Merge pull request #31 from paulocv/main

CEPH Round 02

model-metadata/CEPH-MetaRSV.yaml

@@ -6,7 +6,7 @@ model_contributors: [
     {
         "name": "Marco Ajelli",
         "affiliation": "Indiana University Bloomington",
-        "email": "[email protected]",
+        "email": "[email protected]"
     },
     {
         "name": "Shreeya Mhade",
@@ -21,18 +21,28 @@ model_contributors: [
     {
         "name": "Maria Litvinova",
         "affiliation": "Indiana University Bloomington",
-        "email": "[email protected]",
+        "email": "[email protected]"
     },
     {
         "name": "Snigdha Agrawal",
         "affiliation": "Indiana University Bloomington",
-        "email": "[email protected]",
+        "email": "[email protected]"
+    },
+    {
+        "name": "Allisandra G. Kummer",
+        "affiliation": "Indiana University Bloomington",
+        "email": "[email protected]"
+    },
+    {
+        "name": "Kedir Turi",
+        "affiliation": "Indiana University Bloomington",
+        "email": "[email protected]"
     }
 ]
 license: "CC-BY_SA-4.0"
 methods: "Age-structured ordinary differential equations model"
-methods_long: "The model framework is based on ordinary differential equations and age-stratified contact matrices derived from both macro (census) and micro (survey) data sources. RSV transmissibility follows a seonal pattern which is calibrated using  hospitalization data from RSV-Net for the 2021-2022 and 2022-2023 seasons. Furthermore, our model uses age-dependent infection-to-hospitalization risks, whose posterior distribution is estimated by our optimization procedure and their prior distribution is based on RSV literature."
-model_version: "1.0"
+methods_long: "The model framework is based on ordinary differential equations and age-stratified contact matrices derived from both macro (census) and micro (survey) data sources. RSV transmissibility follows a seonal pattern which is calibrated using  hospitalization data from RSV-Net for the 2021-2022, 2022-2023 and 2023-2024 seasons. Furthermore, our model uses age-dependent infection-to-hospitalization risks, whose posterior distribution is estimated by our optimization procedure and their prior distribution is based on RSV literature."
+model_version: "1.2"
 website_url: "https://publichealth.indiana.edu/research/faculty-directory/profile.html?user=majelli"
 team_funding: "Cooperative Agreement no. NU38OT000297 from the Council of State and Territorial Epidemiologists (CSTE)"
 data_inputs: "RSV-Net data taken from the RSV-Net webpage; demographic data from this repository; contact pattern data from Mistry et al. Nature Communications 2021."