CiteULike | Further Information

• {"link"=>{"url"=>"http://www.citeulike.org/user/tietoukka/article/7163181"}, "post_time"=>"2010-05-13 09:14:31", "tag"=>["dengue", "el_nino", "precipitation", "temperatures"], "linkout"=>{"type"=>"DOI", "url"=>"http://dx.doi.org/10.1371/journal.pmed.1000168"}, "username"=>"tietoukka", "article_id"=>"7163181"}

Mendeley | Further Information

{"title"=>"Multiyear climate variability and dengue - El Niño southern oscillation, weather, and dengue incidence in Puerto Rico, Mexico, and Thailand: A longitudinal data analysis", "type"=>"journal", "authors"=>[{"first_name"=>"Michael A.", "last_name"=>"Johansson", "scopus_author_id"=>"16233749100"}, {"first_name"=>"Derek A T", "last_name"=>"Cummings", "scopus_author_id"=>"9842706300"}, {"first_name"=>"Gregory E.", "last_name"=>"Glass", "scopus_author_id"=>"7103236648"}], "year"=>2009, "source"=>"PLoS Medicine", "identifiers"=>{"pui"=>"358015992", "issn"=>"15491277", "isbn"=>"1549-1277", "doi"=>"10.1371/journal.pmed.1000168", "scopus"=>"2-s2.0-72949114078", "pmid"=>"19918363", "sgr"=>"72949114078"}, "id"=>"dc25c058-ec74-30eb-b3c2-38b69bb0ee95", "abstract"=>"BACKGROUND: The mosquito-borne dengue viruses are a major public health problem throughout the tropical and subtropical regions of the world. Changes in temperature and precipitation have well-defined roles in the transmission cycle and may thus play a role in changing incidence levels. The El Niño Southern Oscillation (ENSO) is a multiyear climate driver of local temperature and precipitation worldwide. Previous studies have reported varying degrees of association between ENSO and dengue incidence.\\n\\nMETHODS AND FINDINGS: We analyzed the relationship between ENSO, local weather, and dengue incidence in Puerto Rico, Mexico, and Thailand using wavelet analysis to identify time- and frequency-specific association. In Puerto Rico, ENSO was transiently associated with temperature and dengue incidence on multiyear scales. However, only local precipitation and not temperature was associated with dengue on multiyear scales. In Thailand, ENSO was associated with both temperature and precipitation. Although precipitation was associated with dengue incidence, the association was nonstationary and likely spurious. In Mexico, no association between any of the variables was observed on the multiyear scale.\\n\\nCONCLUSIONS: The evidence for a relationship between ENSO, climate, and dengue incidence presented here is weak. While multiyear climate variability may play a role in endemic interannual dengue dynamics, we did not find evidence of a strong, consistent relationship in any of the study areas. The role of ENSO may be obscured by local climate heterogeneity, insufficient data, randomly coincident outbreaks, and other, potentially stronger, intrinsic factors regulating transmission dynamics.", "link"=>"http://www.mendeley.com/research/multiyear-climate-variability-dengue-el-ni%C3%B1o-southern-oscillation-weather-dengue-incidence-puerto-ri", "reader_count"=>228, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>12, "Librarian"=>1, "Researcher"=>57, "Student > Doctoral Student"=>14, "Student > Ph. D. Student"=>41, "Student > Postgraduate"=>9, "Student > Master"=>38, "Other"=>8, "Student > Bachelor"=>23, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>4, "Professor"=>15}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>12, "Librarian"=>1, "Researcher"=>57, "Student > Doctoral Student"=>14, "Student > Ph. D. Student"=>41, "Student > Postgraduate"=>9, "Student > Master"=>38, "Other"=>8, "Student > Bachelor"=>23, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>4, "Professor"=>15}, "reader_count_by_subject_area"=>{"Unspecified"=>13, "Agricultural and Biological Sciences"=>69, "Veterinary Science and Veterinary Medicine"=>2, "Chemistry"=>1, "Computer Science"=>11, "Earth and Planetary Sciences"=>9, "Economics, Econometrics and Finance"=>1, "Engineering"=>7, "Environmental Science"=>23, "Biochemistry, Genetics and Molecular Biology"=>8, "Nursing and Health Professions"=>3, "Materials Science"=>1, "Mathematics"=>10, "Medicine and Dentistry"=>54, "Physics and Astronomy"=>4, "Psychology"=>1, "Social Sciences"=>9, "Immunology and Microbiology"=>2}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>54}, "Social Sciences"=>{"Social Sciences"=>9}, "Physics and Astronomy"=>{"Physics and Astronomy"=>4}, "Psychology"=>{"Psychology"=>1}, "Mathematics"=>{"Mathematics"=>10}, "Unspecified"=>{"Unspecified"=>13}, "Environmental Science"=>{"Environmental Science"=>23}, "Engineering"=>{"Engineering"=>7}, "Chemistry"=>{"Chemistry"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>9}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>69}, "Computer Science"=>{"Computer Science"=>11}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>8}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>2}}, "reader_count_by_country"=>{"Colombia"=>2, "United States"=>9, "Sri Lanka"=>1, "United Kingdom"=>1, "Thailand"=>1, "French Polynesia"=>1, "Costa Rica"=>1, "Vietnam"=>1, "Brazil"=>2, "Mexico"=>3, "France"=>1, "Australia"=>1, "Germany"=>2}, "group_count"=>23}

