist	0	diploma	8	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	0	1	0	37	2	2,020
65	38	female	national_reference	peri_urban	lab_technologist	0	diploma	1	0	1	19	1	0	0	0	1	0	1	0	0	0	1	1	0	0	3	0	0	0	58	2	2,023
66	20	male	district	peri_urban	lab_technologist	1	diploma	3	1	0	0	0	0	0	0	1	1	0	0	1	0	1	1	0	0	4	0	0	0	136	1	2,019
67	44	female	national_reference	rural	other	0	on_job_training	12	0	1	11	0	0	0	0	0	0	1	0	0	0	0	1	0	0	5	0	0	0	51	1	2,020
68	54	male	private	urban	lab_assistant	0	diploma	8	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	5	0	0	0	86	1	2,020
69	35	female	national_reference	urban	lab_technologist	1	diploma	3	1	1	17	0	0	0	1	0	0	0	0	0	0	0	1	1	0	4	0	0	0	97	8	2,019
70	47	female	district	rural	lab_assistant	0	on_job_training	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	1	0	4	0	1	0	101	4	2,023
71	39	female	private	peri_urban	lab_technologist	0	certificate	21	0	0	0	0	0	1	0	0	0	1	0	1	0	0	1	0	0	2	0	0	0	102	0	2,021
72	49	male	health_centre	urban	lab_assistant	0	certificate	3	0	0	0	0	0	0	0	1	1	0	1	0	0	0	1	1	0	1	0	1	0	42	2	2,021
73	20	male	regional	urban	lab_technologist	0	on_job_training	8	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	7	0	1	0	117	3	2,023
74	52	female	regional	urban	lab_technician	1	diploma	0	1	0	0	0	0	0	0	1	0	0	0	0	0	1	1	0	0	4	0	0	0	66	47	2,020
75	40	male	health_centre	rural	lab_technologist	0	diploma	4	0	0	0	1	0	0	1	1	0	0	1	0	0	0	1	0	0	2	0	1	0	106	4	2,021
76	44	male	regional	remote	other	1	diploma	17	1	1	15	0	0	1	1	1	0	0	1	0	0	0	1	0	0	5	0	1	0	81	3	2,020
77	36	female	district	peri_urban	lab_technician	0	certificate	0	0	0	0	0	0	0	1	1	0	0	0	1	0	0	1	0	0	3	0	0	0	54	2	2,023
78	27	male	health_centre	urban	phlebotomist	0	certificate	8	0	0	0	0	0	0	0	1	1	0	0	0	0	0	1	1	0	2	0	1	1	143	11	2,023
79	44	female	district	peri_urban	lab_technician	0	certificate	25	0	0	0	1	0	0	0	0	1	0	0	0	0	1	1	0	0	5	0	0	0	205	1	2,021
80	50	male	health_centre	urban	lab_technician	0	on_job_training	6	0	0	0	1	0	1	0	0	0	1	0	0	0	1	1	1	0	2	0	0	0	62	4	2,022
81	50	male	health_centre	urban	lab_technician	0	certificate	9	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	1	0	5	0	0	0	78	0	2,023
82	65	male	health_centre	urban	lab_assistant	0	diploma	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	1	0	0	4	0	0	0	48	4	2,022
83	63	male	district	rural	lab_scientist	0	diploma	3	0	0	0	1	0	0	1	1	0	0	0	0	0	0	0	0	0	5	0	0	0	113	6	2,022
84	29	female	national_reference	peri_urban	lab_assistant	0	certificate	6	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	0	1	0	0	0	58	6	2,023
85	20	female	district	urban	lab_technologist	1	diploma	16	0	0	0	0	0	0	0	1	0	1	0	0	0	0	1	0	0	4	0	0	0	120	8	2,019
86	33	female	health_centre	urban	lab_scientist	0	on_job_training	10	0	0	0	0	0	0	1	0	0	1	0	0	0	0	1	0	0	5	0	0	0	94	15	2,023
87	38	female	health_centre	rural	lab_scientist	0	certificate	17	0	0	0	1	0	0	0	1	1	0	0	0	1	0	1	0	0	3	0	0	0	105	2	2,021
88	42	female	health_centre	rural	lab_technician	0	certificate	0	0	1	27	0	1	0	0	1	0	0	0	0	1	0	1	0	1	5	1	0	0	61	2	2,021
89	40	female	health_centre	urban	lab_technician	0	degree	4	0	0	0	0	0	0	0	1	1	1	0	1	0	0	1	0	0	3	0	0	0	28	2	2,023
90	52	female	private	remote	lab_technologist	0	certificate	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	4	0	0	0	161	3	2,022
91	29	female	district	remote	lab_assistant	0	on_job_training	1	0	0	0	0	0	0	0	1	1	0	0	0	1	0	1	0	0	3	0	0	0	127	5	2,022
92	31	female	private	urban	lab_assistant	1	certificate	5	0	0	0	0	0	0	0	1	0	1	0	1	0	0	0	0	0	5	0	0	0	164	9	2,020
93	32	female	private	urban	lab_technologist	1	on_job_training	1	0	0	0	1	0	0	0	1	0	1	0	0	0	1	1	0	0	3	0	0	0	63	6	2,020
94	41	female	health_centre	urban	phlebotomist	1	certificate	8	0	0	0	0	0	1	1	1	0	1	0	0	0	0	0	0	0	4	0	0	0	45	0	2,023
95	40	female	health_centre	remote	lab_technologist	0	on_job_training	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	3	0	1	0	41	8	2,022
96	37	male	health_centre	rural	other	0	degree	8	0	1	9	0	0	0	1	0	0	0	1	1	0	0	1	0	0	4	0	1	0	35	2	2,021
97	32	female	health_centre	urban	lab_technician	0	certificate	9	0	0	0	0	0	0	1	1	0	0	0	1	0	0	1	1	0	4	0	0	0	63	3	2,023
98	30	female	district	rural	lab_technician	0	certificate	0	0	1	23	0	0	0	0	0	0	0	1	1	1	0	1	0	0	4	0	1	0	116	5	2,020
99	40	female	regional	urban	lab_technologist	0	certificate	7	0	0	0	1	0	0	0	1	0	0	1	0	0	0	0	0	0	5	0	0	0	60	4	2,022
100	47	male	district	remote	lab_scientist	0	on_job_training	0	0	1	21	1	0	0	0	1	0	0	0	0	0	0	1	0	1	1	1	0	0	61	1	2,020

