| 1 |
Zhao_2020 |
Large-scale Lassa fever outbreaks in Nigeria: quantifying the association between disease reproduction number and local rainfall |
Zhao, Shi; Musa, Salihu S.; Fu, Hao; He, Daihai; Qin, Jing |
2020 |
2020-01-10 |
COMM-USE |
N |
PMC7019145 |
31918780.0 |
10.1017/s0950268819002267 |
99lxmq4u |
0.881310 |
Li_C_2018, Kenah_2012, batista_2020, Griette_2020 |
Zhao_2019, Akhmetzhanov_2019 |
| 2 |
Kirkham_2005 |
1 Introduction |
Kirkham, M.B. |
2005 |
2005-12-31 |
PMC |
N |
PMC7149343 |
|
10.1016/b978-012409751-3/50001-3 |
gg3rq0uv |
0.876713 |
Bocharov_2018 |
Kirkham_2014 |
| 3 |
Zhao_2019 |
Large-scale Lassa fever outbreaks in Nigeria: quantifying the association between disease reproduction number and local rainfall |
Shi Zhao; Salihu S. Musa; Hao Fu; Daihai He; Jing Qin |
2019 |
2019-04-08 |
BioRxiv |
N |
|
|
10.1101/602706 |
6l8r09cd |
0.811725 |
|
Zhao_2020, Akhmetzhanov_2019 |
| 4 |
Vogl_2019 |
The Diffusion of the Black Death and Today’s Global Epidemics |
Vogl, Gero |
2019 |
2019-01-10 |
PMC |
N |
PMC7153044 |
|
10.1007/978-3-030-04681-1_7 |
7yjeqnqb |
0.714701 |
|
Fan_K_2020, Liu_D_2013, Lv_W_2019 |
| 5 |
Kirkham_2014 |
Chapter 1 Introduction |
Kirkham, M.B. |
2014 |
2014-12-31 |
PMC |
N |
PMC7149570 |
|
10.1016/b978-0-12-420022-7.00001-x |
bez2p4kb |
0.698145 |
Bocharov_2018, Zheng_2020 |
Kirkham_2005 |
| 6 |
Napp_2016 |
Understanding Spatio-Temporal Variability in the Reproduction Ratio of the Bluetongue (BTV-1) Epidemic in Southern Spain (Andalusia) in 2007 Using Epidemic Trees |
Napp, S.; Allepuz, A.; Purse, B. V.; Casal, J.; García-Bocanegra, I.; Burgin, L. E.; Searle, K. R. |
2016 |
2016-03-10 |
COMM-USE |
N |
PMC4786328 |
26963397.0 |
10.1371/journal.pone.0151151 |
zo9yngfc |
0.517734 |
Li_C_2018 |
Kretzschmar_2020 |
| 7 |
Er_C_2016 |
Production impact of influenza A(H1N1)pdm09 virus infection on fattening pigs in Norway |
Er, Chiek; Skjerve, Eystein; Brun, Edgar; Hofmo, Peer Ola; Framstad, Tore; Lium, Bjørn |
2016 |
2016-02-23 |
PMC |
N |
PMC7109966 |
27065145.0 |
10.2527/jas.2015-9251 |
lo8l1kiv |
0.478578 |
batista_2020, Li_C_2018, Kenah_2012 |
Andraud_2014 |
| 8 |
Kochanczyk_2020 |
Impact of the contact and exclusion rates on the spread of COVID-19 pandemic |
Marek Kochanczyk; Frederic Grabowski; Tomasz Lipniacki |
2020 |
2020-03-17 |
BioRxiv |
N |
|
|
10.1101/2020.03.13.20035485 |
s956fh59 |
0.461352 |
Li_C_2018, Wu_Q_2014, Tao_Y_2020, Chen_2018, Gong_2013 |
Kretzschmar_2020 |
| 9 |
MONDAL_2020 |
Possibilities of exponential or Sigmoid growth of Covid19 data in different states of India |
SUPRIYA MONDAL; Sabyasachi Ghosh |
2020 |
2020-04-14 |
BioRxiv |
Y |
|
|
10.1101/2020.04.10.20060442 |
bz13hdvz |
0.456364 |
Li_C_2018, Zheng_2020 |
Mondal_2020, Smeets_2020, Distante_2020, Ma_Z_2020 |
| 10 |
Notari_2020 |
Temperature dependence of COVID-19 transmission |
Alessio Notari |
2020 |
2020-03-30 |
BioRxiv |
N |
|
|
10.1101/2020.03.26.20044529 |
0oma7hdu |
0.431166 |
Li_C_2018, Gong_2013, Wu_Q_2014, Lauro_2020 |
Weber_2020 |
| 11 |
Ma_J_2020 |
Estimating epidemic exponential growth rate and basic reproduction number |
Ma, Junling |
2020 |
2020-01-08 |
COMM-USE |
N |
PMC6962332 |
31956741.0 |
10.1016/j.idm.2019.12.009 |
osol7wdp |
0.428076 |