ORCID

CrossRef

• http://doi.org/10.1371/journal.pntd.0003063
• http://doi.org/10.4269/ajtmh.13-0303
• http://doi.org/10.3390/insects9030098
• http://doi.org/10.1029/2019GH000186
• http://doi.org/10.4269/ajtmh.12-0478
• http://doi.org/10.1371/journal.pntd.0003957
• http://doi.org/10.3934/environsci.2017.1.83
• http://doi.org/10.1007/s12517-018-4119-9
• http://doi.org/10.1371/journal.pntd.0003306
• http://doi.org/10.1038/s41598-018-24003-z
• http://doi.org/10.1080/17513758.2018.1535096
• http://doi.org/10.1093/aje/kws140
• http://doi.org/10.1371/journal.pone.0178698
• http://doi.org/10.1016/j.cageo.2010.01.008
• http://doi.org/10.3390/tropicalmed3010005
• http://doi.org/10.1111/tmi.12754
• http://doi.org/10.1098/rsif.2013.0585
• http://doi.org/10.1371/journal.pone.0064773
• http://doi.org/10.2149/tmh.2013-24
• http://doi.org/10.1038/s41467-019-10099-y
• http://doi.org/10.1371/journal.pone.0152688
• http://doi.org/10.1016/j.actatropica.2017.04.017
• http://doi.org/10.4000/confins.15431
• http://doi.org/10.1371/journal.pone.0207999
• http://doi.org/10.1603/ME11242
• http://doi.org/10.4269/ajtmh.2011.10-0609
• http://doi.org/10.1016/j.scitotenv.2018.11.395
• http://doi.org/10.1155/2017/8045435
• http://doi.org/10.1371/journal.pntd.0002159
• http://doi.org/10.1016/j.scitotenv.2018.09.357
• http://doi.org/10.1111/j.1365-3156.2011.02734.x
• http://doi.org/10.1111/eva.12554
• http://doi.org/10.1186/s13071-018-3280-z
• http://doi.org/10.1073/pnas.1806094116
• http://doi.org/10.1016/j.actatropica.2017.07.015
• http://doi.org/10.1371/journal.pone.0187830
• http://doi.org/10.1371/journal.pone.0146495
• http://doi.org/10.3390/ijerph13111087
• http://doi.org/10.1371/journal.pcbi.1003308
• http://doi.org/10.1038/srep05157
• http://doi.org/10.4269/ajtmh.18-0783
• http://doi.org/10.1016/j.ijid.2012.07.002
• http://doi.org/10.1371/journal.pone.0157971
• http://doi.org/10.1038/s41598-017-13163-z
• http://doi.org/10.1016/j.apgeog.2018.10.005
• http://doi.org/10.1371/journal.pone.0208203
• http://doi.org/10.1038/s41598-018-38034-z
• http://doi.org/10.1186/1471-2334-11-172
• http://doi.org/10.1016/j.gloenvcha.2014.09.007
• http://doi.org/10.1186/1471-2334-14-167
• http://doi.org/10.3390/atmos9070282
• http://doi.org/10.1073/pnas.1107485109
• http://doi.org/10.1016/j.scitotenv.2017.11.314
• http://doi.org/10.1371/journal.pone.0095447
• http://doi.org/10.1080/17565529.2014.951012
• http://doi.org/10.1016/j.uclim.2017.10.008
• http://doi.org/10.1603/ME11156
• http://doi.org/10.1371/journal.pntd.0004968
• http://doi.org/10.1038/srep33707
• http://doi.org/10.1186/1471-2334-12-98
• http://doi.org/10.1590/1806-9061-2016-0411
• http://doi.org/10.1186/s12889-018-5532-4
• http://doi.org/10.4269/ajtmh.15-0846
• http://doi.org/10.1590/0102-311x00123417
• http://doi.org/10.1186/1471-2458-12-982
• http://doi.org/10.3389/fpubh.2015.00187
• http://doi.org/10.1016/j.mbs.2017.03.007
• http://doi.org/10.1603/ME12245
• http://doi.org/10.1007/s40471-017-0095-y
• http://doi.org/10.1073/pnas.1909865116
• http://doi.org/10.1371/journal.pntd.0003003
• http://doi.org/10.1371/journal.pntd.0006284
• http://doi.org/10.1371/journal.pntd.0004002
• http://doi.org/10.1038/s41467-019-09035-x
• http://doi.org/10.1098/rsif.2015.0024
• http://doi.org/10.1371/journal.pntd.0004842
• http://doi.org/10.1186/s12879-019-3874-x
• http://doi.org/10.1258/ebm.2011.010402
• http://doi.org/10.1073/pnas.1501375112
• http://doi.org/10.1038/srep16105
• http://doi.org/10.4269/ajtmh.13-0321
• http://doi.org/10.1016/j.actatropica.2014.10.005
• http://doi.org/10.1371/journal.pcbi.1005607
• http://doi.org/10.1017/S0031182012000431
• http://doi.org/10.1016/S1473-3099(14)70781-9
• http://doi.org/10.1371/journal.pmed.1000185
• http://doi.org/10.1016/j.micinf.2009.12.011
• http://doi.org/10.1371/journal.pntd.0005797
• http://doi.org/10.1093/aje/kwv064
• http://doi.org/10.1016/j.jinf.2019.07.008
• http://doi.org/10.1016/j.annemergmed.2014.04.008
• http://doi.org/10.1016/j.scitotenv.2017.12.200
• http://doi.org/10.1111/tmi.12325
• http://doi.org/10.3390/ijgi3020732
• http://doi.org/10.1155/2017/8947067
• http://doi.org/10.1371/journal.pone.0053847
• http://doi.org/10.1007/s00705-010-0721-1
• http://doi.org/10.1371/journal.pntd.0006935
• http://doi.org/10.1016/j.arcmed.2018.01.003
• http://doi.org/10.1186/1472-6947-12-124
• http://doi.org/10.1371/journal.pntd.0007606
• http://doi.org/10.1186/s12879-018-3045-5
• http://doi.org/10.1371/journal.pntd.0006554
• http://doi.org/10.1371/journal.pone.0125049
• http://doi.org/10.1186/s12889-018-5251-x
• http://doi.org/10.1177/0309133311417942
• http://doi.org/10.1088/1748-9326/ab0036
• http://doi.org/10.1371/journal.pntd.0004681
• http://doi.org/10.1371/journal.pntd.0002260
• http://doi.org/10.1371/journal.pone.0169199
• http://doi.org/10.1007/s00484-018-1633-0
• http://doi.org/10.1186/1475-2875-10-190
• http://doi.org/10.1371/journal.pntd.0001470
• http://doi.org/10.1080/24694452.2018.1511413
• http://doi.org/10.1111/zph.12213
• http://doi.org/10.3390/ijerph110909409
• http://doi.org/10.1371/journal.pntd.0000747
• http://doi.org/10.1007/s12250-015-3621-4
• http://doi.org/10.3390/ijerph16132296
• http://doi.org/10.1371/journal.pntd.0003155
• http://doi.org/10.1099/vir.0.059998-0
• http://doi.org/10.1038/s41598-019-43353-w
• http://doi.org/10.1093/infdis/jis526
• http://doi.org/10.1186/s12889-016-2923-2
• http://doi.org/10.1080/00031305.2016.1148631
• http://doi.org/10.1016/j.apm.2016.11.022
• http://doi.org/10.1371/journal.pcbi.1000898
• http://doi.org/10.3389/fcimb.2017.00317
• http://doi.org/10.1007/s00477-015-1053-1
• http://doi.org/10.1016/j.vaccine.2019.10.010
• http://doi.org/10.1371/journal.pntd.0001322
• http://doi.org/10.1371/journal.pntd.0001378
• http://doi.org/10.1093/jtm/taw062
• http://doi.org/10.1586/14787210.2015.1028364
• http://doi.org/10.1371/journal.pone.0028873
• http://doi.org/10.3390/ijerph111010694
• http://doi.org/10.1371/journal.pntd.0001633
• http://doi.org/10.1289/ehp.1306556
• http://doi.org/10.1016/j.socscimed.2016.12.010

DataCite

Europe PMC Citations | Further Information

Europe PMC Database Citations

PubMed Central

• 3586607
• 4620875
• 3126728
• 3528427
• 3986908
• 3534444
• 3527308
• 4784273
• 3155970
• 3855512
• 2770118
• 4281303
• 2932675
• 3812071
• 3869155
• 3281819
• 3443104
• 3558489
• 3748059
• 3989333
• 4427447
• 4709116
• 4816319
• 2903474
• 3181236
• 3243685
• 3279338
• 3341328
• 3617145
• 4519153
• 4537107
• 3674989
• 4102451
• 4120682
• 4191945
• 4238988
• 4148136
• 3530371
• 4199026
• 4211001
• 3083744
• 3752767
• 3854883
• 4155567
• 3929176
• 4323421
• 3523792
• 3965842
• 4042128
• 4633589
• 4519658

