Colomb Medica
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Throughout the COVID-19 pandemic, the main risk factors associated with the progression to severe disease or death have been typically advanced age, diabetes mellitus, obesity, high blood pressure, heart disease, and chronic pneumopathy. Because of their immunosuppression status, persons with HIV were also expected to have a higher susceptibility to infection or a poor clinical evolution. So far, this has not been confirmed to happen, giving way to hypotheses about the role of immunosuppression or the use of antiretrovirals, which could explain this paradox. In this article we present the existing data on the epidemiology and characteristics of HIV-COVID-19 co-infection, discuss the available evidence on the possible factors involved in the evolution of individuals affected by both viruses, analyze other determinants that may negatively affect persons with HIV during the pandemic, and present recommendations for the prevention and care of COVID-19 infection in the context of HIV.
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Review
Non-pharmaceutical interventions for containment, mitigation and suppression of COVID-19 infection.
The best scientific evidence is required to design effective Non-pharmaceutical interventions to help policymakers to contain COVID-19. ⋯ Some countries are focused on establishing travel restrictions, isolation of identified cases, and high-risk people. Others have a combination of mandatory quarantine and other drastic social distancing measures. The timing to implement the interventions varied from the first fifteen days after detecting the first case to more than 30 days. The effectiveness of isolated non-pharmaceutical interventions may be limited, but combined interventions have shown to be effective in reducing the transmissibility of the disease, the collapse of health care services, and mortality. When the number of new cases has been controlled, it is necessary to maintain social distancing measures, self-isolation, and contact tracing for several months. The policy decision-making in this time should be aimed to optimize the opportunities of saving lives, reducing the collapse of health services, and minimizing the economic and social impact over the general population, but principally over the most vulnerable. The timing of implementing and lifting interventions could have a substantial effect on those objectives.
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Currently, there are several mathematical models that have been developed to understand the dynamics of COVID-19 infection. However, the difference in the sociocultural contexts between countries requires the specific adjustment of these estimates to each scenario. This article analyses the main elements used for the construction of models from epidemiological patterns, to describe the interaction, explain the dynamics of infection and recovery, and to predict possible scenarios that may arise with the introduction of public health measures such as social distancing and quarantines, specifically in the case of the pandemic unleashed by the new SARS-CoV-2/COVID-19 virus. ⋯ Mathematical models are highly relevant for making objective and effective decisions to control and eradicate the disease. These models used for COVID-19 have supported and will continue to provide information for the selection and implementation of programs and public policies that prevent associated complications, reduce the speed of the virus spread and minimize the occurrence of severe cases of the disease that may collapse health systems.
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Coronavirus illness 2019 (COVID-19) is an airways infection caused by the new coronavirus (SARS-CoV-2) which has been quickly disseminated all over the world, affecting to the general population including women in pregnancy time. As being a recent infection, the evidence that supports the best practices for the management of the infection during pregnancy is limited, and most of the questions have not been completely solved yet. ⋯ Its purpose is to promote useful interventions to prevent new infections as well as prompt and adequate attention to avoid serious complications or deaths, trying to be adapted to the different contexts in which attention to expectant mothers is provided. Guidelines are set within a well-scientific evidence and available recommendations up to date.