Use of medicinal plants for COVID-19 prevention and respiratory symptom treatment during the pandemic in Cusco, Peru: A cross-sectional survey

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

The burden of the COVID-19 pandemic in Peru has led to people seeking alternative treatments as preventives and treatment options such as medicinal plants. This study aimed to assess factors associated with the use of medicinal plants as preventive or treatment of respiratory symptom related to COVID-19 during the pandemic in Cusco, Peru.

Method

A web-based cross-sectional study was conducted on general public (20- to 70-year-old) from August 31 to September 20, 2020. Data were collected using a structured questionnaire via Google Forms, it consisted of an 11-item questionnaire that was developed and validated by expert judgment using Aiken’s V (Aiken’s V > 0.9). Both descriptive statistics and bivariate followed by multivariable logistic regression analyses were conducted to assess factors associated with the use of medicinal plants for COVID-19 prevention and respiratory symptom treatment during the pandemic. Prevalence ratios (PR) with 95% Confidence Interval (CI), and a P-value of 0.05 was used to determine statistical significance.

Results

A total of 1,747 respondents participated in the study, 80.2% reported that they used medicinal plants as preventives, while 71% reported that they used them to treat respiratory symptoms. At least, 24% of respondents used medicinal plants when presenting with two or more respiratory symptoms, while at least 11% used plants for malaise. For treatment or prevention, the multivariate analysis showed that most respondents used eucalyptus (p < 0.001 for both), ginger (p < 0.022 for both), spiked pepper (p < 0.003 for both), garlic (p = 0.023 for prevention), and chamomile (p = 0.011 for treatment). The respondents with COVID-19 (p < 0.001), at older ages (p = 0.046), and with a family member or friend who had COVID-19 (p < 0.001) used more plants for prevention. However, the respondents with technical or higher education used less plants for treatment (p < 0.001).

Conclusion

There was a significant use of medicinal plants for both prevention and treatment, which was associated with several population characteristics and whether respondents had COVID-19.

Related collections

Most cited references 100

Record: found
Abstract: found
Article: not found

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Chaolin Huang, Yeming Wang, Xingwang Li … (2020)

Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.

0 comments Cited 22217 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

An interactive web-based dashboard to track COVID-19 in real time

Ensheng Dong, Hongru Du, Lauren Gardner (2020)

In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.

0 comments Cited 4690 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Immune responses in COVID-19 and potential vaccines: Lessons learned from SARS and MERS epidemic

(2020)

As the world is witnessing the epidemic of COVID-19, a disease caused by a novel coronavirus, SARS-CoV-2, emerging genetics and clinical evidences suggest a similar path to those of SARS and MERS. The rapid genomic sequencing and open access data, together with advanced vaccine technology, are expected to give us more knowledge on the pathogen itself, including the host immune response as well as the plan for therapeutic vaccines in the near future. This review aims to provide a comparative view among SARS-CoV, MERS-CoV and the newly epidemic SARS-CoV-2, in the hope to gain a better understanding of the host-pathogen interaction, host immune responses, and the pathogen immune evasion strategies. This predictive view may help in designing an immune intervention or preventive vaccine for COVID-19 in the near future.

0 comments Cited 715 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Magaly Villena-Tejada:

ORCID: https://orcid.org/0000-0003-4756-0251

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draft

Ingrid Vera-Ferchau: Role: Data curationRole: Formal analysisRole: InvestigationRole: Methodology

Anahí Cardona-Rivero: Role: Data curationRole: Formal analysisRole: Methodology

Rina Zamalloa-Cornejo: Role: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: ValidationRole: Visualization

Maritza Quispe-Florez: Role: Data curationRole: InvestigationRole: Writing – original draft

Zany Frisancho-Triveño: Role: Data curationRole: Formal analysisRole: MethodologyRole: Software

Rosario C. Abarca-Meléndez: Role: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draft

Susan G. Alvarez-Sucari: Role: Data curationRole: Formal analysisRole: MethodologyRole: Writing – original draft

