Datasets:

electricsheepafrica
/

africa-synth-climate-wildfire-smoke-respiratory-all

record_id string	scenario string	year int64	month int64	in_fire_season int64	age int64	sex string	setting string	is_child_u5 int64	is_elderly_60plus int64	pre_existing_asthma int64	pre_existing_copd int64	smoker int64	pm25_smoke_ugm3 float64	pm25_total_ugm3 float64	aqi_category string	fire_proximity_km float64	smoke_days_per_season int64	fire_count int64	mask_use int64	stayed_indoors int64	vulnerability_index float64	exposure_risk_score float64	cough int64	wheeze int64	dyspnoea int64	eye_irritation int64	ari_episode int64	asthma_exacerbation int64	er_visit int64	climate_fire_trend float64
FOR-00000	forest_clearing_burn	2,014	11	0	29	male	peri_urban	0	0	1	0	0	28.3	40	moderate	14.7	26	3	0	0	0.3	0.08	0	0	0	0	0	1	0	0.0632
FOR-00001	forest_clearing_burn	2,021	8	1	62	female	peri_urban	0	1	0	0	0	300.8	319.6	hazardous	0.5	76	1	0	0	0.35	0.746	0	0	0	0	0	0	0	0.1
FOR-00002	forest_clearing_burn	2,015	5	0	29	male	rural	0	0	1	0	0	27.1	38.2	moderate	4.8	31	6	0	0	0.3	0.076	0	0	0	0	0	1	0	0.0782
FOR-00003	forest_clearing_burn	2,022	12	0	19	male	urban	0	0	0	0	0	18.3	33.7	good	3.9	19	1	0	0	0.15	0.034	0	0	0	0	0	0	0	0.1
FOR-00004	forest_clearing_burn	2,015	8	1	48	male	rural	0	0	0	0	0	208.8	231.1	very_unhealthy	9.4	46	3	0	1	0.15	0.139	1	0	0	1	0	0	0	0.0847
FOR-00005	forest_clearing_burn	2,020	12	0	34	female	rural	0	0	0	0	0	5	22.4	good	9.1	24	5	0	0	0.15	0.022	0	0	0	0	0	0	0	0.1
FOR-00006	forest_clearing_burn	2,014	11	0	40	female	peri_urban	0	0	0	0	0	18.9	26.4	good	8.3	16	2	0	0	0.15	0.026	0	0	0	0	0	0	0	0.0592
FOR-00007	forest_clearing_burn	2,021	5	0	14	male	urban	0	0	0	0	0	20.5	44	moderate	9.3	10	1	0	0	0.15	0.044	0	0	0	0	0	0	0	0.1
FOR-00008	forest_clearing_burn	2,015	12	0	29	female	rural	0	0	1	0	0	38.8	52.2	moderate	14.7	18	3	0	0	0.3	0.104	0	0	0	0	0	0	0	0.0747
FOR-00009	forest_clearing_burn	2,013	1	0	54	female	rural	0	0	0	0	0	27.8	46.1	moderate	3.1	9	0	0	0	0.15	0.046	0	0	0	0	0	0	0	0.0474
FOR-00010	forest_clearing_burn	2,020	4	0	41	female	rural	0	0	0	0	0	27.2	56.2	unhealthy	8.6	16	1	0	0	0.15	0.056	0	0	0	0	0	0	0	0.1
FOR-00011	forest_clearing_burn	2,023	1	0	49	male	peri_urban	0	0	0	1	0	13.7	25.6	good	12.7	17	1	0	0	0.3	0.051	1	0	1	0	0	0	0	0.1
