Data Science Statistics Correlations of Mobility and Covid19 Transmission

Attached you can find 5 articles (links to be downloaded) all related to
“Geo-located digital platform feature as a metric to measure the efficiency mobility in Covid19 times. Is the generalized model valid for under-developing markets?”

The research proposal should include the following (separate) sections:
1) problem statement
2) literature overview
3) research question
4) methodology
5) references (the 5 articles)

PLAGARISM – Turnitin score for plagiarism should be below 20% – needs to be checked PLEASE, even with other tools

The problem statement should indicate which problem the research sets out to solve. It provides a context of the value of conducting research in the proposed area.

Problem

The problem in this research to be identified in the articles is the relevance of the metric of using the Mobility index (from Google, Twitter, apple, Facebook) to show important relevance in under-developing markets. (Latin America countries)

Is using geo-location from digital platforms provides suffice information to understand the impact on the rate infections?
Is this metric useful in Latin America where the density of the population not only is high but the precarious social circumstances can impact the measurement.?

The question is that it has been used several models to use geo-located feature from social media to create quantities variables as Mobility index.
This research is to validate the case studies presented in the articles, to analyze the reproducibility of them globally as they state.

This is good reference for countries like USA, Italy, Spain, China, but the observations lead that the index presented in the studies (2 of the articles at least) show that it is related but at what extension.
In Mexico the mobility started again in June and the number of cases (infections) still growing with and without the people were locked down (mobility index is showing lightly increase but still growing the number of cases).

Mexico, as instance is using Facebook, Twitter and Google to provide mobility index, but after the beginning of the ‘new normal’, this mobility has increased again and the number of cases keep growing with the same rate. Is this metric really efficient or worth to measure in Latin America Markets.? This won’t be demonstrated in this research but it will open a door to debate more. I want to focus on understanding the correlation between Ratio contagions and mobility to open a discussion how is observed in under-developing markets with the open source data.

The literature overview should demonstrate how the 5 scientific research papers connect.

**The Problem and the other sections can be modified if that is needed to reach the goal. If you can connect the papers in different way

An explicit research gap should be identified. This is very important. The gap would be the factor that some countries with high density the metric doesn’t’ show the density effect of the population. How do we explain that number of cases keep increasing in Brazil and Mexico and the lockdown measures have been in place for 3 months, and after the ease the lockdown measures the tendency of increase didn’t change. That is the gap

To what extent can you cluster the papers in different approaches or perspectives?
Where is existing knowledge “thin”?
Has to be critical and creative.

** The research question should follow logically from the research gap identified in the overview / Make sure that it is not a yes/no question
Here is a link to help to do a good research question based on my previous comments
https://writingcenter.gmu.edu/guides/how-to-write-a-research-question

The methodology section should explain what kind of research (it will be quantitative using apple/google mobility metrics, we won’t use twitter to keep the same line of original methodoly ) is needed to answer the research question.

There needs to be a description of how the research on those articles will look like and which data it will be collected.
We have to mention which type of analysis you are going to use, in this case it will be regression-based technique (relations (mobility, death-rate, recovering – are assumed to be linear)

The amount of words should be between 700-800 words

Attached you can find the articles and the example of a paper that used other ‘problem’/’research question.

Here are 5 the papers, the main task is create a summary of each that can help to connect them in the construction of the ‘research question’ and show the summaries in the overview.

The Study of the Effects of Mobility Trends on the Statistical Models of the COVID-19 Virus Spreading (4 pages)
https://www.ejgm.co.uk/article/the-study-of-the-effects-of-mobility-trends-on-the-statistical-models-of-the-covid-19-virus-8212

Report 26 Reduction in mobility and COVID-19 transmission (the first 17 pages have the content)
https://spiral.imperial.ac.uk:8443/handle/10044/1/79643

Correlations of Mobility and Covid-19 Transmission in Global Data (the first 17 pages have the content)
https://via.hypothes.is/https://www.medrxiv.org/content/10.1101/2020.05.06.20093039v3#annotations:t5o__qhdEeqKlVdd5xdqXQ

The Twitter Social Mobility Index: Measuring Social Distancing Practices from Geolocated Tweets
https://arxiv.org/abs/2004.02397

Understanding epidemic data and statistics: A case study of COVID19
https://onlinelibrary.wiley.com/doi/10.1002/jmv.25885

Relevant Editorials and tools to get ideas of the content to validate the research question

Facebook and Google Survey Data May Help Map Covid-19’s Spread
https://www.wired.com/story/survey-data-facebook-google-map-covid-19-carnegie-mellon/

Social Distancing Scoreboard
https://www.unacast.com/covid19/social-distancing-scoreboard

How Apple and Google’s Social Distancing Maps Work
https://www.wired.com/story/apple-google-social-distancing-maps-privacy/

Understanding Human Mobility from Twitter
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0131469&type=printable

Open Data Source you can check the mobility index in all countries

https://www.apple.com/covid19/mobility

https://www.google.com/covid19/mobility/

———- JUST ADDING MORE INFORMATION ——

Basically the articles show that there are correlation between mobility and infections but based on observations like Mexico case, there is a relation but it is not heavy. With or without mobility the trend In Mexico continues up ….different to other countries like Spain, Italy, USA and UK the infections got reduced. Brazil, Peru and Mexico is not the case, specially because the poor conditions and the density of the population in small places to live. Even they reached 60% of mobility index, the cases didn’t decreased.

Some articles are big but it is for the statistics per country, you can focus on

Industrialized countries
– USA
– Spain
– Italy

Non industrialized countries
– Mexico
– Peru
– Brazil

My teacher mentioned this:
Being ambitious is never a problem! ? It sounds as a good entry to further research the correlation between infections and staying-at-home. In a sense, you are hypothesizing whether the relation is moderated by the variable type of market. That is certainly interesting. Just make sure that it is clear how you can research this moderation. You will need to define “different markets” clearly and show you can use the data/features to come to an interesting analysis. Moderation effects could be done by a regression-based technique. If you have other ideas of how to test it, feel free. The idea of the assignment is that it becomes clear that the possible moderation can be seen as a research gap in the 5 articles that you bring in. Furthermore, it needs to be clear how you are going to research it (what data, which technique) to answer your research question. Practical relevance is, of course, very clear.

Also it was suggested that in the methodology we can insert that observation that in poor countries the relevance is not as high. You can insert a results section after the methodology.

Use the example of the document/paper that it is attached to get a better idea.

thanks so much