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The Global Risks Index

NXS-GRX-BRA · South America · Regions

Para

First-level unit, Brazil: people, area, the units inside and neighbours, with risk values when released.

Map All 27 first-level units
Page GRX-BRA-REdition Baseline Edition 2026Evidence close 2026-09-30ISO BRA / BRStatus UN member stateValues not yet publishedMethod v1.0.0-draft
9,294,936
people (GHSL 2025)
1,240,913 km²
area
4.3%
of Brazil
144
units inside

01Ramani

Inside Para

The 144 ADM2 units of Para.

FIG 1 · 144 units inside Para
Loading the map

Units rise with people per km² · GHSL 2025 raster · terrain · ADM1 ADM2Risk values when released
Lowest fifthLow fifthMiddle fifthHigh fifthHighest fifthNo data
Column height and colour show people per km² by unit, in quantile fifths among the units shown (the key on the map gives the breaks); units with no people on the grid are grey, not the lowest class; the raster beneath is the GHSL 2025 population grid. Source observations, not index values. Choose a humanitarian figure from the list to colour and raise the units by it; each figure shows its source on the unit page. Select a unit to drill into the units inside it; the path above the map climbs back.
02Figures

People, area and density

Source observations from open grids summed inside the boundary; not index values.

Watu · GHSL 2025

9,294,936

4.3% of Brazil.

Watu · WorldPop 2025

8,324,461

-10% against GHSL; the two grids differ in method.

Area

1,240,913 km²

7 people per km².

Code

BR-PA

Subdivision code as carried by the boundary source.

Ukanda wa pwani ulio chini

1,265,341

people on land at or below 10 m, 13.6% of the unit (GEBCO 2024 and GHSL 2025).

03Humanitarian data

Para in humanitarian data

Source observations from the Humanitarian Data Exchange, matched to this unit by name, each with its reference date, provider and licence. They are not index values.

Population · 2022-12-31

8,120,131

people. UNFPA · Creative Commons Attribution for Intergovernmental Organisations (CC BY-IGO).

Poverty headcount · 2015-12-31

10.2%

of people in multidimensional poverty. Oxford Poverty & Human Development Initiative · Public Domain / No restrictions (CC0).

04Units

144 units inside Para

Each unit has its own page.

Boundary licences: Creative Commons Attribution 2.5 Generic · Creative Commons Attribution 3.0 Intergovernmental Organisations (CC BY 3.0 IGO)

