The data used to build the models: Pertussis morbidity and mortality burden considering various Brazilian data sources
Pertussis is associated with significant disease burden in children worldwide. In addition to its cyclical nature, resurgences of pertussis cases, hospitalizations and deaths have been reported by many countries. We describe the dynamics of pertussis in Brazil, a middle-income country that has exper...
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| Veröffentlicht in: | Vaccine 2021-01, Vol.39 (1), p.137-146 |
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| creator | Bagattini, Angela M. Policena, Gabriela Minamisava, Ruth Andrade, Ana Lucia S. Nishioka, Sérgio de A. Sinha, Anushua Russell, Louise B. Toscano, Cristiana M. |
| description | Pertussis is associated with significant disease burden in children worldwide. In addition to its cyclical nature, resurgences of pertussis cases, hospitalizations and deaths have been reported by many countries. We describe the dynamics of pertussis in Brazil, a middle-income country that has experienced a resurgence and that provides good quality data to allow building a dynamic transmission disease model.
We conducted a descriptive analysis of pertussis burden considering data from the national disease surveillance system, national hospitalization information system and national mortality registry. Study period was 2000–2016. Absolute numbers and rates per 100,000 inhabitants over time, by age sub-groups and geographical regions are presented.
From 2000 to 2016, a total of 37,299 reported pertussis cases, 25,240 hospitalizations, and 601 deaths due to pertussis were reported. Although the outcomes – pertussis cases, hospitalizations, and deaths – come from independent information systems, our results document low disease burden with periodic increases every 3–4 years during the years 2000–2010, followed by a sharp increase which peaked in 2014. In both periods, disease burden is concentrated in young children, while its more serious outcomes – hospitalizations and deaths, are concentrated in infants. Pre-outbreak and outbreak disease burden as well as timing of peak during the outbreak period vary by states and within geographical regions, representing valuable resources of data for modelling purposes.
Consistent disease burden patterns were observed over time in Brazil using a variety of data sources. Given the scarcity of good epidemiological data on pertussis available from low- and middle-income countries, our reported data provide valuable information for the assessment of the public health impact and cost-effectiveness modelling studies of newer strategies to prevent and control pertussis. These data were used to build and calibrate a national dynamic transmission model, which was used to evaluate the cost-effectiveness of maternal immunization.
Clinical Trial registry name and registration number: Not applicable. |
| doi_str_mv | 10.1016/j.vaccine.2020.09.007 |
| format | Article |
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We conducted a descriptive analysis of pertussis burden considering data from the national disease surveillance system, national hospitalization information system and national mortality registry. Study period was 2000–2016. Absolute numbers and rates per 100,000 inhabitants over time, by age sub-groups and geographical regions are presented.
From 2000 to 2016, a total of 37,299 reported pertussis cases, 25,240 hospitalizations, and 601 deaths due to pertussis were reported. Although the outcomes – pertussis cases, hospitalizations, and deaths – come from independent information systems, our results document low disease burden with periodic increases every 3–4 years during the years 2000–2010, followed by a sharp increase which peaked in 2014. In both periods, disease burden is concentrated in young children, while its more serious outcomes – hospitalizations and deaths, are concentrated in infants. Pre-outbreak and outbreak disease burden as well as timing of peak during the outbreak period vary by states and within geographical regions, representing valuable resources of data for modelling purposes.
Consistent disease burden patterns were observed over time in Brazil using a variety of data sources. Given the scarcity of good epidemiological data on pertussis available from low- and middle-income countries, our reported data provide valuable information for the assessment of the public health impact and cost-effectiveness modelling studies of newer strategies to prevent and control pertussis. These data were used to build and calibrate a national dynamic transmission model, which was used to evaluate the cost-effectiveness of maternal immunization.
Clinical Trial registry name and registration number: Not applicable.</description><identifier>ISSN: 0264-410X</identifier><identifier>EISSN: 1873-2518</identifier><identifier>DOI: 10.1016/j.vaccine.2020.09.007</identifier><identifier>PMID: 33303181</identifier><language>eng</language><publisher>Netherlands: Elsevier Ltd</publisher><subject>Brazil - epidemiology ; Child ; Child, Preschool ; Children ; Data sources ; Disease disease burden ; Disease transmission ; Epidemiology ; Fatalities ; Humans ; Immunization ; Income ; Infant ; Infants ; Information Storage and Retrieval ; Information systems ; Laboratories ; Modelling ; Morbidity ; Mortality ; Outbreaks ; Pertussis ; Pertussis Vaccine ; Public health ; Surveillance ; Vaccination ; Whooping cough ; Whooping Cough - epidemiology</subject><ispartof>Vaccine, 2021-01, Vol.39 (1), p.137-146</ispartof><rights>2020 The Authors</rights><rights>Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.</rights><rights>2020. The Authors</rights><rights>2020 The Authors 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c561t-1d5c3d2a90a7517903b8a185f427591861ce02191e09ac61ce0d7110ea0b68753</citedby><cites>FETCH-LOGICAL-c561t-1d5c3d2a90a7517903b8a185f427591861ce02191e09ac61ce0d7110ea0b68753</cites><orcidid>0000-0003-4281-2536</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0264410X2031149X$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33303181$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bagattini, Angela M.</creatorcontrib><creatorcontrib>Policena, Gabriela</creatorcontrib><creatorcontrib>Minamisava, Ruth</creatorcontrib><creatorcontrib>Andrade, Ana Lucia S.</creatorcontrib><creatorcontrib>Nishioka, Sérgio de A.</creatorcontrib><creatorcontrib>Sinha, Anushua</creatorcontrib><creatorcontrib>Russell, Louise B.</creatorcontrib><creatorcontrib>Toscano, Cristiana M.</creatorcontrib><title>The data used to build the models: Pertussis morbidity and mortality burden considering various Brazilian data sources</title><title>Vaccine</title><addtitle>Vaccine</addtitle><description>Pertussis is associated with significant disease burden in children worldwide. In addition to its cyclical nature, resurgences of pertussis cases, hospitalizations and deaths have been reported by many countries. We describe the dynamics of pertussis in Brazil, a middle-income country that has experienced a resurgence and that provides good quality data to allow building a dynamic transmission disease model.