FOR-00012	forest_clearing_burn	2,011	3	0	7	female	rural	0	0	0	0	0	32.1	48.6	moderate	11.5	22	1	0	0	0.15	0.049	1	0	0	0	0	0	0	0.0164
FOR-00013	forest_clearing_burn	2,010	4	0	37	male	rural	0	0	0	0	1	7.6	20.9	good	18.4	17	0	0	0	0.25	0.035	0	0	1	0	0	0	0	0.0027
FOR-00014	forest_clearing_burn	2,012	6	1	54	female	rural	0	0	0	0	0	34.3	50.8	moderate	5	98	2	0	0	0.15	0.051	0	0	0	0	0	0	0	0.0337
FOR-00015	forest_clearing_burn	2,022	11	0	18	male	rural	0	0	0	0	0	21	40.5	moderate	0.5	15	2	1	0	0.15	0.028	0	0	0	0	1	0	1	0.1
FOR-00016	forest_clearing_burn	2,022	4	0	40	male	peri_urban	0	0	0	0	1	5	14.7	good	12	7	2	0	0	0.25	0.024	0	0	0	0	0	0	0	0.1
FOR-00017	forest_clearing_burn	2,011	8	1	23	male	peri_urban	0	0	1	0	0	20	38.1	moderate	7.7	120	1	0	0	0.3	0.076	0	0	0	0	0	0	0	0.0133
FOR-00018	forest_clearing_burn	2,023	5	0	74	female	rural	0	1	0	0	0	27.4	49.2	moderate	0.5	12	1	0	0	0.35	0.115	0	1	0	0	0	0	0	0.1
FOR-00019	forest_clearing_burn	2,020	10	0	11	female	peri_urban	0	0	0	0	0	22.5	46	moderate	8.8	5	3	0	0	0.15	0.046	0	0	0	0	0	0	0	0.1
FOR-00020	forest_clearing_burn	2,020	11	0	29	female	rural	0	0	0	0	0	28.8	49.7	moderate	7.5	10	3	0	0	0.15	0.05	1	1	0	0	0	0	0	0.1
FOR-00021	forest_clearing_burn	2,020	1	0	28	male	rural	0	0	0	0	0	16.7	43.5	moderate	2.3	10	0	0	0	0.15	0.044	0	0	0	0	0	0	0	0.1
FOR-00022	forest_clearing_burn	2,020	6	1	10	female	peri_urban	0	0	0	0	0	187.7	211.9	very_unhealthy	8.5	98	0	0	0	0.15	0.212	1	1	0	0	0	0	0	0.1
FOR-00023	forest_clearing_burn	2,018	6	1	6	male	rural	0	0	0	0	0	131.2	145	unhealthy	10.4	91	2	0	1	0.15	0.087	0	0	0	1	1	0	0	0.1
FOR-00024	forest_clearing_burn	2,010	1	0	38	female	rural	0	0	0	0	0	19.9	33.9	good	5.2	3	1	0	0	0.15	0.034	0	0	1	0	0	0	0	0.0047
FOR-00025	forest_clearing_burn	2,013	2	0	24	male	peri_urban	0	0	0	0	0	29.3	48.7	moderate	0.5	15	2	0	0	0.15	0.049	0	0	1	0	0	0	0	0.045
FOR-00026	forest_clearing_burn	2,016	7	1	8	male	rural	0	0	0	0	0	62	81.2	unhealthy	2.2	86	1	0	0	0.15	0.081	0	0	0	0	1	0	0	0.0875
FOR-00027	forest_clearing_burn	2,024	11	0	47	female	rural	0	0	0	0	0	19.7	33.3	good	4.3	13	0	1	0	0.15	0.023	0	0	0	0	0	0	0	0.1
FOR-00028	forest_clearing_burn	2,011	5	0	50	male	urban	0	0	1	0	0	13.2	38.5	moderate	7.9	25	1	0	0	0.3	0.077	0	0	0	0	0	0	0	0.0171
FOR-00029	forest_clearing_burn	2,011	6	1	12	female	rural	0	0	0	0	0	382	404.1	hazardous	16.4	115	0	1	1	0.15	0.17	0	0	0	0	0	0	0	0.0141
