Serological Measures of Malaria Transmission in Haiti: Comparison of Longitudinal and Cross-Sectional Methods
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{"title"=>"Serological measures of malaria transmission in haiti: Comparison of longitudinal and cross-sectional methods", "type"=>"journal", "authors"=>[{"first_name"=>"Benjamin F.", "last_name"=>"Arnold", "scopus_author_id"=>"16174532400"}, {"first_name"=>"Jeffrey W.", "last_name"=>"Priest", "scopus_author_id"=>"7102955068"}, {"first_name"=>"Katy L.", "last_name"=>"Hamlin", "scopus_author_id"=>"55328905500"}, {"first_name"=>"Delynn M.", "last_name"=>"Moss", "scopus_author_id"=>"7201847850"}, {"first_name"=>"John M.", "last_name"=>"Colford", "scopus_author_id"=>"7004130553"}, {"first_name"=>"Patrick J.", "last_name"=>"Lammie", "scopus_author_id"=>"7005743394"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84898640483", "doi"=>"10.1371/journal.pone.0093684", "pui"=>"372838966", "pmid"=>"24691467", "scopus"=>"2-s2.0-84898640483", "issn"=>"19326203", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)"}, "id"=>"f54465d1-a404-338b-8604-c13c9c24ebeb", "abstract"=>"BACKGROUND: Efforts to monitor malaria transmission increasingly use cross-sectional surveys to estimate transmission intensity from seroprevalence data using malarial antibodies. To date, seroconversion rates estimated from cross-sectional surveys have not been compared to rates estimated in prospective cohorts. Our objective was to compare seroconversion rates estimated in a prospective cohort with those from a cross-sectional survey in a low-transmission population.\\n\\nMETHODS AND FINDINGS: The analysis included two studies from Haiti: a prospective cohort of 142 children ages ≤ 11 years followed for up to 9 years, and a concurrent cross-sectional survey of 383 individuals ages 0-90 years old. From all individuals, we analyzed 1,154 blood spot specimens for the malaria antibody MSP-1(19) using a multiplex bead antigen assay. We classified individuals as positive for malaria using a cutoff derived from the mean plus 3 standard deviations in antibody responses from a negative control set of unexposed individuals. We estimated prospective seroconversion rates from the longitudinal cohort based on 13 incident seroconversions among 646 person-years at risk. We also estimated seroconversion rates from the cross-sectional survey using a reversible catalytic model fit with maximum likelihood. We found the two approaches provided consistent results: the seroconversion rate for ages ≤ 11 years was 0.020 (0.010, 0.032) estimated prospectively versus 0.023 (0.001, 0.052) in the cross-sectional survey.\\n\\nCONCLUSIONS: The estimation of seroconversion rates using cross-sectional data is a widespread and generalizable problem for many infectious diseases that can be measured using antibody titers. The consistency between these two estimates lends credibility to model-based estimates of malaria seroconversion rates using cross-sectional surveys. This study also demonstrates the utility of including malaria antibody measures in multiplex assays alongside targets for vaccine coverage and other neglected tropical diseases, which together could comprise an integrated, large-scale serological surveillance platform.", "link"=>"http://www.mendeley.com/research/serological-measures-malaria-transmission-haiti-comparison-longitudinal-crosssectional-methods", "reader_count"=>46, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Librarian"=>2, "Researcher"=>11, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>5, "Other"=>3, "Student > Master"=>10, "Student > Bachelor"=>4, "Professor"=>3, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Librarian"=>2, "Researcher"=>11, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>5, "Other"=>3, "Student > Master"=>10, "Student > Bachelor"=>4, "Professor"=>3, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Agricultural and Biological Sciences"=>15, "Arts and Humanities"=>1, "Earth and Planetary Sciences"=>1, "Economics, Econometrics and Finance"=>1, "Engineering"=>1, "Environmental Science"=>2, "Nursing and Health Professions"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Medicine and Dentistry"=>12, "Psychology"=>1, "Social Sciences"=>3, "Immunology and Microbiology"=>1, "Mathematics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>12}, "Social Sciences"=>{"Social Sciences"=>3}, "Psychology"=>{"Psychology"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>5}, "Environmental Science"=>{"Environmental Science"=>2}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>15}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}}, "reader_count_by_country"=>{"United Kingdom"=>1}, "group_count"=>10}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1442352"], "description"=>"<p>N is number of individuals.</p><p>CI: Confidence Interval.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "immunology", "Clinical immunology", "Immune response", "organisms", "protozoans", "Parasitic protozoans", "Malarial parasites", "Plasmodium falciparum", "epidemiology", "Epidemiological methods and statistics", "Infectious disease epidemiology", "Molecular epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "Public and occupational health", "Global health", "research design", "Clinical research design", "Cross-sectional studies", "Longitudinal studies", "seroprevalence", "estimates", "antibody", "haiti"], "article_id"=>980192, "categories"=>["Biological Sciences"], "users"=>["Benjamin F. Arnold", "Jeffrey W. Priest", "Katy L. Hamlin", "Delynn M. Moss", "John M. Colford Jr", "Patrick J. Lammie"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0093684.t002", "stats"=>{"downloads"=>2, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Age_specific_seroprevalence_estimates_based_on_the_MSP_1_19_antibody_in_Miton_Haiti_in_1998_/980192", "title"=>"Age-specific seroprevalence estimates based on the MSP-1<sub>19</sub> antibody in Miton, Haiti in 1998.