OKRS24-24 Resolved conflicts

Author: dmytrotsko

config.toml

@@ -119,67 +119,134 @@ relativeURLs = false
     name = "Tools Overview"
     url = "/tools/"
     weight = 1
+# utils
 [[menu.main]]
     parent = "tools"
-    name = "COVIDcast Dashboard"
+    identifier = "utils"
+    name = "Dashboards"
+    url = "/tools/#dashboards"
+    weight = 9
+[[menu.main]]
+    parent = "utils"
+    name = "Delphi Epidata Dashboard"
     url = "/covidcast/"
     weight = 10
 [[menu.main]]
-    parent = "tools"
-    name = "COVIDcast R Package"
-    url = "https://cmu-delphi.github.io/covidcast/covidcastR/"
-    weight = 11
-[[menu.main]]
-    parent = "tools"
-    name = "COVIDcast Python Package"
-    url = "https://cmu-delphi.github.io/covidcast/covidcast-py/html/"
-    weight = 12
-[[menu.main]]
-    parent = "tools"
+    parent = "utils"
     name = "Indicator Status"
     url = "/covidcast/indicator-status"
     weight = 20
 [[menu.main]]
-    parent = "tools"
+    parent = "utils"
     name = "Dashboard Builder"
     url = "/covidcast/dashboard"
     weight = 30
 [[menu.main]]
-    parent = "tools"
+    parent = "utils"
     name = "Forecast Evaluation"
     url = "/forecast-eval/"
     weight = 40
 [[menu.main]]
-    parent = "tools"
-    name = "EpiVis"
+    parent = "utils"
+    name = "Epi Signal Visualization"
     url = "/epivis/"
     weight = 50
 [[menu.main]]
     parent = "tools"
-    name = "Archived Tools"
-    url = "/tools/archive/"
+    name = "Archived"
+    url = "/tools/#archived"
     weight = 80
 
+[[menu.main]]
+    parent = "tools"
+    identifier = "forecasting"
+    name = "Forecasting"
+    url = "/tools/#forecasting"
+    weight = 50
 
 [[menu.main]]
-    identier = "github"
-    pre = "brands/github"
-    name = "GitHub"
-    url = "https://github.com/cmu-delphi/"
+    parent = "forecasting"
+    name = "COVID Forecasting"
+    url = "https://covid19forecasthub.org/"
+    weight = 1
+[[menu.main]]
+    parent = "forecasting"
+    name = "Flu Forecasting"
+    url = "https://www.cdc.gov/flu/weekly/flusight/index.html"
+    weight = 2
+
+[[menu.main]]
+    identier = "Code"
+    pre = "solid/code"
+    name = "Code"
+    url = "code"
     weight = 90
+[[menu.main]]
+    parent = "Code"
+    name = "Code Overview"
+    url = "code"
+    weight = 1
+[[menu.main]]
+    parent = "Code"
+    identifier = "APIClients"
+    name = "API and Clients"
+    url = "/code/#api-and-clients"
+    weight = 2
+[[menu.main]]
+    parent = "APIClients"
+    name = "Epidata"
+    url = "https://github.com/cmu-delphi/delphi-epidata"
+    weight = 7
+[[menu.main]]
+    parent = "APIClients"
+    name = "Epidatr"
+    url = "https://cmu-delphi.github.io/epidatr/"
+    weight = 8
+[[menu.main]]
+    parent = "APIClients"
+    name = "Epidatpy"
+    url = "https://github.com/cmu-delphi/epidatpy"
+    weight = 9
 
+[[menu.main]]
+    parent = "Code"
+    identifier = "forecastingCode"
+    name = "Forecasting"
+    url = "code#forecasting"
+    weight = 10
+[[menu.main]]
+    parent = "forecastingCode"
+    name = "Forecasting Manual"
+    weight = 1
+[[menu.main]]
+    parent = "forecastingCode"
+    name = "Epiprocess"
+    url = "https://cmu-delphi.github.io/epiprocess/"
+    weight = 7
+[[menu.main]]
+    parent = "forecastingCode"
+    name = "Epipredict"
+    url = "https://cmu-delphi.github.io/epipredict/"
+    weight = 7
+[[menu.main]]
+    parent = "Code"
+    name = "Github"
+    pre = "brands/github"
+    url = "https://github.com/cmu-delphi/"
+    weight = 70
 
 [[menu.main]]
     identifier = "api"
-    name = "API"
+    name = "Epidata API"
     pre = "solid/database"
     url = "https://cmu-delphi.github.io/delphi-epidata/"
     weight = 100
 