Unit Code People (GHSL) People (WorldPop) Area km² Per km² Share Coast ≤ 10 m
Abaetetuba – 176,000 166,330 1,617.48 109 1.9% 66,075
Abel Figueiredo – 21,079 18,040 617.84 34 0.2% 0
Acará – 65,632 59,316 4,364.27 15 0.7% 2,445
Afuá – 43,841 39,148 8,377.18 5 0.5% 4,130
Água Azul do Norte – 31,733 15,952 7,143.32 4 0.3% 0
Alenquer – 67,986 76,392 23,747.94 3 0.7% 20,348
Almeirim – 55,721 40,345 73,284.78 1 0.6% 25,047
Altamira – 147,133 138,154 160,221.54 1 1.6% 0
Anajás – 32,294 29,809 6,942.36 5 0.3% 1,767
Ananindeua – 446,788 433,088 191.23 2,336 4.7% 91,315
Anapu – 32,295 36,390 11,947.32 3 0.3% 103
Augusto Corrêa – 50,903 46,113 1,102.17 46 0.5% 9,975
Aurora do Pará – 33,072 21,696 1,820.53 18 0.4% 126
Aveiro – 19,175 19,396 17,152.26 1 0.2% 4,640
Bagre – 33,973 37,960 4,417.23 8 0.4% 3,507
Baião – 56,455 59,027 3,775.55 15 0.6% 9,844
Bannach – 3,873 4,248 2,969.27 1 0% 0
Barcarena – 157,331 150,469 1,316.2 120 1.7% 16,967
Belém – 1,651,610 1,346,655 1,063.49 1,553 17.5% 430,419
Belterra – 19,137 18,061 4,417.43 4 0.2% 1,643
Benevides – 45,152 49,909 188.41 240 0.5% 9,876
Bom Jesus do Tocantins – 18,817 19,297 2,827.17 7 0.2% 0
Bonito – 17,993 12,286 587.92 31 0.2% 0
Bragança – 142,362 130,100 2,135.48 67 1.5% 31,865
Brasil Novo – 18,058 26,664 6,390.21 3 0.2% 0
Brejo Grande do Araguaia – 8,832 6,705 1,293.03 7 0.1% 0
Breu Branco – 69,067 42,486 3,955.29 17 0.7% 382
Breves – 114,412 112,661 9,609.46 12 1.2% 24,486
Bujaru – 33,935 25,729 999.52 34 0.4% 3,144
Cachoeira do Arari – 19,850 18,096 3,113.85 6 0.2% 10,375
Cachoeira do Piriá – 43,639 22,721 2,430.8 18 0.5% 29
Cametá – 155,106 143,464 3,096.31 50 1.6% 39,865
Canaã dos Carajás – 42,506 96,482 3,160.25 13 0.5% 0
Capanema – 77,260 75,390 625.75 123 0.8% 572
Capitão Poço – 60,362 59,692 2,913.89 21 0.6% 4
Castanhal – 219,144 205,011 1,036.32 211 2.3% 16
Chaves – 25,603 21,337 12,590.34 2 0.3% 12,450
Colares – 14,821 14,861 385.79 38 0.2% 1,431
Conceição do Araguaia – 54,458 45,400 5,854.36 9 0.6% 0
Concórdia do Pará – 32,285 22,117 702.9 46 0.3% 91
Cumaru do Norte – 14,871 15,197 17,156.41 1 0.2% 0
Curionópolis – 17,287 20,363 2,381.27 7 0.2% 0
Curralinho – 28,939 25,579 3,633.82 8 0.3% 4,421
Curuá – 15,154 14,063 1,435.13 11 0.2% 6,897
Curuçá – 47,360 45,312 678.95 70 0.5% 3,060
Dom Eliseu – 69,902 64,223 5,292.06 13 0.7% 0
Eldorado do Carajás – 38,373 26,869 2,970.72 13 0.4% 0
Faro – 17,959 14,804 11,824.26 2 0.2% 9,655
Floresta do Araguaia – 22,695 18,597 3,458.33 7 0.2% 0
Garrafão do Norte – 30,827 24,799 1,614.82 19 0.3% 0
Goianésia do Pará – 40,069 25,082 7,057.06 6 0.4% 0
Gurupá – 39,495 33,724 8,609.03 5 0.4% 3,117
Igarapé-Açu – 45,448 38,525 788.95 58 0.5% 74
Igarapé-Miri – 70,836 67,395 2,006.44 35 0.8% 18,518
Inhangapi – 10,734 9,480 473.74 23 0.1% 982
Ipixuna do Pará – 76,437 23,710 5,238.69 15 0.8% 16
Irituia – 38,007 31,446 1,391.53 27 0.4% 670
Itaituba – 117,531 133,730 62,309.44 2 1.2% 41,410
Itupiranga – 60,856 48,624 7,913.08 8 0.6% 0
Jacareacanga – 13,628 27,573 53,535.86 0 0.1% 0
Jacundá – 65,893 32,224 2,018.63 33 0.7% 0
Juruti – 64,820 53,526 8,340.31 8 0.7% 10,952
Limoeiro do Ajuru – 32,444 32,017 1,495.91 22 0.3% 5,466
Mãe do Rio – 32,956 36,845 471.32 70 0.3% 0
Magalhães Barata – 17,432 13,380 325.78 54 0.2% 4,255
Marabá – 315,063 286,906 15,191.47 21 3.3% 0
Maracanã – 29,107 20,941 812.01 36 0.3% 4,020
Marapanim – 16,455 11,278 807.2 20 0.2% 1,801
Marituba – 125,340 105,013 103.16 1,215 1.3% 6,525
Medicilândia – 35,582 28,087 8,309.53 4 0.4% 0
Melgaço – 29,528 28,221 6,804.27 4 0.3% 5,444
Mocajuba – 32,893 27,300 875.08 38 0.3% 15,357
