Our project is addressing this challenge by proposing a solution to the critical points of COVID-19 spread based on data collected from government agencies, identifying the factors of human activity that could be associated with the spread of the virus. This allows to inform the community in a quick, effective and simple way about which places are the focus of propagation and should be avoided taking into account the analyses made; knowing that the main focuses are high population density, high flow of people, agglomeration, among others.
In addition, the project seeks to prevent the sources of infection and predict them, taking into account the user's recurrent places and their current state of health; data that will be taken from the application, and then provide the user with a result that takes into account the danger to which they will be exposed when going to any different area.
Our project is in the first phase in which the process is shown at the beginning of the application, where a previous analysis of the person with data provided by it is performed, then when the app is finished you can choose your place of interest and thus get the probability percentage of being a focus of contagion depending on where you want to go.
Our app stands out and is different from the others because of its accessibility and ease when making use of it. It is effective because its analyses are very accurate depending on the location chosen, it also takes into account the population density to clearly calculate the risk of contagion that the person might have and whether it is possible for it to be a vector of the virus.
As the number of cases of COVID-19 increases, the need to find solutions or methods to reduce the rate of infection increases.
In the development of this project, global data on the number of people infected by the virus are considered to corroborate the pattern that the greater the population density, the greater the number of people infected.
Local data provided by government authorities in a small area of Colombia in the department of Antioquia was used to confirm the expected pattern.
The objective of this project will be to inform the user about the conditions of their destination, taking into account important factors that influence the spread of the virus, it will also identify whether or not the user is a vector of infection and give recommendations according to the result obtained, such as quarantine and communication with their health system.
For development, global statistics were observed to find a pattern of infections and danger scores were assigned based on this.
The resources of information provided in the documents sent by Space Apps specifically the NASA SEDAC Global COVID-19 viewer were taken into account to obtain general information about the behavior of the virus on the planet. All this was complemented with other local sources such as national pages in order to obtain more detailed information and data from departmental statistics.
The scarcity of available data, especially on case counts of the disease to date, greatly limits the accuracy of the estimates and does not allow for reliable forecasts of the spread of the epidemic. It was also noted that the number of case growth has been uneven in Latin America due to increased testing and that abrupt changes from day to day are a specific product of late outcomes, therefore the data may not be as accurate.
Another problem identified is that despite multiple information about the virus, there was no consistency in the ideas and even contradictions could be found that made it difficult to obtain accurate data, in addition, some data was outdated and delayed the search for statistical reports.
Office software such as word, excel, powerpoint and pdf were used; in addition, the program ArcGis, specifically ArcMap, was used to design a local map where the population density is compared with the number of infected people. Hardware such as computers and cell phones were used for the development of the project, along with Python programming language.
The analysis has some very important strengths. Firstly, the early pattern of person-to-person transmission, the exponential way in which the data has grown and the difference in the number of people infected in Latin America compared to China, the USA and Spain, which shows that taking early isolation measures had a positive effect on lowering the infection curve.
There was an increase in the ability to search for information and in statistical analysis, deepening the information on the controls taken in different countries and how these have given a mostly positive result. The possibility of working within an interdisciplinary framework with people of different ages and knowledge, in order to obtain a project full of good ideas and information that is easily accessible to the public and can be used quickly and easily.
https://drive.google.com/file/d/1AsGfxJER-STdY5DmUC0XoosdWtCExtrS/view?usp=sharing
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