 [params]
     description = "Developing the Theory and Practice of Epidemiological Forecasting"
-    mission = "Develop the theory and practice of epidemiological tracking and forecasting, with a long-term vision of making this technology as universally accepted and useful as weather forecasting is today."
+    mission = "To develop the theory and practice of epidemic detection, tracking and forecasting, and their use in decision making, both public and private.  Our vision is to make this technology as useful as weather forecasting is today."
     apiUrl = "https://cmu-delphi.github.io/delphi-epidata"
+    toolUrl = "/tools/"
     twitter = "CmuDelphi"
     contactForm = "https://docs.google.com/forms/d/e/1FAIpQLScqgT1fKZr5VWBfsaSp-DNaN03aV6EoZU4YljIzHJ1Wl_zmtg/viewform"
     feedbackForm = "https://docs.google.com/forms/d/e/1FAIpQLSeIeOJtrAhdOriEyiRY7LkpQX8DZBY19dl6De8l56Q9CZhmxw/viewform?usp=pp_url&entry.1245962748="

content/_index.md

@@ -4,10 +4,15 @@ description: Developing the Theory and Practice of Epidemiological Forecasting
 layout: landing
 
 carousel:
+  - pre: Delphi Careers
+    title: Seeking Software Engineering Manager to Lead Development and Operations Teams
+    ref: careers
+    alt: View Position
+    image: cmu-bldg-7-hero.jpg
   - pre: Tools
     title: Real-time Indicators of Infectious Disease Activity
     ref: covidcast
-    alt: Explore the COVIDcast Dashboard
+    alt: Explore the Delphi Epidata Dashboard
     image: covidcast_v2.jpg
   - pre: News
     title: CDC Selects Delphi Research Group at CMU as Center of Innovation in Outbreak Analytics and Disease Modeling
@@ -38,7 +43,7 @@ carousel:
     title: "Collaborative Hubs: Making the Most of Predictive Epidemic Modeling"
     link: https://doi.org/10.2105/AJPH.2022.306831
     alt: View Paper
-    image: research-hero-collaborative-hubs.jpg  
+    image: research-hero-collaborative-hubs.jpg
   - pre: Research
     title: Introduction to the Delphi Real-Time Signal Repository
     link: https://www.medrxiv.org/content/10.1101/2021.07.12.21259660v1

content/about/_index.md

@@ -1,36 +1,34 @@
 ---
-title: Delphi Research Group
+title: About The Delphi Group
 linkTitle: About Delphi
 layout: about
-
-collaborators:
-- name: Amazon
-  group: collaborator
-- name: Centers for Disease Control and Prevention
-  group: collaborator
-- name: Change Healthcare
-  group: collaborator
-- name: Defense Threat Reduction Agency
-  group: collaborator
-- name: Facebook
-  group: collaborator
-- name: Google
-  group: collaborator
-- name: Google.org
-  group: collaborator
-- name: Optum
-  group: collaborator
-- name: Quidel Inc.
-  group: collaborator
-- name: Uptake
-  group: collaborator
-
 ---
 
-### Who are we?
+**Our mission:** To develop the theory and practice of epidemic detection, tracking and forecasting, and their use in decision making, both public and private.
+
+**Our vision:** To make this technology as useful as weather forecasting is today.
 
-We're a research group based out of Carnegie Mellon University dedicated to developing the theory and practice of epidemic tracking and forecasting. Pre-pandemic we worked mostly on influenza, dengue and norovirus; we've now picked up a focus on COVID. We procure unique data streams that reflect epidemic (or pandemic) activity, extract relevant indicators, and make these publicly and continuously available. We and others then use these indicators for nowcasting (situational awareness) and short-term forecasting.
+- Founded in 2012 at Carnegie Mellon University, now spanning 3 universities
+- Perennial winners of CDC’s [“predict the flu” challenge](https://www.cdc.gov/flu/weekly/flusight/index.html) since 2014
+- Designated a 6-year [National Center of Excellence for Flu Forecasting](https://delphi.cmu.edu/about/center-of-excellence/) by [CDC’s Influenza Division](https://www.cdc.gov/ncird/flu.html) (2019-2025)
+- Designated a 5-year [National Center for Innovation](https://www.cs.cmu.edu/news/2023/delphi-cdc-center) by [CDC’s Center for Forecasting and Outbreak Analytics](https://www.cdc.gov/forecast-outbreak-analytics/index.html) (2023-2028)
+- Our [Epidata repository](https://cmu-delphi.github.io/delphi-epidata/) of real-time, geographically-detailed epidemic signals contains more than 500 signals totalling over 4 billion records, with 3 million records being added daily.  It receives on average 100,000 queries/day, from more than 50,000 unique IP addresses in a 3 month period.
+- Data partners and collaborators include CDC, UnitedHealth/Optum, Change Healthcare, Google, Meta, Amazon, QuidelOrtho, and others
+- Funders include CDC, DTRA, Google, Meta, Optum, McCune Foundation, Uptake and others
 