Christian R. Mejia: Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing

Jaime A. Yañez:

ORCID: https://orcid.org/0000-0002-9713-1829

Role: ConceptualizationRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing

Mohd Adnan: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS One

Journal ID (publisher-id): plos

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 22 September 2021

Publication date Collection: 2021

Publication date PMC-release: 22 September 2021

Volume: 16

Issue: 9

Electronic Location Identifier: e0257165

Affiliations

[1 ] Departamento Académico de Farmacia, Facultad de Ciencias de la Salud, Universidad Nacional de San Antonio Abad del Cusco, Cusco, Peru

[2 ] Departamento Académico de Matemáticas y Estadística, Facultad de Ciencias, Universidad Nacional de San Antonio Abad del Cusco, Cusco, Peru

[3 ] Departamento Académico de Biología, Facultad de Ciencias, Universidad Nacional de San Antonio Abad del Cusco, Cusco, Peru

[4 ] Escuela Profesional de Farmacia y Bioquímica, Facultad de Ciencias de la Salud, Universidad Nacional de San Antonio Abad del Cusco, Cusco, Peru

[5 ] Facultad de Medicina, Universidad Continental, Lima, Peru

[6 ] Vicerrectorado de Investigación, Universidad Norbert Wiener, Lima, Peru

[7 ] Gerencia Corporativa de Asuntos Científicos y Regulatorios, Teoma Global, Lima, Peru

University of Hail, SAUDI ARABIA

Author notes

Competing Interests: The authors declare that they have no conflict of interests. JAY is currently employed by the commercial company Teoma Global, but there is no conflict of interest related to any of the medicinal plants or commercial products. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

* E-mail: magaly.villena@ 123456unsaac.edu.pe (MVT); jaime.yanez@ 123456uwiener.edu.pe (JAY)

Author information

Magaly Villena-Tejada https://orcid.org/0000-0003-4756-0251

Jaime A. Yañez https://orcid.org/0000-0002-9713-1829

Article

Publisher ID: PONE-D-21-15800

DOI: 10.1371/journal.pone.0257165

PMC ID: 8457479

PubMed ID: 34550994

SO-VID: da82c807-26db-47cc-bbd7-606dffc10dd5

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 12 May 2021

Date accepted : 24 August 2021

Page count

Figures: 0, Tables: 4, Pages: 18

Funding

Funded by: Universidad Nacional de San Antonio Abad del Cusco (UNSAAC)

Award ID: R-446-2020-UNSAAC

Award Recipient :

ORCID: https://orcid.org/0000-0003-4756-0251

Magaly Villena-Tejada

The authors would like to thank the Universidad Nacional de San Antonio Abad del Cusco (UNSAAC) grant R-446-2020-UNSAAC. The funder provided support in the form of expenses related to the data collection from the survey, commercial license for the statistical software, translation and publication fees. The funder did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the Author Contributions section.

Custom metadata

Data Availability Anonymized data set supporting the findings of this study is stored at the Dryad data repository ( https://datadryad.org/stash/share/Yke7zt5MuVeD7aE8ie5G_jrbYPE8ZaRCLH58FuYI9QI).

Outbreaks COVID-19

ScienceOpen disciplines: Uncategorized

Data availability:

ScienceOpen disciplines: Uncategorized

Comments

Comment on this article

scite_

Cited by 27

See all cited by

Most referenced authors 2,096

See all reference authors

Use of medicinal plants for COVID-19 prevention and respiratory symptom treatment during the pandemic in Cusco, Peru: A cross-sectional survey

Read this article at

Abstract

Background

Method

Results

Conclusion

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 100

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

An interactive web-based dashboard to track COVID-19 in real time

Immune responses in COVID-19 and potential vaccines: Lessons learned from SARS and MERS epidemic

Author and article information

Contributors

Journal

Affiliations

Author notes

Author information

Article

History

Page count

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 295

Cited by 27

Most referenced authors 2,096