TY - JOUR
T1 - NetworkSIR and EnvironmentalSIR
T2 - Effective, Open-Source Epidemic Modeling in the Absence of Data
AU - Pickering, Madison A.
AU - Venkatesan, Subbarayan
AU - Lehmann, Christoph
AU - Saleh, Sameh N
AU - Medford, Richard J.
N1 - Publisher Copyright:
©2021 AMIA - All rights reserved.
PY - 2021
Y1 - 2021
N2 - The rapidly changing situation characterized by the COVID-19 pandemic highlighted a need for new epidemic modeling strategies. Due to an absence of computationally efficient models robust to paucity of reliable data, we developed NetworkSIR, a model capable of making predictions when only the approximate population density is known. We then extend NetworkSIR to capture the effect of indirect disease spread on the progression of an epidemic (EnvironmentalSIR).
AB - The rapidly changing situation characterized by the COVID-19 pandemic highlighted a need for new epidemic modeling strategies. Due to an absence of computationally efficient models robust to paucity of reliable data, we developed NetworkSIR, a model capable of making predictions when only the approximate population density is known. We then extend NetworkSIR to capture the effect of indirect disease spread on the progression of an epidemic (EnvironmentalSIR).
UR - http://www.scopus.com/inward/record.url?scp=85126855627&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85126855627&partnerID=8YFLogxK
M3 - Article
C2 - 35308930
AN - SCOPUS:85126855627
SN - 1559-4076
VL - 2021
SP - 1009
EP - 1018
JO - AMIA ... Annual Symposium proceedings. AMIA Symposium
JF - AMIA ... Annual Symposium proceedings. AMIA Symposium
ER -