June 2020
COVID-19: THE IECS DEVELOPED AN INTERACTIVE TOOL TO EVALUATE THE IMPACT OF THE PANDEMIC ON THE HEALTH SYSTEMS OF LATIN AMERICA AND THE CARIBBEAN
WITH FINANCING FROM THE INTER-AMERICAN DEVELOPMENT BANK (IDB), IT IS INTENDED FOR HEALTH DECISION-MAKERS AND THEIR WORK TEAMS IN 26 COUNTRIES IN THE REGION AND ALLOWS YOU TO ANTICIPATE HOW THE IMPLEMENTATION OF DIFFERENT MEASURES HAS AN EFFECT ON THE EVOLUTION OF THE CURVE OF CASES AND THE POSSIBLE DATE OF SATURATION OF HEALTH RESOURCES (INTENSIVE THERAPY BEDS AND RESPIRATORS).
A friendly, interactive and free access tool developed by the Institute of Clinical and Health Effectiveness (IECS) will allow health decision-makers in Latin America and the Caribbean and their work teams to can project sufficiently in advance the result of the different public health measures on the evolution of the curve of COVID-19 infections, deaths and occupancy of intensive care beds and respirators, directors of the institution reported.
The model, which was financed by Inter-American Development Bank (IDB) and will be available in a online platform, was carried out by two areas of the IECS: the Center for Implementation and Innovation of Public Policies (CIIPS) and Health Technology Assessment Department.
“Aspires to be a useful tool for local decision makers that allows them to frame problems and potential solutions, since it provides key information both on the dynamics of viral transmission and on the impact of public policies implemented on health systems, in particular on their critical resources, under various scenarios, adapted to the specific characteristics of the country", point out the researchers who worked on the development of the tool, who will do this Tuesday the 30th in a webinar organized by the IDB.
Among other questions, the model attempts to answer: How many infections and deaths could be expected per day according to the measures implemented? When are the peaks of cases and deaths expected in the different scenarios? How will the occupancy curve of intensive care beds and respirator use evolve? When could critical health services be saturated?
But, fundamentally, guides how these indicators can change depending on the policies adopted, their duration and their degree of compliance. And it would allow, for example, to regulate cycles of greater or lesser relaxation of confinement and other social distancing measures without overwhelming the response capacity of the health system.
“Beyond the fact that this model is not intended to be a prediction model, the objective is that the decision maker or his technical team can parameterize [assign value to] the variables and adjust them to their own context to apply the necessary public health policies and have an overview of their effects well in advance", emphasizes Dr. Adolfo Rubinstein, director of the CIIPS, of the IECS.
“It is an example of how evidence can guide the execution of public policies, even in contexts of high uncertainty”, highlights Dr. Andrés Pichon Riviere, executive director of the IECS.
The so-called “Comprehensive Model of Preparedness and Response of Health Systems in Latin America and the Caribbean” is focused on the following countries: Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Colombia, Costa Rica, Chile, Ecuador, El Salvador , Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Dominican Republic, Suriname, Trinidad and Tobago, Uruguay and Venezuela.
HOW IT WAS MADE AND HOW IT WORKS
To develop the tool, IECS researchers carried out a systematic review of all available sources (from publications in scientific journals and preprint servers to organizational websites, media reports and posts on social networks) to define different epidemiological and health parameters. For example, incubation time, days with symptoms prior to hospitalization or duration of stay in critical care units.
“These indicators can be easily modified based on the appearance of new evidence or according to the reality of each country,” clarifies Dr. Rubinstein.
On the other hand, a exhaustive survey of the resources and critical inputs of the health systems of each country, including the number of general and intensive care beds, the number of respirators and the availability of doctors, nurses or respiratory kinesiologists.
On the screen, Users of the model can observe a traffic light that represents the different levels of restriction of public health measures: from not taking any to suspending classes, expanding testing and decreeing mandatory social isolation (quarantine). The implementation of these measures and the level of adherence of the population are linked to a R0 or “basic reproductive number,” which is an average measure of the number of people who become infected from each positive case.
“Unlike traditional forecasting sites, public health interventions, healthcare resources (e.g. number of beds or doctors) and epidemiological parameters can be modified to run the model computation again and obtain different results”, adds Pigeon Riviere.
Thus, The authorities can project the evolution of the curves in the coming months and how much the beds could be saturated if they apply a more or less flexible quarantine, which, in turn, will be related to a R0 different that can also be configured. For example, you can anticipate what would happen if months are interspersed with a R0 de 1,1 and 1,3, or if the R0 at 1,0 or 1,1 for three months and then released to reach 1,2 or 1,3. Or what would happen if that indicator remained at 1,5.
In all cases, it is not a model that inevitably predicts what will happen with COVID-19 in a country or what policy they will adopt. "This interactive tool allows you to generate scenarios, update results and see the impact of the measures in terms of the evolution of the curve and the capacity of the health system, so that helps decide a strategy to contain, mitigate or suppress the epidemic", says Rubinstein.
In the coming weeks, the authors of this tool plan to train technical teams in the region to use it.