Scopus | Further Information

{"@_fa"=>"true", "link"=>[{"@_fa"=>"true", "@ref"=>"self", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/72949114078"}, {"@_fa"=>"true", "@ref"=>"author-affiliation", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/72949114078?field=author,affiliation"}, {"@_fa"=>"true", "@ref"=>"scopus", "@href"=>"https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=72949114078&origin=inward"}, {"@_fa"=>"true", "@ref"=>"scopus-citedby", "@href"=>"https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=72949114078&origin=inward"}], "prism:url"=>"https://api.elsevier.com/content/abstract/scopus_id/72949114078", "dc:identifier"=>"SCOPUS_ID:72949114078", "eid"=>"2-s2.0-72949114078", "dc:title"=>"Multiyear climate variability and dengue - El Niño southern oscillation, weather, and dengue incidence in Puerto Rico, Mexico, and Thailand: A longitudinal data analysis", "dc:creator"=>"Johansson M.", "prism:publicationName"=>"PLoS Medicine", "prism:issn"=>"15491277", "prism:eIssn"=>"15491676", "prism:volume"=>"6", "prism:issueIdentifier"=>"11", "prism:pageRange"=>nil, "prism:coverDate"=>"2009-11-01", "prism:coverDisplayDate"=>"November 2009", "prism:doi"=>"10.1371/journal.pmed.1000168", "citedby-count"=>"161", "affiliation"=>[{"@_fa"=>"true", "affilname"=>"Centers for Disease Control and Prevention San Juan", "affiliation-city"=>"San Juan", "affiliation-country"=>"Puerto Rico"}, {"@_fa"=>"true", "affilname"=>"Johns Hopkins Bloomberg School of Public Health", "affiliation-city"=>"Baltimore", "affiliation-country"=>"United States"}], "pubmed-id"=>"19918363", "prism:aggregationType"=>"Journal", "subtype"=>"ar", "subtypeDescription"=>"Article", "article-number"=>"e1000168", "source-id"=>"144840", "openaccess"=>"1", "openaccessFlag"=>true}

Web of Science® | Further Information

Article Coverage

Article Coverage Curated

Facebook

• {"url"=>"http%3A%2F%2Fjournals.plos.org%2Fplosmedicine%2Farticle%3Fid%3D10.1371%252Fjournal.pmed.1000168", "share_count"=>0, "like_count"=>0, "comment_count"=>0, "click_count"=>0, "total_count"=>0}

Journal Comments | Further Information

• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/817cc25e-25b5-4d66-807c-490bd460222e", "title"=>"Wavelet Analysis of Multiyear Climate Variability and Dengue: The crucial influence of data transformation and null hypothesis tested", "body"=>"Wavelet Analysis of Multiyear Climate Variability and Dengue: The crucial influence of data transformation and null hypothesis tested\n\nBernard Cazelles, Mario Chavez\n\nIn an interesting work, Johansson et al [1] examine the dynamic relationship between climate variables and the incidence of dengue in Thailand, Mexico and Puerto Rico using wavelet analysis. The strength of this work is the comparison between countries in contrasted environment, and they find no systematic significant association between multi-annual dengue outbreaks and El Niño. But one of the main findings of Johansson et al [1] is that dengue incidence oscillations are dominated by a marked seasonal component in these three countries. They also emphasize the weakness of multiyear oscillations contrarily to previous studies [2,3]. Rohani [4] commented the paper underlying that this strong seasonality is a clear fingerprint of the influence of local weather variables on disease incidence and may have important consequences in term of prediction. Significant predictors of dengue epidemic risk, such as local climatic drivers (e.g. rainfall, humidity and temperature) may be usefully employed in early warning systems. Moreover the absence of a significant influence of El Niño on dengue transmission reported by the authors also seems to be important information for the development of predictive tools [4].\nNevertheless, the results obtained by Johansson et al [1] are strongly relied on the methodological choices associated with the wavelet analysis done. The authors have used a log-transformation of the dengue cases and for testing the wavelet patterns obtained they have used an AR(p) process. As the obtained results are not in the line of previous published works where the important role of the 2-3 year periodic components is highlighted [2,3], it is crucial to point out the weakness of their methodological choices. Firstly, it is well know that the log-transformation greatly homogenizes the variance of time series and thus gives more weight to the dominant oscillations. For this reason, in epidemiology there is more and more works that prefer the square-root-transformation (e.g. [5]). To simply illustrate the effect of these transformations we have applied wavelet analysis to the dengue dataset of Thailand with no-transformation, square-root-transformation and log-transformation (Fig. S1). This figure clearly demonstrates that compared to the results obtained with no-transformation, those with log-transformation give more emphasis to the seasonal component. This can be easily explained because a homogenization of amplitude of the time series by a log-transformation induces an important reduction of the variance. \nThe second methodological drawback is the choice of an AR(p) stochastic process (without specifying the p order used in their paper) to test the statistical significance of the wavelet patterns. As stressed by the authors, it is clear that the use of white noise is frequently insufficient and red noise (AR(1) process) appears not always supported by the spectral characteristics of ecological and epidemiological time series. Similarly, AR(p) with higher order considerably reduce the discrimination power of the hypothesis testing in case of pseudo-periodic data. We think that a bootstrapping approach driven by the data allowing null stochastic processes in accordance with the characteristics of the dataset is preferable. We then suggested using a class of bootstrapped series that models the underlying statistical structure of the time series as 1/(ƒ^β) noise i.e. bootstrapped series with a similar slope (β) as the raw series in their power spectra [6]. The Fig S2 illustrates our comment. White noise gives equal importance to all the periodic components, red noise gives significance only to periodic component lesser than 15 months, and our proposed 1/(ƒ^β) process gives importance to larger periodic bands in greater adequation with the apparent reality.\nThese two methodological shortcomings greatly weaken the presented findings [1]. Contrarily our results (see Fig S2B) support the fact that the multi-year components of dengue epidemics are more important than claimed by the authors [1]. Particularly with a better detection of multiyear components both in dengue and climatic time series, one can expect to find more clear statistical association, event discontinuous, between these series as its bas been stressed in previous works [2,3]. This may greatly modify the different conclusions drawn based on this study even in terms of prediction [4]. \nA deeper understanding of infectious disease dynamics is important in order to forecast the effects of environmental changes. Nonstationarity of relationships between climate and disease could induce problems for disease prediction. Conventional statistical methods may fail to reveal a relationship between climate and health when discontinuous associations are present. Wavelet approaches [7,8] appear particularly appropriate and have been used for both descriptions of epidemiological time series and quantification of nonstationary relationships between epidemiological and environmental time series. Nevertheless some cautions have to be considered for a straightforward interpretation of the obtained results.\n\nBernard Cazelles (E-mail: cazelles@biologie.ens.fr)\nUMR 7625, UPMC-CNRS-ENS, Ecole Normale Supérieure, 46 rue d’Ulm, 75230 Paris cedex 05, France and UMMISCO UMI 209 IRD-UPMC, 93142 Bondy, France\n\nMario Chavez (E-mail: mario.chavez@upmc.fr)\nUMR 7225 UPMC-CNRS, Hôpital de La Pitié-Salpêtrière, 47 Bd. de l'Hôpital, 75651 Paris cedex 13, France.