Merge pull request #670 from cmu-delphi/release/v3.0.15

Release v3.0.15

Author: krivard

assets/images/landing-page/hero-images/comparing-ensemble-forecasts-hero.jpg

@@ -29,6 +29,11 @@ carousel:
     ref: 2021-09-30-ensemble-analysis
     alt: View Post
     image: ensemble-hero.jpg
+  - pre: Research
+    title: "Comparing Trained and Untrained Probabilistic Ensemble Forecasts of COVID-19 Cases and Deaths in the United States"
+    link: https://doi.org/10.1016/j.ijforecast.2022.06.005
+    alt: View Paper
+    image: comparing-ensemble-forecasts-hero.jpg
   - pre: Research
     title: "Collaborative Hubs: Making the Most of Predictive Epidemic Modeling"
     link: https://doi.org/10.2105/AJPH.2022.306831

content/_index.md

@@ -1,6 +1,12 @@
 ---
 title: Research
 papers:
+  - title: "Comparing Trained and Untrained Probabilistic Ensemble Forecasts of COVID-19 Cases and Deaths in the United States"
+    image: comparing-ensemble-forecasts-thumb.jpg
+    authors: Ray, Brooks, Bien, Biggerstaff, Bosse, Bracher, Cramer, Funk, Gerding, Johansson, Rumack, Wang, Zorn, Tibshirani, Reich
+    link: https://doi.org/10.1016/j.ijforecast.2022.06.005
+    journal: International Journal of Forecasting 
+    year: 2022
   - title: "Real-Time Estimation of COVID-19 Infections: Deconvolution and Sensor Fusion"
     image: nowcasting-thumb.jpg
     authors: Jahja, Chin, Tibshirani
@@ -16,14 +22,14 @@ papers:
   - title: "Smooth Multi-Period Forecasting with Application to Prediction of COVID-19 Cases"
     image: smoothing-paper-teaser.jpg
     authors: Tuzhilina, Hastie, McDonald, Tay, Tibshirani
-    link: https://arxiv.org/pdf/2202.09723.pdf
-    journal: Preprint
+    link: https://arxiv.org/abs/2202.09723
+    journal: arXiv
     year: 2022
   - title: "Recalibrating Probabilistic Forecasts of Epidemics"
     image: recalibrating-thumb.jpg
     authors: Rumack, Tibshirani, Rosenfeld
     link: https://arxiv.org/abs/2112.06305
-    journal: Preprint
+    journal: arXiv
     year: 2021 
   - title: "Big Data, Big Problems: Responding to \"Are We There Yet?\""
     image: response.jpg

content/about/publications/images/comparing-ensemble-forecasts-thumb.jpg

@@ -69,8 +69,8 @@ streams in tracking the COVID-19 pandemic](https://www.pnas.org/cc/beyond-cases-
 
 More recent work on nowcasting using COVID-19 indicators:
 
-- [Real-time estimation of COVID-19 infections via deconvolution and sensor
-  fusion](https://arxiv.org/abs/2112.06697)
+- [Real-time estimation of COVID-19 infections: Deconvolution and sensor
+  fusion](https://doi.org/10.1214/22-STS856)
   by Jahja et al. 
 
 ## Severity Pyramid

content/about/publications/index.md

@@ -59,6 +59,7 @@ Our primary description of the survey and its results over the first year of ope
 
 Other research publications using the survey data include:
 
+- J. M. Cox-Ganser, P. K. Henneberger, D. N. Weissman, G. Guthrie, and C. P. Groth (2022). [COVID-19 test positivity by occupation using the Delphi US COVID-19 Trends and Impact Survey, September–November 2020](https://doi.org/10.1002/ajim.23410). *American Journal of Industrial Medicine*.
 - M. Jahja, A. Chin, and R.J. Tibshirani (2022). [Real-Time Estimation of COVID-19 Infections: Deconvolution and Sensor Fusion](https://doi.org/10.1214/22-STS856). *Statistical Science* 37 (2), 207-228.
 - Henneberger, PK, Cox-Ganser, JM, Guthrie, GM, Groth, CP (2022). [Estimates of COVID-19 vaccine uptake in major occupational groups and detailed occupational categories in the United States, April–May 2021](https://doi.org/10.1002/ajim.23370). *American Journal of Industrial Medicine* 65 (7), 525-536.
 - K. E. Wiens, C. P. Smith, E. Badillo-Goicoechea, K. H. Grantz, M. K. Grabowski, A. S. Azman, E. A. Stuart, and J. Lessler (2022). [In-person schooling and associated COVID-19 risk in the United States over spring semester 2021](https://doi.org/10.1126/sciadv.abm9128). *Science Advances* 8, eabm9128.
@@ -106,9 +107,7 @@ Access to de-identified individual survey responses is available to qualified re
 
 ## Who can I contact?
 
-Questions from survey respondents about consent, research ethics, or how their data is used: [[email protected]](mailto:[email protected])
-
-Getting access to survey data for research: [complete this form](https://dataforgood.fb.com/docs/covid-19-symptom-survey-request-for-data-access/)
+Getting access to survey data for research: [complete this form](https://dataforgood.facebook.com/dfg/docs/covid-19-trends-and-impact-survey-request-for-data-access)
 
