-
1
-
-
85059245670
-
Ramping up the response to Ebola
-
Nuzzo JB, Inglesby TV. Ramping up the response to Ebola. N Engl J Med 2018;37926:2490-2491.
-
(2018)
N Engl J Med
, vol.379
, Issue.26
, pp. 2490-2491
-
-
Nuzzo, J.B.1
Inglesby, T.V.2
-
2
-
-
85056803078
-
Mapping yellow fever virus in Brazil
-
Friedrich MJ. Mapping yellow fever virus in Brazil. JAMA 2018;32019:1969.
-
(2018)
JAMA
, Issue.320
, pp. 19
-
-
Friedrich, M.J.1
-
3
-
-
85066960608
-
Outbreak investigation of Nipah virus disease in Kerala, India, 2018
-
Arunkumar G, Chandni R, Mourya DT, et al. Outbreak investigation of Nipah virus disease in Kerala, India, 2018. J Infect Dis 2019;21912:1867-1878.
-
(2019)
J Infect Dis
, vol.219
, Issue.12
, pp. 1867-1878
-
-
Arunkumar, G.1
Chandni, R.2
Mourya, D.T.3
-
4
-
-
84986573066
-
Eco-social processes influencing infectious disease emergence and spread
-
Jones BA, Betson M, Pfeiffer DU. Eco-social processes influencing infectious disease emergence and spread. Parasitology 2017;1441:26-36.
-
(2017)
Parasitology
, vol.144
, Issue.1
, pp. 26-36
-
-
Jones, B.A.1
Betson, M.2
Pfeiffer, D.U.3
-
5
-
-
84929502037
-
Effect of climate change on vectorborne disease risk in the UK
-
Medlock JM, Leach SA. Effect of climate change on vectorborne disease risk in the UK. Lancet Infect Dis 2015;156: 721-730.
-
(2015)
Lancet Infect Dis
, vol.15
, Issue.6
, pp. 721-730
-
-
Medlock, J.M.1
Leach, S.A.2
-
6
-
-
85043470133
-
Infection forecasts powered by big data
-
Eisenstein M. Infection forecasts powered by big data. Nature 2018;5557695:S2-S4.
-
(2018)
Nature
, vol.555
, Issue.7695
, pp. 2-4
-
-
Eisenstein, M.1
-
7
-
-
85016071260
-
Forecasting Ebola with a regression transmission model
-
Asher J. Forecasting Ebola with a regression transmission model. Epidemics 2018;22:50-55.
-
(2018)
Epidemics
, Issue.22
, pp. 50-55
-
-
Asher, J.1
-
8
-
-
85029747062
-
The RAPIDD Ebola forecasting challenge: Synthesis and lessons learnt
-
Viboud C, Sun K, Gaffey R, et al. The RAPIDD Ebola forecasting challenge: synthesis and lessons learnt. Epidemics 2018;22:13-21.
-
(2018)
Epidemics
, Issue.22
, pp. 13-21
-
-
Viboud, C.1
Sun, K.2
Gaffey, R.3
-
9
-
-
85071275576
-
-
About ProMEDmail. Accessed July
-
International Society for Infectious Diseases. About ProMEDmail. https://www.promedmail.org/aboutus/. Accessed July 9, 2019.
-
(2019)
International Society for Infectious Diseases
, vol.9
-
-
-
10
-
-
85071243658
-
-
Accessed July
-
HealthMap. About HealthMap. http://www.diseasedaily. org/about. Accessed July 9, 2019.
-
(2019)
HealthMap. About HealthMap
, vol.9
-
-
-
11
-
-
85071256074
-
-
Accessed July
-
World Health Organization. https://www.who.int/. Accessed July 9, 2019.
-
(2019)
World Health Organization
, vol.9
-
-
-
12
-
-
85071264364
-
-
Accessed July
-
Flowminder. http://flowminder.org. Accessed July 9, 2019.
-
(2019)
Flowminder
, vol.9
-
-
-
13
-
-
85071234896
-
-
Accessed July
-
Flirt. https://flirt.eha.io. Accessed July 9, 2019.
-
(2019)
Flirt
, vol.9
-
-
-
14
-
-
85071234580
-
-
Accessed July
-
Global Health Security Agenda. https://www.ghsagenda.org/. Accessed July 9, 2019.
-
(2019)
Global Health Security Agenda
, vol.9
-
-
-
15
-
-
85071235152
-
-
Accessed July
-
UNICEF. https://www.unicef.org/. Accessed July 9, 2019.
-
(2019)
UNICEF
, vol.9
-
-
-
17
-
-
85071241008
-
-
Accessed July
-
NASA Earthdata. https://earthdata.nasa.gov/. Accessed July 9, 2019.
-
(2019)
NASA Earthdata
, vol.9
-
-
-
18
-
-
85071273692
-
-
Accessed July
-
Natural Earth. http://www.naturalearthdata.com. Accessed July 9, 2019.