\n\n1. Johansson MA, Cummings DAT, Glass GE (2009) Multi-year variability and dengue: El Nino Southern Southern Oscillation, weather, and dengue incidence in Puerto Rico, Mexico, and Thailand. PLoS Med 6: e168. doi:10.1371/journal.pmed.1000168.\n2. Cummings DA, Irizarry RA, Huang NE, Endy TP, Nisalak A, et al. (2004) Travelling waves in the occurrence of dengue haemorrhagic fever in Thailand. Nature 427: 344–347.\n3. Cazelles B, Chavez M, McMichael AJ, Hales S (2005) Nonstationary influence of El Niño on the synchronous dengue epidemics in Thailand. PLoS Med 2: e106. doi:10.1371/journal.pmed.0020106.\n4. Rohani P (2009) The link between dengue incidence and El Niño Southern Oscillation. PLoS Med 6: e185. doi:10.1371/journal.pmed.1000185.\n5. Grenfell BT, Bjørnstad ON, Kappey J (2001) Travelling waves and spatial hierarchies in measles epidemics. Nature 414: 716–723.\n6. Rouyer T, Fromentin JM, Stenseth NC, Cazelles, B (2008) Analysing multiple time series and extending significance testing in wavelet analysis. Marine Ecology Progress Series, 359: 11-23.\n7. Cazelles B, Chavez M, Magny GC, Guégan JF, Hales S (2007) Time-dependent spectral analysis of epidemiological time-series with wavelets. J R Soc Interface 4: 625–636.\n8. Cazelles B, Chavez M, Berteaux D, Ménard F, Vik JO, Jenouvrier S, Stenseth NC (2008) Wavelet analysis of ecological time series. Oecologia: 156, 287-304.\n\n\n\nFigure S1 Influence of data transformation on the wavelet analysis. (A-C-E) The dengue hemorrhagic fever cases in Thailand: the row data (A), the square-root-transformed data (C) and log-transformed (E). (B-D-F) The wavelet power spectrum of the 3 transformed time series respectively. The colors code for power values from dark blue, low values, to dark red, high values. The black lines show the 5% significant levels computed based on 1000 bootstrapped series based on an AR(1) process (red noise). The dashed lines show the cone of influence, which indicates the region not influenced by edge effects, and the white lines show the local maxima of the wavelet power spectra. \n\nFigure S2 Influence of the null stochastic process employed for testing the wavelet power spectra. The dengue hemorrhagic fever cases in Thailand with log-transformation have been used. The significant levels have been computed based on 1000 bootstrapped series with: (A) white noise process; (B) 1/(ƒ^β) noise process; (C) red noise process, AR(1). The colors code for power values from dark blue, low values, to dark red, high values. The black lines the show the 5% significant levels computed based on 1000 bootstrapped series based on a given process. The dashed lines show the cone of influence, which indicates the region not influenced by edge effects, and the white lines show the local maxima of the wavelet power spectra.\n\n\n", "isRemoved"=>false, "created"=>"2010-05-01T21:59:13Z", "lastModified"=>"2010-05-01T21:59:13Z", "creator"=>{"userId"=>"29075"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.1000168", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>1, "mostRecentActivity"=>"2010-07-07T21:17:31Z", "replies"=>[{"type"=>"REPLY", "parentID"=>11809, "annotationUri"=>"info:doi/10.1371/reply/0028c6bb-55e9-40d0-83ec-5cd8704b7c9f", "title"=>"RE: Wavelet Analysis of Multiyear Climate Variability and Dengue: The crucial influence of data transformation and null hypothesis tested", "body"=>"We thank Cazelles and Chavez for their comments on our manuscript. We agree that careful consideration of the statistical significance of our findings is critical. However, we disagree with some of the assertions regarding our findings.\r\n\r\nFirst, we did not intend to imply that inter-annual variability is not an important part of dengue dynamics. Rather, we believe that it is extremely important. What our analysis shows is that the inter-annual variation does not exhibit strong stationarity and is not strongly associated with the assessed climate variables. Although not statistically significant here, the generally high power at long periods in the transforms is consistent with other analyses [1-4].\r\n\r\nCazelles and Chavez also bring up two important methodological issues: the data transformation choice and the definition of the null hypothesis. We used wavelet analysis to analyze periodic components within dengue time series. To elucidate these components, it is often necessary to reduce skewing in the data by transformation and standardize the mean and variance by normalization. Histograms of all three dengue time series studied here show significant skewing which can be reduced effectively by log transformation, but not the square-root transformation.\r\n\r\nAs Cazelles and Chavez report, if we had analyzed the skewed, square-root transformed data, we would have found slightly different results in some cases. However, even then, the only significance found at multi-year scales was transient and thus supports the assertion that inter-annual variability is important but does not represent a stationary periodic. In coherence analysis, the square-root transformation slightly altered the shape and area of significance, but again did not qualitatively affect the conclusions.\r\n\r\nIn our manuscript we stated that our null hypothesis for wavelet significance was “the variability of the observed time-series is equivalent to the expected variability of a random process with similar first-order autocorrelation.” That is, a red noise, AR(1) process. As suggested, we reanalyzed the data using a pink-noise (1/(ƒ^β)) process. Regardless of data transformation (log or square-root), using pink rather than red noise did not result in notably different characterization of significance in any of the wavelet transforms.\r\n\r\nIn conclusion, we appreciate the attention of Cazelles and Chavez to the details of wavelet analysis for epidemiological data. We agree that a pink-noise is a reasonable null hypothesis and disagree that a square-root transformation is adequate for the data in question. Most importantly, neither of these components affects our conclusions about the non-stationarity of multi-year fluctuation in dengue incidence and the lack of evidence for a strong, biologically-plausible relationship between multi-year climate variability and dengue.\r\n\r\nMichael A. Johansson\r\nDivision of Vector-Borne Infectious Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico\r\n\r\nDerek A. T. Cummings\r\nDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America\r\n\r\nGregory E. Glass\r\nW. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America\r\n\r\n1. Hay SI, Myers MF, Burke DS, Vaughn DW, Endy T, et al. (2000) Etiology of interepidemic periods of mosquito-borne disease. Proc Natl Acad Sci U S A 97:9335–9339.\r\n\r\n2. Cummings DA, Irizarry RA, Huang NE, Endy TP, Nisalak A, et al. (2004) Travelling waves in the occurrence of dengue haemorrhagic fever in Thailand. Nature 427: 344–347.\r\n\r\n3. Cazelles B, Chavez M, McMichael AJ, Hales S (2005) Nonstationary influence of El Niño on the synchronous dengue epidemics in Thailand. PLoS Med 2: e106.doi:10.1371/journal.pmed.0020106.\r\n\r\n4. Nagao Y, Koelle K (2008) Decreases in dengue transmission may act to increase the incidence of dengue hemorrhagic fever. Proc Natl Acad Sci U S A 105: 2238–2243.\r\n", "isRemoved"=>false, "created"=>"2010-07-07T21:17:31Z", "lastModified"=>"2010-07-07T21:17:31Z", "creator"=>{"userId"=>"174145"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pmed.1000168", "state"=>"published", "journals"=>{"PLoSMedicine"=>{"journalKey"=>"PLoSMedicine", "eIssn"=>"1549-1676", "title"=>"PLOS Medicine"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2010-07-07T21:17:31Z", "replies"=>[]}]}

