Merge pull request #253 from dfarrow0/dfarrow_readme

update readme

Author: krivard

README.md

@@ -8,26 +8,22 @@ This is the home of [Delphi](https://delphi.cmu.edu/)'s epidemiological data
 API. See our [API documentation](https://cmu-delphi.github.io/delphi-epidata/)
 for details on the available data sets, APIs, and clients.
 
-# COVID-19 Notice
+## COVIDcast
 
-We are working on collecting several new data sources that may be useful for
-nowcasting and forecasting ILI during the COVID-19 pandemic.  Each of these will
-make these available as soon as individually possible, through our [covidcast
-endpoint](https://cmu-delphi.github.io/delphi-epidata/api/covidcast.html).
+At the present, our primary focus is developing and expanding the
+[COVIDcast API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast.html),
+which offers a number of data streams relating to the ongoing COVID-19
+pandemic and powers the [COVIDcast project](https://covidcast.cmu.edu/).
 
-For a list of many other data sources relevant to COVID-19, publicly available
-through external sites, we have compiled a simple
-[spreadsheet](https://docs.google.com/spreadsheets/d/16Nn_3ZvSLnpxRyA2DkoMMzyrd11-AlGJXasS0owln88/edit#gid=0).
+Our other, non-COVID data sources remain generally available on a best-effort
+basis. However, non-COVID sources should be held to scrutiny at this time since
+they were designed to serve as indicators of typical seasonal ILI
+(influenza-like illness), not pandemic ILI or CLI (COVID-like illness).
 
-**Note:** apart from the COVID-19-specific data sources described above, the
-rest of this repository was built to support modeling and forecasting efforts
-surrounding seasonal influenza (and dengue).  All other data sources than those
-in our covidcast endpoint should be **held to great scrutiny** (if they are even
-to be considered at all in this pandemic period), since they were designed to
-serve as indicators of typical seasonal ILI (influenza-like illness), and
-certainly not pandemic ILI or CLI (covid-like illness).
+For a high-level introduction to the COVIDcast API, see our recent
+[blog post](https://delphi.cmu.edu/blog/2020/10/07/accessing-open-covid-19-data-via-the-covidcast-epidata-api/).
 
-## Contributing
+# Contributing
 
 If you are interested in contributing:
 
@@ -37,36 +33,19 @@ If you are interested in contributing:
   [open an issue](https://github.com/cmu-delphi/delphi-epidata/issues/new)
   describing your idea.
 
-## Citing
+# Citing
 
 We hope that this API is useful to others outside of our group, especially for
 epidemiological and other scientific research. If you use this API and would
 like to cite it, we would gratefully recommend the following copy:
 
 > David C. Farrow,
 > Logan C. Brooks,
-> Aaron Rumack,
 > Ryan J. Tibshirani,
 > Roni Rosenfeld
 > (2015).
 > _Delphi Epidata API_.
 > https://github.com/cmu-delphi/delphi-epidata
 
-# Related work
-
- - Cook, Samantha, et al. "Assessing Google flu trends performance in the United
-   States during the 2009 influenza virus A (H1N1) pandemic." PloS one 6.8
-   (2011): e23610.
- - Broniatowski, David A., Michael J. Paul, and Mark Dredze. "National and local
-   influenza surveillance through Twitter: an analysis of the 2012-2013
-   influenza epidemic." (2013): e83672.
- - Dredze, Mark, et al. "HealthTweets. org: A Platform for Public Health
-   Surveillance using Twitter." AAAI Conference on Artificial
-   Intelligence. 2014.
- - Generous, Nicholas, et al. "Global disease monitoring and forecasting with
-   Wikipedia." (2014): e1003892.
- - Hickmann, Kyle S., et al. "Forecasting the 2013–2014 Influenza Season Using
-   Wikipedia." (2015): e1004239.
- - McIver, David J., and John S. Brownstein. "Wikipedia usage estimates
-   prevalence of influenza-like illness in the United States in near real-time."
-   PLoS Comput Biol 10.4 (2014): e1003581.
+See [related work](docs/related_work.md) for a sample of additional work in
+this area.

docs/related_work.md

@@ -0,0 +1,21 @@
+# Related work
+
+The works listed below, along with numerous others, were an early inspiration
+for the Epidata API:
+
+- Cook, Samantha, et al. "Assessing Google flu trends performance in the United
+  States during the 2009 influenza virus A (H1N1) pandemic." PloS one 6.8
+  (2011): e23610.
+- Broniatowski, David A., Michael J. Paul, and Mark Dredze. "National and local
+  influenza surveillance through Twitter: an analysis of the 2012-2013
+  influenza epidemic." (2013): e83672.
+- Dredze, Mark, et al. "HealthTweets. org: A Platform for Public Health
+  Surveillance using Twitter." AAAI Conference on Artificial
+  Intelligence. 2014.
+- Generous, Nicholas, et al. "Global disease monitoring and forecasting with
+  Wikipedia." (2014): e1003892.
+- Hickmann, Kyle S., et al. "Forecasting the 2013–2014 Influenza Season Using
+  Wikipedia." (2015): e1004239.
+- McIver, David J., and John S. Brownstein. "Wikipedia usage estimates
+  prevalence of influenza-like illness in the United States in near real-time."
+  PLoS Comput Biol 10.4 (2014): e1003581.