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Laboratory Workforce & Training

Abstract

Synthetic dataset modeling laboratory workforce across three SSA scenarios. Captures cadre mix, qualifications, CPD, supervision, working conditions, salary, job satisfaction, emigration intention, retention, and career pathways. Parameterized from SSA lab workforce research.

Parameterization Evidence

Parameter	Value	Source	Year
SSA lab professionals	0.9 per 10,000 pop	Nkengasong et al. Lancet	2018
Brain drain	20-40% emigration	Nkengasong et al.	2018
Workforce gap	>140,000 needed	WHO	2021
Rural vacancy rates	20-40%	WHO	2021

Validation

Usage

from datasets import load_dataset
ds = load_dataset("electricsheepafrica/laboratory-workforce-training", name="shortage_workforce")
df = ds['train'].to_pandas()

References

Nkengasong JN et al. (2018). Laboratory medicine Africa. Lancet. DOI: 10.1016/S0140-6736(18)30625-8
Schroeder LF & Amukele T (2014). Medical labs SSA. Clin Chem. DOI: 10.1373/clinchem.2013.217141
WHO (2021). Health workforce statistics

License

CC-BY-4.0

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Size of downloaded dataset files:

3.42 MB

Size of the auto-converted Parquet files:

722 kB

Number of rows:

30,000