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.
Background Contact tracing is a key 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 to our knowledge have assessed its impact on COVID-19 mortality. This study assesses the impact of contact tracing in a middle-income country and provides data to support the expansion of contact tracing strategies with the aim of improving 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). We proxied contact tracing performance as the proportion of cases identified through contact tracing out of all cases identified, as suggested by WHO guidelines. 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 the daily number of COVID-19 deaths. 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 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 to contain infectious diseases and its prioritization as a surveillance strategy will have a substantial impact on reducing deaths while minimizing the impact on the fragile economic systems of lower and middle-income countries. This study provides lessons for other LMIC.
Objetivo. Determinar la estructura temporal y espacial del virus del síndrome respiratorio agudo grave (SARS-CoV-2, por su sigla en inglés), causante de la enfermedad por coronavirus (COVID-19, por su sigla en inglés) en las ciudades de Cartagena y Barranquilla para tomar acciones necesarias que apoyen el rastreo de contactos. Métodos. Estudio ecológico transversal que incluye análisis espacial basado en densidades Kernel de variables como casos, alertas desde una aplicación móvil, vulnerabilidad poblacional, índice de pobreza multidimensional, aplicación de interpolación espacial (IDW, por su sigla en inglés) de los casos activos y, por último, la aplicación de la técnica de superposición espacial como resultado final. Se utilizó la base de datos del Instituto Nacional de Salud de las ciudades de Cartagena y Barranquilla y el Departamento de Estadística Nacional. Resultados. El análisis determinó el comportamiento epidemiológico ascendente de los casos en las dos ciudades e identificó la dirección espacial de propagación de la enfermedad en los barrios, a través de la interpolación espacial. Se detectaron las zonas en las cuales intervenir en 15 barrios de Cartagena y 13 de Barranquilla, en 50 metros alrededor de los casos activos con menos de 21 días de evolución y según las capas de riesgo geográfico, como mecanismo para frenar la propagación de la COVID-19. Conclusiones. El análisis espacial permitió determinar la estructura temporal y espacial como metodología complementaria útil para el rastreo de contactos, y aportó la evidencia científica necesaria para la aplicación de medidas de intervención directa donde fuera necesario, dirigidas a reducir el contagio del SARS-CoV-2.
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