Reading Data Sets
Digital collection of annotated data sets.
Digital collection of annotated data sets.
Research update by the COVID-19 Data Working Group.
Often considered a "social disease" HIV/AIDS can be linked to certain social groups and subsequent behaviors within these groups. Taking this a step further, poor prognosis in treatment can be linked to social stratification. In the early 90's in Baltimore, a study was performed that linked race to reception of timely medical intervention. Modifications to the programs, such as removing insurance status as a determining factor for care, drastically reduced racially-biased outcomes. In the Rwandan campaign, Partners in Health instituted proximal care to rural regions-- the areas where care was most significantly lacking. This, in turn, can greatly mitigate the effects of social violence. Moreover, structural interventions (such as changing the accepted and prescribed practices of international bodies) can greatly reduce the effects of disease within a population. This includes such things as when and how drugs are administered, who is receiving medications, and changing conventional practices proven to enhance the spread of disease.
The article primarily argues that, although there are interventions and steps in place, "biosecurity" is not currently a viable or stable entity. The four main areas stated in this article (emerging infectious disease, bioterrorism, cutting-edge life sciences, and food safety) are not formerly understood or controlled enough to make a feasible and honest plan that ensures safety. While steps can be taken and measures used, the dynamic nature of these fields and the human condition prevents us from establishing a truly flawless safety net at this time. One only has to look at the re-emergence of previously extinct diseases such as measles, the prevalence of pertussis, or the assertion of chemotherapy's deadliness to see we do not have a full handle on any of these fields.
This is a list of analytics by the COVID-19 Data Group.