-### Who is our audience?
+**Our strategy:**
+1. Procure [real-time, aggregated data streams](https://cmu-delphi.github.io/delphi-epidata/) informative of varied infectious diseases and syndromes, in collaboration with industry partners and public health agencies
+1. Extract signals—many at daily and county-level resolution—from these streams and make them widely available via the [Delphi Epidata platform](https://delphi.cmu.edu/covidcast/) and [API](https://cmu-delphi.github.io/delphi-epidata/); enhance their value with automated revision tracking, revision projection, anomaly detection, trend detection, access control, smoothing, and geographic, temporal and demographic disaggregation
+1. Develop and deploy algorithms for epidemic detection, tracking (nowcasting), and forecasting
+1. Develop and share tools for [signal access](https://cmu-delphi.github.io/epidatr/), [processing](https://cmu-delphi.github.io/epiprocess/), and [forecasting](https://cmu-delphi.github.io/epipredict/)
+1. Work closely with public health agencies to understand and support their needs
+1. Make it all real-time, operational, maximally accessible, and open-source
 
-Public health authorities (federal, state, local), the healthcare industry, the public and private sectors, fellow researchers working on epidemic tracking and forecasting, data journalists, and the general public.
+**Our target users:**
+- CDC, state and local public health agencies (STLTs)
+  - Although our long term goal is global, our near-term focus is the U.S.)
+- The epi-forecasting research community
+- The healthcare industry
+- Other public, private and government organizations
+- Data journalists
+- The general public

content/about/careers/headless/2024-4-software-engineering-manager.md

@@ -0,0 +1,9 @@
+---
+date: 2024-04-16
+title: Software Engineering Manager
+---
+
+We seek a talented engineering manager capable of translating organizational goals between the executive and engineering teams, supporting, and mentoring technical staff, and providing sage yet flexible opinions for technical guidance.
+
+[Apply to the Software Engineering Manager position](https://cmu.wd5.myworkdayjobs.com/CMU/job/Pittsburgh-PA/Software-Engineering-Manager---School-of-Computer-Science---MLD_2021470).
+

content/code/_index.md

@@ -0,0 +1,65 @@
+---
+title: Code Overview
+linkTitle: Code
+layout: single
+---
+
+In addition to the Delphi Epidata API server code, we have a number of user-oriented code packages, such as API clients and time-series modeling for epidemiology.
+All source code is freely available on [GitHub](https://github.com/cmu-delphi/).
+
+## API and clients
+
+### [Epidata](https://github.com/cmu-delphi/delphi-epidata)
+
+The core server code for the [Delphi Epidata API](https://cmu-delphi.github.io/delphi-epidata/).
+
+### [Epidatr](https://cmu-delphi.github.io/epidatr/)
+
+R client for the [Delphi Epidata API](https://cmu-delphi.github.io/delphi-epidata/).
+It allows you to cache queries locally to speed up data access and seamlessly integrate pulling from our API into your pipelines.
+
+### [Epidatpy](https://github.com/cmu-delphi/epidatpy) (WIP)
+
+A work-in-progress Python client for the [Delphi Epidata API](https://cmu-delphi.github.io/delphi-epidata/).
+Not yet recommended for production, but we are happy to receive feedback!
+
+## Forecasting
+
+### [Introduction to Epidemiological Forecasting: Delphi Tools, Data, and Lessons](https://cmu-delphi.github.io/delphi-tooling-book/)
+
+An introduction to epidemiological forecasting using our tools: epiprocess and epipredict.
+
+### [Epiprocess](https://cmu-delphi.github.io/epiprocess/)
+
+A collection of data structures and methods for handling epidemiological data.
+The major features are:
+- The epi_df structure, which allows you track epidemiological data measured over location and time (and other potential keys).
+- The epi_archive structure, which allows you to store epi_df objects in a versioned archive and to query the archive for the state of the data at any point in time.
+- Support for applying generic functions across a sliding time window, building on tools like [slider](https://slider.r-lib.org/). Comes with support for
+  - handling gaps in time
+  - automatically handling grouping of keys
+- Support for version aware data transformation and forecasting, which allows for simple and accurate backtesting of forecasting models (using only the actual data that was available at the time of the forecast and not the revised versions).
+- Growth rate estimation, as estimated using relative rates of change, linear regression, smooth splines, or polynomial trend filtering.
+- Outlier detection and correction, using rolling median or LOESS trend decomposition.
+- Signal correlation over space, time and other keys. It also supports lagged correlations, automatically handles grouping by the specified keys, and handles time gaps.
+
+### [Epipredict](https://cmu-delphi.github.io/epipredict/)
+
+A framework for building epidata pipelines involving transformation and forecasting. It is designed to work smoothly with epiprocess and provides a simple interface for defining and running forecasting workflows. It supports:
+- A simple interface for defining a sequence of data pre-processing, forecasting, and post-processing steps.
+- A collection of data processing steps common to epidata.
+- A collection of pre-packaged forecasting models commonly used by Delphi's forecasting team.
+
+## Deprecated Packages
+
+### [Covidcast](https://github.com/cmu-delphi/covidcast)
+
+A collection of R and Python packages for accessing and analyzing data from the Delphi COVIDcast API.
+
+### [Epiforecast](https://github.com/cmu-delphi/epiforecast-R)
+
+R package that implements several methods for epidemiological forecasting empirical bayes (EB), basis regression (BR), and time-weighted kernel density estimation (twkde).
+
+### [utils](https://github.com/cmu-delphi/utils)
+
+Python utility package for handling dates and locations.