Moju – 88,746 88,907 9,137.75 10 0.9% 12,607
Mojuí dos Campos – 22,756 36,117 5,009.41 5 0.2% 0
Monte Alegre – 63,139 63,575 18,233.08 3 0.7% 16,918
Muaná – 45,725 50,681 3,779.3 12 0.5% 16,164
Nova Esperança do Piriá – 25,229 21,809 2,821.79 9 0.3% 0
Nova Ipixuna – 18,904 13,890 1,571.27 12 0.2% 0
Nova Timboteua – 18,957 14,032 492.35 39 0.2% 288
Novo Progresso – 28,793 37,261 38,328.57 1 0.3% 0
Novo Repartimento – 83,672 60,415 15,468.9 5 0.9% 0
Óbidos – 61,412 55,966 28,143.05 2 0.7% 15,945
Oeiras do Pará – 42,173 43,502 3,868.87 11 0.4% 8,647
Oriximiná – 81,449 70,919 108,096.59 1 0.9% 39,756
Ourém – 17,372 16,212 565.17 31 0.2% 5
Ourilândia do Norte – 34,947 34,762 14,474.8 2 0.4% 0
Pacajá – 53,513 42,923 11,882.32 5 0.6% 0
Palestina do Pará – 8,071 6,293 988.71 8 0.1% 0
Paragominas – 129,529 111,212 19,427.18 7 1.4% 0
Parauapebas – 219,775 304,305 6,916.16 32 2.3% 0
Pau D’Arco – 6,647 7,292 1,677.44 4 0.1% 0
Peixe-Boi – 10,435 9,428 452.3 23 0.1% 302
Piçarra – 15,032 13,148 3,326.95 5 0.2% 0
Placas – 33,950 17,312 7,205.19 5 0.4% 0
Ponta de Pedras – 43,754 32,357 3,379.58 13 0.5% 23,956
Portel – 69,508 67,998 25,498.46 3 0.7% 13,535
Porto de Moz – 45,215 43,473 17,500 3 0.5% 13,684
Prainha – 36,738 39,257 14,851.69 2 0.4% 10,345
Primavera – 12,107 10,683 259.55 47 0.1% 984
Quatipuru – 15,821 11,838 304.43 52 0.2% 5,539
Redenção – 96,471 91,191 3,840.36 25 1% 0
Rio Maria – 21,358 19,384 4,136.38 5 0.2% 0
Rondon do Pará – 59,142 56,949 8,284.13 7 0.6% 0
Rurópolis – 54,034 33,667 7,052.51 8 0.6% 332
Salinópolis – 30,864 29,348 226.75 136 0.3% 10,183
Salvaterra – 25,848 27,397 923.27 28 0.3% 8,241
Santa Bárbara do Pará – 23,483 22,118 279.88 84 0.2% 1,123
Santa Cruz do Arari – 6,688 5,177 1,081.57 6 0.1% 4,739
Santa Izabel do Pará – 96,406 97,512 720.51 134 1% 706
Santa Luzia do Pará – 22,460 20,952 1,353.88 17 0.2% 0
Santa Maria das Barreiras – 24,007 16,463 10,373.73 2 0.3% 0
Santa Maria do Pará – 28,305 25,570 459.66 62 0.3% 0
Santana do Araguaia – 80,871 24,970 11,638.57 7 0.9% 0
Santarém – 273,217 348,290 17,982.35 15 2.9% 40,245
Santarém Novo – 5,915 4,763 230.62 26 0.1% 77
Santo Antônio do Tauá – 30,970 25,866 539.72 57 0.3% 277
São Caetano de Odivelas – 21,817 18,507 467.23 47 0.2% 2,094
São Domingos do Araguaia – 28,768 20,464 1,400.31 21 0.3% 0
São Domingos do Capim – 43,688 37,284 1,693.39 26 0.5% 7,227
São Félix do Xingu – 149,379 55,731 84,573.4 2 1.6% 0
São Francisco do Pará – 17,268 14,753 481.88 36 0.2% 16
São Geraldo do Araguaia – 28,736 23,616 3,184.73 9 0.3% 0
São João da Ponta – 3,494 2,132 196.48 18 0% 54
São João de Pirabas – 25,833 20,896 671.28 38 0.3% 4,850
São João do Araguaia – 16,108 13,588 1,284.64 13 0.2% 0
São Miguel do Guamá – 66,263 55,311 1,099.92 60 0.7% 10,081
São Sebastião da Boa Vista – 30,134 27,601 1,640.31 18 0.3% 9,309
Sapucaia – 6,678 6,546 1,303.68 5 0.1% 0
Senador José Porfírio – 13,967 24,935 14,482.74 1 0.1% 3,307
Soure – 30,827 26,125 2,869.11 11 0.3% 18,669
Tailândia – 118,294 70,098 4,450.51 27 1.3% 0
Terra Alta – 13,022 10,459 205.51 63 0.1% 0
Terra Santa – 21,164 20,052 1,904.44 11 0.2% 13,218
Tomé-Açu – 70,466 72,105 5,169.04 14 0.7% 370
Tracuateua – 38,207 32,377 869.29 44 0.4% 7,356
Trairão – 21,099 14,583 12,043.92 2 0.2% 0
Tucumã – 45,054 42,278 2,522.57 18 0.5% 0
Tucuruí – 125,720 89,407 2,093.26 60 1.3% 15,531
Ulianópolis – 66,451 35,922 5,111.35 13 0.7% 0
Uruará – 53,273 42,803 10,840.89 5 0.6% 0
Vigia – 60,924 53,908 402.15 151 0.6% 8,430
Viseu – 57,706 53,417 4,995.57 12 0.6% 2,710
Vitória do Xingu – 16,882 17,255 3,103.09 5 0.2% 1,875
Xinguara – 50,899 58,203 3,790.11 13 0.5% 0
05Exposure