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-01 03:25:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1442350"], "description"=>"<p>Panel A includes individuals with incident seroconversions, and panel B includes those who were seropositive at their first measurement. The dashed line marks the cutoff value (365) used to determine seropositive antibody levels. The light grey lines plot antibody profiles for seronegative children, and the solid black line in each plot is a loess smoother over the seronegative children antibody levels.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "immunology", "Clinical immunology", "Immune response", "organisms", "protozoans", "Parasitic protozoans", "Malarial parasites", "Plasmodium falciparum", "epidemiology", "Epidemiological methods and statistics", "Infectious disease epidemiology", "Molecular epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "Public and occupational health", "Global health", "research design", "Clinical research design", "Cross-sectional studies", "Longitudinal studies", "antibody", "optical", "profiles", "children", "haiti", "longitudinal"], "article_id"=>980190, "categories"=>["Biological Sciences"], "users"=>["Benjamin F. Arnold", "Jeffrey W. Priest", "Katy L. Hamlin", "Delynn M. Moss", "John M. Colford Jr", "Patrick J. Lammie"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0093684.g002", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MSP_1_19_antibody_optical_density_profiles_for_children_in_the_L_233_og_226_ne_Haiti_longitudinal_study_1991_8211_1999_/980190", "title"=>"MSP-1<sub>19</sub> antibody optical density profiles for children in the Léogâne, Haiti longitudinal study, 1991–1999.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-01 03:25:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1442355"], "description"=>"<div><p>Background</p><p>Efforts to monitor malaria transmission increasingly use cross-sectional surveys to estimate transmission intensity from seroprevalence data using malarial antibodies. To date, seroconversion rates estimated from cross-sectional surveys have not been compared to rates estimated in prospective cohorts. Our objective was to compare seroconversion rates estimated in a prospective cohort with those from a cross-sectional survey in a low-transmission population.</p><p>Methods and Findings</p><p>The analysis included two studies from Haiti: a prospective cohort of 142 children ages ≤11 years followed for up to 9 years, and a concurrent cross-sectional survey of 383 individuals ages 0–90 years old. From all individuals, we analyzed 1,154 blood spot specimens for the malaria antibody MSP-1<sub>19</sub> using a multiplex bead antigen assay. We classified individuals as positive for malaria using a cutoff derived from the mean plus 3 standard deviations in antibody responses from a negative control set of unexposed individuals. We estimated prospective seroconversion rates from the longitudinal cohort based on 13 incident seroconversions among 646 person-years at risk. We also estimated seroconversion rates from the cross-sectional survey using a reversible catalytic model fit with maximum likelihood. We found the two approaches provided consistent results: the seroconversion rate for ages ≤11 years was 0.020 (0.010, 0.032) estimated prospectively versus 0.023 (0.001, 0.052) in the cross-sectional survey.</p><p>Conclusions</p><p>The estimation of seroconversion rates using cross-sectional data is a widespread and generalizable problem for many infectious diseases that can be measured using antibody titers. The consistency between these two estimates lends credibility to model-based estimates of malaria seroconversion rates using cross-sectional surveys. This study also demonstrates the utility of including malaria antibody measures in multiplex assays alongside targets for vaccine coverage and other neglected tropical diseases, which together could comprise an integrated, large-scale serological surveillance platform.</p></div>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "immunology", "Clinical immunology", "Immune response", "organisms", "protozoans", "Parasitic protozoans", "Malarial parasites", "Plasmodium falciparum", "epidemiology", "Epidemiological methods and statistics", "Infectious disease epidemiology", "Molecular epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "Public and occupational health", "Global health", "research design", "Clinical research design", "Cross-sectional studies", "Longitudinal studies", "measures", "longitudinal", "cross-sectional"], "article_id"=>980195, "categories"=>["Biological Sciences"], "users"=>["Benjamin F. Arnold", "Jeffrey W. Priest", "Katy L. Hamlin", "Delynn M. Moss", "John M. Colford Jr", "Patrick J. Lammie"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0093684", "stats"=>{"downloads"=>6, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Serological_Measures_of_Malaria_Transmission_in_Haiti_Comparison_of_Longitudinal_and_Cross_Sectional_Methods_/980195", "title"=>"Serological Measures of Malaria Transmission in Haiti: Comparison of Longitudinal and Cross-Sectional Methods", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-01 03:25:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1442354"], "description"=>"<p>N is number of measurements.</p><p>CI: Confidence Interval.