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36 changes: 35 additions & 1 deletion _data/biblio.yml
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pages: "e1011263"
doi: "https://doi.org/10.1371/journal.pcbi.1011263"

- key: Briga2024
author: "M. Briga, E. Goult, T. S. Brett, P. Rohani, and M. Domenech de Cellès"
year: "2024"
title: "Maternal pertussis immunization and the blunting of routine vaccine effectiveness: a meta-analysis and modeling study"
journal: "Nature Communications"
volume: "15"
number: "1"
doi: "https://doi.org/10.1038/s41467-024-44943-7"

- key: Brillinger1980
author: "D. R. Brillinger, J. Guckenheimer, P. Guttorp, and G. Oster"
year: "1980"
Expand All @@ -350,6 +359,14 @@
pages: "460–472"
doi: "https://doi.org/10.1111/1365-2656.12656"

- key: Byrne2024
author: "C. Byrne, A. C. Márquez, B. Cai, D. Coombs, and S. Gantt"
year: "2024"
title: "Spatial kinetics and immune control of murine cytomegalovirus infection in the salivary glands"
journal: "bioRxiv"
eprint: "2024.02.22.581694"
doi: "https://doi.org/10.1101/2024.02.22.581694"

- key: Cabore2022
author: "J. W. Cabore, H. C. Karamagi, H. K. Kipruto, J. K. Mungatu, J. A. Asamani, B. Droti, R. Titi-ofei, A. B. W. Seydi, S. N. Kidane, T. Balde, A. S. Gueye, L. Makubalo, and M. R. Moeti"
year: "2022"
Expand Down Expand Up @@ -819,7 +836,7 @@
volume: "80"
number: "6"
pages: "1789–1805"
doi: "https://doi.org/10.1890/0012-9658(1999)080%5B1789:wdpcas%5D2.0.co;2"
doi: "https://doi.org/10.1890/0012-9658(1999)0801789:wdpcas2.0.co;2"

- key: Kendall2005
author: "B. E. Kendall, S. P. Ellner, E. McCauley, S. N. Wood, C. J. Briggs, W. M. Murdoch, and P. Turchin"
Expand Down Expand Up @@ -1084,6 +1101,14 @@
address: "Oxford"
doi: "https://doi.org/10.1093/oso/9780198577300.003.0006"

- key: Mietchen2024
author: "M. S. Mietchen, E. Clancey, C. McMichael, and E. T. Lofgren"
year: "2024"
title: "Estimating SARS-CoV-2 transmission parameters between coinciding outbreaks in a university population and the surrounding community"
journal: "medRxiv"
eprint: "2024.01.10.24301116"
doi: "https://doi.org/10.1101/2024.01.10.24301116"

- key: Molodecky2023
author: "N. A. Molodecky, H. Jafari, R. M. Safdar, J. A. Ahmed, A. Mahamud, A. S. Bandyopadhyay, H. Shukla, A. Quddus, M. Zaffran, R. W. Sutter, N. C. Grassly, and I. M. Blake"
year: "2023"
Expand All @@ -1093,6 +1118,15 @@
pages: "A93–A104"
doi: "https://doi.org/10.1016/j.vaccine.2021.09.037"

- key: Moore2024
author: "S. Moore, S. Cavany, T. A. Perkins, and G. F. C. España"
year: "2024"
title: "Projecting the future impact of emerging SARS-CoV-2 variants under uncertainty: Modeling the initial Omicron outbreak"
journal: "Epidemics"
volume: "47"
pages: "100759"
doi: "https://doi.org/10.1016/j.epidem.2024.100759"

- key: Musa2020
author: "S. S. Musa, S. Zhao, D. Gao, Q. Lin, G. Chowell, and D. He"
year: "2020"
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71 changes: 57 additions & 14 deletions vignettes/pomp.bib
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Expand Up @@ -236,6 +236,20 @@ @Article{Brett2023
owner = {kingaa},
}