-
(2019)
Natural Earth
, vol.9
-
-
-
19
-
-
85071265510
-
Healthsites.io: The global healthsites mapping project
-
Hostettler S Najih Besson S, Bolay JC, eds. Technologies for Development: From Innovation to Social Impact. Cham, Switzerland, Springer
-
Saameli R, Kalubi D, Herringer M, Sutton T, de Roodenbeke E. Healthsites.io: The Global Healthsites Mapping Project. In: Hostettler S, Najih Besson S, Bolay JC, eds. Technologies for Development: From Innovation to Social Impact. Cham, Switzerland: UNESCO, Springer; 2018.
-
(2018)
UNESCO
-
-
Saameli, R.1
Kalubi, D.2
Herringer, M.3
Sutton, T.4
De Roodenbeke, E.5
-
20
-
-
85071228251
-
-
Accessed July
-
Flowminder. http://flowminder.org. Accessed July 9, 2019.
-
(2019)
Flowminder
, vol.9
-
-
-
21
-
-
85071226420
-
-
Geographic Information Science & Technology Accessed July
-
Oak Ridge National Laboratory. LandScan_: Geographic Information Science & Technology. https://landscan.ornl. gov/. Accessed July 9, 2019.
-
(2019)
Oak Ridge National Laboratory. LandScan
, vol.9
-
-
-
22
-
-
85071256232
-
-
Mapping population distributions Accessed July
-
WorldPop. Mapping population distributions. http://www. worldpop.org.uk/. Accessed July 9, 2019.
-
(2019)
WorldPop
, vol.9
-
-
-
23
-
-
85071278924
-
-
Disaster maps. Accessed July
-
Facebook Data for Good. Disaster maps. https://dataforgood. fb.com/tools/disaster-maps/. Accessed July 9, 2019.
-
(2019)
Facebook Data for Good
, vol.9
-
-
-
24
-
-
66249102261
-
Digital disease detection-harnessing the web for public health surveillance
-
Brownstein JS, Freifeld CC, Madoff LC. Digital disease detection-harnessing the web for public health surveillance. N Engl J Med 2009;36021:2153-2155, 2157.
-
(2009)
N Engl J Med
, vol.360
, Issue.21
, pp. 2153-2155
-
-
Brownstein, J.S.1
Freifeld, C.C.2
Madoff, L.C.3
-
25
-
-
85071228695
-
-
Recent disease incidents. Accessed July
-
Medisys. Recent disease incidents. http://medisys.newsbrief. eu/medisys/helsinkiedition/en/home.html. Accessed July 9, 2019.
-
(2019)
Medisys
-
-
-
26
-
-
85071259582
-
-
About GPHIN Accessed July
-
Government of Canada. About GPHIN. https://gphin. canada.ca/cepr/aboutgphin-rmispenbref.jsp?language=en-CA. Accessed July 9, 2019.
-
(2019)
Government of Canada
, vol.9
-
-
-
28
-
-
85016029141
-
A simple approach to measure transmissibility and forecast incidence
-
Nouvellet P, Cori A, Garske T, et al. A simple approach to measure transmissibility and forecast incidence. Epidemics 2018;22:29-35.
-
(2018)
Epidemics
, Issue.22
, pp. 29-35
-
-
Nouvellet, P.1
Cori, A.2
Garske, T.3
-
30
-
-
85063503731
-
Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings
-
Kraemer MUG, Golding N, Bisanzio D, et al. Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings. Sci Rep 2019;91:5151.
-
(2019)
Sci Rep
, vol.9
, Issue.1
, pp. 5151
-
-
Mug, K.1
Golding, N.2
Bisanzio, D.3
-
31
-
-
84923285575
-
Commentary: Containing the Ebola outbreak-The potential and challenge of mobile network data
-
Wesolowski A, Buckee CO, Bengtsson L, Wetter E, Lu X, Tatem AJ. Commentary: containing the Ebola outbreak-The potential and challenge of mobile network data. PLoS Curr 2014;6.
-
(2014)
PLoS Curr
, pp. 6
-
-
Wesolowski, A.1
Buckee, C.O.2
Bengtsson, L.3
Wetter, E.4
Lu, X.5
Tatem, A.J.6
-
32
-
-
84937064804
-
The global distribution of the arbovirus vectors
-
Kraemer MUG et al. The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus. eLife 2015;4: e08347.
-
(2015)
Aedes Aegypti and Ae. Albopictus. ELife
, vol.4
, pp. 08347
-
-
Mug, K.1
-
33
-
-
84952864803
-
Progress and challenges in infectious disease cartography
-
Kraemer MUG, Hay SI, Pigott DM, Smith DL, Wint GRW, Golding N. Progress and challenges in infectious disease cartography. Trends Parasitol 2016;321:19-29.
-
(2016)
Trends Parasitol
, vol.32
, Issue.1
, pp. 19-29
-
-
Mug, K.1
Hay, S.I.2
Pigott, D.M.3
Smith, D.L.4
Grw, W.5
Golding, N.6
-
34
-
-
85027529293
-
Global yellow fever vaccination coverage from 1970 to 2016: An adjusted retrospective analysis
-
Shearer FM, Moyes CL, Pigott DM, et al. Global yellow fever vaccination coverage from 1970 to 2016: An adjusted retrospective analysis. Lancet Infect Dis 2017;1711:1209-1217.
