Epidemiological Algorithm for Early Detection of COVID-19 Cases in a Mexican Oncologic Center
An early detection tool for latent COVID-19 infections in oncology staff and patients is essential to prevent outbreaks in a cancer center. (1) Background: In this study, we developed and implemented two early detection tools for the radiotherapy area to identify COVID-19 cases opportunely. (2) Meth...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/10/3/462 |
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| author | Moisés González-Escamilla Diana Cristina Pérez-Ibave Carlos Horacio Burciaga-Flores Vanessa Natali Ortiz-Murillo Genaro A. Ramírez-Correa Patricia Rodríguez-Niño Rafael Piñeiro-Retif Hazyadee Frecia Rodríguez-Gutiérrez Fernando Alcorta-Nuñez Juan Francisco González-Guerrero Oscar Vidal-Gutiérrez María Lourdes Garza-Rodríguez |
| author_facet | Moisés González-Escamilla Diana Cristina Pérez-Ibave Carlos Horacio Burciaga-Flores Vanessa Natali Ortiz-Murillo Genaro A. Ramírez-Correa Patricia Rodríguez-Niño Rafael Piñeiro-Retif Hazyadee Frecia Rodríguez-Gutiérrez Fernando Alcorta-Nuñez Juan Francisco González-Guerrero Oscar Vidal-Gutiérrez María Lourdes Garza-Rodríguez |
| author_sort | Moisés González-Escamilla |
| collection | DOAJ |
| description | An early detection tool for latent COVID-19 infections in oncology staff and patients is essential to prevent outbreaks in a cancer center. (1) Background: In this study, we developed and implemented two early detection tools for the radiotherapy area to identify COVID-19 cases opportunely. (2) Methods: Staff and patients answered a questionnaire (electronic and paper surveys, respectively) with clinical and epidemiological information. The data were collected through two online survey tools: Real-Time Tracking (R-Track) and Summary of Factors (S-Facts). Cut-off values were established according to the algorithm models. SARS-CoV-2 qRT-PCR tests confirmed the positive algorithms individuals. (3) Results: Oncology staff members (<i>n</i> = 142) were tested, and 14% (<i>n</i> = 20) were positives for the R-Track algorithm; 75% (<i>n</i> = 15) were qRT-PCR positive. The S-Facts Algorithm identified 7.75% (<i>n</i> = 11) positive oncology staff members, and 81.82% (<i>n</i> = 9) were qRT-PCR positive. Oncology patients (<i>n</i> = 369) were evaluated, and 1.36% (<i>n</i> = 5) were positive for the Algorithm used. The five patients (100%) were confirmed by qRT-PCR. (4) Conclusions: The proposed early detection tools have proved to be a low-cost and efficient tool in a country where qRT-PCR tests and vaccines are insufficient for the population. |
| first_indexed | 2024-03-09T19:46:27Z |
| format | Article |
| id | doaj.art-7ea9f16af34e4b2eab53de46aee02123 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-09T19:46:27Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-7ea9f16af34e4b2eab53de46aee021232023-11-24T01:21:56ZengMDPI AGHealthcare2227-90322022-03-0110346210.3390/healthcare10030462Epidemiological Algorithm for Early Detection of COVID-19 Cases in a Mexican Oncologic CenterMoisés González-Escamilla0Diana Cristina Pérez-Ibave1Carlos Horacio Burciaga-Flores2Vanessa Natali Ortiz-Murillo3Genaro A. Ramírez-Correa4Patricia Rodríguez-Niño5Rafael Piñeiro-Retif6Hazyadee Frecia Rodríguez-Gutiérrez7Fernando Alcorta-Nuñez8Juan Francisco González-Guerrero9Oscar Vidal-Gutiérrez10María Lourdes Garza-Rodríguez11Centro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoCentro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoCentro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoFacultad de Medicina, Universidad Autónoma de Nuevo León, Av. Francisco I. Madero S/N, Mitras Centro Monterrey, Monterrey 64460, MexicoDepartment of Molecular Science, The University of Texas Rio Grande Valley School of Medicine, McAllen, TX 78504, USACentro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoCentro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoCentro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoCentro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoCentro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoCentro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoCentro Universitario Contra el Cáncer, Universidad Autónoma de Nuevo León, Hospital Universitario “Dr. José Eleuterio González”, Av. Francisco I. Madero S/N, Mitras Centro, Monterrey 64460, MexicoAn early detection tool for latent COVID-19 infections in oncology staff and patients is essential to prevent outbreaks in a cancer center. (1) Background: In this study, we developed and implemented two early detection tools for the radiotherapy area to identify COVID-19 cases opportunely. (2) Methods: Staff and patients answered a questionnaire (electronic and paper surveys, respectively) with clinical and epidemiological information. The data were collected through two online survey tools: Real-Time Tracking (R-Track) and Summary of Factors (S-Facts). Cut-off values were established according to the algorithm models. SARS-CoV-2 qRT-PCR tests confirmed the positive algorithms individuals. (3) Results: Oncology staff members (<i>n</i> = 142) were tested, and 14% (<i>n</i> = 20) were positives for the R-Track algorithm; 75% (<i>n</i> = 15) were qRT-PCR positive. The S-Facts Algorithm identified 7.75% (<i>n</i> = 11) positive oncology staff members, and 81.82% (<i>n</i> = 9) were qRT-PCR positive. Oncology patients (<i>n</i> = 369) were evaluated, and 1.36% (<i>n</i> = 5) were positive for the Algorithm used. The five patients (100%) were confirmed by qRT-PCR. (4) Conclusions: The proposed early detection tools have proved to be a low-cost and efficient tool in a country where qRT-PCR tests and vaccines are insufficient for the population.https://www.mdpi.com/2227-9032/10/3/462COVID-19SARS-CoV-2preventionelectronic early detection tools |
| spellingShingle | Moisés González-Escamilla Diana Cristina Pérez-Ibave Carlos Horacio Burciaga-Flores Vanessa Natali Ortiz-Murillo Genaro A. Ramírez-Correa Patricia Rodríguez-Niño Rafael Piñeiro-Retif Hazyadee Frecia Rodríguez-Gutiérrez Fernando Alcorta-Nuñez Juan Francisco González-Guerrero Oscar Vidal-Gutiérrez María Lourdes Garza-Rodríguez Epidemiological Algorithm for Early Detection of COVID-19 Cases in a Mexican Oncologic Center Healthcare COVID-19 SARS-CoV-2 prevention electronic early detection tools |
| title | Epidemiological Algorithm for Early Detection of COVID-19 Cases in a Mexican Oncologic Center |
| title_full | Epidemiological Algorithm for Early Detection of COVID-19 Cases in a Mexican Oncologic Center |
| title_fullStr | Epidemiological Algorithm for Early Detection of COVID-19 Cases in a Mexican Oncologic Center |
| title_full_unstemmed | Epidemiological Algorithm for Early Detection of COVID-19 Cases in a Mexican Oncologic Center |
| title_short | Epidemiological Algorithm for Early Detection of COVID-19 Cases in a Mexican Oncologic Center |
| title_sort | epidemiological algorithm for early detection of covid 19 cases in a mexican oncologic center |
| topic | COVID-19 SARS-CoV-2 prevention electronic early detection tools |
| url | https://www.mdpi.com/2227-9032/10/3/462 |
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