ABSTRACT
Objective: Determine the temporal and spatial structure of the severe acute respiratory syndrome virus (SARS-CoV-2) that causes coronavirus disease (COVID-19), in the cities of Cartagena and Barranquilla, Colombia, in order to take necessary actions to support contact tracing. Methods: Cross-sectional ecological study with spatial analysis based on kernel densities of variables, including cases, mobile application alerts, population vulnerability, multidimensional poverty index; inverse distance weighted spatial interpolation of active cases; and, finally, the spatial superposition technique as a final result. The database of the National Institute of Health of the cities of Cartagena and Barranquilla and the Department of National Statistics was used. Results: The analysis identified an upward epidemiological trend in cases in the two cities, and determined the spatial direction of disease spread in neighborhoods, through spatial interpolation. Intervention areas were detected in 15 neighborhoods in Cartagena and 13 in Barranquilla, 50 meters around active cases with fewer than 21 days of evolution and by geographical risk layers, as a mechanism to stop the spread of COVID-19. Conclusions: Spatial analysis proved to be a useful complementary methodology for contact tracing, by determining temporal and spatial structure and providing necessary scientific evidence for the application of direct intervention measures, where necessary, to reduce the spread of SARS-CoV-2.
Objetivo: Determinar a estrutura temporal e espacial do vírus da síndrome respiratória aguda grave (SARS-CoV-2, na sigla em inglês), causador da doença pelo coronavírus de 2019 (COVID-19, na sigla em inglês), nas cidades de Cartagena e Barranquilla, visando a tomar ações necessárias que apoiem o rastreamento de contatos. Métodos: Estudo ecológico transversal que inclui análise espacial baseada em densidade de Kernel de variáveis como casos, alertas de um aplicativo móvel, vulnerabilidade populacional, índice de pobreza multidimensional, aplicação de interpolação espacial (IDW, na sigla em inglês) de casos ativos e, por último, aplicação da técnica de sobreposição espacial como resultado final. Foram utilizadas as bases de dados do Instituto Nacional de Saúde para as cidades de Cartagena e Barranquilla e do Departamento Nacional de Estatística. Resultados: A análise determinou o comportamento epidemiológico ascendente dos casos nas duas cidades e identificou a direção espacial de propagação da doença nos bairros, por meio de interpolação espacial. Foram detectadas áreas para intervenção em 15 bairros de Cartagena e 13 de Barranquilla, em 50 metros ao redor dos casos ativos com menos de 21 dias de evolução e de acordo com as camadas de risco geográfico, como mecanismo para impedir a propagação da COVID-19. Conclusões: A análise espacial permitiu determinar a estrutura temporal e espacial como uma metodologia complementar útil para o rastreamento de contatos, e forneceu a evidência científica necessária para a aplicação de medidas de intervenção direta, quando necessário, visando a reduzir o contágio pelo SARS-CoV-2.
ABSTRACT
BACKGROUND: The higher number of cases and deaths caused by COVID-19 in Colombia occurred during the third epidemic peak, where the Mu variant was associated with 50% of the cases. OBJECTIVE: To evaluate the association between the clinical outcome of COVID-19 with health conditions and SARS-CoV-2 lineages. METHODS: In this study, clinical metadata and SARS-CoV-2 lineages from 535 patients with different degrees of COVID-19 severity were obtained after the SARS-CoV-2 genomic surveillance in Colombia. Then, the associations between these variables were determined using a multidimensional unfolding analysis. RESULTS: Asymptomatic, symptomatic, severe, and deceased outcomes represented 15.2%, 29.7%, 7.3%, and 47.8% of the cases, respectively. Males tend to develop more serious COVID-19, and severe or fatal outcomes were typically observed in patients aged >60 years with comorbidities, including chronic obstructive pulmonary disease, heart disease, kidney disease, obesity, asthma, and smoking history. The SARS-CoV-2 Mu and Gamma variants dominated the third epidemic peak and accounted for most fatal cases with odd ratio values of 128.2 (CI 53.0-310.1) and 18.6 (CI 8.294-41.917). CONCLUSION: This study shows the high impact of SARS-CoV-2 lineages with higher prevalence on public health and the importance of monitoring COVID-19 risk factors to control the associated mortality.
