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vol.13 suppl.1EFECTOS DEL TRATAMIENTO CON PLASMA DE CONVALECIENTE EN PACIENTES CON COVID-19: REVISIÓN SISTEMÁTICA Y METAANÁLISISOverestimation of COVID-19 cases based on results of the rRT-PCR for detection of SARS-CoV-2 author indexsubject indexarticles search
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Revista Argentina de Salud Pública

Print version ISSN 1852-8724On-line version ISSN 1853-810X


BERGERO, Paula  and  GUISONI, Nara. Mathematical modelling of dengue-COVID-19 coinfection: a first approximation. Rev. argent. salud pública [online]. 2021, vol.13, suppl.1, pp.11-11. ISSN 1852-8724.


: At the beginning of the pandemic, the WHO warned that the simultaneous transmission of dengue and COVID-19 in some regions could lead to cases of coinfection. Symptoms overlap and additional difficulty in management are some of the possible complications. In July of2020, the PAHO declared an epidemiological alert for dengue in the context of a pandemic, adding underreporting, delayed consultation, and interruption of entomological control, among possible aggravating factors. However, the impact of the overlap is not yet clear. The aim of this work was to analyze the co-infection curves in different co-epidemic scenarios. We consider possible effects of the pandemic on the epidemiology of dengue.


: We developed a mathematical model of co-infection, of a deterministic type, based on previous models of both diseases.


: For a given dengue outbreak, the final fraction of co-infection depends on the reproductive number of COVID-19. The co-infection curve depends on the overlap of the epidemics, the overlap area being an estimator of the final fraction. A quarantine that reduces COVID-19 cases would also reduce co-infection, being more effective the earlier. If quarantine affects the dengue dynamics, the modelpredicts an increase and advance in cases, whose effect on the co-infection curve depends on the overlap dynamics.


: The proposed model offers a first approach to make co-infection visible and understand the mechanisms that could affect it.

Keywords : Dengue; COVID-19 Pandemic; Coinfection; Mathematical Modelling; Argentina.

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