@Article{Briga2024,
author = {Briga, Michael and Goult, Elizabeth and Brett, Tobias S. and Rohani, Pejman and Domenech de Cell{\`{e}}s, Matthieu},
journal = {Nature Communications},
title = {Maternal pertussis immunization and the blunting of routine vaccine effectiveness: a meta-analysis and modeling study},
year = {2024},
number = {1},
volume = {15},
creationdate = {2024-04-16T12:37:08},
doi = {10.1038/s41467-024-44943-7},
file = {:Briga2024.pdf:PDF},
groups = {pomp, alumni},
modificationdate = {2024-04-16T12:37:20},
}

@InCollection{Brillinger1980,
author = {Brillinger, D. R. and Guckenheimer, J. and Guttorp, P. and Oster, G.},
booktitle = {Some Mathematical Questions in Biology},
Expand Down Expand Up @@ -269,6 +283,18 @@ @InBook{Brillinger2011
owner = {kingaa},
}

@Article{Byrne2024,
author = {Byrne, Catherine and M{\'{a}}rquez, Ana Citlali and Cai, Bing and Coombs, Daniel and Gantt, Soren},
journal = {bioRxiv},
title = {Spatial kinetics and immune control of murine cytomegalovirus infection in the salivary glands},
year = {2024},
creationdate = {2024-04-16T12:27:43},
doi = {10.1101/2024.02.22.581694},
eprint = {2024.02.22.581694},
groups = {pomp},
modificationdate = {2024-04-16T12:30:11},
}

@Article{Childs2021,
author = {Childs, Marissa L. and Kain, Morgan P. and Harris, Mallory J. and Kirk, Devin and Couper, Lisa and Nova, Nicole and Delwel, Isabel and Ritchie, Jacob and Becker, Alexander D. and Mordecai, Erin A.},
journal = {Proc R Soc Lond B},
Expand Down Expand Up @@ -740,10 +766,25 @@ @Article{Mietchen2024
creationdate = {2024-01-16T07:24:06},
doi = {10.1101/2024.01.10.24301116},
eprint = {2024.01.10.24301116},
modificationdate = {2024-01-16T07:29:06},
groups = {pomp},
modificationdate = {2024-04-16T12:32:32},
owner = {kingaa},
}

@Article{Moore2024,
author = {Moore, Sean and Cavany, Sean and Perkins, T. Alex and Espa{\~{n}}a, Guido Felipe Camargo},
journal = {Epidemics},
title = {Projecting the future impact of emerging {SARS-CoV-2} variants under uncertainty: Modeling the initial {Omicron} outbreak},
year = {2024},
issn = {1755-4365},
pages = {100759},
volume = {47},
creationdate = {2024-04-16T12:33:39},
doi = {10.1016/j.epidem.2024.100759},
groups = {pomp},
modificationdate = {2024-04-16T12:34:50},
}

@InCollection{Murphy2001,
author = {Murphy, Kevin and Russell, Stuart},
booktitle = {{Sequential Monte Carlo Methods in Practice}},
Expand Down Expand Up @@ -1637,19 +1678,21 @@ @Article{Dattner2020
}

