Inefficacious drugs against covid-19: analysis of sales, tweets, and search engines

ABSTRACT OBJECTIVE Assess the correlation between the sales of two drugs with no proven efficacy against covid-19, ivermectin and chloroquine, and other relevant variables, such as Google® searches, number of tweets related to these drugs, number of cases and deaths resulting from covid-19. METHODS...

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Main Authors: Irineu de Brito Junior (Author), Flaviane Azevedo Saraiva (Author), Nathan de Campos Bruno (Author), Roberto Fray da Silva (Author), Celso Mitsuo Hino (Author), Hugo Tsugunobu Yoshida Yoshizaki (Author)
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Published: Universidade de São Paulo, 2024-02-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Irineu de Brito Junior  |e author 
700 1 0 |a Flaviane Azevedo Saraiva  |e author 
700 1 0 |a Nathan de Campos Bruno  |e author 
700 1 0 |a Roberto Fray da Silva  |e author 
700 1 0 |a Celso Mitsuo Hino  |e author 
700 1 0 |a Hugo Tsugunobu Yoshida Yoshizaki  |e author 
245 0 0 |a Inefficacious drugs against covid-19: analysis of sales, tweets, and search engines 
260 |b Universidade de São Paulo,   |c 2024-02-01T00:00:00Z. 
500 |a 1518-8787 
500 |a 10.11606/s1518-8787.2024058005413 
520 |a ABSTRACT OBJECTIVE Assess the correlation between the sales of two drugs with no proven efficacy against covid-19, ivermectin and chloroquine, and other relevant variables, such as Google® searches, number of tweets related to these drugs, number of cases and deaths resulting from covid-19. METHODS The methodology adopted in this study has four stages: data collection, data processing, exploratory data analysis, and correlation analysis. Spearman's method was used to obtain cross-correlations between each pair of variables. RESULTS The results show similar behaviors between variables. Peaks occurred in the same or near periods. The exploratory data analysis showed shortage of chloroquine in the period corresponding to the beginning of advertising for the application of these drugs against covid-19. Both drugs showed a high and statistically significant correlation with the other variables. Also, some of them showed a higher correlation with drug sales when we employed a one-month lag. In the case of chloroquine, this was observed for the number of deaths. In the case of ivermectin, this was observed for the number of tweets, cases, and deaths. CONCLUSIONS The results contribute to decision making in crisis management by governments, industries, and stores. In times of crisis, as observed during the covid-19 pandemic, some variables can help sales forecasting, especially Google® and tweets, which provide a real-time analysis of the situation. Monitoring social media platforms and search engines would allow the determination of drug use by the population and better prediction of potential peaks in the demand for these drugs. 
546 |a EN 
546 |a ES 
546 |a PT 
690 |a Social Media 
690 |a Chloroquine 
690 |a Ivermectin 
690 |a Covid-19 
690 |a Search Engine 
690 |a Infodemic 
690 |a Pandemic 
690 |a SARS-CoV-2 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n Revista de Saúde Pública, Vol 58 (2024) 
787 0 |n http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102024000100205&lng=en&tlng=en 
787 0 |n http://www.scielo.br/pdf/rsp/v58/1518-8787-rsp-58-06.pdf 
787 0 |n https://doaj.org/toc/1518-8787 
856 4 1 |u https://doaj.org/article/c09f8ff41b8e4ee88fbdaeaf0ac0df37  |z Connect to this object online.