Cargando…
A Preparedness Model for Mother–Baby Linked Longitudinal Surveillance for Emerging Threats
INTRODUCTION: Public health responses often lack the infrastructure to capture the impact of public health emergencies on pregnant women and infants, with limited mechanisms for linking pregnant women with their infants nationally to monitor long-term effects. In 2019, the Centers for Disease Contro...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780211/ https://www.ncbi.nlm.nih.gov/pubmed/33394275 http://dx.doi.org/10.1007/s10995-020-03106-y |
_version_ | 1783631469090963456 |
---|---|
author | Woodworth, Kate R. Reynolds, Megan R. Burkel, Veronica Gates, Cymone Eckert, Valorie McDermott, Catherine Barton, Jerusha Wilburn, Amanda Halai, Umme-Aiman Brown, Catherine M. Bocour, Angelica Longcore, Nicole Orkis, Lauren Lopez, Camille Delgado Sizemore, Lindsey Ellis, Esther M. Schillie, Sarah Gupta, Neil Bowen, Virginia B. Torrone, Elizabeth Ellington, Sascha R. Delaney, Augustina Olson, Samantha M. Roth, Nicole M. Whitehill, Florence Zambrano, Laura D. Meaney-Delman, Dana Fehrenbach, S. Nicole Honein, Margaret A. Tong, Van T. Gilboa, Suzanne M. |
author_facet | Woodworth, Kate R. Reynolds, Megan R. Burkel, Veronica Gates, Cymone Eckert, Valorie McDermott, Catherine Barton, Jerusha Wilburn, Amanda Halai, Umme-Aiman Brown, Catherine M. Bocour, Angelica Longcore, Nicole Orkis, Lauren Lopez, Camille Delgado Sizemore, Lindsey Ellis, Esther M. Schillie, Sarah Gupta, Neil Bowen, Virginia B. Torrone, Elizabeth Ellington, Sascha R. Delaney, Augustina Olson, Samantha M. Roth, Nicole M. Whitehill, Florence Zambrano, Laura D. Meaney-Delman, Dana Fehrenbach, S. Nicole Honein, Margaret A. Tong, Van T. Gilboa, Suzanne M. |
author_sort | Woodworth, Kate R. |
collection | PubMed |
description | INTRODUCTION: Public health responses often lack the infrastructure to capture the impact of public health emergencies on pregnant women and infants, with limited mechanisms for linking pregnant women with their infants nationally to monitor long-term effects. In 2019, the Centers for Disease Control and Prevention (CDC), in close collaboration with state, local, and territorial health departments, began a 5-year initiative to establish population-based mother–baby linked longitudinal surveillance, the Surveillance for Emerging Threats to Mothers and Babies Network (SET-NET). OBJECTIVES: The objective of this report is to describe an expanded surveillance approach that leverages and modernizes existing surveillance systems to address the impact of emerging health threats during pregnancy on pregnant women and their infants. METHODS: Mother–baby pairs are identified through prospective identification during pregnancy and/or identification of an infant with retrospective linking to maternal information. All data are obtained from existing data sources (e.g., electronic medical records, vital statistics, laboratory reports, and health department investigations and case reporting). RESULTS: Variables were selected for inclusion to address key surveillance questions proposed by CDC and health department subject matter experts. General variables include maternal demographics and health history, pregnancy and infant outcomes, maternal and infant laboratory results, and child health outcomes up to the second birthday. Exposure-specific modular variables are included for hepatitis C, syphilis, and Coronavirus Disease 2019 (COVID-19). The system is structured into four relational datasets (maternal, pregnancy outcomes and birth, infant/child follow-up, and laboratory testing). DISCUSSION: SET-NET provides a population-based mother–baby linked longitudinal surveillance approach and has already demonstrated rapid adaptation to COVID-19. This innovative approach leverages existing data sources and rapidly collects data and informs clinical guidance and practice. These data can help to reduce exposure risk and adverse outcomes among pregnant women and their infants, direct public health action, and strengthen public health systems. |
format | Online Article Text |
id | pubmed-7780211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-77802112021-01-04 A Preparedness Model for Mother–Baby Linked Longitudinal Surveillance for Emerging Threats Woodworth, Kate R. Reynolds, Megan R. Burkel, Veronica Gates, Cymone Eckert, Valorie McDermott, Catherine Barton, Jerusha Wilburn, Amanda Halai, Umme-Aiman Brown, Catherine M. Bocour, Angelica Longcore, Nicole Orkis, Lauren Lopez, Camille Delgado Sizemore, Lindsey Ellis, Esther M. Schillie, Sarah Gupta, Neil Bowen, Virginia B. Torrone, Elizabeth Ellington, Sascha R. Delaney, Augustina Olson, Samantha M. Roth, Nicole M. Whitehill, Florence Zambrano, Laura D. Meaney-Delman, Dana Fehrenbach, S. Nicole Honein, Margaret A. Tong, Van T. Gilboa, Suzanne M. Matern Child Health J Methodological Notes INTRODUCTION: Public health responses often lack the infrastructure to capture the impact of public health emergencies on pregnant women and infants, with limited mechanisms for linking pregnant women with their infants nationally to monitor long-term effects. In 2019, the Centers for Disease Control and Prevention (CDC), in close collaboration with state, local, and territorial health departments, began a 5-year initiative to establish population-based mother–baby linked longitudinal surveillance, the Surveillance for Emerging Threats to Mothers and Babies Network (SET-NET). OBJECTIVES: The objective of this report is to describe an expanded surveillance approach that leverages and modernizes existing surveillance systems to address the impact of emerging health threats during pregnancy on pregnant women and their infants. METHODS: Mother–baby pairs are identified through prospective identification during pregnancy and/or identification of an infant with retrospective linking to maternal information. All data are obtained from existing data sources (e.g., electronic medical records, vital statistics, laboratory reports, and health department investigations and case reporting). RESULTS: Variables were selected for inclusion to address key surveillance questions proposed by CDC and health department subject matter experts. General variables include maternal demographics and health history, pregnancy and infant outcomes, maternal and infant laboratory results, and child health outcomes up to the second birthday. Exposure-specific modular variables are included for hepatitis C, syphilis, and Coronavirus Disease 2019 (COVID-19). The system is structured into four relational datasets (maternal, pregnancy outcomes and birth, infant/child follow-up, and laboratory