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Atlas of internal migration in Brazil 2022 Census · 2017–2022

Migration in Rio Vermelho/MG (2017–2022)

Rio Vermelho/MG had a reference population (aged 5 or over in 2022) of 11,975 people. In the 2017–2022 five-year period, the municipality received 760 in-migrants and lost 855 out-migrants to other municipalities in Brazil, resulting in a net migration of −95 people (−7.92 per 1,000 population) and a migration effectiveness index (IEM) of −0.059. This classifies the municipality, for the period, as one of migratory depletion. In addition, 0 arrived with an unreported origin and 10 came from abroad.

Indicators

Migration indicators for Rio Vermelho/MG, 2017–2022
IndicatorEstimate95% CIPrecision
In-migrants760556 to 964good
Out-migrants855608 to 1,102good
Net migration−95−415 to 225not classified
Net migration rate, TLM (per 1,000 pop.)−7.92--
Migration effectiveness index (IEM)−0.059--

Sample of in-migrants: 100-499 observations. Sample of out-migrants: 100-499 observations. 95% confidence interval computed as estimate ± 1.96 × standard error.

Top origins and destinations

Top 10 origins of in-migrants to Rio Vermelho/MG
OriginPeoplePrecision
Belo Horizonte/MG · view pair in the atlas170use with caution
São Paulo/SP · view pair in the atlas55low precision
Barueri/SP · view pair in the atlas45low precision
Serra Azul de Minas/MG · view pair in the atlas40low precision
Cotia/SP · view pair in the atlas35low precision
Itamarandiba/MG · view pair in the atlas30low precision
Top 10 destinations of out-migrants from Rio Vermelho/MG
DestinationPeoplePrecision
Cotia/SP · view pair in the atlas115low precision
Guanhães/MG · view pair in the atlas70low precision
Coluna/MG · view pair in the atlas50low precision
Felício dos Santos/MG · view pair in the atlas45low precision
Vespasiano/MG · view pair in the atlas40low precision

Profile of migrants and residents

In-migrants (arrivals)

Migrant type
CategoryEstimateShareSample
Return to municipality of birth42055.3%50-99
First move from municipality of birth19025.0%20-49
Multi-step migration15019.7%20-49
Educational attainment (people aged 25 and over)
CategoryEstimateShareSample
No schooling or incomplete elementary17037.0%20-49
Completed high school, incomplete higher education15533.7%20-49
Completed elementary, incomplete high school7015.2%5-19
Completed higher education6514.1%5-19
Household income per capita (in 2022 minimum wages)
CategoryEstimateShareSample
¼ to ½ minimum wage26034.2%50-99
½ to 1 minimum wage22529.6%20-49
Up to ¼ of a minimum wage19025.0%20-49
1 to 2 minimum wages759.9%5-19
Other / suppressed101.3%<5
Age and sex
CategoryEstimateShareSample
Ages 25–39, female16521.7%20-49
Ages 25–39, male11515.1%20-49
Ages 5–14, female9512.5%5-19
Ages 15–24, female9011.8%20-49
Ages 5–14, male8010.5%5-19
Ages 40–59, female709.2%5-19
Ages 40–59, male709.2%5-19
Ages 15–24, male354.6%5-19
Ages 60 and over, male303.9%5-19
Other / suppressed101.3%<5

Out-migrants (departures)

Migrant type
CategoryEstimateShareSample
First move from municipality of birth69080.7%100-499
Multi-step migration14517.0%20-49
Return to municipality of birth202.3%5-19
Educational attainment (people aged 25 and over)
CategoryEstimateShareSample
No schooling or incomplete elementary24057.1%20-49
Completed high school, incomplete higher education12028.6%5-19
Other / suppressed307.1%<5
Completed higher education307.1%5-19
Household income per capita (in 2022 minimum wages)
CategoryEstimateShareSample
1 to 2 minimum wages23527.3%20-49
½ to 1 minimum wage21525.0%20-49
Up to ¼ of a minimum wage19022.1%20-49
¼ to ½ minimum wage12014.0%20-49
More than 2 minimum wages758.7%5-19
Other / suppressed252.9%<5
Age and sex
CategoryEstimateShareSample
Ages 15–24, male15518.1%5-19
Ages 15–24, female15017.5%5-19
Ages 25–39, female14016.4%20-49
Ages 25–39, male758.8%5-19
Ages 5–14, female657.6%5-19
Ages 5–14, male607.0%5-19
Ages 40–59, female607.0%5-19
Ages 60 and over, male556.4%5-19
Ages 60 and over, female556.4%5-19
Ages 40–59, male404.7%5-19

Non-migrant residents

Educational attainment (people aged 25 and over)
CategoryEstimateShareSample
No schooling or incomplete elementary5,17566.5%>=500
Completed high school, incomplete higher education1,27516.4%100-499
Completed elementary, incomplete high school80510.3%100-499
Completed higher education5256.7%100-499
Household income per capita (in 2022 minimum wages)
CategoryEstimateShareSample
½ to 1 minimum wage4,11534.7%>=500
¼ to ½ minimum wage3,17526.7%>=500
Up to ¼ of a minimum wage2,51021.1%100-499
1 to 2 minimum wages1,48012.5%100-499
More than 2 minimum wages5504.6%100-499
Not applicable (collective dwelling)400.3%5-19
Age and sex
CategoryEstimateShareSample
Ages 40–59, male1,59014.2%100-499
Ages 40–59, female1,51513.5%100-499
Ages 60 and over, female1,32511.8%100-499
Ages 25–39, male1,13510.1%100-499
Ages 60 and over, male1,12510.0%100-499
Ages 25–39, female1,0859.7%100-499
Ages 15–24, male1,0209.1%100-499
Ages 15–24, female9058.1%100-499
Ages 5–14, male7907.1%100-499
Ages 5–14, female7056.3%100-499

Commuting (work and study)

Commuting indicators for Rio Vermelho/MG
Employed persons (aged 10 and over)4,450
Commute out to work in another municipality265
Commute in from another municipality to work here130
Net commuting−130
Out-commuting rate (%)5.91
Commuting attraction index0.950
Median commuting time90 min

Open Rio Vermelho/MG in the interactive atlas →

Methodological note

Estimates from the sample microdata of the 2022 Demographic Census (IBGE, controlled access), fixed-date migration question (residence on July 31, 2017 compared with residence on July 31, 2022). Every estimate is rounded to multiples of 5 and has passed statistical disclosure control (no cell with fewer than 5 people or 3 sampled households). See the full methodology and the glossary.

How to cite this page

Daniel Pessini Sobreira. Atlas da migração interna no Brasil [Atlas of internal migration in Brazil]: Rio Vermelho/MG. Data from the 2022 Demographic Census (IBGE). Data version: 2026-10-01. Available at: https://atlas-da-migracao.github.io/en/municipio/rio-vermelho-mg-3156007/. Dataset DOI: https://doi.org/10.5281/zenodo.22469791.