Adapting for the COVID-19 pandemic in Ecuador, a characterization of hospital strategies and patients.

The World Health Organization (WHO) declared coronavirus disease-2019 (COVID-19) a global pandemic on 11 March 2020. In Ecuador, the first case of COVID-19 was recorded on 29 February 2020. Despite efforts to control its spread, SARS-CoV-2 overran the Ecuadorian public health system, which became one of the most affected in Latin America on 24 April 2020. The Hospital General del Sur de Quito (HGSQ) had to transition from a general to a specific COVID-19 health center in a short period of time to fulfill the health demand from patients with respiratory afflictions. Here, we summarized the implementations applied in the HGSQ to become a COVID-19 exclusive hospital, including the rearrangement of hospital rooms and a triage strategy based on a severity score calculated through an artificial intelligence (AI)-assisted chest computed tomography (CT). Moreover, we present clinical, epidemiological, and laboratory data from 75 laboratory tested COVID-19 patients, which represent the first outbreak of Quito city. The majority of patients were male with a median age of 50 years. We found differences in laboratory parameters between intensive care unit (ICU) and non-ICU cases considering C-reactive protein, lactate dehydrogenase, and lymphocytes. Sensitivity and specificity of the AI-assisted chest CT were 21.4% and 66.7%, respectively, when considering a score >70%; regardless, this system became a cornerstone of hospital triage due to the lack of RT-PCR testing and timely results. If health workers act as vectors of SARS-CoV-2 at their domiciles, they can seed outbreaks that might put 1,879,047 people at risk of infection within 15 km around the hospital. Despite our limited sample size, the information presented can be used as a local example that might aid future responses in low and middle-income countries facing respiratory transmitted epidemics.

Cycle Threshold Values in the Context of Multiple RT-PCR Testing for SARS-CoV-2.

PURPOSE: Discharge or follow up of confirmed coronavirus disease 2019 (COVID-19) cases depend on accurate interpretation of RT-PCR. Currently, positive/negative interpretations are based on amplification instead of quantification of cycle threshold (Ct) values, which could be used as proxies of patient infectiousness. Here, we measured Ct values in hospitalized confirmed COVID-19 patients at different times and its implications in diagnosis and follow up. PATIENTS AND METHODS: Observational study between March 17th-May 12th, 2020 using multiple RT-PCR testing. A cohort of 118 Hispanic hospitalized patients with confirmed COVID-19 diagnosis in a reference hospital in Quito, Ecuador. Multiple RT-PCR tests were performed using deep nasal swab samples and the assessment of SARS-CoV-2 genes N, RdRP, and E. RESULTS: Patients' median age was of 49 years (range: 24-91) with a male majority (62.7%). We found increasing levels of Ct values in time, with a mean Ct value of 29.13 (n = 61, standard deviation (sd) = 5.55) for the first test and 34.38 (n = 60, sd = 4), 35.52 (n = 20, sd = 2.85), and 36.12 (n = 6, sd = 3.28), for the second, third, and fourth tests, respectively. Time to RT-PCR lack of amplification for all tests was of 34 days while time to RT-PCR Ct values >33 was of 30 days. CONCLUSION: Cycle thresholds can potentially be used to improve diagnosis, management and control. We found that turnover time for negativity can be large for hospitalized patients and that 11% cases persisted with infectious Ct values for more time than the current isolation recommendations.