Nature

Reddit

Research Blogging

ScienceSeeker | Further Information

Twitter

• {"id"=>"479068813116186628", "text"=>"#nowreading \"Multiyear Climate Variability and #Dengue—El Niño Southern Oscillation, Weather, and Dengue Incidence\" http://t.co/vOPW75aAMI", "created_at"=>"2014-06-18T01:11:20Z", "user"=>"CaritoTV", "user_name"=>"Brenda Carolina", "user_profile_image"=>"http://pbs.twimg.com/profile_images/429840605704097792/QXxasMJ__normal.jpeg"}

Wikipedia

Wordpress.com | Further Information

Counter

• {"month"=>"11", "year"=>"2009", "pdf_views"=>"161", "xml_views"=>"10", "html_views"=>"550"}
• {"month"=>"12", "year"=>"2009", "pdf_views"=>"68", "xml_views"=>"15", "html_views"=>"247"}
• {"month"=>"1", "year"=>"2010", "pdf_views"=>"37", "xml_views"=>"2", "html_views"=>"137"}
• {"month"=>"2", "year"=>"2010", "pdf_views"=>"37", "xml_views"=>"0", "html_views"=>"140"}
• {"month"=>"3", "year"=>"2010", "pdf_views"=>"31", "xml_views"=>"0", "html_views"=>"152"}
• {"month"=>"4", "year"=>"2010", "pdf_views"=>"25", "xml_views"=>"2", "html_views"=>"114"}
• {"month"=>"5", "year"=>"2010", "pdf_views"=>"21", "xml_views"=>"0", "html_views"=>"267"}
• {"month"=>"6", "year"=>"2010", "pdf_views"=>"22", "xml_views"=>"0", "html_views"=>"114"}
• {"month"=>"7", "year"=>"2010", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"99"}
• {"month"=>"8", "year"=>"2010", "pdf_views"=>"31", "xml_views"=>"1", "html_views"=>"127"}
• {"month"=>"9", "year"=>"2010", "pdf_views"=>"28", "xml_views"=>"1", "html_views"=>"130"}
• {"month"=>"10", "year"=>"2010", "pdf_views"=>"28", "xml_views"=>"1", "html_views"=>"137"}
• {"month"=>"11", "year"=>"2010", "pdf_views"=>"21", "xml_views"=>"0", "html_views"=>"92"}
• {"month"=>"12", "year"=>"2010", "pdf_views"=>"16", "xml_views"=>"0", "html_views"=>"56"}
• {"month"=>"1", "year"=>"2011", "pdf_views"=>"14", "xml_views"=>"2", "html_views"=>"46"}
• {"month"=>"2", "year"=>"2011", "pdf_views"=>"20", "xml_views"=>"0", "html_views"=>"45"}
• {"month"=>"3", "year"=>"2011", "pdf_views"=>"16", "xml_views"=>"0", "html_views"=>"69"}
• {"month"=>"4", "year"=>"2011", "pdf_views"=>"15", "xml_views"=>"0", "html_views"=>"42"}
• {"month"=>"5", "year"=>"2011", "pdf_views"=>"17", "xml_views"=>"1", "html_views"=>"41"}
• {"month"=>"6", "year"=>"2011", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"30"}
• {"month"=>"7", "year"=>"2011", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"21"}
• {"month"=>"8", "year"=>"2011", "pdf_views"=>"12", "xml_views"=>"1", "html_views"=>"27"}
• {"month"=>"9", "year"=>"2011", "pdf_views"=>"17", "xml_views"=>"2", "html_views"=>"70"}
• {"month"=>"10", "year"=>"2011", "pdf_views"=>"18", "xml_views"=>"1", "html_views"=>"101"}
• {"month"=>"11", "year"=>"2011", "pdf_views"=>"18", "xml_views"=>"0", "html_views"=>"86"}
• {"month"=>"12", "year"=>"2011", "pdf_views"=>"15", "xml_views"=>"0", "html_views"=>"65"}
• {"month"=>"1", "year"=>"2012", "pdf_views"=>"12", "xml_views"=>"0", "html_views"=>"64"}
• {"month"=>"2", "year"=>"2012", "pdf_views"=>"36", "xml_views"=>"0", "html_views"=>"102"}
• {"month"=>"3", "year"=>"2012", "pdf_views"=>"31", "xml_views"=>"0", "html_views"=>"79"}
• {"month"=>"4", "year"=>"2012", "pdf_views"=>"22", "xml_views"=>"1", "html_views"=>"66"}
• {"month"=>"5", "year"=>"2012", "pdf_views"=>"22", "xml_views"=>"1", "html_views"=>"57"}
• {"month"=>"6", "year"=>"2012", "pdf_views"=>"11", "xml_views"=>"1", "html_views"=>"47"}
• {"month"=>"7", "year"=>"2012", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"50"}
• {"month"=>"8", "year"=>"2012", "pdf_views"=>"18", "xml_views"=>"6", "html_views"=>"80"}
• {"month"=>"9", "year"=>"2012", "pdf_views"=>"18", "xml_views"=>"0", "html_views"=>"56"}
• {"month"=>"10", "year"=>"2012", "pdf_views"=>"17", "xml_views"=>"1", "html_views"=>"71"}
• {"month"=>"11", "year"=>"2012", "pdf_views"=>"23", "xml_views"=>"1", "html_views"=>"86"}
• {"month"=>"12", "year"=>"2012", "pdf_views"=>"26", "xml_views"=>"0", "html_views"=>"84"}
• {"month"=>"1", "year"=>"2013", "pdf_views"=>"17", "xml_views"=>"0", "html_views"=>"95"}
• {"month"=>"2", "year"=>"2013", "pdf_views"=>"26", "xml_views"=>"2", "html_views"=>"133"}
• {"month"=>"3", "year"=>"2013", "pdf_views"=>"23", "xml_views"=>"0", "html_views"=>"120"}
• {"month"=>"4", "year"=>"2013", "pdf_views"=>"18", "xml_views"=>"0", "html_views"=>"151"}
• {"month"=>"5", "year"=>"2013", "pdf_views"=>"23", "xml_views"=>"0", "html_views"=>"158"}
• {"month"=>"6", "year"=>"2013", "pdf_views"=>"14", "xml_views"=>"0", "html_views"=>"117"}
• {"month"=>"7", "year"=>"2013", "pdf_views"=>"17", "xml_views"=>"0", "html_views"=>"115"}
• {"month"=>"8", "year"=>"2013", "pdf_views"=>"29", "xml_views"=>"9", "html_views"=>"114"}
• {"month"=>"9", "year"=>"2013", "pdf_views"=>"23", "xml_views"=>"2", "html_views"=>"130"}
• {"month"=>"10", "year"=>"2013", "pdf_views"=>"18", "xml_views"=>"1", "html_views"=>"116"}
• {"month"=>"11", "year"=>"2013", "pdf_views"=>"14", "xml_views"=>"1", "html_views"=>"86"}
• {"month"=>"12", "year"=>"2013", "pdf_views"=>"19", "xml_views"=>"1", "html_views"=>"57"}
• {"month"=>"1", "year"=>"2014", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"60"}
• {"month"=>"2", "year"=>"2014", "pdf_views"=>"14", "xml_views"=>"1", "html_views"=>"73"}
• {"month"=>"3", "year"=>"2014", "pdf_views"=>"17", "xml_views"=>"2", "html_views"=>"66"}
• {"month"=>"4", "year"=>"2014", "pdf_views"=>"18", "xml_views"=>"5", "html_views"=>"100"}
• {"month"=>"5", "year"=>"2014", "pdf_views"=>"14", "xml_views"=>"1", "html_views"=>"104"}
• {"month"=>"6", "year"=>"2014", "pdf_views"=>"24", "xml_views"=>"0", "html_views"=>"85"}
• {"month"=>"7", "year"=>"2014", "pdf_views"=>"15", "xml_views"=>"0", "html_views"=>"62"}
• {"month"=>"8", "year"=>"2014", "pdf_views"=>"20", "xml_views"=>"4", "html_views"=>"97"}
