Adaptation · Where to spend first

District Adaptation Priority Index

Hazard exposure alone does not tell you where adaptation money should go first: a wealthy district can absorb a shock a poor one cannot. This index pairs each district's multi-hazard exposure with its relative poverty, so the top of the list is where high exposure meets the least capacity to cope.

Source: BDPolicyLab exposure atlas · Meta Relative Wealth Index

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Latest source data is available.

All 64 district rows were parsed.

Current finding and action

Patuakhali ranks first at 81.0 points. Use the ranking to sequence appraisal, then test each district's project pipeline and local context.

First-ranked district

Patuakhali · 81.0 points

Source: BDPolicyLab adaptation priority index

High-priority threshold

6 districts at 65+ points

Source: BDPolicyLab adaptation priority index

Coverage

64 districts

Source: GovTwin district profiles · exposure atlas

All districts, ranked

Priority is the mean of two within-country percentiles (0 to 100): the multi-hazard exposure rank and the poverty rank (Meta Relative Wealth Index, poorer districts rank higher). Equal weight, no hidden weighting.

#	District	Division	Priority	Exposure (0-100)	Poverty (0-100)	Flood %	<5 m %	PM2.5 (µg/m³)
1	Patuakhali	Barishal	81.0	67	95	86	99	74.3
2	Bhola	Barishal	78.5	69	88	90	96	81.7
3	Barguna	Barishal	74.0	56	92	96	99	71.8
4	Bandarban	Chattogram	68.0	38	98	5	0	59.4
5	Magura	Khulna	66.5	58	75	84	24	76
6	Habiganj	Sylhet	65.5	47	84	57	22	68.2
7	Khagrachhari	Chattogram	64.5	32	97	8	0	62.5
8	Rangamati	Chattogram	64.5	29	100	12	0	56.8
9	Kishoreganj	Dhaka	61.5	57	66	44	35	75.7
10	Sunamganj	Sylhet	61.5	37	86	70	35	45.2
11	Barishal	Barishal	59.5	71	48	96	96	74.7
12	Naogaon	Rajshahi	58.5	34	83	56	0	60.7
13	Pabna	Rajshahi	58.5	65	52	86	1	69.9
14	Pirojpur	Barishal	58.0	52	64	98	99	72.2
15	Dinajpur	Rangpur	57.5	24	91	24	0	68.3
16	Jhenaidah	Khulna	56.5	51	62	49	2	72.4
17	Thakurgaon	Rangpur	56.5	19	94	3	0	66.5
18	Noakhali	Chattogram	56.0	82	30	84	83	85.3
19	Gaibandha	Rangpur	55.5	39	72	84	0	67.3
20	Netrokona	Mymensingh	55.5	30	81	58	11	50.5
21	Chapainawabganj	Rajshahi	55.0	33	77	61	0	54.9
22	Narail	Khulna	53.0	51	55	80	79	74.3
23	Chattogram	Chattogram	52.5	91	14	22	43	84.4
24	Faridpur	Dhaka	52.5	69	36	91	33	75.4
25	Satkhira	Khulna	52.5	46	59	24	88	64.7
26	Kurigram	Rangpur	52.0	26	78	78	0	55.9
27	Rangpur	Rangpur	51.0	29	73	42	0	68.3
28	Khulna	Khulna	50.5	68	33	44	88	75.2
29	Natore	Rajshahi	50.5	43	58	83	0	62.5
30	Panchagarh	Rangpur	50.5	12	89	18	0	51
31	Jamalpur	Mymensingh	50.0	39	61	87	0	69.9
32	Dhaka	Dhaka	49.5	97	2	45	27	81.5
33	Bagerhat	Khulna	49.0	60	38	94	96	74.2
34	Gopalganj	Dhaka	49.0	57	41	96	92	74
35	Lakshmipur	Chattogram	49.0	71	27	97	83	84.6
36	Narayanganj	Dhaka	49.0	95	3	91	80	82.1
37	Jhalokati	Barishal	48.5	44	53	98	100	70.1
38	Rajbari	Dhaka	48.5	58	39	91	4	75.2
39	Bogura	Rajshahi	48.0	46	50	56	0	69.6
40	Sirajganj	Rajshahi	48.0	62	34	93	3	76
41	Lalmonirhat	Rangpur	47.5	15	80	56	0	55.2
42	Brahmanbaria	Chattogram	45.5	72	19	84	59	75.4
43	Joypurhat	Rajshahi	45.0	20	70	32	0	64.6
44	Mymensingh	Mymensingh	45.0	34	56	19	1	66.8
45	Shariatpur	Dhaka	43.5	64	23	94	85	79.2
46	Chandpur	Chattogram	43.0	74	12	93	94	81.7
47	Chuadanga	Khulna	43.0	42	44	46	0	64.3
48	Comilla	Chattogram	43.0	80	6	76	42	77
49	Rajshahi	Rajshahi	43.0	44	42	70	0	55.1
50	Nilphamari	Rangpur	42.5	16	69	32	0	62.9
51	Tangail	Dhaka	42.5	63	22	75	1	79.1
52	Munshiganj	Dhaka	41.5	75	8	94	84	82.8
53	Sherpur	Mymensingh	41.5	16	67	54	0	63.2
54	Madaripur	Dhaka	41.0	62	20	95	77	76.2
55	Gazipur	Dhaka	40.5	76	5	27	14	80.4
56	Kushtia	Khulna	40.0	55	25	77	1	63.5
57	Meherpur	Khulna	40.0	35	45	66	0	58.1
58	Jessore	Khulna	39.0	50	28	22	29	72.2
59	Manikganj	Dhaka	39.0	62	16	94	10	79.9
60	Moulvibazar	Sylhet	39.0	31	47	36	1	53
61	Feni	Chattogram	37.5	66	9	78	46	82.3
62	Narsingdi	Dhaka	36.5	62	11	52	39	79.7
63	Sylhet	Sylhet	36.0	41	31	50	1	42.1
64	Cox's Bazar	Chattogram	28.5	40	17	17	51	73.1

Method and sources

Exposure rank: the combined multi-hazard rank from the exposure atlas (GloFAS flood, FABDEM low-elevation, MODIS heat, ACAG PM2.5, population-weighted with WorldPop 2020). Poverty rank: Meta Relative Wealth Index national district ranking (1 = poorest), from the GovTwin district profile (HDX). Both are converted to a 0 to 100 within-country percentile and averaged with equal weight. This is a relative prioritisation across the 64 districts, not an absolute need estimate; it deliberately uses no socioeconomic weighting beyond the two stated inputs.

Source: GloFAS · FABDEM · MODIS · ACAG · WorldPop 2020 · Meta RWI