Spatio-Temporal Dynamics of Cholera during the First Year of the Epidemic in Haiti
Publication Date
April 04, 2013
Journal
PLOS Neglected Tropical Diseases
Authors
Jean Gaudart, Stanislas Rebaudet, Robert Barrais, Jacques Boncy, et al
Volume
7
Issue
4
Pages
e2145
DOI
https://dx.plos.org/10.1371/journal.pntd.0002145
Publisher URL
http://journals.plos.org/plosntds/article?id=10.1371%2Fjournal.pntd.0002145
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23593516
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3617102
Europe PMC
http://europepmc.org/abstract/MED/23593516
Web of Science
000318153100010
Scopus
84876855572
Mendeley
http://www.mendeley.com/research/spatiotemporal-dynamics-cholera-during-first-year-epidemic-haiti
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Mendeley | Further Information

{"title"=>"Spatio-Temporal Dynamics of Cholera during the First Year of the Epidemic in Haiti", "type"=>"journal", "authors"=>[{"first_name"=>"Jean", "last_name"=>"Gaudart", "scopus_author_id"=>"56091387500"}, {"first_name"=>"Stanislas", "last_name"=>"Rebaudet", "scopus_author_id"=>"21741331400"}, {"first_name"=>"Robert", "last_name"=>"Barrais", "scopus_author_id"=>"42161060100"}, {"first_name"=>"Jacques", "last_name"=>"Boncy", "scopus_author_id"=>"6603232581"}, {"first_name"=>"Benoit", "last_name"=>"Faucher", "scopus_author_id"=>"8901670900"}, {"first_name"=>"Martine", "last_name"=>"Piarroux", "scopus_author_id"=>"24376534000"}, {"first_name"=>"Roc", "last_name"=>"Magloire", "scopus_author_id"=>"6505866869"}, {"first_name"=>"Gabriel", "last_name"=>"Thimothe", "scopus_author_id"=>"55538196200"}, {"first_name"=>"Renaud", "last_name"=>"Piarroux", "scopus_author_id"=>"7003681059"}], "year"=>2013, "source"=>"PLoS Neglected Tropical Diseases", "identifiers"=>{"sgr"=>"84876855572", "doi"=>"10.1371/journal.pntd.0002145", "issn"=>"19352735", "pui"=>"368819533", "isbn"=>"1935-2735", "pmid"=>"23593516", "scopus"=>"2-s2.0-84876855572"}, "id"=>"554073e7-0fb4-3df2-b552-12b06183a2f7", "abstract"=>"BACKGROUND In October 2010, cholera importation in Haiti triggered an epidemic that rapidly proved to be the world's largest epidemic of the seventh cholera pandemic. To establish effective control and elimination policies, strategies rely on the analysis of cholera dynamics. In this report, we describe the spatio-temporal dynamics of cholera and the associated environmental factors. METHODOLOGY/PRINCIPAL FINDINGS Cholera-associated morbidity and mortality data were prospectively collected at the commune level according to the World Health Organization standard definition. Attack and mortality rates were estimated and mapped to assess epidemic clusters and trends. The relationships between environmental factors were assessed at the commune level using multivariate analysis. The global attack and mortality rates were 488.9 cases/10,000 inhabitants and 6.24 deaths/10,000 inhabitants, respectively. Attack rates displayed a significantly high level of spatial heterogeneity (varying from 64.7 to 3070.9 per 10,000 inhabitants), thereby suggesting disparate outbreak processes. The epidemic course exhibited two principal outbreaks. The first outbreak (October 16, 2010-January 30, 2011) displayed a centrifugal spread of a damping wave that suddenly emerged from Mirebalais. The second outbreak began at the end of May 2011, concomitant with the onset of the rainy season, and displayed a highly fragmented epidemic pattern. Environmental factors (river and rice fields: p<0.003) played a role in disease dynamics exclusively during the early phases of the epidemic. CONCLUSION Our findings demonstrate that the epidemic is still evolving, with a changing transmission pattern as time passes. Such an evolution could have hardly been anticipated, especially in a country struck by cholera for the first time. These results argue for the need for control measures involving intense efforts in rapid and exhaustive case tracking.", "link"=>"http://www.mendeley.com/research/spatiotemporal-dynamics-cholera-during-first-year-epidemic-haiti", "reader_count"=>84, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>1, "Researcher"=>28, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>17, "Student > Postgraduate"=>2, "Student > Master"=>15, "Other"=>2, "Student > Bachelor"=>6, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>1, "Researcher"=>28, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>17, "Student > Postgraduate"=>2, "Student > Master"=>15, "Other"=>2, "Student > Bachelor"=>6, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Engineering"=>5, "Unspecified"=>12, "Environmental Science"=>4, "Nursing and Health Professions"=>3, "Mathematics"=>1, "Medicine and Dentistry"=>33, "Agricultural and Biological Sciences"=>13, "Social Sciences"=>2, "Computer Science"=>7, "Immunology and Microbiology"=>2, "Decision Sciences"=>1, "Earth and Planetary Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>5}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>33}, "Social Sciences"=>{"Social Sciences"=>2}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>13}, "Computer Science"=>{"Computer Science"=>7}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>12}, "Environmental Science"=>{"Environmental Science"=>4}}, "reader_count_by_country"=>{"United States"=>4, "Brazil"=>1}, "group_count"=>7}

CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1015641"], "description"=>"<p>The colored scales represent yearly attack (a) and mortality (b) rates per 10,000 inhabitants in communes of Haiti (from October 16, 2010 to October 15, 2011).</p>", "links"=>[], "tags"=>["cholera", "morbidity", "rates"], "article_id"=>675520, "categories"=>["Biotechnology", "Infectious Diseases"], "users"=>["Jean Gaudart", "Stanislas Rebaudet", "Robert Barrais", "Jacques Boncy", "Benoit Faucher", "Martine Piarroux", "Roc Magloire", "Gabriel Thimothe", "Renaud Piarroux"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0002145.g001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mapping_one_year_of_cholera_morbidity_and_mortality_rates_in_Haiti_/675520", "title"=>"Mapping one year of cholera morbidity and mortality rates in Haiti.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-04 01:32:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/1015650"], "description"=>"<p>Analysis of cases (a), rainfall (b), and cross-wavelet (c) between cases and rainfall are presented. The Y-axes represent length of the wavelet analysis window (from 3 to 26 days) and the color scales represent the spectral values for each length of the analysis window.</p>", "links"=>[], "tags"=>["public health and epidemiology", "Infectious diseases"], "article_id"=>675529, "categories"=>["Biotechnology", "Infectious Diseases"], "users"=>["Jean Gaudart", "Stanislas Rebaudet", "Robert Barrais", "Jacques Boncy", "Benoit Faucher", "Martine Piarroux", "Roc Magloire", "Gabriel Thimothe", "Renaud Piarroux"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0002145.g005", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Spectral_analysis_of_time_series_/675529", "title"=>"Spectral analysis of time series.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-04 01:32:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/1015648"], "description"=>"<p>a) Hierarchical cluster analysis (HCA) of communal epidemic profiles and b) Communal mapping of the epidemic profile classes. Median (25th–75th percentiles) communal cases observed during the period are provided for each class of profile. The graphs represent the median (solid line) and 25th–75th percentiles (dotted lines) of daily communal cases standardized by the total number of cases during the period.</p>", "links"=>[], "tags"=>["profiles", "outbreak", "phases"], "article_id"=>675527, "categories"=>["Biotechnology", "Infectious Diseases"], "users"=>["Jean Gaudart", "Stanislas Rebaudet", "Robert Barrais", "Jacques Boncy", "Benoit Faucher", "Martine Piarroux", "Roc Magloire", "Gabriel Thimothe", "Renaud Piarroux"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0002145.g004", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Epidemic_profiles_of_the_first_outbreak_phases_phases_1_and_2_/675527", "title"=>"Epidemic profiles of the first outbreak phases (phases 1 and 2).