COVID-19 pandemic in Panama: lessons of the unique risks and research opportunities for Latin America

The bibliometric landscape of infectious disease research in Panama (1990-2019)

Background

This work aims to analyze the landscape of scientific publications on subjects related to One Health and infectious diseases in Panama. The research questions are: How does the One Health research landscape look like in Panama? Are historical research efforts aligned with the One Health concept? What infectious diseases have received more attention from the local scientific community since 1990?

Methods

Boolean searches on the Web of Science, SCOPUS and PubMed were undertaken to evaluate the main trends of publications related to One Health and infectious disease research in the country of Panama, between 1990 and 2019.

Results

4546 publications were identified since 1990, including 3564 peer-reviewed articles interconnected with One Health related descriptors, and 211 articles focused particularly on infectious diseases. A pattern of exponential growth in the number of publications with various contributions from Panamanian institutions was observed. The rate of multidisciplinary research was moderate, whereas those of interinstitutional and intersectoral research ranged from low to very low. Research efforts have centered largely on protozoan, neglected and arthropod-borne diseases with a strong emphasis on malaria, Chagas and leishmaniasis.

Conclusion

Panama has scientific capabilities on One Health to tackle future infectious disease threats, but the official collaboration schemes and strategic investment to develop further competencies need to be conciliated with modern times, aka the pandemics era. The main proposition here, addressed to the government of Panama, is to launch a One Health regional center to promote multidisciplinary, interinstitutional and intersectoral research activities in Panama and beyond.

Analyzing Spanish-Language Public Sentiment in the Context of a Pandemic and Social Unrest: The Panama Case

Over the past decade, an increase in global connectivity and social media users has changed the way in which opinions and sentiments are shared. Platforms such as Twitter can act as public forums for expressing opinions on non-personal matters, but often also as an outlet for individuals to share their feelings and personal thoughts. This becomes especially evident during times of crisis, such as a massive civil disorder or a pandemic. This study proposes the estimation and analysis of sentiments expressed by Twitter users of the Republic of Panama during the years 2019 and 2020. The proposed workflow is comprised of the extraction, quantification, processing and analysis of Spanish-language Twitter data based on Sentiment Analysis. This case of study highlights the importance of developing natural language processing resources explicitly devised for supporting opinion mining applications in Latin American countries, where language regionalisms can drastically change the lexicon on each country. A comparative analysis performed between popular machine learning algorithms demonstrated that a version of a distributed gradient boosting algorithm could infer sentiment polarity contained in Spanish text in an accurate and time-effective manner. This algorithm is the tool used to analyze over 20 million tweets produced between the years of 2019 and 2020 by residents of the Republic of Panama, accurately displaying strong sentiment responses to events occurred in the country over the two years that the analysis performed spanned. The obtained results highlight the potential that methodologies such as the one proposed in this study could have for transparent government monitoring of responses to public policies on a population scale.

Keeping Citizens Informed and Engaged During the COVID-19 Pandemic Using #YoMeInformoPMA: A Case from Latin America

Social media platforms contribute to the dissemination of information and encourage communication between health agencies and the public, especially during health crises. Public health agencies must engage in carefully crafted educational, communicative, and interactive practices to be effective in their messaging to build relationships with the public. Using quantitative content, social network, and thematic analysis, this study examined 2,500 tweets from April to August 2020 that included the hashtag #YoMeInformoPMA. Panama's Public Health Ministry created the #YoMeInformoPMA hashtag to keep citizens informed and engaged during the COVID-19 pandemic. Research on social media use and implementation in Latin America during the COVID-19 pandemic, to inform and engage the public, is limited. Therefore, the aim of this investigation was to analyze strategies, themes, multimedia formats, key actors, and overall communications patterns of a Latin American health community hashtag. Our results determined that actors using the hashtag #YoMeInformoPMA mainly used an interactive strategy, a message that aims to promote casual conversations, advice, and problem-solving. Findings highlighted evidence of a communication strategy by specific actors in this network, supporting recent studies that indicate engagement between the public and health agencies can take place on social media. Practical implications and recommendations for communication preparation via social media for future health crises are discussed.

Epidemiology of COVID-19 in the State of Sergipe/Brazil and Its Relationship with Social Indicators

A pandemic is capable of generating a great impact, not only from the point of view of health, but also socioeconomically. In March 2020, the World Health Organization (WHO) declared that a new pandemic situation had arisen, due to the SARS-CoV-2 virus, whose probable origin was zoonotic. The largest number of cases of this disease is concentrated in the United States of America (USA), India, and Brazil. The mortality rate is estimated at 3.4%, but regional differences may exist, and places with a high demographic density have become true epicentres and may be related to higher rates of transmission. In addition to the above, lower human development indexes (HDI) can be related to worse outcomes, especially in the North and Northeast regions of Brazil since they are the least developed places. The Northeast region is the second-most-affected place in the number of COVID-19 cases in Brazil. An analytical observational study of an ecological type was carried out from April to October 2020 to assess the epidemiological situation of COVID-19 in the state of Sergipe and specifically to analyse the incidence of cases and deaths resulting from COVID-19 in the different health regions of the state of Sergipe, in relation to the values of the HDI and demographic density. During the study period, 84,325 cases of COVID-19 were identified, in which 2205 resulted in death. In most of the regions studied, there was a positive association between the number of cases and deaths and the greater the demographic density, but there was no increase in the risk of becoming ill, nor of dying the lower the HDI. Large and crowded cities are places of greatest vulnerability to illness, due to their greater capacity of transmitting the virus; however, further studies are needed to identify other factors that are decisive in the outcomes of this new disease.

Performance of a Point of Care Test for Detecting IgM and IgG Antibodies Against SARS-CoV-2 and Seroprevalence in Blood Donors and Health Care Workers in Panama

Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic, which has reached 28 million cases worldwide in 1 year. The serological detection of antibodies against the virus will play a pivotal role in complementing molecular tests to improve diagnostic accuracy, contact tracing, vaccine efficacy testing, and seroprevalence surveillance. Here, we aimed first to evaluate a lateral flow assay's ability to identify specific IgM and IgG antibodies against SARS-CoV-2 and second, to report the seroprevalence estimates of these antibodies among health care workers and healthy volunteer blood donors in Panama. We recruited study participants between April 30th and July 7th, 2020. For the test validation and performance evaluation, we analyzed serum samples from participants with clinical symptoms and confirmed positive RT-PCR for SARS-CoV-2, and a set of pre-pandemic serum samples. We used two by two table analysis to determine the test positive and negative percentage agreement as well as the Kappa agreement value with a 95% confidence interval. Then, we used the lateral flow assay to determine seroprevalence among serum samples from COVID-19 patients, potentially exposed health care workers, and healthy volunteer donors. Our results show this assay reached a positive percent agreement of 97.2% (95% CI 84.2-100.0%) for detecting both IgM and IgG. The assay showed a Kappa of 0.898 (95%CI 0.811-0.985) and 0.918 (95% CI 0.839-0.997) for IgM and IgG, respectively. The evaluation of serum samples from hospitalized COVID-19 patients indicates a correlation between test sensitivity and the number of days since symptom onset; the highest positive percent agreement [87% (95% CI 67.0-96.3%)] was observed at ≥15 days post-symptom onset (PSO). We found an overall antibody seroprevalence of 11.6% (95% CI 8.5-15.8%) among both health care workers and healthy blood donors. Our findings suggest this lateral flow assay could contribute significantly to implementing seroprevalence testing in locations with active community transmission of SARS-CoV-2.