1 |
Ak, Ç., Chitsazan, A. D., Gönen, M., Etzioni, R., and Grossberg, A. J. (2022). Spatial prediction of COVID-19 pandemic dynamics in the United States. ISPRS International Journal of Geo-Information, 11(9):470.
|
|
2 |
Amaral, O. E. d. (2020). The victory of Jair Bolsonaro according to the Brazilian electoral study of 2018. Brazilian Political Science Review, 14:e0004.
|
|
3 |
Aron, J. and Muellbauer, J. (2022). Excess mortality versus COVID-19 death rates: A spatial analysis of socioeconomic disparities and political allegiance across U.S. States. Review of Income and Wealth, 68(2):348–392.
|
|
4 |
Ayifah, R. N. Y. and Ayifah, E. (2023). COVID-19 lockdown policy and national elections: A quasi-experimental analysis of Ghana’s 2020 election. International Social Science Journal, 73(248):685–704.
|
|
5 |
Barberia, L., Moreira, N. d. P., Carvalho, R. d. J., Oliveira, M. L. C., Rosa, I. S. C., and Zamudio, M. (2022). The relationship between ideology and COVID-19 deaths: what we know and what we still need to know. Brazilian Political Science Review, 16:e0002.
|
|
6 |
Bolognesi, B., Ribeiro, E., and Codato, A. (2020). Esquerda, centro ou direita? Como classificar os partidos no Brasil. Observatório das Eleições.
|
|
7 |
Box, G. E., Jenkins, G. M., Reinsel, G. C., and Ljung, G. M. (2015). Time series analysis: forecasting and control. John Wiley & Sons.
|
|
8 |
Breiman, L. (2001). Random forests. Machine learning, 45:5–32.
|
|
9 |
Cipullo, D. and Le Moglie, M. (2022). To vote, or not to vote? Electoral campaigns and the spread of COVID-19. European Journal of Political Economy, 72:102118.
|
|
10 |
Constantino, S. M., Cooperman, A. D., and Moreira, T. M. (2021). Voting in a global pandemic: assessing dueling influences of COVID-19 on turnout. Social Science Quarterly, 102(5):2210–2235.
|
|
11 |
Desmet, K. and Wacziarg, R. (2022). JUE insight: Understanding spatial variation in COVID-19 across the United States. Journal of urban economics, 127:103332.
|
|
12 |
Fernandes, G. A. d. A. L. and de Almeida Lopes Fernandes, I. F. (2022). Populism and health. An evaluation of the effects of right-wing populism on the COVID-19 pandemic in Brazil. PLoS One, 17(12):e0269349.
|
|
13 |
Hartigan, J. A., Wong, M. A., et al. (1979). A k-means clustering algorithm. Applied statistics, 28(1):100–108.
|
|
14 |
Lima, E. E. C. d., Costa, L. C. C. d., Souza, R. F., Rocha, C. O. d. E., and Ichihara, M. Y. T. (2024). Presidential election results in 2018-2022 and its association with excess mortality during the 2020-2021 COVID-19 pandemic in brazilian municipalities. Cadernos de Saúde Pública, 40:e00194723.
|
|
15 |
Menuzzo, V. A., Santanchè, A., and Gomes-Jr, L. (2021). Evaluating the cohesion of municipalities’ discourse during the COVID-19 pandemic. In Anais do XXXVI Simpósio Brasileiro de Bancos de Dados, pages 295–300. SBC.
|
|
16 |
Rennó, L. R. (2020). The Bolsonaro voter: issue positions and vote choice in the 2018 brazilian presidential elections. Latin American Politics and Society, 62(4):1–23.
|
|
17 |
Rönn, M. M., Menzies, N. A., and Salomon, J. A. (2023). Vaccination and voting patterns in the U.S.: analysis of COVID-19 and flu surveys from 2010 to 2022. American Journal of Preventive Medicine, 65(3):458–466.
|
|
18 |
Sott, M. K., Bender, M. S., and da Silva Baum, K. (2022). COVID-19 outbreak in Brazil: health, social, political, and economic implications. International Journal of Health Services, 52(4):442–454.
|
|
19 |
Tiwari, S., Chanak, P., and Singh, S. K. (2022). A review of the machine learning algorithms for COVID-19 case analysis. IEEE Transactions on Artificial Intelligence, 4(1):44–59.
|
|
20 |
Wu, S. (2023). The spatial data analysis of determinants of U.S. presidential voting results in the rustbelt states during the COVID-19 pandemic. ISPRS International Journal of Geo-Information, 12(6):212.
|
|
21 |
Xavier, D. R., e Silva, E. L., Lara, F. A., e Silva, G. R., Oliveira, M. F., Gurgel, H., and Barcellos, C. (2022). Involvement of political and socio-economic factors in the spatial and temporal dynamics of COVID-19 outcomes in Brazil: a population-based study. The Lancet Regional Health–Americas, 10.
|
|