FOR-00030	forest_clearing_burn	2,014	7	1	27	female	rural	0	0	0	0	0	307.8	328.5	hazardous	9.3	66	3	0	1	0.15	0.197	0	0	1	0	0	0	0	0.0583
FOR-00031	forest_clearing_burn	2,015	6	1	15	female	peri_urban	0	0	0	0	0	108.9	130.5	unhealthy	5.9	100	1	0	0	0.15	0.13	0	0	0	0	0	0	0	0.0779
FOR-00032	forest_clearing_burn	2,018	4	0	20	female	rural	0	0	0	0	0	7.2	30	good	5.4	6	1	0	0	0.15	0.03	0	0	0	0	0	0	0	0.1
FOR-00033	forest_clearing_burn	2,018	1	0	58	male	rural	0	0	0	0	0	32.2	54.9	moderate	10.4	13	1	0	0	0.15	0.055	0	0	0	0	0	0	0	0.1
FOR-00034	forest_clearing_burn	2,014	9	1	1	female	rural	1	0	0	0	0	94.3	108.8	unhealthy	0.5	59	1	0	0	0.4	0.29	0	1	0	0	0	0	0	0.0642
FOR-00035	forest_clearing_burn	2,024	4	0	12	female	rural	0	0	0	0	0	23.9	54.4	moderate	0.5	19	1	0	0	0.15	0.054	0	1	0	0	0	0	0	0.1
FOR-00036	forest_clearing_burn	2,013	6	1	10	male	rural	0	0	0	0	0	306.7	322.5	hazardous	6.9	34	1	0	1	0.15	0.193	0	1	0	0	0	0	0	0.0495
FOR-00037	forest_clearing_burn	2,011	9	1	24	male	rural	0	0	0	0	0	317.7	344.9	hazardous	2.9	52	1	0	0	0.15	0.345	0	0	0	0	1	0	0	0.0237
FOR-00038	forest_clearing_burn	2,014	3	0	42	female	peri_urban	0	0	1	0	0	27.1	24.5	good	8.1	9	1	0	0	0.3	0.049	0	0	0	0	0	0	0	0.0585
FOR-00039	forest_clearing_burn	2,023	1	0	39	female	rural	0	0	0	0	1	17.9	41.8	moderate	7.5	11	0	0	0	0.25	0.07	0	0	0	0	0	0	0	0.1
FOR-00040	forest_clearing_burn	2,012	10	0	31	female	urban	0	0	0	0	0	18.9	57	unhealthy	7.7	29	2	0	0	0.15	0.057	0	0	0	0	0	0	0	0.0243
FOR-00041	forest_clearing_burn	2,016	2	0	13	male	peri_urban	0	0	0	0	0	37.5	52.4	moderate	7.8	12	4	0	0	0.15	0.052	1	0	0	0	0	0	0	0.0867
FOR-00042	forest_clearing_burn	2,015	4	0	33	male	rural	0	0	1	0	0	11.5	51.8	moderate	13.3	9	2	0	0	0.3	0.104	0	0	0	0	0	0	0	0.0759
FOR-00043	forest_clearing_burn	2,022	2	0	34	female	rural	0	0	0	0	0	18.5	31.4	good	0.5	0	2	0	0	0.15	0.031	0	0	0	0	0	0	0	0.1
FOR-00044	forest_clearing_burn	2,024	1	0	16	male	rural	0	0	0	0	0	24.5	48.2	moderate	0.5	22	3	0	0	0.15	0.048	0	1	0	0	0	0	0	0.1
FOR-00045	forest_clearing_burn	2,011	1	0	38	female	rural	0	0	0	0	0	38.1	53.2	moderate	5.6	22	0	0	0	0.15	0.053	0	1	0	0	0	0	0	0.0076
FOR-00046	forest_clearing_burn	2,020	1	0	14	male	peri_urban	0	0	0	0	0	20.2	43.8	moderate	0.5	22	1	0	0	0.15	0.044	0	0	0	0	0	0	0	0.1