• {"month"=>"9", "year"=>"2014", "pdf_views"=>"15", "xml_views"=>"1", "html_views"=>"75"}
• {"month"=>"10", "year"=>"2014", "pdf_views"=>"19", "xml_views"=>"2", "html_views"=>"118"}
• {"month"=>"11", "year"=>"2014", "pdf_views"=>"22", "xml_views"=>"1", "html_views"=>"99"}
• {"month"=>"12", "year"=>"2014", "pdf_views"=>"9", "xml_views"=>"2", "html_views"=>"80"}
• {"month"=>"1", "year"=>"2015", "pdf_views"=>"14", "xml_views"=>"0", "html_views"=>"83"}
• {"month"=>"2", "year"=>"2015", "pdf_views"=>"12", "xml_views"=>"0", "html_views"=>"56"}
• {"month"=>"3", "year"=>"2015", "pdf_views"=>"35", "xml_views"=>"0", "html_views"=>"116"}
• {"month"=>"4", "year"=>"2015", "pdf_views"=>"16", "xml_views"=>"0", "html_views"=>"93"}
• {"month"=>"5", "year"=>"2015", "pdf_views"=>"20", "xml_views"=>"1", "html_views"=>"88"}
• {"month"=>"6", "year"=>"2015", "pdf_views"=>"14", "xml_views"=>"0", "html_views"=>"81"}
• {"month"=>"7", "year"=>"2015", "pdf_views"=>"15", "xml_views"=>"0", "html_views"=>"73"}
• {"month"=>"8", "year"=>"2015", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"65"}
• {"month"=>"9", "year"=>"2015", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"79"}
• {"month"=>"10", "year"=>"2015", "pdf_views"=>"21", "xml_views"=>"0", "html_views"=>"119"}
• {"month"=>"11", "year"=>"2015", "pdf_views"=>"17", "xml_views"=>"0", "html_views"=>"90"}
• {"month"=>"12", "year"=>"2015", "pdf_views"=>"14", "xml_views"=>"1", "html_views"=>"134"}
• {"month"=>"1", "year"=>"2016", "pdf_views"=>"20", "xml_views"=>"0", "html_views"=>"105"}
• {"month"=>"2", "year"=>"2016", "pdf_views"=>"23", "xml_views"=>"0", "html_views"=>"95"}
• {"month"=>"3", "year"=>"2016", "pdf_views"=>"17", "xml_views"=>"0", "html_views"=>"96"}
• {"month"=>"4", "year"=>"2016", "pdf_views"=>"26", "xml_views"=>"0", "html_views"=>"138"}
• {"month"=>"5", "year"=>"2016", "pdf_views"=>"23", "xml_views"=>"0", "html_views"=>"60"}
• {"month"=>"6", "year"=>"2016", "pdf_views"=>"16", "xml_views"=>"0", "html_views"=>"104"}
• {"month"=>"7", "year"=>"2016", "pdf_views"=>"12", "xml_views"=>"0", "html_views"=>"48"}
• {"month"=>"8", "year"=>"2016", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"73"}
• {"month"=>"9", "year"=>"2016", "pdf_views"=>"26", "xml_views"=>"0", "html_views"=>"107"}
• {"month"=>"10", "year"=>"2016", "pdf_views"=>"19", "xml_views"=>"0", "html_views"=>"87"}
• {"month"=>"11", "year"=>"2016", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"76"}
• {"month"=>"12", "year"=>"2016", "pdf_views"=>"25", "xml_views"=>"0", "html_views"=>"80"}
• {"month"=>"1", "year"=>"2017", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"61"}
• {"month"=>"2", "year"=>"2017", "pdf_views"=>"23", "xml_views"=>"2", "html_views"=>"61"}
• {"month"=>"3", "year"=>"2017", "pdf_views"=>"14", "xml_views"=>"1", "html_views"=>"100"}
• {"month"=>"4", "year"=>"2017", "pdf_views"=>"14", "xml_views"=>"0", "html_views"=>"91"}
• {"month"=>"5", "year"=>"2017", "pdf_views"=>"14", "xml_views"=>"4", "html_views"=>"82"}
• {"month"=>"6", "year"=>"2017", "pdf_views"=>"17", "xml_views"=>"0", "html_views"=>"81"}
• {"month"=>"7", "year"=>"2017", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"92"}
• {"month"=>"8", "year"=>"2017", "pdf_views"=>"20", "xml_views"=>"1", "html_views"=>"162"}
• {"month"=>"9", "year"=>"2017", "pdf_views"=>"21", "xml_views"=>"5", "html_views"=>"202"}
• {"month"=>"10", "year"=>"2017", "pdf_views"=>"18", "xml_views"=>"2", "html_views"=>"143"}
• {"month"=>"11", "year"=>"2017", "pdf_views"=>"27", "xml_views"=>"1", "html_views"=>"92"}
• {"month"=>"12", "year"=>"2017", "pdf_views"=>"22", "xml_views"=>"0", "html_views"=>"59"}
• {"month"=>"1", "year"=>"2018", "pdf_views"=>"21", "xml_views"=>"2", "html_views"=>"95"}
• {"month"=>"2", "year"=>"2018", "pdf_views"=>"13", "xml_views"=>"1", "html_views"=>"33"}
• {"month"=>"3", "year"=>"2018", "pdf_views"=>"40", "xml_views"=>"3", "html_views"=>"73"}
• {"month"=>"4", "year"=>"2018", "pdf_views"=>"21", "xml_views"=>"0", "html_views"=>"44"}
• {"month"=>"5", "year"=>"2018", "pdf_views"=>"18", "xml_views"=>"0", "html_views"=>"48"}
• {"month"=>"6", "year"=>"2018", "pdf_views"=>"24", "xml_views"=>"5", "html_views"=>"38"}
• {"month"=>"7", "year"=>"2018", "pdf_views"=>"23", "xml_views"=>"6", "html_views"=>"42"}
• {"month"=>"8", "year"=>"2018", "pdf_views"=>"19", "xml_views"=>"1", "html_views"=>"40"}
• {"month"=>"9", "year"=>"2018", "pdf_views"=>"24", "xml_views"=>"1", "html_views"=>"43"}
• {"month"=>"10", "year"=>"2018", "pdf_views"=>"18", "xml_views"=>"1", "html_views"=>"49"}
• {"month"=>"11", "year"=>"2018", "pdf_views"=>"15", "xml_views"=>"0", "html_views"=>"43"}
• {"month"=>"12", "year"=>"2018", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"37"}
• {"month"=>"1", "year"=>"2019", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"24"}
• {"month"=>"2", "year"=>"2019", "pdf_views"=>"16", "xml_views"=>"0", "html_views"=>"28"}
• {"month"=>"3", "year"=>"2019", "pdf_views"=>"25", "xml_views"=>"1", "html_views"=>"52"}
• {"month"=>"4", "year"=>"2019", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"31"}
• {"month"=>"5", "year"=>"2019", "pdf_views"=>"20", "xml_views"=>"0", "html_views"=>"52"}
• {"month"=>"6", "year"=>"2019", "pdf_views"=>"27", "xml_views"=>"0", "html_views"=>"27"}
• {"month"=>"7", "year"=>"2019", "pdf_views"=>"25", "xml_views"=>"0", "html_views"=>"30"}
• {"month"=>"8", "year"=>"2019", "pdf_views"=>"31", "xml_views"=>"2", "html_views"=>"29"}
• {"month"=>"9", "year"=>"2019", "pdf_views"=>"18", "xml_views"=>"0", "html_views"=>"68"}
• {"month"=>"10", "year"=>"2019", "pdf_views"=>"31", "xml_views"=>"0", "html_views"=>"42"}
• {"month"=>"11", "year"=>"2019", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"47"}
• {"month"=>"12", "year"=>"2019", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"12"}

