Lorena Barberia

44 papers receiving 632 citations

Lorena Barberia's Hit Papers

Spatiotemporal pattern of COVID-19 spread in Brazil 2021 · 205 citations
2050+1+3Years since publication50100150200

Peers

Lorena Barberia
Comparison fields: 5 of 103
  • Modeling and Simulation 124
  • Health 92
  • Economics and Econometrics 135
  • Sociology and Political Science 195
  • Demography 45
Replace Elize Massard da Fonseca with:
Elize Massard da Fonseca Brazil
Luke Taylor Australia
Siddharth Chandra United States
Matthew M. Kavanagh United States
Nathaniel M. Lewis United Kingdom
Naeem Ahmed United Kingdom
Svenn‐Erik Mamelund Norway
Ben Oppenheim United States
Sophie Harman United Kingdom
Arush Lal United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Lorena Barberia

Since Specialization
Citations

This map shows the geographic impact of Lorena Barberia's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lorena Barberia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lorena Barberia more than expected).

Fields of papers citing papers by Lorena Barberia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lorena Barberia. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lorena Barberia. The network helps show where Lorena Barberia may publish in the future.

Co-authors

The 25 scholars most cited alongside Lorena Barberia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lorena Barberia Line = papers co-authored together Lorena Barberia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Spatiotemporal pattern of COVID-19 spread in Brazil
Hit paper breakdown →
2021205
2 2020106
3 200256
4 201128
5 201326
6
The Cuban Economy at the Start of the Twenty-First-Century
200422
7 201019
8 202218
9 202118
10 202216
11 202114
12 202311
13 202310
14 200310
15 20219
16 20229
17
Remittances To Cuba: An Evaluation of Cuban and US Government Policy Measures
20029
18
Who gets political appointments?: Party loyalty and bureaucratic expertise in Brazil
20148
19 20218
20 20217

About Lorena Barberia

Lorena Barberia is a scholar working on Sociology and Political Science, Modeling and Simulation, Economics and Econometrics, Political Science and International Relations and Health, having authored 52 papers that have together received 672 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (14 papers), Vaccine Coverage and Hesitancy (7 papers), COVID-19 Pandemic Impacts (7 papers), COVID-19 Impact on Reproduction (4 papers), COVID-19 and Mental Health (4 papers), Income, Poverty, and Inequality (3 papers), Misinformation and Its Impacts (3 papers) and Education and Public Policy (3 papers). The work is most often cited by research in Modeling and Simulation (124 citations), Health (92 citations), Economics and Econometrics (135 citations), Sociology and Political Science (195 citations) and Demography (45 citations). Lorena Barberia has collaborated with scholars based in Brazil, United States and United Kingdom. Frequent co-authors include Eduardo J. Gómez, Susan Eckstein, George Avelino, Erin Abbott, Susie Gurzenda, Jeffrey C. Blossom, Márcia C. Castro, Beatriz Rache, Karina Braga Ribeiro and Sun Kim. Their work appears in journals such as The Lancet Regional Health - Americas, The Lancet, Vaccine, Social Science Quarterly and Global Health Research and Policy.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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