FOR-00047	forest_clearing_burn	2,018	7	1	19	male	peri_urban	0	0	0	0	0	180.7	211.3	very_unhealthy	9.4	40	1	0	0	0.15	0.211	0	0	0	0	0	0	0	0.1
FOR-00048	forest_clearing_burn	2,020	11	0	16	male	rural	0	0	0	0	0	29	56.2	unhealthy	3.9	14	2	0	0	0.15	0.056	0	0	0	0	0	0	0	0.1
FOR-00049	forest_clearing_burn	2,021	10	0	25	male	rural	0	0	0	0	0	33.2	54.1	moderate	5.9	22	2	0	0	0.15	0.054	0	0	0	0	0	0	0	0.1
FOR-00050	forest_clearing_burn	2,014	9	1	30	male	rural	0	0	0	0	0	436.5	463.1	hazardous	15.8	5	3	0	0	0.15	0.463	1	0	0	1	0	0	0	0.0618
FOR-00051	forest_clearing_burn	2,022	12	0	45	male	rural	0	0	0	0	1	5	29.7	good	10.4	16	1	0	0	0.25	0.05	0	0	0	0	0	0	0	0.1
FOR-00052	forest_clearing_burn	2,012	12	0	59	male	rural	0	0	1	0	0	22.4	44	moderate	5.1	24	3	0	0	0.3	0.088	1	0	0	0	0	1	0	0.0289
FOR-00053	forest_clearing_burn	2,013	3	0	37	female	rural	0	0	0	0	0	11.2	28.1	good	9.6	11	3	0	0	0.15	0.028	0	0	0	0	0	0	0	0.0535
FOR-00054	forest_clearing_burn	2,022	9	1	49	male	urban	0	0	0	0	0	437.3	448.5	hazardous	9.4	72	0	0	0	0.15	0.448	1	0	1	0	0	0	0	0.1
FOR-00055	forest_clearing_burn	2,017	3	0	25	female	rural	0	0	0	0	0	29.1	67.4	unhealthy	14.7	17	3	0	0	0.15	0.067	0	0	0	0	0	0	0	0.1
FOR-00056	forest_clearing_burn	2,019	11	0	30	female	rural	0	0	0	0	0	26.5	52.3	moderate	0.5	16	3	0	0	0.15	0.052	0	0	0	0	0	0	0	0.1
FOR-00057	forest_clearing_burn	2,019	5	0	12	female	peri_urban	0	0	1	0	0	10.9	23.3	good	10.2	0	2	0	0	0.3	0.047	1	0	0	0	0	0	0	0.1
FOR-00058	forest_clearing_burn	2,023	1	0	34	male	peri_urban	0	0	0	0	0	36.7	51.1	moderate	0.5	13	2	0	0	0.15	0.051	0	1	0	0	0	0	0	0.1
FOR-00059	forest_clearing_burn	2,016	10	0	19	female	urban	0	0	0	0	0	13.3	26.4	good	6.3	21	1	0	0	0.15	0.026	0	0	0	0	0	0	0	0.091
FOR-00060	forest_clearing_burn	2,012	9	1	28	male	rural	0	0	0	0	0	244.3	266.8	hazardous	13.9	110	1	0	1	0.15	0.16	0	0	0	1	0	0	0	0.0301
FOR-00061	forest_clearing_burn	2,021	4	0	56	female	rural	0	0	0	0	0	18.5	43	moderate	3.3	22	4	0	0	0.15	0.043	0	0	0	0	0	0	0	0.1
FOR-00062	forest_clearing_burn	2,020	7	1	17	female	rural	0	0	0	0	0	118.2	156.5	very_unhealthy	5.9	119	1	0	0	0.15	0.157	0	0	1	0	0	0	0	0.1
FOR-00063	forest_clearing_burn	2,010	6	1	14	female	peri_urban	0	0	0	0	0	124.6	142.9	unhealthy	11.1	83	2	0	0	0.15	0.143	1	0	0	0	0	0	0	-0.0042
FOR-00064	forest_clearing_burn	2,019	3	0	9	male	rural	0	0	0	0	0	20.5	32.6	good	11.7	28	1	0	0	0.15	0.033	0	0	0	0	1	0	0	0.1