content/covidcast/_index.md

@@ -1,6 +1,6 @@
 ---
-title: COVIDcast Dashboard
-description: COVIDcast tracks and forecasts the spread of COVID-19. By Carnegie Mellon's Delphi Research Group.
+title: Delphi Epidata Dashboard
+description: Delphi Epidata tracks and forecasts the spread of COVID-19. By Carnegie Mellon's Delphi Research Group.
 layout: covidcast_app
 app_mode: landing
 order: 1

content/epidemic-signals/_index.md

@@ -42,7 +42,7 @@ in the United States. It has several parts.
 
 ## See Also
 
-- [COVIDcast dashboard]({{< relref "covidcast" >}})
+- [Delphi Epidata dashboard]({{< relref "covidcast" >}})
 - [CTIS dashboard]({{< relref "covidcast/survey-results" >}})
 - [Export data tool]({{< relref "covidcast/export" >}})
 - [API documentation](https://cmu-delphi.github.io/delphi-epidata/api/covidcast.html)

content/epidemic-signals/ctis.md

@@ -42,7 +42,7 @@ To account for the differences between Facebook users and the United States popu
 
 ## Where can I see the results?
 
-Our [CTIS Results Dashboard]({{< relref "covidcast/survey-results" >}}) shows aggregate survey results, ranging from rates of COVID-like symptoms over mask usage to mental health. In addition, our [COVIDcast dashboard]({{< relref "covidcast" >}}) shows basic aggregate survey results, revealing the rates of mask usage and COVID-like symptoms across the United States. The data used by both tools is also freely available for download through the [COVIDcast API]({{< apiref "api/covidcast.html">}}) and our [COVIDcast Exporter]({{< relref "covidcast/export" >}}). Facebook also publishes [a map](https://covid-survey.dataforgood.fb.com/) based on the United States and international aggregate data.
+Our [CTIS Results Dashboard]({{< relref "covidcast/survey-results" >}}) shows aggregate survey results, ranging from rates of COVID-like symptoms over mask usage to mental health. In addition, our [Delphi Epidata dashboard]({{< relref "covidcast" >}}) shows basic aggregate survey results, revealing the rates of mask usage and COVID-like symptoms across the United States. The data used by both tools is also freely available for download through the [COVIDcast API]({{< apiref "api/covidcast.html">}}) and our [COVIDcast Exporter]({{< relref "covidcast/export" >}}). Facebook also publishes [a map](https://covid-survey.dataforgood.fb.com/) based on the United States and international aggregate data.
 
 The [Symptom Data Challenge](https://www.symptomchallenge.org/) challenged participants to enable earlier detection and improved situational awareness of the COVID-19 outbreak by using data from these symptom surveys. Check out the [the challenge website](https://www.symptomchallenge.org/) for more details about the Challenge and the finalists.