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-04 01:32:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/1015643"], "description"=>"<p>Daily cholera cases (red), daily rainfall (blue), and epidemic phases (grey) (September 15, 2010 to October 16, 2011) are presented. Accumulated rainfall data were obtained from the Daily Global and Regional Rainfall (TMPA-RT 3B42RT derived).</p>", "links"=>[], "tags"=>["cholera"], "article_id"=>675522, "categories"=>["Biotechnology", "Infectious Diseases"], "users"=>["Jean Gaudart", "Stanislas Rebaudet", "Robert Barrais", "Jacques Boncy", "Benoit Faucher", "Martine Piarroux", "Roc Magloire", "Gabriel Thimothe", "Renaud Piarroux"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0002145.g002", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Temporal_cholera_dynamics_/675522", "title"=>"Temporal cholera dynamics.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-04 01:32:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/1015653"], "description"=>"<p>Standardized incidence ratios (p-values) were estimated using the multivariate regression model.</p>*<p>Factor excluded using stepwise analysis.</p>†<p>Significant factors (boldface).</p>‡<p>Non-significant factors kept using stepwise analysis.</p>", "links"=>[], "tags"=>["public health and epidemiology", "Infectious diseases"], "article_id"=>675530, "categories"=>["Biotechnology", "Infectious Diseases"], "users"=>["Jean Gaudart", "Stanislas Rebaudet", "Robert Barrais", "Jacques Boncy", "Benoit Faucher", "Martine Piarroux", "Roc Magloire", "Gabriel Thimothe", "Renaud Piarroux"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0002145.t001", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Impact_of_local_environmental_factors_during_each_epidemic_phase_/675530", "title"=>"Impact of local environmental factors during each epidemic phase.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-04-04 01:32:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1015645"], "description"=>"<p>Daily incidence rates (DIRs) and high-risk spatial clusters for each epidemic phase.</p>", "links"=>[], "tags"=>["incidence", "rates", "high-risk", "spatial", "clusters"], "article_id"=>675524, "categories"=>["Biotechnology", "Infectious Diseases"], "users"=>["Jean Gaudart", "Stanislas Rebaudet", "Robert Barrais", "Jacques Boncy", "Benoit Faucher", "Martine Piarroux", "Roc Magloire", "Gabriel Thimothe", "Renaud Piarroux"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0002145.g003", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Daily_incidence_rates_DIRs_and_high_risk_spatial_clusters_for_each_epidemic_phase_/675524", "title"=>"Daily incidence rates (DIRs) and high-risk spatial clusters for each epidemic phase.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-04 01:32:04"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"11", "full-text"=>"10", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}

Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Agriculture", "average_usage"=>[241, 422, 551, 659, 765, 866, 954, 1043, 1142, 1235, 1311, 1397, 1462]}, {"subject_area"=>"/Biology and life sciences/Organisms", "average_usage"=>[281, 484, 611, 728, 835, 934, 1030, 1123, 1214, 1299, 1383, 1464]}, {"subject_area"=>"/Earth sciences/Marine and aquatic sciences", "average_usage"=>[299, 492, 619, 718, 826, 932, 1037, 1143, 1246, 1333, 1414, 1517, 1575]}, {"subject_area"=>"/Ecology and environmental sciences/Aquatic environments", "average_usage"=>[276, 480, 624, 713, 810, 927, 1024, 1130, 1221, 1318, 1422, 1506, 1587]}, {"subject_area"=>"/Medicine and health sciences/Epidemiology", "average_usage"=>[263, 452, 568, 671, 758, 847, 921, 1023, 1101, 1187, 1264, 1340, 1394]}, {"subject_area"=>"/Medicine and health sciences/Infectious diseases", "average_usage"=>[297, 523, 655, 765, 866, 971, 1070, 1159, 1256, 1337, 1424, 1496, 1568]}, {"subject_area"=>"/People and places/Demography", "average_usage"=>[253, 440, 552, 650, 735, 820, 902, 976, 1042, 1112, 1192, 1271, 1337]}, {"subject_area"=>"/People and places/Geographical locations", "average_usage"=>[263, 456, 571, 673, 776, 866, 955, 1040, 1132, 1217, 1310, 1391, 1454]}]}
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