ABSTRACT
BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to cause very high morbidity and mortality throughout Latin American countries. However, few population-based seroprevalence surveys have been conducted to quantify attack rates and characterize drivers of transmission. METHODS: We conducted a population-based cross-sectional study to assess the seroprevalence of antibodies against SARS-CoV-2 in ten cities in Colombia between September and December 2020. The study involved multi-stage cluster sampling at each city. Participants provided a serum sample and answered a demographic and risk factor questionnaire. Prior infection by SARS-CoV-2 was ascertained using the "SARS-CoV-2 Total (COV2T) Advia Centaur - Siemens" chemiluminescence assay. FINDINGS: A total of 17863 participants from 7320 households participated in the study. Seroprevalence varied substantially between cities, ranging from 26% (95%CI 23-29 %) in Medellín to 68% (95%CI 62-74 %) in Guapi. There were no differences in seroprevalence by sex, but seropositivity was higher in certain ethnic groups. There was substantial heterogeneity in seroprevalence within cities, driven to a large extent by a strong association between socioeconomic stratum and seropositivity. INTERPRETATION: Colombia has been one of the Latin American countries most affected by the COVID-19 pandemic. This study documented very high attack rates in several Colombian cities by the end of 2020 and identified key drivers of heterogeneities including ethnicity and socioeconomic stratum. Few studies of seroprevalence of SARS-CoV-2 have been conducted in Latin America, and therefore this study contributes to the fundamental understanding of the pandemic in the region. FUNDING: The study was sponsored by, Ministerio de Ciencia y Tecnología e Innovación -CT361/2020, Ministerio de Salud y Protección Social, Fundación Universitaria del Norte, Imperial College of London, Universidad Nacional de Colombia (Sede Medellín), Universidad de Córdoba, California University, Unidad Nacional de Gestión del Riesgo, Centro de Atención y Diagnóstico de Enfermedades Infecciosas -CDI-, Centro Internacional de Entrenamiento e Investigaciones Médicas -CIDEIM-, Departamento Administrativo Nacional de Estadística - DANE, Fondo Nacional de Turismo -FONTUR-, Secretarías de Salud Departamentales, Distritales y Municipales and Instituto Nacional de Salud.
ABSTRACT
BACKGROUND: Contact tracing is a crucial part of the public health surveillance toolkit. However, it is labor-intensive and costly to carry it out. Some countries have faced challenges implementing contact tracing, and no impact evaluations using empirical data have assessed its impact on COVID-19 mortality. This study assesses the impact of contact tracing in a middle-income country, providing data to support the expansion and optimization of contact tracing strategies to improve infection control. METHODS: We obtained publicly available data on all confirmed COVID-19 cases in Colombia between March 2 and June 16, 2020. (N = 54,931 cases over 135 days of observation). As suggested by WHO guidelines, we proxied contact tracing performance as the proportion of cases identified through contact tracing out of all cases identified. We calculated the daily proportion of cases identified through contact tracing across 37 geographical units (32 departments and five districts). Further, we used a sequential log-log fixed-effects model to estimate the 21-days, 28-days, 42-days, and 56-days lagged impact of the proportion of cases identified through contact tracing on daily COVID-19 mortality. Both the proportion of cases identified through contact tracing and the daily number of COVID-19 deaths are smoothed using 7-day moving averages. Models control for the prevalence of active cases, second-degree polynomials, and mobility indices. Robustness checks to include supply-side variables were performed. RESULTS: We found that a 10 percent increase in the proportion of cases identified through contact tracing is related to COVID-19 mortality reductions between 0.8% and 3.4%. Our models explain between 47%-70% of the variance in mortality. Results are robust to changes of specification and inclusion of supply-side variables. CONCLUSION: Contact tracing is instrumental in containing infectious diseases. Its prioritization as a surveillance strategy will substantially impact reducing deaths while minimizing the impact on the fragile economic systems of lower and middle-income countries. This study provides lessons for other LMIC.