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Renato%20Gonzlez-4 Instituto Tecnológico de Santo Domingo - INTEC delivers COVID-19 risk management and predictive model to Public Health

Publication date:

06 October 2021

INTEC delivers COVID-19 risk management and predictive model to Public Health

SANTO DOMINGO. A multidisciplinary team of the Instituto Tecnológico de Santo Domingo (INTEC), in conjunction with the Laboratory of Innovation and Territorial Intelligence of the Inter-American Development Bank (IDB-LAB), designed a model for predecir el epidemiological behavior for the COVID-19, which will allow estimating its evolution in the country and its impact on the population in terms of public health.

When presenting the tool to the Ministry of Public Health, the professor Renato González, specialist in Data Science of the INTEC Engineering Area and leader of the project, and doctor Manuel Colome, a specialist in epidemiology from the Health Sciences Area and a member of the design team, indicated that the model allows handling data on morbidity, mortality, lethality, health planning and non-pharmacological interventions to manage the pandemic.

"The prediction of COVID-19 is a dynamic, stochastic-situational problem, in which government measures and social behavior play a determining role in the behavior of the virus expansion, in addition to the biological characteristics of the agent," he said. González, in the meeting that was led by the Minister of Public Health, Daniel Rivera, he rector of INTEC, Julio Sánchez Maríñez and engineer Smeldy Ramírez, specialist in private sector development at BIDLAB.

El predictive model, developed after a hard work of 16 months, allows manage el epidemic risk in emergencies caused by epidemics and health crisis, to take preventive and reactive actions by the competent authorities, by geographic areas and population sectors, tending to slow down the expansion rate of the virus and incidence rates in vulnerable and high-risk groups.

In addition, it takes into account the application of state policies of containment, mitigation and suppression, along with social behavior in terms of social distancing measures, use of masks, hand hygiene, adherence to vaccination, among others. In this way, risk can be managed efficiently, without significantly affecting the economy.

Gather%C3%B3n_SP Instituto Tecnológico de Santo Domingo - INTEC delivers COVID-19 risk management and predictive model to Public Health

Dr. Daniel Rivera said that the institution "works with basic health indicators and has as a central goal the fight against COVID-19, reduce the pandemic, avoid possible curves and have effective systems for possible variants, give firm answers that allow the return to normality ”.

Eladio Pérez, Vice Minister of Collective Health, will be responsible for coordinating with INTEC, the actions for the application of the model, following an agreement with the Ministry of Public Health that would integrate a technical team made up of INTEC researchers and technical staff from the government entity. to give continuity to the project in a second stage.

Predictive Model Modules

The COVID-19 Risk Management and Predictive Model –designed exclusively for the Dominican Republic–, is composed of three modules that meet specific objectives and that are interrelated to provide the necessary information for the management of the pandemic at the macro and micro determinants.

The macro-predictive model of the incidence curve allows the elaboration of scenarios and assumptions of behavior of the epidemiological expansion curve of COVID-19, considering key performance indicators, such as social distancing, hand hygiene, isolation and quarantine.

The sample design model on the prevalence of the SARS-CoV-2 virus (the cause of the COVID-19 disease) aims to estimate the prevalence of virus infection in the population and identify existing active cases, recovered and host susceptibility through a field epidemiology study.

“We will use databases of Social Security, SIUBEN, Civil, Demographic and Cartographic Registry and the National Statistics Office to create a representative sample of the Dominican population by geographic areas, high-risk groups, age and vulnerable groups according to the dimensions of inequality ”, explained González.

Finally, the model for tracking infected cases and predicting micro-predictive outbreaks is based on “Machine Learning” and “Network Analysis” to detect outbreaks and quantify their individual impact on the geographically located population and demographic conditions. socioeconomic and environmental conditions of the affected families throughout the national territory.

INTEC team

Manuel_Colome Instituto Tecnológico de Santo Domingo - INTEC entrega a Salud Pública modelo predictivo y de gestión de riesgo del COVID-19

The team that designed the model is made up of, in addition to Professors González and Colomé, Boanerges Domínguez and Felipe Llaugel, data specialists; Eladio Pérez, specialist in epidemiology; José Achécar Chupani, specialist in statistics and four students from INTEC's School of Software Engineering.

The meeting was also attended by Víctor Gómez-Valenzuela, vice-rector for Research and Liaison at INTEC; Miguel Robiou and Fernando Santamaría, dean and associate dean, respectively, of the Health Sciences Area.