COVID-19 mortality in two waves of the pandemic in Cali, Colombia, before and during vaccination roll-out.

Objective: To describe the variation in COVID-19 mortality among residents of Cali, Colombia, in the second wave of the pandemic, before vaccines, and in the fourth wave, with vaccination roll-out in process, taking into account variables of sex, age group, comorbidities, and interval between onset of symptoms and death, and to estimate the number of deaths averted by vaccination. Methods: A cross-sectional study of second wave and fourth wave deaths and vaccination coverage. The frequencies of attributes of deceased population in the two waves were compared, including comorbidities. Machado's method was used to calculate an estimate of the number of deaths averted in the fourth wave. Results: There were 1 133 deaths in the second wave and 754 deaths in the fourth wave. It was calculated that approximately 3 763 deaths were averted in the fourth wave in Cali in the context of vaccination roll-out. Conclusions: The decline in COVID-19-associated mortality observed supports the continuation of the vaccination program. Given the lack of data to explain other possible reasons for this decline, such as on the severity of novel viral variants, the limitations of the study are discussed.

[Predictions of a SEIR model for COVID-19 cases in Cali-Colombia]. / Predicciones de un modelo SEIR para casos de COVID-19 en Cali, Colombia.

OBJECTIVE: To predict the number of cases of COVID-19 in the city of Cali-Colombia through the development of a SEIR model. METHODS: A SEIR compartmental deterministic model was used considering the states: susceptible (S), exposed (E), infected (I) and recovered (R). The model parameters were selected according to the literature review, in the case of the case fatality rate data from the Municipal Secretary of Health were used. Several scenarios were considered taking into account variations in the basic number of reproduction (R0), and the prediction until april 9 was compared with the observed data. RESULTS: Through the SEIR model it was found that with the highest basic number of reproduction [2,6] and using the case fatality rate for the city of 2,0%, the maximum number of cases would be reached on June 1 with 195 666 (prevalence). However, when comparing the observed with the expected cases, at the beginning the observed occurrence was above the projected, but then the trend changes decreasing the slope. CONCLUSIONS: SEIR epidemiological models are widely used methods for projecting cases in infectious diseases, however it must be taken into account that they are deterministic models that can use assumed parameters and could generate imprecise results.

[SARS-coV-2 spatio - temporal analysis in Cali, Colombia]. / Análisis espacio-temporal del SARS-COV-2 en Cali, Colombia.

OBJECTIVE: To describe the spatio-temporal distribution of the COVID-19 in the city of Cali during the first month of the epidemic. METHODS: An exploratory analysis of spatial data was carried out, consisting of a kernel density analysis and the presence of spatial patterns was verified by the K-Ripley function. RESULTS: The spatial distribution of the cases tends to initially concentrate in the north and south of the city, with a changing dynamic towards the east and west. CONCLUSIONS: The identified spatial pattern may be influenced by the isolation measures taken at the local and national level, but the effect of the low access of the general population to diagnostic tests, delays and restraints to know the results cannot be ruled out and even possible biases due to difficulties in the technique of taking the sample or its conservation.

Predictions of a seir model for COVID-19 cases in Cali-Colombia / Predicciones de un modelo seir para casos de COVID-19 en Cali, Colombia

Objective To predict the number of cases of COVID-19 in the city of Cali-Colombia through the development of a SEIR model. Methods A SEIR compartmental deterministic model was used considering the states: susceptible (S), exposed (E), infected (I) and recovered (R). The model parameters were selected according to the literature review, in the case of the case fatality rate data from the Municipal Secretary of Health were used. Several scenarios were considered taking into account variations in the basic number of reproduction (R0), and the predic-tion until april 9 was compared with the observed data. Results Through the SEIR model it was found that with the highest basic number of reproduction [2,6] and using the case fatality rate for the city of 2,0%, the maximum number of cases would be reached on June 1 with 195 666 (prevalence). However, when comparing the observed with the expected cases, at the beginning the observed occurrence was above the projected, but then the trend changes decreasing the slope. Conclusions SEIR epidemiological models are widely used methods for projecting cases in infectious diseases, however it must be taken into account that they are deterministic models that can use assumed parameters and could generate imprecise results.

Spatial modeling and socioeconomic inequities of COVID-19 in the urban area of the city of Cali, Colombia.

COVID-19 has spread worldwide with a high variability in cases and mortality between populations. This research aims to assess socioeconomic inequities of COVID-19 in the city of Cali, Colombia, during the first and second peaks of the pandemic in this city. An ecological study by neighborhoods was carried out, were COVID-19 cases were analyzed using a Bayesian hierarchical spatial model that includes potential risk factors such as the index of unsatisfied basic needs and socioeconomic variables as well as random effects to account for residual variation. Maps showing the geographic patterns of the estimated relative risks as well as exceedance probabilities were created. The results indicate that in the first wave, the neighborhoods with the greatest unsatisfied basic needs and low socioeconomic strata, were more likely to report positive cases for COVID-19. For the second wave, the disease begins to spread through different neighborhoods of the city and middle socioeconomic strata presents the highest risk followed by the lower strata. These findings indicate the importance of measuring social determinants in the study of the distribution of cases due to COVID-19 for its inclusion in the interventions and measures implemented to contain contagions and reduce impacts on the most vulnerable populations.