testing). DISCUSSION: SET-NET provides a population-based mother–baby linked longitudinal surveillance approach and has already demonstrated rapid adaptation to COVID-19. This innovative approach leverages existing data sources and rapidly collects data and informs clinical guidance and practice. These data can help to reduce exposure risk and adverse outcomes among pregnant women and their infants, direct public health action, and strengthen public health systems. Springer US 2021-01-04 2021 /pmc/articles/PMC7780211/ /pubmed/33394275 http://dx.doi.org/10.1007/s10995-020-03106-y Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Methodological Notes Woodworth, Kate R. Reynolds, Megan R. Burkel, Veronica Gates, Cymone Eckert, Valorie McDermott, Catherine Barton, Jerusha Wilburn, Amanda Halai, Umme-Aiman Brown, Catherine M. Bocour, Angelica Longcore, Nicole Orkis, Lauren Lopez, Camille Delgado Sizemore, Lindsey Ellis, Esther M. Schillie, Sarah Gupta, Neil Bowen, Virginia B. Torrone, Elizabeth Ellington, Sascha R. Delaney, Augustina Olson, Samantha M. Roth, Nicole M. Whitehill, Florence Zambrano, Laura D. Meaney-Delman, Dana Fehrenbach, S. Nicole Honein, Margaret A. Tong, Van T. Gilboa, Suzanne M. A Preparedness Model for Mother–Baby Linked Longitudinal Surveillance for Emerging Threats |
title | A Preparedness Model for Mother–Baby Linked Longitudinal Surveillance for Emerging Threats |
title_full | A Preparedness Model for Mother–Baby Linked Longitudinal Surveillance for Emerging Threats |
title_fullStr | A Preparedness Model for Mother–Baby Linked Longitudinal Surveillance for Emerging Threats |
title_full_unstemmed | A Preparedness Model for Mother–Baby Linked Longitudinal Surveillance for Emerging Threats |
title_short | A Preparedness Model for Mother–Baby Linked Longitudinal Surveillance for Emerging Threats |
title_sort | preparedness model for mother–baby linked longitudinal surveillance for emerging threats |
topic | Methodological Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780211/ https://www.ncbi.nlm.nih.gov/pubmed/33394275 http://dx.doi.org/10.1007/s10995-020-03106-y |
work_keys_str_mv | AT woodworthkater apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT reynoldsmeganr apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT burkelveronica apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT gatescymone apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT eckertvalorie apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT mcdermottcatherine apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT bartonjerusha apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT wilburnamanda apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT halaiummeaiman apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT browncatherinem apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT bocourangelica apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT longcorenicole apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT orkislauren apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT lopezcamilledelgado apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT sizemorelindsey apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT ellisestherm apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT schilliesarah apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT guptaneil apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT bowenvirginiab apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT torroneelizabeth apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT ellingtonsaschar apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT delaneyaugustina apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT olsonsamantham apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT rothnicolem apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT whitehillflorence apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT zambranolaurad apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT meaneydelmandana apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT fehrenbachsnicole apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT honeinmargareta apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT tongvant apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT gilboasuzannem apreparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT woodworthkater preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT reynoldsmeganr preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT burkelveronica preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT gatescymone preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT eckertvalorie preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT mcdermottcatherine preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT bartonjerusha preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT wilburnamanda preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT halaiummeaiman preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT browncatherinem preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT bocourangelica preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT longcorenicole preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT orkislauren preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT lopezcamilledelgado preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT sizemorelindsey preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT ellisestherm preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT schilliesarah preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT guptaneil preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT bowenvirginiab preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT torroneelizabeth preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT ellingtonsaschar preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT delaneyaugustina preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT olsonsamantham preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT rothnicolem preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT whitehillflorence preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT zambranolaurad preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT meaneydelmandana preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT fehrenbachsnicole preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT honeinmargareta preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT tongvant preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats AT gilboasuzannem preparednessmodelformotherbabylinkedlongitudinalsurveillanceforemergingthreats |