We conducted a descriptive analysis of pertussis burden considering data from the national disease surveillance system, national hospitalization information system and national mortality registry. Study period was 2000–2016. Absolute numbers and rates per 100,000 inhabitants over time, by age sub-groups and geographical regions are presented.
From 2000 to 2016, a total of 37,299 reported pertussis cases, 25,240 hospitalizations, and 601 deaths due to pertussis were reported. Although the outcomes – pertussis cases, hospitalizations, and deaths – come from independent information systems, our results document low disease burden with periodic increases every 3–4 years during the years 2000–2010, followed by a sharp increase which peaked in 2014. In both periods, disease burden is concentrated in young children, while its more serious outcomes – hospitalizations and deaths, are concentrated in infants. Pre-outbreak and outbreak disease burden as well as timing of peak during the outbreak period vary by states and within geographical regions, representing valuable resources of data for modelling purposes.
Consistent disease burden patterns were observed over time in Brazil using a variety of data sources. Given the scarcity of good epidemiological data on pertussis available from low- and middle-income countries, our reported data provide valuable information for the assessment of the public health impact and cost-effectiveness modelling studies of newer strategies to prevent and control pertussis. These data were used to build and calibrate a national dynamic transmission model, which was used to evaluate the cost-effectiveness of maternal immunization.
Clinical Trial registry name and registration number: Not applicable.</description><subject>Brazil - epidemiology</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Data sources</subject><subject>Disease disease burden</subject><subject>Disease transmission</subject><subject>Epidemiology</subject><subject>Fatalities</subject><subject>Humans</subject><subject>Immunization</subject><subject>Income</subject><subject>Infant</subject><subject>Infants</subject><subject>Information Storage and Retrieval</subject><subject>Information systems</subject><subject>Laboratories</subject><subject>Modelling</subject><subject>Morbidity</subject><subject>Mortality</subject><subject>Outbreaks</subject><subject>Pertussis</subject><subject>Pertussis Vaccine</subject><subject>Public health</subject><subject>Surveillance</subject><subject>Vaccination</subject><subject>Whooping cough</subject><subject>Whooping Cough - epidemiology</subject><issn>0264-410X</issn><issn>1873-2518</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkU9v1DAQxS0EokvhI4AiceGSMBPHccKBCir-SZXgUCRulmPPtl5l7WInkcqnx2GXCrhwsmf8mzd-eow9RagQsH25qxZtjPNU1VBDBX0FIO-xDXaSl7XA7j7bQN02ZYPw7YQ9SmkHAIJj_5CdcM6BY4cbtlxeU2H1pIs5kS2mUAyzG_Mlt_fB0pheFV8oTnNKLuVOHJx1022hvV2rSY9rNczRki9M8MlZis5fFYuOLsypeBv1Dzc67Q9bUpijofSYPdjqMdGT43nKvr5_d3n-sbz4_OHT-ZuL0ogWpxKtMNzWugctBcoe-NBp7MS2qaXosWvRENTYI0Gvza_KSkQgDUPbScFP2euD7s087Mka8lPUo7qJbq_jrQraqb9fvLtWV2FRUvJ1Pgu8OArE8H2mNKm9S4bGUXvK9lTdSGxarGWX0ef_oLts1md7mWozIFD0mRIHysSQUqTt3WcQ1Jqs2qljsmpNVkGvcrJ57tmfTu6mfkeZgbMDkDOjxVFUyTjyhqyLZCZlg_vPip_hF7j1</recordid><startdate>20210103</startdate><enddate>20210103</enddate><creator>Bagattini, Angela M.</creator><creator>Policena, Gabriela</creator><creator>Minamisava, Ruth</creator><creator>Andrade, Ana Lucia S.</creator><creator>Nishioka, Sérgio de A.</creator><creator>Sinha, Anushua</creator><creator>Russell, Louise B.</creator><creator>Toscano, Cristiana M.</creator><general>Elsevier Ltd</general><general>Elsevier Limited</general><general>Elsevier Science</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7RV</scope><scope>7T2</scope><scope>7T5</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0R</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2O</scope><scope>M7N</scope><scope>M7P</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-4281-2536</orcidid></search><sort><creationdate>20210103</creationdate><title>The data used to build the models: Pertussis morbidity and mortality burden considering various Brazilian data sources</title><author>Bagattini, Angela M. ; Policena, Gabriela ; Minamisava, Ruth ; Andrade, Ana Lucia S. ; Nishioka, Sérgio de A. ; Sinha, Anushua ; Russell, Louise B. ; Toscano, Cristiana M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c561t-1d5c3d2a90a7517903b8a185f427591861ce02191e09ac61ce0d7110ea0b68753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Brazil - epidemiology</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Children</topic><topic>Data sources</topic><topic>Disease disease burden</topic><topic>Disease transmission</topic><topic>Epidemiology</topic><topic>Fatalities</topic><topic>Humans</topic><topic>Immunization</topic><topic>Income</topic><topic>Infant</topic><topic>Infants</topic><topic>Information Storage and Retrieval</topic><topic>Information systems</topic><topic>Laboratories</topic><topic>Modelling</topic><topic>Morbidity</topic><topic>Mortality</topic><topic>Outbreaks</topic><topic>Pertussis</topic><topic>Pertussis Vaccine</topic><topic>Public health</topic><topic>Surveillance</topic><topic>Vaccination</topic><topic>Whooping cough</topic><topic>Whooping Cough - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bagattini, Angela M.