-
(2017)
Lancet Infect Dis
, vol.17
, Issue.11
, pp. 1209-1217
-
-
Shearer, F.M.1
Moyes, C.L.2
Pigott, D.M.3
-
35
-
-
84926190253
-
Eight challenges in modelling infectious livestock diseases
-
Brooks-Pollock E, de Jong MC, Keeling MJ, Klinkenberg D, Wood JL. Eight challenges in modelling infectious livestock diseases. Epidemics 2015;10:1-5.
-
(2015)
Epidemics
, vol.10
, pp. 1-5
-
-
Brooks-Pollock, E.1
De Jong, M.C.2
Keeling, M.J.3
Klinkenberg, D.4
Wood, J.L.5
-
36
-
-
85014125352
-
Global distribution and environmental suitability for chikungunya virus
-
1952 to 2015
-
Nsoesie EO, Kraemer MU, Golding N, et al. Global distribution and environmental suitability for chikungunya virus, 1952 to 2015. Euro Surveill 2016;2120.
-
(2016)
Euro Surveill
, Issue.21
, pp. 20
-
-
Nsoesie, E.O.1
Kraemer, M.U.2
Golding, N.3
-
37
-
-
84969756961
-
Mapping global environmental suitability for Zika virus
-
Apr
-
Messina JP, Kraemer MU, Brady OJ, et al. Mapping global environmental suitability for Zika virus. Elife 2016 Apr 19;5.
-
(2016)
Elife
, vol.19
, pp. 5
-
-
Messina, J.P.1
Kraemer, M.U.2
Brady, O.J.3
-
38
-
-
85041469604
-
Existing and potential risk infection zones of yellow fever worldwide: A modelling analysis
-
Shearer FM, Longbottom J, Browne AJ, et al. Existing and potential risk infection zones of yellow fever worldwide: A modelling analysis. Lancet Glob Health 2018;63:e270-e278.
-
(2018)
Lancet Glob Health
, vol.6
, Issue.3
, pp. 270-278
-
-
Shearer, F.M.1
Longbottom, J.2
Browne, A.J.3
-
39
-
-
84866563012
-
Drivers, dynamics, and control of emerging vector-borne zoonotic diseases
-
Kilpatrick AM, Randolph SE. Drivers, dynamics, and control of emerging vector-borne zoonotic diseases. Lancet 2012; 3809857:1946-1955.
-
(2012)
Lancet
, vol.380
, Issue.9857
, pp. 1946-1955
-
-
Kilpatrick, A.M.1
Randolph, S.E.2
-
40
-
-
85071230358
-
-
Accessed July
-
R Epidemics Consortium. RECON. https://www. repidemicsconsortium.org/. Accessed July 9, 2019.
-
(2019)
RECON
, vol.9
-
-
Epidemics, R.1
-
43
-
-
85009274885
-
Real-Time forecasting of infectious disease dynamics with a stochastic semi-mechanistic model
-
Funk S, Camacho A, Kucharski AJ, Eggo RM, Edmunds WJ. Real-Time forecasting of infectious disease dynamics with a stochastic semi-mechanistic model. Epidemics 2018; 22:56-61.
-
(2018)
Epidemics
, Issue.22
, pp. 56-61
-
-
Funk, S.1
Camacho, A.2
Kucharski, A.J.3
Eggo, R.M.4
Edmunds, W.J.5
-
44
-
-
85032635968
-
Developing a dengue forecast model using machine learning: A case study in China
-
Guo P, Liu T, Zhang Q, et al. Developing a dengue forecast model using machine learning: A case study in China. PLoS Negl Trop Dis 2017;1110:e0005973.
-
(2017)
PLoS Negl Trop Dis
, vol.11
, Issue.10
, pp. 0005973
-
-
Guo, P.1
Liu, T.2
Zhang, Q.3
-
45
-
-
85017531304
-
Ecdc round table report and promed-mail most useful international information sources for the netherlands early warning committee
-
Bijkerk P, Monnier AA, Fanoy EB, Kardamanidis K, Friesema IH, Knol MJ. ECDC Round Table Report and ProMed-mail most useful international information sources for the Netherlands Early Warning Committee. Euro Surveill 2017;2214:30502.
-
(2017)
Euro Surveill
, vol.22
, Issue.14
, pp. 30502
-
-
Bijkerk, P.1
Monnier, A.A.2
Fanoy, E.B.3
Kardamanidis, K.4
Friesema, I.H.5
Knol, M.J.6
-
46
-
-
85071228369
-
-
Global Outbreak Alert and Response Network Accessed July
-
World Health Organization. Global Outbreak Alert and Response Network. https://www.who.int/ihr/alert-and-response/outbreak-network/en/. Accessed July 9, 2019.
-
(2019)
World Health Organization
, vol.9
-
-
|