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An algorithm to estimate on-stream the number of COVID-19 cases

A study that presents a method to mitigate the epidemic effects by estimating the number of COVID-19 cases without having to wait for laboratory confirmations


Description of the Study:

  • Title: Estimating COVID-19 cases and outbreaks on-stream through phone calls.
  • Principal investigators: Ezequiel Alvarez, Daniela Obando, Sebastian Crespo, Enio Garcia, Nicolas Kreplak and Franco Marsico.
  • Centers of Implementation: International Center for Advanced Studies (ICAS) and Ministerio de Salud de la Provincia de Buenos Aires.
  • Study Population: Population of the different districts of Buenos Aires Province.
  • Methods: The calls to the 148 COVID-line were modeled as background (proportional to population) plus signal (proportional to infected) and they were fit in the Province of Buenos Aires (Argentina) with coefficient of determination R2 > 0.85.

Objectives of the Study:

Principal Objective: To present an algorithm to estimate on-stream the number of COVID-19 cases using the data from telephone calls to a COVID-line.

Secondary Objectives:
(1) To describe the COVID-line data and present the details of the mathematical model to estimate the number of cases using the phone calls data.
(2) To show how the model works in Buenos Aires Province and how it can be used to track on-stream the epidemic.
(3) To present the Early Outbreak Alarm and show its details in Villa Azul (Quilmes) case.


More about this Study:

Scientific Context: The COVID-19 epidemic has been causing global damage to practically all aspects of world society since early 2020. The difficulties in controlling the epidemic are in part due to a crucial combination of being highly contagious, having a long incubation period during which infections are possible a few days before symptoms onset, having mild or asymptomatic cases and also because the diagnosis may take a few days after contacting the Health Care system. So having information on changes in the epidemic evolution or outbreaks rise before laboratory-confirmation is crucial in decision making for Public Health policies.

Added value: This algorithm has been one of the main tools in the Province of Buenos Aires Health Care system dashboard during the epidemic, and its current and upgrade versions are still being used to track the epidemic and detect outbreaks.

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