Lloyd_2009, Li_C_2018, Bocharov_2018, Wu_Q_2014 |
Fan_K_2020, Wang_2014, Guo_W_2018, Nishiura_2009 |
| 12 |
Kevorkian_2020 |
Tracking the Covid-19 pandemic : Simple visualization of the epidemic states and trajectories of select European countries & assessing the effects of delays in official response. |
Antoine Kevorkian; Thierry Grenet; Hubert Gallee |
2020 |
2020-03-17 |
BioRxiv |
Y |
|
|
10.1101/2020.03.14.20035964 |
5u04irwz |
0.421284 |
Li_C_2018 |
Kretzschmar_2020, Ghaffarzadegan_2020 |
| 13 |
Archer_2012 |
Reproductive Number and Serial Interval of the First Wave of Influenza A(H1N1)pdm09 Virus in South Africa |
Archer, Brett N.; Tempia, Stefano; White, Laura F.; Pagano, Marcello; Cohen, Cheryl |
2012 |
2012-11-16 |
COMM-USE |
N |
PMC3500305 |
23166682.0 |
10.1371/journal.pone.0049482 |
9voqa1oy |
0.398635 |
|
Hilton_2020 |
| 14 |
Liu_W_2015 |
Model Selection and Evaluation Based on Emerging Infectious Disease Data Sets including A/H1N1 and Ebola |
Liu, Wendi; Tang, Sanyi; Xiao, Yanni |
2015 |
2015-09-15 |
COMM-USE |
N |
PMC4586906 |
26451161.0 |
10.1155/2015/207105 |
0j4is0n4 |
0.387403 |
|
Tang_2020, Zareie_2020 |
| 15 |
Roy_A_2020 |
Nature of transmission of Covid19 in India |
Anushree Roy; Sayan Kar |
2020 |
2020-04-17 |
BioRxiv |
Y |
|
|
10.1101/2020.04.14.20065821 |
iv7dok0v |
0.385463 |
Li_C_2018, Gong_2013, Welch_2011, Sadun_2020 |
|
| 16 |
Xu_S_2020 |
Estimating the Growth Rate and Doubling Time for Short-Term Prediction and Monitoring Trend During the COVID-19 Pandemic with a SAS Macro |
Stanley Xu; Christina Clarke; Susan Shetterly; Komal Narwaney |
2020 |
2020-04-11 |
BioRxiv |
Y |
|
|
10.1101/2020.04.08.20057943 |
10mbsqmo |
0.381823 |
|
Ke_R_2020 |
| 17 |
Weber_2020 |
Trend analysis of the COVID-19 pandemic in China and the rest of the world |
Albertine Weber; Flavio Iannelli; Sebastian Goncalves |
2020 |
2020-03-23 |
BioRxiv |
Y |
|
|
10.1101/2020.03.19.20037192 |
vsqaxqy4 |
0.374859 |
Zheng_2020, Li_C_2018 |
Zhou_2020 |
| 18 |
Ma_Z_2020 |
A Simple Mathematical Model for Estimating the Inflection Points of COVID-19 Outbreaks |
Zhanshan (Sam) Ma |
2020 |
2020-03-27 |
BioRxiv |
Y |
|
|
10.1101/2020.03.25.20043893 |
fttqmts4 |
0.374149 |
Kenah_2012, Höhle_2007, Lloyd_2009, Pekalp_2019 |
|
| 19 |
Jung_2020 |
Real time estimation of the risk of death from novel coronavirus (2019-nCoV) infection: Inference using exported cases |
Sung-mok Jung; Andrei R. Akhmetzhanov; Katsuma Hayashi; Natalie M. Linton; Yichi Yang; Baoyin Yuan; Tetsuro Kobayashi; Ryo Kinoshita; Hiroshi Nishiura |
2020 |
2020-02-02 |
BioRxiv |
Y |
|
|
10.1101/2020.01.29.20019547 |
rr5qhsam |
0.356480 |
|
Tang_2020 |
| 20 |
Santillana_2018 |
Relatedness of the incidence decay with exponential adjustment (IDEA) model, “Farr's law” and SIR compartmental difference equation models |
Santillana, Mauricio; Tuite, Ashleigh; Nasserie, Tahmina; Fine, Paul; Champredon, David; Chindelevitch, Leonid; Dushoff, Jonathan; Fisman, David |
2018 |
2018-03-09 |
None |
N |
PMC6326218 |
30839910.0 |
10.1016/j.idm.2018.03.001 |
tmt8vdzj |
0.351135 |
Bocharov_2018, Bifolchi_2013, Chowell_2017, Renna_2020 |
Safi_2011, Clancy_2015, Zimmer_2017, Cazelles_2018 |
| 21 |
Park_2018 |