@Article{Kain2021,
author = {Kain, Morgan P. and Childs, Marissa L. and Becker, Alexander D. and Mordecai, Erin A.},
journal = {Epidemics},
title = {Chopping the tail: How preventing superspreading can help to maintain {COVID-19} control},
year = {2021},
pages = {100430},
pmcid = {PMC7833509},
pmid = {33360871},
volume = {34},
abstract = {Disease transmission is notoriously heterogeneous, and SARS-CoV-2 is no exception. A skewed distribution where few individuals or events are responsible for the majority of transmission can result in explosive, superspreading events, which produce rapid and volatile epidemic dynamics, especially early or late in epidemics. Anticipating and preventing superspreading events can produce large reductions in overall transmission rates. Here, we present a stochastic compartmental (SEIR) epidemiological model framework for estimating transmission parameters from multiple imperfectly observed data streams, including reported cases, deaths, and mobile phone-based mobility that incorporates individual-level heterogeneity in transmission using previous estimates for SARS-CoV-1 and SARS-CoV-2. We parameterize the model for COVID-19 epidemic dynamics by estimating a time-varying transmission rate that incorporates the impact of non-pharmaceutical intervention strategies that change over time, in five epidemiologically distinct settings--Los Angeles and Santa Clara Counties, California; Seattle (King County), Washington; Atlanta (Dekalb and Fulton Counties), Georgia; and Miami (Miami-Dade County), Florida. We find that the effective reproduction number (RE) dropped below 1 rapidly in all five locations following social distancing orders in mid-March, 2020, but that gradually increasing mobility starting around mid-April led to an RE once again above 1 in late May (Los Angeles, Miami, and Atlanta) or early June (Santa Clara County and Seattle). However, we find that increased social distancing starting in mid-July in response to epidemic resurgence once again dropped RE below 1 in all locations by August 14. We next used the fitted model to ask: how does truncating the individual-level transmission rate distribution (which removes periods of time with especially high individual transmission rates and thus models superspreading events) affect epidemic dynamics and control? We find that interventions that truncate the transmission rate distribution while partially relaxing social distancing are broadly effective, with impacts on epidemic growth on par with the strongest population-wide social distancing observed in April, 2020. Given that social distancing interventions will be needed to maintain epidemic control until a vaccine becomes widely available, {\textquotedblleft}chopping off the tail{\textquotedblright} to reduce the probability of superspreading events presents a promising option to alleviate the need for extreme general social distancing.},
creationdate = {2021-01-18},
doi = {10.1016/j.epidem.2020.100430},
groups = {pomp},
owner = {kingaa},
author = {Kain, Morgan P. and Childs, Marissa L. and Becker, Alexander D. and Mordecai, Erin A.},
journal = {Epidemics},
title = {Chopping the tail: How preventing superspreading can help to maintain {COVID-19} control},
year = {2021},
issn = {1755-4365},
pages = {100430},
pmcid = {PMC7833509},
pmid = {33360871},
volume = {34},
abstract = {Disease transmission is notoriously heterogeneous, and SARS-CoV-2 is no exception. A skewed distribution where few individuals or events are responsible for the majority of transmission can result in explosive, superspreading events, which produce rapid and volatile epidemic dynamics, especially early or late in epidemics. Anticipating and preventing superspreading events can produce large reductions in overall transmission rates. Here, we present a stochastic compartmental (SEIR) epidemiological model framework for estimating transmission parameters from multiple imperfectly observed data streams, including reported cases, deaths, and mobile phone-based mobility that incorporates individual-level heterogeneity in transmission using previous estimates for SARS-CoV-1 and SARS-CoV-2. We parameterize the model for COVID-19 epidemic dynamics by estimating a time-varying transmission rate that incorporates the impact of non-pharmaceutical intervention strategies that change over time, in five epidemiologically distinct settings--Los Angeles and Santa Clara Counties, California; Seattle (King County), Washington; Atlanta (Dekalb and Fulton Counties), Georgia; and Miami (Miami-Dade County), Florida. We find that the effective reproduction number (RE) dropped below 1 rapidly in all five locations following social distancing orders in mid-March, 2020, but that gradually increasing mobility starting around mid-April led to an RE once again above 1 in late May (Los Angeles, Miami, and Atlanta) or early June (Santa Clara County and Seattle). However, we find that increased social distancing starting in mid-July in response to epidemic resurgence once again dropped RE below 1 in all locations by August 14. We next used the fitted model to ask: how does truncating the individual-level transmission rate distribution (which removes periods of time with especially high individual transmission rates and thus models superspreading events) affect epidemic dynamics and control? We find that interventions that truncate the transmission rate distribution while partially relaxing social distancing are broadly effective, with impacts on epidemic growth on par with the strongest population-wide social distancing observed in April, 2020. Given that social distancing interventions will be needed to maintain epidemic control until a vaccine becomes widely available, {\textquotedblleft}chopping off the tail{\textquotedblright} to reduce the probability of superspreading events presents a promising option to alleviate the need for extreme general social distancing.},
creationdate = {2021-01-18},
doi = {10.1016/j.epidem.2020.100430},
groups = {pomp},
modificationdate = {2024-04-16T12:29:46},
owner = {kingaa},
}

@Article{ONeill2010,
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