Figshare

• {"files"=>["https://ndownloader.figshare.com/files/434775", "https://ndownloader.figshare.com/files/434805", "https://ndownloader.figshare.com/files/434838", "https://ndownloader.figshare.com/files/434866", "https://ndownloader.figshare.com/files/434930", "https://ndownloader.figshare.com/files/434972"], "description"=>"<div><h3>Background</h3><p>The mosquito-borne dengue viruses are a major public health problem throughout the tropical and subtropical regions of the world. Changes in temperature and precipitation have well-defined roles in the transmission cycle and may thus play a role in changing incidence levels. The El Niño Southern Oscillation (ENSO) is a multiyear climate driver of local temperature and precipitation worldwide. Previous studies have reported varying degrees of association between ENSO and dengue incidence.</p><h3>Methods and Findings</h3><p>We analyzed the relationship between ENSO, local weather, and dengue incidence in Puerto Rico, Mexico, and Thailand using wavelet analysis to identify time- and frequency-specific association. In Puerto Rico, ENSO was transiently associated with temperature and dengue incidence on multiyear scales. However, only local precipitation and not temperature was associated with dengue on multiyear scales. In Thailand, ENSO was associated with both temperature and precipitation. Although precipitation was associated with dengue incidence, the association was nonstationary and likely spurious. In Mexico, no association between any of the variables was observed on the multiyear scale.</p><h3>Conclusions</h3><p>The evidence for a relationship between ENSO, climate, and dengue incidence presented here is weak. While multiyear climate variability may play a role in endemic interannual dengue dynamics, we did not find evidence of a strong, consistent relationship in any of the study areas. The role of ENSO may be obscured by local climate heterogeneity, insufficient data, randomly coincident outbreaks, and other, potentially stronger, intrinsic factors regulating transmission dynamics.</p><h3></h3><p><em>Please see later in the article for the Editors' Summary</em></p></div>", "links"=>[], "tags"=>["multiyear", "variability", "dengue", "incidence", "puerto", "longitudinal"], "article_id"=>145763, "categories"=>["Mathematics", "Biological Sciences", "Neuroscience", "Cancer", "Ecology", "Medicine"], "users"=>["Michael A. Johansson", "Derek A. T. Cummings", "Gregory E. Glass"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1000168.s001", "https://dx.doi.org/10.1371/journal.pmed.1000168.s002", "https://dx.doi.org/10.1371/journal.pmed.1000168.s003", "https://dx.doi.org/10.1371/journal.pmed.1000168.s004", "https://dx.doi.org/10.1371/journal.pmed.1000168.s005", "https://dx.doi.org/10.1371/journal.pmed.1000168.s006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Multiyear_Climate_Variability_and_Dengue_El_Ni_o_Southern_Oscillation_Weather_and_Dengue_Incidence_in_Puerto_Rico_Mexico_and_Thailand_A_Longitudinal_Data_Analysis/145763", "title"=>"Multiyear Climate Variability and Dengue—El Niño Southern Oscillation, Weather, and Dengue Incidence in Puerto Rico, Mexico, and Thailand: A Longitudinal Data Analysis", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2009-11-17 01:36:03"}
• {"files"=>["https://ndownloader.figshare.com/files/875451"], "description"=>"<p>(A) Reported cases of dengue in Puerto Rico by month. (B) Wavelet spectrum of (A). Power increases from blue to red. Areas where power is significantly high (95% confidence level) are encircled by black lines. Shaded areas indicate the presence of significant edge effects. (C) Wavelet spectrum of monthly average mean temperature in Puerto Rico (average minimum and maximum temperature behave similarly to mean temperature and are not shown). (D) Wavelet spectrum of monthly cumulative precipitation in Puerto Rico. (E) Wavelet spectrum of ENSO.</p>", "links"=>[], "tags"=>["spectra", "precipitation", "puerto", "rico"], "article_id"=>545909, "categories"=>["Mathematics", "Computational Biology", "Neuroscience", "Infectious Diseases", "Cancer", "Ecology", "Medicine"], "users"=>["Michael A. Johansson", "Derek A. T. Cummings", "Gregory E. Glass"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1000168.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Wavelet_spectra_of_dengue_temperature_and_precipitation_in_Puerto_Rico_and_ENSO_/545909", "title"=>"Wavelet spectra of dengue, temperature, and precipitation in Puerto Rico and ENSO.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-11-17 01:38:29"}
• {"files"=>["https://ndownloader.figshare.com/files/875524"], "description"=>"<p>(A) Squared coherence plot of dengue incidence in Puerto Rico and ENSO. Coherence increases from blue to red. Areas where coherence is significantly high (95% confidence level) are encircled by black lines. Shaded areas indicate the presence of edge effects. (B) Phase of ENSO (solid black) and dengue incidence (red) and phase difference (dashed black) at a periodicity of 3–4.5 y. (C) Reconstructed ENSO (black) and dengue incidence (red) at a periodicity of 3–4.5 y. A similarly scaled Morlet wavelet is superimposed (blue).</p>", "links"=>[], "tags"=>["enso", "dengue", "puerto"], "article_id"=>545982, "categories"=>["Mathematics", "Computational Biology", "Neuroscience", "Infectious Diseases", "Cancer", "Ecology", "Medicine"], "users"=>["Michael A. Johansson", "Derek A. T. Cummings", "Gregory E. Glass"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1000168.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Coherence_between_ENSO_and_dengue_in_Puerto_Rico_/545982", "title"=>"Coherence between ENSO and dengue in Puerto Rico.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-11-17 01:39:42"}
• {"files"=>["https://ndownloader.figshare.com/files/875619"], "description"=>"<p>(A) Squared coherence plot of ENSO and dengue incidence in Mexico. (B) Squared coherence plot of ENSO and dengue incidence in Thailand. Features are as described in <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000168#pmed-1000168-g002\" target=\"_blank\">Figure 2A</a>.</p>", "links"=>[], "tags"=>["enso", "dengue", "mexico"], "article_id"=>546076, "categories"=>["Mathematics", "Computational Biology", "Neuroscience", "Infectious Diseases", "Cancer", "Ecology", "Medicine"], "users"=>["Michael A. Johansson", "Derek A. T. Cummings", "Gregory E. Glass"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1000168.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Coherence_between_ENSO_and_dengue_in_Mexico_and_Thailand_/546076", "title"=>"Coherence between ENSO and dengue in Mexico and Thailand.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-11-17 01:41:16"}
• {"files"=>["https://ndownloader.figshare.com/files/875669"], "description"=>"<p>(A) Squared coherence plot of ENSO and temperature. (B) Squared coherence plot of ENSO and precipitation. (C) Squared coherence plot of temperature and dengue incidence. (D) Squared coherence plot of precipitation and dengue incidence. Features are as described in <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000168#pmed-1000168-g002\" target=\"_blank\">Figure 2A</a>.</p>", "links"=>[], "tags"=>["dengue", "puerto"], "article_id"=>546128, "categories"=>["Mathematics", "Computational Biology", "Neuroscience", "Infectious Diseases", "Cancer", "Ecology", "Medicine"], "users"=>["Michael A. Johansson", "Derek A. T. Cummings", "Gregory E. Glass"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1000168.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Coherence_between_ENSO_weather_and_dengue_in_Puerto_Rico_/546128", "title"=>"Coherence between ENSO, weather, and dengue in Puerto Rico.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-11-17 01:42:08"}