FOR-00065	forest_clearing_burn	2,011	8	1	54	male	rural	0	0	0	0	0	387.5	412.8	hazardous	5.3	98	2	1	0	0.15	0.289	0	0	0	0	0	0	0	0.0128
FOR-00066	forest_clearing_burn	2,019	5	0	52	female	peri_urban	0	0	0	0	0	18.2	32.6	good	13.2	29	0	0	0	0.15	0.033	1	0	0	0	0	0	0	0.1
FOR-00067	forest_clearing_burn	2,012	10	0	34	male	peri_urban	0	0	0	0	0	10.5	36	moderate	0.5	30	0	0	0	0.15	0.036	0	0	0	0	0	0	0	0.0288
FOR-00068	forest_clearing_burn	2,017	1	0	27	female	rural	0	0	0	0	0	11.2	18.3	good	6.4	26	1	0	0	0.15	0.018	0	0	0	0	0	0	0	0.1
FOR-00069	forest_clearing_burn	2,015	1	0	25	male	peri_urban	0	0	0	0	1	10	34.3	good	6.6	25	4	0	0	0.25	0.057	0	0	0	0	0	0	0	0.0778
FOR-00070	forest_clearing_burn	2,019	4	0	12	male	urban	0	0	0	0	0	5	10	good	2.1	21	1	0	0	0.15	0.01	0	0	0	0	0	0	0	0.1
FOR-00071	forest_clearing_burn	2,020	8	1	56	female	rural	0	0	0	0	0	331	356.5	hazardous	5.4	120	1	0	0	0.15	0.357	0	0	0	0	0	0	0	0.1
FOR-00072	forest_clearing_burn	2,018	10	0	17	female	rural	0	0	1	0	0	37.5	48	moderate	2	18	0	0	0	0.3	0.096	0	0	0	0	0	1	0	0.1
FOR-00073	forest_clearing_burn	2,019	9	1	34	male	rural	0	0	1	0	0	359.4	373	hazardous	6.4	80	2	0	0	0.3	0.746	1	1	0	1	1	0	0	0.1
FOR-00074	forest_clearing_burn	2,013	1	0	59	female	rural	0	0	0	0	0	17.2	47.1	moderate	13.3	19	2	0	0	0.15	0.047	1	0	0	0	0	0	0	0.0411
FOR-00075	forest_clearing_burn	2,014	1	0	24	male	rural	0	0	0	0	0	18.9	43.7	moderate	13.4	17	0	0	0	0.15	0.044	0	0	0	0	1	0	0	0.068
FOR-00076	forest_clearing_burn	2,016	10	0	2	male	urban	1	0	0	0	0	47.9	56.2	unhealthy	12.6	11	3	0	0	0.4	0.15	1	0	0	0	0	0	0	0.0957
FOR-00077	forest_clearing_burn	2,014	4	0	1	male	rural	1	0	0	0	0	26.8	35.4	moderate	5.6	22	1	0	0	0.4	0.094	0	0	0	0	0	0	0	0.0608
FOR-00078	forest_clearing_burn	2,011	9	1	33	female	peri_urban	0	0	0	0	0	155	161.1	very_unhealthy	8.1	99	1	0	0	0.15	0.161	0	0	0	0	0	0	0	0.0088
FOR-00079	forest_clearing_burn	2,023	2	0	34	male	rural	0	0	0	0	0	11.6	32.9	good	0.5	10	2	0	0	0.15	0.033	0	0	0	0	0	0	0	0.1
FOR-00080	forest_clearing_burn	2,015	8	1	54	male	rural	0	0	0	0	0	289.5	319	hazardous	4	68	1	0	1	0.15	0.191	0	0	0	1	0	0	0	0.0826
FOR-00081	forest_clearing_burn	2,018	12	0	44	male	urban	0	0	0	0	0	20.1	37	moderate	8.5	22	2	0	0	0.15	0.037	0	0	0	0	0	0	0	0.1
