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How Rice Fights Pandemics

Nature–Crop–Human Interactions Shaped Covid-19 Outcomes

Dados Bibliográficos

ID21453640
AutoresThomas Talhelm (0000-0002-0954-5758, University of Chicago, IL, USA), Cheol-Sung Lee (0000-0003-3661-981X, University of Chicago, IL, USA, autor correspondente), Alexander English (0000-0002-0142-146X, Zhejiang University, Hangzhou, China, autor correspondente), Shuang Wang (0000-0002-7914-2081, Shanghai International Studies University)
Ano2023
Volume49
Fascículo11
Páginas1567-1586
Data de publicação2023-11-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoPersonality and Social Psychology Bulletin (JOURNAL)
Identificadores do periódicoISSN: 0146-1672 • E-ISSN: 1552-7433
EditoraSAGE Publications (PUBLISHER • US)
DOI10.1177/01461672221107209
PMID35856451
OpenAlexW4285993196
IdiomaEN
Citações recebidas10
Referências citadas33

Wealthy nations led health preparedness rankings in 2019, yet many poor nations controlled COVID-19 better. We argue that a history of rice farming explains why some societies did better. We outline how traditional rice farming led to tight social norms and low-mobility social networks. These social structures helped coordinate societies against COVID-19. Study 1 compares rice- and wheat-farming prefectures within China. Comparing within China allows for controlled comparisons of regions with the same national government, language family, and other potential confounds. Study 2 tests whether the findings generalize to cultures globally. The data show rice-farming nations have tighter social norms and less-mobile relationships, which predict better COVID outcomes. Rice-farming nations suffered just 3% of the COVID deaths of nonrice nations. These findings suggest that long-run cultural differences influence how rice societies—with over 50% of the world’s population—controlled COVID-19. The culture was critical, yet the preparedness rankings mostly ignored it

Agriculture · China · Coronavirus disease 2019 (COVID-19) · Development economics · Economic growth · Economics · Geography · Government (linguistics) · Pandemic · Political science · Population · Preparedness · Socioeconomics · Sociology · COVID-19 epidemiological studies · Cultural Differences and Values · Demography · Medicine · Zoonotic diseases and public health

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Obras citantes distintas10
Citações por ano2,5
Intervalo de citações2022 - 2026 (5)
Velocidade de citaçãocurrent
Altamente citadoNão
Tipos de citaçãoNeutras: 7
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