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "immunology", "Clinical immunology", "Immune response", "organisms", "protozoans", "Parasitic protozoans", "Malarial parasites", "Plasmodium falciparum", "epidemiology", "Epidemiological methods and statistics", "Infectious disease epidemiology", "Molecular epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "Public and occupational health", "Global health", "research design", "Clinical research design", "Cross-sectional studies", "Longitudinal studies", "seroprevalence", "estimates", "antibody", "142", "children", "followed", "longitudinally", "haiti"], "article_id"=>980194, "categories"=>["Biological Sciences"], "users"=>["Benjamin F. Arnold", "Jeffrey W. Priest", "Katy L. Hamlin", "Delynn M. Moss", "John M. Colford Jr", "Patrick J. Lammie"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0093684.t001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Age_specific_seroprevalence_estimates_based_on_the_MSP_1_19_antibody_measured_in_142_children_followed_longitudinally_in_L_233_og_226_ne_Haiti_1991_8211_1999_/980194", "title"=>"Age-specific seroprevalence estimates based on the MSP-1<sub>19</sub> antibody measured in 142 children followed longitudinally in Léogâne, Haiti 1991–1999.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-01 03:25:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1442349"], "description"=>"<p>Panel A includes antibody responses from the longitudinal study in Léogâne, Haiti, 1991–1999. Panel B includes antibody responses from the cross-sectional survey in Miton, Haiti, 1998.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "immunology", "Clinical immunology", "Immune response", "organisms", "protozoans", "Parasitic protozoans", "Malarial parasites", "Plasmodium falciparum", "epidemiology", "Epidemiological methods and statistics", "Infectious disease epidemiology", "Molecular epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "Public and occupational health", "Global health", "research design", "Clinical research design", "Cross-sectional studies", "Longitudinal studies", "antibody", "optical", "responses"], "article_id"=>980189, "categories"=>["Biological Sciences"], "users"=>["Benjamin F. Arnold", "Jeffrey W. Priest", "Katy L. Hamlin", "Delynn M. Moss", "John M. Colford Jr", "Patrick J. Lammie"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0093684.g001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MSP_1_19_antibody_optical_density_responses_for_different_age_categories_/980189", "title"=>"MSP-1<sub>19</sub> antibody optical density responses for different age categories.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-01 03:25:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1442353"], "description"=>"<p>CI: Confidence Interval; RC: Reversible Catalytic model.</p><p>* Lower 95% confidence intervals truncated at the lower bound of possible parameter values (0.001).</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "immunology", "Clinical immunology", "Immune response", "organisms", "protozoans", "Parasitic protozoans", "Malarial parasites", "Plasmodium falciparum", "epidemiology", "Epidemiological methods and statistics", "Infectious disease epidemiology", "Molecular epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "Public and occupational health", "Global health", "research design", "Clinical research design", "Cross-sectional studies", "Longitudinal studies", "seroconversion", "reversion", "rates", "calculated", "cohorts", "estimation"], "article_id"=>980193, "categories"=>["Biological Sciences"], "users"=>["Benjamin F. Arnold", "Jeffrey W. Priest", "Katy L. Hamlin", "Delynn M. Moss", "John M. Colford Jr", "Patrick J. Lammie"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0093684.t003", "stats"=>{"downloads"=>7, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_seroconversion_and_reversion_rates_calculated_from_different_study_cohorts_and_different_estimation_approaches_/980193", "title"=>"Comparison of seroconversion and reversion rates calculated from different study cohorts and different estimation approaches.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-01 03:25:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1442351"], "description"=>"<p>Seroprevalence estimates for the age categories in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0093684#pone-0093684-t002\" target=\"_blank\">Table 2</a> (points) are plotted at the midpoint of the age categories, and the line in the plot is the predicted prevalence from the reversible catalytic model.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "immunology", "Clinical immunology", "Immune response", "organisms", "protozoans", "Parasitic protozoans", "Malarial parasites", "Plasmodium falciparum", "epidemiology", "Epidemiological methods and statistics", "Infectious disease epidemiology", "Molecular epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "Public and occupational health", "Global health", "research design", "Clinical research design", "Cross-sectional studies", "Longitudinal studies", "estimates", "cross-sectional"], "article_id"=>980191, "categories"=>["Biological Sciences"], "users"=>["Benjamin F. Arnold", "Jeffrey W. Priest", "Katy L. Hamlin", "Delynn M. Moss", "John M. Colford Jr", "Patrick J. Lammie"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0093684.g003", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Seroprevalence_estimates_from_the_cross_sectional_survey_in_Miton_Haiti_1998_/980191", "title"=>"Seroprevalence estimates from the cross-sectional survey in Miton, Haiti, 1998.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-01 03:25:11"}

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Relative Metric

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