Effect of Ivermectin on Time to Resolution of Symptoms Among Adults With Mild COVID-19: A Randomized Clinical Trial.

Importance: Ivermectin is widely prescribed as a potential treatment for COVID-19 despite uncertainty about its clinical benefit. Objective: To determine whether ivermectin is an efficacious treatment for mild COVID-19. Design, Setting, and Participants: Double-blind, randomized trial conducted at a single site in Cali, Colombia. Potential study participants were identified by simple random sampling from the state's health department electronic database of patients with symptomatic, laboratory-confirmed COVID-19 during the study period. A total of 476 adult patients with mild disease and symptoms for 7 days or fewer (at home or hospitalized) were enrolled between July 15 and November 30, 2020, and followed up through December 21, 2020. Intervention: Patients were randomized to receive ivermectin, 300 µg/kg of body weight per day for 5 days (n = 200) or placebo (n = 200). Main Outcomes and Measures: Primary outcome was time to resolution of symptoms within a 21-day follow-up period. Solicited adverse events and serious adverse events were also collected. Results: Among 400 patients who were randomized in the primary analysis population (median age, 37 years [interquartile range {IQR}, 29-48]; 231 women [58%]), 398 (99.5%) completed the trial. The median time to resolution of symptoms was 10 days (IQR, 9-13) in the ivermectin group compared with 12 days (IQR, 9-13) in the placebo group (hazard ratio for resolution of symptoms, 1.07 [95% CI, 0.87 to 1.32]; P = .53 by log-rank test). By day 21, 82% in the ivermectin group and 79% in the placebo group had resolved symptoms. The most common solicited adverse event was headache, reported by 104 patients (52%) given ivermectin and 111 (56%) who received placebo. The most common serious adverse event was multiorgan failure, occurring in 4 patients (2 in each group). Conclusion and Relevance: Among adults with mild COVID-19, a 5-day course of ivermectin, compared with placebo, did not significantly improve the time to resolution of symptoms. The findings do not support the use of ivermectin for treatment of mild COVID-19, although larger trials may be needed to understand the effects of ivermectin on other clinically relevant outcomes. Trial Registration: ClinicalTrials.gov Identifier: NCT04405843.

Predicciones de un modelo SEIR para casos de COVID-19 en Cali, Colombia

RESUMEN Objetivo Predecir el número de casos de COVID-19 en la ciudad de Cali-Colombia mediante el desarrollo de un modelo SEIR. Métodos Se utilizó un modelo determinista compartimental SEIR considerando los estados: susceptibles (S), expuestos (E), infectados (I) y recuperados (R). Los parámetros del modelo fueron seleccionados de acuerdo a la revisión de literatura. En el caso de la tasa de letalidad, se usaron los datos de la Secretaría de Salud Municipal de Cali. Se plantearon varios escenarios teniendo en cuenta variaciones en el número básico de reproducción (R0) y en la tasa de letalidad;además, se comparó la predicción hasta el 9 de abril con los datos observados. Resultados A través del modelo SEIR se encontró que, con el número básico de reproducción más alto (2,6) y utilizando la letalidad calculada para la ciudad de 2,0%, el número máximo de casos se alcanzaría el primero de junio con 195 666 (prevalencia);sin embargo, al comparar los casos observados con los esperados, al inicio la ocurrencia observada estaba por encima de la proyectada;pero luego cambia la tendencia con una disminución marcada de la pendiente. Conclusiones Los modelos epidemiológicos SEIR son métodos muy utilizados para la proyección de casos en enfermedades infecciosas;sin embargo, se debe tener en cuenta que son modelos deterministas que pueden utilizar parámetros supuestos y podrían generar resultados imprecisos.(AU) ABSTRACT Objective To predict the number of cases of COVID-19 in the city of Cali-Colombia through the development of a SEIR model. Methods A SEIR compartmental deterministic model was used considering the states: susceptible (S), exposed (E), infected (I) and recovered (R). The model parameters were selected according to the literature review, in the case of the case fatality rate data from the Municipal Secretary of Health were used. Several scenarios were considered taking into account variations in the basic number of reproduction (R0), and the prediction until april 9 was compared with the observed data. Results Through the SEIR model it was found that with the highest basic number of reproduction [2,6] and using the case fatality rate for the city of 2,0%, the maximum number of cases would be reached on June 1 with 195 666 (prevalence). However, when comparing the observed with the expected cases, at the beginning the observed occurrence was above the projected, but then the trend changes decreasing the slope. Conclusions SEIR epidemiological models are widely used methods for projecting cases in infectious diseases, however it must be taken into account that they are deterministic models that can use assumed parameters and could generate imprecise results.(AU)