A practical generation interval-based approach to inferring the strength of epidemics from their speed |
Sang Woo Park; David Champredon; Joshua S. Weitz; Jonathan Dushoff |
2018 |
2018-05-02 |
BioRxiv |
N |
|
|
10.1101/312397 |
jry46itn |
0.334608 |
Bifolchi_2013, O'Dea_2010, Lloyd_2009, Giardina_2017 |
Thompson_2019, Park_2019, Kucharski_2015, Kretzschmar_2020 |
| 22 |
Zhao_2020 |
Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak |
Zhao, Shi; Lin, Qianyin; Ran, Jinjun; Musa, Salihu S.; Yang, Guangpu; Wang, Weiming; Lou, Yijun; Gao, Daozhou; Yang, Lin; He, Daihai; Wang, Maggie H. |
2020 |
2020-01-01 |
None |
Y |
PMC7110798 |
32007643.0 |
10.1016/j.ijid.2020.01.050 |
drqnrwdl |
0.328925 |
Li_C_2018, batista_2020, Griette_2020 |
Zhao_2020 |
| 23 |
Hsieh_2006 |
Real-time Forecast of Multiphase Outbreak |
Hsieh, Ying-Hen; Cheng, Yuan-Sen |
2006 |
2006-01-23 |
PMC |
N |
PMC3293463 |
16494728.0 |
10.3201/eid1201.050396 |
h6cfru7u |
0.327907 |
batista_2020, Schlickeiser_2020 |
Roosa_2020 |
| 24 |
Pongkitivanichkul_2020 |
Estimating the size of COVID-19 epidemic outbreak |
Chakrit Pongkitivanichkul; Daris Samart; Takol Tangphati; Phanit Koomhin; Pimchanok Pimton; Punsiri Dam-O; Apirak Payaka; Phongpichit Channuie |
2020 |
2020-03-31 |
BioRxiv |
N |
|
|
10.1101/2020.03.28.20044339 |
auzioqyz |
0.327226 |
Lloyd_2009, Li_C_2018, Zhao_2013 |
Smeets_2020, Safi_2011, Notari_2020 |
| 25 |
Viboud_2016 |
A generalized-growth model to characterize the early ascending phase of infectious disease outbreaks |
Viboud, Cécile; Simonsen, Lone; Chowell, Gerardo |
2016 |
2016-06-30 |
PMC |
N |
PMC4903879 |
27266847.0 |
10.1016/j.epidem.2016.01.002 |
u7a1as7b |
0.322756 |
Li_C_2018 |
Safi_2011, Chen_2019, Kretzschmar_2020 |
| 26 |
Ziff_2020 |
Fractal kinetics of COVID-19 pandemic |
Anna L. Ziff; Robert M. Ziff |
2020 |
2020-02-20 |
BioRxiv |
Y |
|
|
10.1101/2020.02.16.20023820 |
jljjqs6m |
0.321652 |
Li_C_2018, Li_K_2011, Welch_2011, Lloyd_2009 |
Weber_2020, Peng_2020, Notari_2020, Smeets_2020 |
| 27 |
Mondal_2020 |
Fear of exponential growth in Covid19 data of India and future sketching |
Supriya Mondal; Sabyasachi Ghosh |
2020 |
2020-04-11 |
BioRxiv |
N |
|
|
10.1101/2020.04.09.20058933 |
xmx35h3z |
0.321352 |
Li_C_2018, Liu_Z_2020, Weber_2020 |
MONDAL_2020, Distante_2020, Weber_2020 |
| 28 |
Park_2020 |
Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak |
Sang Woo Park; Benjamin M. Bolker; David Champredon; David J.D. Earn; Michael Li; Joshua S. Weitz; Bryan T. Grenfell; Jonathan Dushoff |
2020 |
2020-02-02 |
BioRxiv |
Y |
|
|
10.1101/2020.01.30.20019877 |
p5aj5k2g |
0.309343 |
Li_C_2018, O'Dea_2010, Lloyd_2009 |
Hilton_2020 |
| 29 |
Burstyn_2020 |
Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: Case study of COVID-19 in Alberta, Canada and Philadelphia, USA |
Igor Burstyn; Neal D. Goldstein; Paul Gustafson |
2020 |
2020-04-11 |
BioRxiv |
Y |
|
|
10.1101/2020.04.08.20057661 |
qu9b07ea |
0.302677 |
Bocharov_2018, Lloyd_2009, Zheng_2020 |
Park_2017 |
| 30 |
Wodarz_2020 |
Patterns of the COVID19 epidemic spread around the world: exponential vs power laws |
Dominik Wodarz; Natalia L. Komarova |
2020 |
2020-04-01 |
BioRxiv |
Y |
|
|
10.1101/2020.03.30.20047274 |
vz829rsy |
0.302508 |
Li_C_2018 |
Weber_2020, Fanelli_2020, Notari_2020 |