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Community centered care data analysis, times of Covid-19

For the past few weeks, the global health emergency caused by Covid-19 has put many questions in my thoughts, from general to more specific in many dimensions. We all know that we should prepare better in the future and this morning reviewing the concept of community centered care “At the Epicenter of the Covid-19 Pandemic and Humanitarian Crises in Italy: Changing Perspectives on Preparation and Mitigation,(2020), Nacoti, Ciocca, ... ” added by the hospital in Bergamo Italy, sparked my interest... how to be prepared, how potentially implement and be smart into the distribution, finally using data from Korea(KCDC and DS4C), I started analyzing looking for responses.

From the data analysis perspective if we can understand the entities and important variables geographically distributed in a region, we can analyze the activity of this approach at least in theory dimension.

Also with an analysis of infection-cases we can explore the more affected regions and maybe create a distributed strategy of community-care-centers, and also distribute medic personal.

As Covid-19 seriously affects the situation of our elderly, we could analyze the concentrations of this population. Example:


This information is using a ratio(coefficient) of eldery population in south-korea, but could be an option to create a better plan based on data analysis. I also included into the dashboard dimension elements like, schools, kinders, and others to explore ideas and variations related to how we can be prepared better in the future.

Taking this line of analysis, can we create community centers close to most probable affected regions? How many elements should we include into entities to define an affected region? 

In addition to this approach, what happens if we have the route of affected people? Here another idea using the dataset of routed patients.

Many elements to connect but seems an interesting layer of information to use and improve our response when we hit on this type of global contingencies.

Pending questions:
  • Is valid the approach to explore the most affected population to include into the analysis of community centered care distribution?
  • Is a valid point to explore other institutions like schools, kinder to include into the analysis of community centers?
  • The route of patients could be an interesting variable to explore dynamic community care centers? 
  • Can we use the data dimension layer to be better prepared in front exceptions and emergencies like our current situation like Covid-19?
Other questions to analyze? Or maybe looking for contribute,  open to connect @nickbortolotti

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