FOR-00082	forest_clearing_burn	2,016	2	0	42	female	rural	0	0	0	0	0	23.5	38	moderate	6	12	2	0	0	0.15	0.038	0	0	0	0	0	0	0	0.0894
FOR-00083	forest_clearing_burn	2,010	2	0	32	female	rural	0	0	0	0	0	21.5	55.9	unhealthy	6.7	21	2	0	0	0.15	0.056	0	0	0	0	0	0	0	0.0076
FOR-00084	forest_clearing_burn	2,023	8	1	34	female	peri_urban	0	0	0	0	0	372.3	397.9	hazardous	6.6	47	1	0	0	0.15	0.398	0	0	0	1	0	0	0	0.1
FOR-00085	forest_clearing_burn	2,019	5	0	25	male	rural	0	0	0	0	0	26.3	30	good	1.4	8	2	0	0	0.15	0.03	0	0	0	0	0	0	0	0.1
FOR-00086	forest_clearing_burn	2,023	6	1	55	female	urban	0	0	0	0	0	318.4	344.6	hazardous	10	110	2	0	0	0.15	0.345	0	1	0	0	0	0	0	0.1
FOR-00087	forest_clearing_burn	2,018	8	1	23	male	urban	0	0	0	0	0	316.3	332.1	hazardous	12	33	2	0	0	0.15	0.332	0	0	0	0	0	0	0	0.1
FOR-00088	forest_clearing_burn	2,014	12	0	34	male	urban	0	0	0	0	0	14.2	40.7	moderate	8.4	23	2	0	0	0.15	0.041	0	0	0	0	0	0	0	0.0732
FOR-00089	forest_clearing_burn	2,016	11	0	29	male	rural	0	0	1	0	0	16.9	29.4	good	4.8	5	7	0	0	0.3	0.059	1	0	0	0	0	1	0	0.0901
FOR-00090	forest_clearing_burn	2,023	11	0	59	female	rural	0	0	0	0	0	18.2	30.9	good	16	22	1	0	0	0.15	0.031	0	0	0	0	0	0	0	0.1
FOR-00091	forest_clearing_burn	2,016	12	0	33	female	rural	0	0	0	0	0	24.5	52	moderate	5.9	3	2	0	0	0.15	0.052	1	0	0	0	0	0	0	0.0941
FOR-00092	forest_clearing_burn	2,018	5	0	52	male	urban	0	0	0	0	0	35	55.1	unhealthy	13.6	5	2	0	0	0.15	0.055	0	0	0	0	0	0	0	0.1
FOR-00093	forest_clearing_burn	2,012	3	0	41	female	peri_urban	0	0	0	0	0	20.6	37.5	moderate	11	20	2	0	0	0.15	0.037	0	0	0	0	0	0	0	0.032
FOR-00094	forest_clearing_burn	2,023	12	0	36	male	rural	0	0	0	0	0	24.1	50.6	moderate	6.4	16	5	0	0	0.15	0.051	0	1	0	0	1	0	0	0.1
FOR-00095	forest_clearing_burn	2,023	4	0	33	male	rural	0	0	0	0	0	14.9	36.3	moderate	5.8	16	0	0	0	0.15	0.036	0	1	0	0	0	0	0	0.1
FOR-00096	forest_clearing_burn	2,015	11	0	32	male	rural	0	0	0	0	0	34.5	67.7	unhealthy	9.1	13	4	0	0	0.15	0.068	0	0	0	0	0	0	0	0.0818
FOR-00097	forest_clearing_burn	2,015	11	0	27	male	urban	0	0	0	0	0	31.9	38.7	moderate	1.2	12	1	0	0	0.15	0.039	0	0	0	0	1	0	1	0.077
FOR-00098	forest_clearing_burn	2,021	7	1	39	male	peri_urban	0	0	0	0	0	60.7	81.7	unhealthy	11.5	80	1	0	0	0.15	0.082	0	1	0	0	0	0	0	0.1
FOR-00099	forest_clearing_burn	2,021	9	1	23	female	urban	0	0	0	0	1	296.1	308.1	hazardous	13.3	88	3	0	1	0.25	0.308	0	0	0	1	0	0	0	0.1