</creatorcontrib><creatorcontrib>Policena, Gabriela</creatorcontrib><creatorcontrib>Minamisava, Ruth</creatorcontrib><creatorcontrib>Andrade, Ana Lucia S.</creatorcontrib><creatorcontrib>Nishioka, Sérgio de A.</creatorcontrib><creatorcontrib>Sinha, Anushua</creatorcontrib><creatorcontrib>Russell, Louise B.</creatorcontrib><creatorcontrib>Toscano, Cristiana M.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Vaccine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bagattini, Angela M.</au><au>Policena, Gabriela</au><au>Minamisava, Ruth</au><au>Andrade, Ana Lucia S.</au><au>Nishioka, Sérgio de A.</au><au>Sinha, Anushua</au><au>Russell, Louise B.</au><au>Toscano, Cristiana M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The data used to build the models: Pertussis morbidity and mortality burden considering various Brazilian data sources</atitle><jtitle>Vaccine</jtitle><addtitle>Vaccine</addtitle><date>2021-01-03</date><risdate>2021</risdate><volume>39</volume><issue>1</issue><spage>137</spage><epage>146</epage><pages>137-146</pages><issn>0264-410X</issn><eissn>1873-2518</eissn><abstract>Pertussis is associated with significant disease burden in children worldwide. In addition to its cyclical nature, resurgences of pertussis cases, hospitalizations and deaths have been reported by many countries. We describe the dynamics of pertussis in Brazil, a middle-income country that has experienced a resurgence and that provides good quality data to allow building a dynamic transmission disease model.
We conducted a descriptive analysis of pertussis burden considering data from the national disease surveillance system, national hospitalization information system and national mortality registry. Study period was 2000–2016. Absolute numbers and rates per 100,000 inhabitants over time, by age sub-groups and geographical regions are presented.
From 2000 to 2016, a total of 37,299 reported pertussis cases, 25,240 hospitalizations, and 601 deaths due to pertussis were reported. Although the outcomes – pertussis cases, hospitalizations, and deaths – come from independent information systems, our results document low disease burden with periodic increases every 3–4 years during the years 2000–2010, followed by a sharp increase which peaked in 2014. In both periods, disease burden is concentrated in young children, while its more serious outcomes – hospitalizations and deaths, are concentrated in infants. Pre-outbreak and outbreak disease burden as well as timing of peak during the outbreak period vary by states and within geographical regions, representing valuable resources of data for modelling purposes.
Consistent disease burden patterns were observed over time in Brazil using a variety of data sources. Given the scarcity of good epidemiological data on pertussis available from low- and middle-income countries, our reported data provide valuable information for the assessment of the public health impact and cost-effectiveness modelling studies of newer strategies to prevent and control pertussis. These data were used to build and calibrate a national dynamic transmission model, which was used to evaluate the cost-effectiveness of maternal immunization.
Clinical Trial registry name and registration number: Not applicable.</abstract><cop>Netherlands</cop><pub>Elsevier Ltd</pub><pmid>33303181</pmid><doi>10.1016/j.vaccine.2020.09.007</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-4281-2536</orcidid><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Brazil - epidemiology Child Child, Preschool Children Data sources Disease disease burden Disease transmission Epidemiology Fatalities Humans Immunization Income Infant Infants Information Storage and Retrieval Information systems Laboratories Modelling Morbidity Mortality Outbreaks Pertussis Pertussis Vaccine Public health Surveillance Vaccination Whooping cough Whooping Cough - epidemiology |
| title | The data used to build the models: Pertussis morbidity and mortality burden considering various Brazilian data sources |
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