Open exposure layers

Count of H3 resolution-3 cells whose centre falls in the unit and that carry each Natural Earth layer.

Urban areas
360.9 H3 cells
Bandari
2 H3 cells
Viwanja vya ndege
1 H3 cells
Major roads
7,002.8 H3 cells
Reli
265.6 H3 cells
Rivers and lakes
5,898.4 H3 cells
06Hatari

Risk values

Values when released. Subnational risk values for Para publish with the edition from The Global Risks Index. Until then, run a scenario on open data for Brazil.
Run a scenario Hazards Domain indices
07Neighbours

Neighbouring units

08Vyanzo

Sources, credits and licences

ADM1 boundaries
geoBoundaries (William & Mary geoLab), gbOpen BRA ADM1, source: geoBoundaries, Wikimedia Commons, licence: Creative Commons Attribution 2.5 Generic · source · represents 2006
ADM2 boundaries
geoBoundaries (William & Mary geoLab), gbOpen BRA ADM2, source: Instituto Brasileiro de Geografia e Estatística (IBGE), OCHA ROLAC, licence: Creative Commons Attribution 3.0 Intergovernmental Organisations (CC BY 3.0 IGO) · source · represents 2020
Basemap
OpenFreeMap © OpenMapTiles (CC BY 4.0) · data © OpenStreetMap contributors (ODbL 1.0). Vector tiles requested by the reader’s browser, unmodified; the map falls back to plain land and sea when the host does not answer.
Terrain
Terrain Tiles (Mapzen, AWS Open Data), compiled from SRTM and other public elevation sources (NASA, USGS, ETOPO1, GMTED, EU-DEM under the Copernicus programme, Geoscience Australia, Kartverket, INEGI, LINZ, data.gov.uk). Display relief, not survey data.
People
GHSL 2025 population grid, European Commission Joint Research Centre (CC BY 4.0), shown at 0.05° and summed per unit; WorldPop 2025 (CC BY 4.0) as a second estimate. Units smaller than a grid cell take the density of the cell under them.
Nchi
Natural Earth (public domain).
Elevation
GEBCO Compilation Group (2024) GEBCO 2024 Grid (public domain), reduced to 0.05°: the share of each cell’s land at or below 10 m, weighted by GHSL 2025 people for the low coastal zone.
Position
Boundaries are shown for location only and take no position on any boundary, name or status.

Hali

The methodology, structure and definitions of The Global Risks Index are a preparatory working draft (2026), circulated for review and comment and not for implementation. No value appears until an edition is released from a governed evidence cut; values then carry intervals, classes, sources and their correction pathway. Simulators run the published methods on numbers you choose and never show a NXS-GRX value.

A country profile reads public evidence about a place. It is not a statement by or about the policy of any government, takes no position on the status of any territory, and does not imply a national programme or participation. Names follow UN M49.

NXS-GRX si nini

NXS-GRX ni taarifa ya utafiti na uchambuzi wa hatari. Si daraja la mikopo wala la ESG na haitumii kipimo chochote cha daraja, si kigezo cha vyombo vya fedha, si takwimu rasmi, si onyo la dharura wala uainishaji rasmi, na si ushauri. Haipaswi kutumiwa kutathmini watu binafsi. Madaraja ya hatari ni mikanda kwenye kipimo kilichochapishwa, kamwe si mpangilio wa nchi au watu.

Ishara za Pulse na uwezekano wa mtazamo ni taarifa za kukaguliwa na mamlaka husika, kamwe si maonyo ya umma; maonyo rasmi hutoka tu kwa mamlaka zilizopewa jukumu.

Taasisi na vyanzo

The Nexus Consortium is stewarded by three independent not-for-profit institutions: The Global Centre for Risk and Innovation (GCRI), through GCRI US in Washington, DC and GCRI Canada in Ontario, with GCRI Canada as Lead Institution, Consortium Secretariat and lead contracting organisation; The Global Risks Forum (GRF); and The Global Risks Alliance (GRA). Technology, infrastructure and service providers work with the Consortium at arm’s length under written agreements, like every other external party in the public-private-planet model, and hold no role in its stewardship.

Every value carries the attribution of its sources, which keep their own licences. External names are cited for interoperability only. Nexus-authored text is intended for CC BY 4.0 on release.

Avis en français

La méthodologie et les définitions du NXS-GRX sont un projet de travail préparatoire (2026). Le NXS-GRX est une information de recherche et d’analyse des risques : ni notation, ni indice de référence financier, ni statistique officielle, ni alerte, ni conseil. Les classes de risque sont des bandes sur une échelle publiée, non des classements.