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

Wildfire Smoke & Respiratory Outcomes in Sub-Saharan Africa

Abstract

A synthetic dataset modelling wildfire smoke exposure and respiratory health outcomes across three fire regime scenarios in sub-Saharan Africa. Each record represents an individual-month observation describing smoke PM2.5 exposure, fire proximity, vulnerability, respiratory symptoms, and health service utilisation. Africa accounts for over 70% of global burned area annually, with savanna fires in West/Central Africa and agricultural clearing burns in the Congo Basin driving massive seasonal smoke plumes.

Scenarios

Savanna Fire Belt: West/Central African savanna fires (Nov-Mar) with widespread seasonal haze.
Forest Clearing Burn: Congo Basin agricultural/forest clearing fires (Jun-Sep) with intense localised smoke.
Urban Peri-Urban Haze: Cities downwind of fire zones with combined ambient + smoke pollution.

Dataset Structure

Each scenario contains 10,000 records (30,000 total). Key columns:

year, month, in_fire_season, age, sex, setting
is_child_u5, is_elderly_60plus, pre_existing_asthma, pre_existing_copd, smoker
pm25_smoke_ugm3, pm25_total_ugm3, aqi_category
fire_proximity_km, smoke_days_per_season, fire_count
mask_use, stayed_indoors, vulnerability_index, exposure_risk_score
cough, wheeze, dyspnoea, eye_irritation
ari_episode, asthma_exacerbation, copd_exacerbation
er_visit, hospitalised, mortality, climate_fire_trend

Parameterization Evidence

Parameter	Value Used	Source	Year
Africa >70% of global burned area	Fire frequency baseline	GFEDv4, van der Werf et al.	2017
Savanna fire PM2.5 100-300 µg/m³ during fire season	Smoke exposure	Roberts et al., Atmos Chem Phys	2009
Forest clearing fires produce denser, localised plumes	Clearing scenario	Reddington et al.	2015
PM2.5 exposure increases ARI risk 1.5-3x	Dose-response	WHO AQG	2021

Validation Summary

The 8-panel validation report (validation_report.png) confirms:

PM2.5 gradient: Forest clearing has highest smoke PM2.5; urban haze adds ambient baseline.
Seasonality: Clear monthly PM2.5 peaks during fire season months per scenario.
Symptoms: Cough and eye irritation dominate; rates highest in forest clearing.
Exposure-ARI: Higher exposure risk scores correlate with more ARI episodes.
Vulnerability: Children <5 and elderly have highest vulnerability indices.
Health cascade: ARI > ER visits > hospitalisation > mortality gradient realistic.
AQI: Forest clearing has most "hazardous" days; urban haze more "unhealthy" days.
Fire proximity: Closer fires produce higher smoke PM2.5 during fire season.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/wildfire-smoke-respiratory", name="forest_clearing_burn")
df = ds["train"].to_pandas()

# Fire season vs non-fire season ARI rates
print(df.groupby("in_fire_season")["ari_episode"].mean())

Intended Uses

Modelling wildfire smoke health impacts in SSA
Evaluating respiratory burden during fire seasons
Training exposure-response models for smoke-related respiratory outcomes

Limitations

Synthetic data: Not from air quality monitoring networks or clinical records.
Simplified fire model: Fire proximity and PM2.5 modeled independently.
No spatial geocoding: Scenarios proxy geography, not precise coordinates.
Mask efficacy: Modeled as binary; real-world compliance varies.

References

van der Werf GR, et al. Global fire emissions estimates during 1997-2016. Earth Syst Sci Data, 2017;9:697-720.
Roberts G, et al. African biomass burning emissions. Atmos Chem Phys, 2009.
Reddington CL, et al. Air quality and health impacts of vegetation fires. Nat Geosci, 2015.
WHO. Global Air Quality Guidelines. WHO, 2021.

Citation

@dataset{electricsheepafrica_wildfire_smoke_respiratory_2025,
  title={Wildfire Smoke and Respiratory Outcomes in Sub-Saharan Africa},
  author={Electric Sheep Africa},
  year={2025},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/electricsheepafrica/wildfire-smoke-respiratory}
}

License

CC-BY-4.0

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