PMC Usage Stats | Further Information

• {"unique-ip"=>"14", "full-text"=>"5", "pdf"=>"4", "abstract"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
• {"unique-ip"=>"8", "full-text"=>"4", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
• {"unique-ip"=>"13", "full-text"=>"14", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
• {"unique-ip"=>"21", "full-text"=>"17", "pdf"=>"10", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"10"}
• {"unique-ip"=>"12", "full-text"=>"14", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2014", "month"=>"11"}
• {"unique-ip"=>"7", "full-text"=>"6", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"12"}
• {"unique-ip"=>"16", "full-text"=>"15", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
• {"unique-ip"=>"16", "full-text"=>"13", "pdf"=>"11", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"2"}
• {"unique-ip"=>"14", "full-text"=>"15", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"3"}
• {"unique-ip"=>"12", "full-text"=>"10", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"4"}
• {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"5", "cited-by"=>"0", "year"=>"2015", "month"=>"5"}
• {"unique-ip"=>"7", "full-text"=>"12", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"6"}
• {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"7"}
• {"unique-ip"=>"13", "full-text"=>"12", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"8"}
• {"unique-ip"=>"10", "full-text"=>"12", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
• {"unique-ip"=>"21", "full-text"=>"21", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"10"}
• {"unique-ip"=>"17", "full-text"=>"17", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2015", "month"=>"11"}
• {"unique-ip"=>"17", "full-text"=>"17", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
• {"unique-ip"=>"21", "full-text"=>"23", "pdf"=>"10", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
• {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
• {"unique-ip"=>"13", "full-text"=>"14", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
• {"unique-ip"=>"18", "full-text"=>"17", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"4"}
• {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
• {"unique-ip"=>"11", "full-text"=>"10", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
• {"unique-ip"=>"9", "full-text"=>"7", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
• {"unique-ip"=>"11", "full-text"=>"10", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"8"}
• {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
• {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
• {"unique-ip"=>"14", "full-text"=>"19", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
• {"unique-ip"=>"32", "full-text"=>"10", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"14", "cited-by"=>"1", "year"=>"2016", "month"=>"12"}
• {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"1"}
• {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"2"}
• {"unique-ip"=>"7", "full-text"=>"6", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"3"}
• {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
• {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"5"}
• {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"6"}
• {"unique-ip"=>"5", "full-text"=>"6", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
• {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
• {"unique-ip"=>"13", "full-text"=>"18", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"9"}
• {"unique-ip"=>"18", "full-text"=>"17", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
• {"unique-ip"=>"12", "full-text"=>"11", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2017", "month"=>"11"}
• {"unique-ip"=>"4", "full-text"=>"8", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
• {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
• {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"2"}
• {"unique-ip"=>"15", "full-text"=>"13", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
• {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
• {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
• {"unique-ip"=>"8", "full-text"=>"10", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
• {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
• {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
• {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
• {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
• {"unique-ip"=>"12", "full-text"=>"8", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
• {"unique-ip"=>"13", "full-text"=>"10", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
• {"unique-ip"=>"12", "full-text"=>"10", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
• {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
• {"unique-ip"=>"2", "full-text"=>"4", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
• {"unique-ip"=>"10", "full-text"=>"8", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
• {"unique-ip"=>"23", "full-text"=>"26", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
• {"unique-ip"=>"15", "full-text"=>"12", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
• {"unique-ip"=>"10", "full-text"=>"12", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
• {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}

Relative Metric

{"start_date"=>"2009-01-01T00:00:00Z", "end_date"=>"2009-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Earth sciences", "average_usage"=>[445, 696, 844, 982, 1110, 1196, 1302, 1431, 1518, 1655, 1750, 1853, 1961, 2029, 2080, 2150, 2221, 2294, 2364, 2465, 2516, 2574, 2645, 2679, 2747, 2849, 2935, 2990, 3069, 3139, 3199, 3266, 3340, 3424, 3494, 3558, 3634, 3764, 3830, 3924, 3999, 4098, 4156, 4217, 4277, 4320, 4375, 4438, 4490, 4556, 4635, 4703, 4767, 4827, 4872, 4931, 5018, 5081, 5136, 5209, 5275, 5358]}, {"subject_area"=>"/Earth sciences/Atmospheric science", "average_usage"=>[371, 699, 789, 971, 1066, 1162, 1234, 1343, 1424, 1533, 1622, 1744, 1827, 1909, 2002, 2087, 2158, 2223, 2279, 2347, 2428, 2496, 2527, 2566, 2612, 2661, 2748, 2840, 2893, 2961, 3027, 3078, 3145, 3204, 3274, 3364, 3425, 3492, 3564, 3619, 3663, 3715, 3788, 3872, 3959, 4012, 4076, 4155, 4259, 4329, 4398, 4469, 4513, 4565, 4861, 4922, 4976, 5022, 5077, 5137, 5226, 5282]}, {"subject_area"=>"/Earth sciences/Marine and aquatic sciences", "average_usage"=>[440, 665, 780, 910, 1042, 1155, 1297, 1380, 1483, 1594, 1726, 1844, 1950, 2026, 2133, 2259, 2351, 2409, 2473, 2531, 2574, 2613, 2658, 2709, 2743, 2780, 2832, 2899, 2976, 3055, 3141, 3214, 3287, 3369, 3432, 3478, 3538, 3573, 3624, 3671, 3707, 3752, 3803, 3839, 3882, 3913, 3958, 4068, 4115, 4168, 4210, 4263, 4290, 4335, 4378, 4442, 4483, 4529, 4575, 4613, 4647, 4683]}, {"subject_area"=>"/Engineering and technology/Signal processing", "average_usage"=>[411, 609, 693, 785, 872, 940, 1016, 1104, 1168, 1222, 1263, 1333, 1389, 1460, 1514, 1568, 1618, 1677, 1768, 1813, 1845, 1896, 1934, 1965, 2004, 2121, 2155, 2239, 2290, 2350, 2373, 2415, 2492, 2534, 2550, 2591, 2626, 2647, 2667, 2694, 2727, 2757, 2933, 2978, 3027, 3059, 3095, 3132, 3162, 3194, 3231, 3267, 3322, 3409, 3498, 3581, 3641, 3667, 3729, 3797, 3880, 3930]}, {"subject_area"=>"/Medicine and health sciences", "average_usage"=>[332, 584, 719, 824, 927, 1030, 1139, 1233, 1322, 1402, 1483, 1570, 1649, 1730, 1806, 1873, 1939, 2003, 2068, 2130, 2191, 2248, 2302, 2362, 2427, 2485, 2544, 2599, 2653, 2709, 2778, 2840, 2896, 2950, 3013, 3073, 3137, 3189, 3253, 3305, 3364, 3423, 3489, 3557, 3606, 3668, 3742, 3797, 3852, 3907, 3962, 4027, 4072, 4132, 4193, 4256, 4308, 4366, 4427, 4493, 4556]}, {"subject_area"=>"/Medicine and health sciences/Infectious diseases", "average_usage"=>[309, 620, 756, 864, 971, 1066, 1164, 1273, 1370, 1458, 1523, 1618, 1705, 1789, 1845, 1923, 2000, 2070, 2142, 2204, 2256, 2324, 2383, 2444, 2509, 2571, 2620, 2688, 2738, 2795, 2853, 2938, 2996, 3053, 3122, 3182, 3240, 3291, 3349, 3407, 3501, 3554, 3615, 3665, 3716, 3771, 3824, 3896, 3946, 4013, 4072, 4122, 4178, 4231, 4274, 4339, 4402, 4479, 4539, 4602, 4650]}, {"subject_area"=>"/Medicine and health sciences/Tropical diseases", "average_usage"=>[262, 539, 658, 749, 834, 916, 1020, 1108, 1196, 1250, 1338, 1408, 1481, 1549, 1611, 1671, 1721, 1786, 1854, 1904, 1968, 2031, 2101, 2158, 2205, 2271, 2326, 2381, 2440, 2488, 2544, 2603, 2658, 2726, 2786, 2839, 2896, 2954, 3019, 3067, 3126, 3181, 3241, 3294, 3367, 3446, 3538, 3634, 3677, 3736, 3785, 3816, 3867, 3946, 4032, 4083, 4121, 4191, 4278, 4344, 4399, 4438]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[340, 575, 698, 803, 889, 974, 1077, 1169, 1245, 1318, 1398, 1468, 1540, 1608, 1679, 1748, 1819, 1877, 1937, 1999, 2044, 2100, 2148, 2198, 2250, 2306, 2357, 2414, 2458, 2517, 2572, 2636, 2690, 2749, 2799, 2861, 2914, 2970, 3026, 3102, 3143, 3237, 3303, 3373, 3441, 3500, 3553, 3608, 3679, 3733, 3791, 3856, 3908, 3962, 4033, 4096, 4149, 4187, 4229, 4281, 4336]}]}

F1000Prime