 ### Media inquiries:
 

content/covid19/_index.md

@@ -3,4 +3,37 @@ title: Flu and Other Pathogens
 layout: single
 ---
 
-Delphi systems developed before the pandemic typically target seasonal Influenza ("Flu"), but often are used to study other diseases including Chikungunya, Dengue, and Norovirus.
+Delphi systems developed before the COVID-19 pandemic typically target seasonal Influenza ("Flu"), but often are used to study other diseases including Chikungunya, Dengue, and Norovirus.
+
+# About Flu Forecasting
+
+Since 2013, Delphi has supported the U.S. CDC’s Influenza Division in advancing and growing a scientific community around influenza forecasting. That year, we participated in the CDC’s inaugural “[Predict the Influenza Season Challenge](https://www.cdc.gov/flu/news/predict-flu-challenge.htm).” We’ve been perennial leaders in forecasting accuracy ever since, taking part in further [flu forecasting challenges](https://www.cdc.gov/flu/weekly/flusight/about-flu-forecasting.htm). In 2019 we were designated a [National Center of Excellence for Influenza Forecasting](https://delphi.cmu.edu/about/center-of-excellence/), which is a CDC-funded and CDC-designated center working on advancing influenza forecasting and enabling and improving the usefulness of forecasts of both seasonal and pandemic influenza.
+
+## Resources and Tools
+
+### [Epidata](https://cmu-delphi.github.io/delphi-epidata/)
+The Epidata API, originally released in 2016, provides real-time access to epidemiological surveillance signals, as well as to historical versions of each signal (“what was known when”). In this system, we compile data from multiple sources and extract signals related to flu, dengue, and other pathogens. Epidata’s influenza and dengue signals served as the precursor for our COVIDCast system.
+
+### [EpiVis](https://delphi.cmu.edu/epivis/)
+EpiVis is an interactive tool for visualizing epidemiological time-series data. Users may explore their own data or utilize existing time series from the numerous data sources provided by the Epidata API.
+
+### [ILI Nearby](https://delphi.cmu.edu/nowcast/)
+In continuous operation since 2016, ILI Nearby is a real-time flu tracking system which utilizes sensor fusion methodology to bring together multiple signals to nowcast (estimate in real-time) the prevalence of Influenza-Like-Illness ("%ILI") in each U.S. state and broader regions of the US. **Note:** Since early 2020, %ILI lost much of its meaning for flu surveillance because of its overlap with Covid-Like-Illness (CLI) and because of drastic changes in healthcare practices and healthcare-seeking behavior. Consequently, ILI Nearby has not been actively maintained since 2019 and should no longer be relied upon for accurate nowcasting of %ILI in the post-pandemic era.
+
+## Research Articles
+- [Recalibrating Probabilistic Forecasts of Epidemics](https://arxiv.org/abs/2112.06305) by Rumack et al.
+- [Pancasting: Forecasting Epidemics from Provisional Data](https://delphi.cmu.edu/~lcbrooks/brooks2020pancasting.pdf) by Logan C. Brooks
+- [Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights](https://papers.nips.cc/paper/2019/hash/b522259710151f8cc7870b970b4e0930-Abstract.html) by Jahja et al.
+- [Nonmechanistic Forecasts of Seasonal Influenza with Iterative One-Week-Ahead Distributions](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006134) by Brooks et al.
+- [A Human Judgment Approach to Epidemiological Forecasting](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005248) by Farrow et al.
+- [Modeling the Past, Present, and Future of Influenza](https://delphi.cmu.edu/~dfarrow/thesis.pdf) by David C. Farrow
+- [Flexible Modeling of Epidemics with an Empirical Bayes Framework](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004382) by Brooks et al.
+
+# About Other Pathogens
+
+Delphi has also worked on other pathogens, including Dengue fever, Norovirus, and Chikungunya. More information about our data on those pathogens is available in our [Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/README.html).
+
+## Research Articles
+- [An Open Challenge to Advance Probabilistic Forecasting for Dengue Epidemics](https://www.pnas.org/doi/full/10.1073/pnas.1909865116) by Johansson et al.
+- [Risk of Dengue for Tourists and Teams during the World Cup 2014 in Brazil](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4120682/) by van Panhuis et al.
+- [A Human Judgment Approach to Epidemiological Forecasting](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005248) by Farrow et al.

content/covid19/ctis.md

@@ -328,9 +328,9 @@ people:
   lastName: Kim
   image: jimi-kim-500x500-min.jpg
   affiliation: University of Texas at Dallas
-  note: Core member, March-April 2020
+  note: Core member, March-April 2020; Contributor, May 2020-June 2021
   team:
-  - contributors
+  - past
 - firstName: Kyungmin
   lastName: Kim
   image: kyungmin-kim.jpg
@@ -414,6 +414,12 @@ people:
   - contributors
   - blog
   note: Core member, April 2020-January 2021
+- firstName: Maggie
+  lastName: Liu
+  image: maggie-liu.jpg
+  affiliation: University of British Columbia
+  team:
+  - contributors  
 - firstName: Michael
   lastName: Xieyang
   lastName: Liu
@@ -422,6 +428,12 @@ people:
   team:
   - past
   note: Core member, March-April 2020; Contributor, Summer 2020
+- firstName: Rachel
+  lastName: Lobay
+  image: rachel-lobay.jpg
+  affiliation: University of British Columbia
+  team:
+  - contributors
 - firstName: Natalia
   lastName: Lombardi de Oliveira
   image: natalia-lombardi-de-oliveira-500x500-min.jpg
@@ -742,7 +754,7 @@ people:
 - firstName: Elena
   lastName: Tuzhilina
   image: elena-tuzhilina-500x500.jpg
-  affiliation: Stanford University
+  affiliation: University of Toronto
   team:
   - contributors
 - firstName: Carlyn