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Using maternal and neonatal data collection systems for coronavirus disease 2019 (COVID-19) vaccines active safety surveillance in low- and middle-income countries: an international modified Delphi study.
Pingray, Veronica; Belizán, María; Matthews, Sarah; Zaraa, Sabra; Berrueta, Mabel; Noguchi, Lisa M; Xiong, Xu; Gurtman, Alejandra; Absalon, Judith; Nelson, Jennifer C; Panagiotakopoulos, Lakshmi; Sevene, Esperanca; Munoz, Flor M; Althabe, Fernando; Mwamwitwa, Kissa W; Rodriguez Cairoli, Federico; Anderson, Steven A; McClure, Elizabeth M; Guillard, Christine; Nakimuli, Annettee; Stergachis, Andy; Buekens, Pierre.
Afiliação
  • Pingray V; Institute for Clinical Effectiveness and Health Policy (IECS-CONICET), Ciudad de Buenos Aires, Buenos Aires, 1414, Argentina.
  • Belizán M; Institute for Clinical Effectiveness and Health Policy (IECS-CONICET), Ciudad de Buenos Aires, Buenos Aires, 1414, Argentina.
  • Matthews S; School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, 70112, USA.
  • Zaraa S; School of Pharmacy, University of Washington, Seattle, Washington, 98195, USA.
  • Berrueta M; Institute for Clinical Effectiveness and Health Policy (IECS-CONICET), Ciudad de Buenos Aires, Buenos Aires, 1414, Argentina.
  • Noguchi LM; Jhpiego, Johns Hopkins University, Baltimore, Maryland, 21231, USA.
  • Xiong X; School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, 70112, USA.
  • Gurtman A; Vaccine Research and Development, Pfizer, Inc, Pearl River, New York, 10965, USA.
  • Absalon J; Vaccine Research and Development, Pfizer, Inc, Pearl River, New York, 10965, USA.
  • Nelson JC; Kaiser Permanente, Washington Health Research Institute, Seattle, Washington, 98101, USA.
  • Panagiotakopoulos L; Centers for Disease Control and Prevention, Atlanta, Georgia, 30333, USA.
  • Sevene E; Department of Physiological Science, Clinical Pharmacology, Faculty of Medicine , Maputo, Mozambique, Eduardo Mondlane University/Manhiça Health Research Centre, Maputo, Maputo, 1102, Mozambique.
  • Munoz FM; Departments of Pediatrics, Molecular Virology and Microbiology,, Baylor College of Medicine, Houston, Texas, 77004, USA.
  • Althabe F; UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction, Department of Sexual and Reproductive Health and Research, World Health Organization, Geneva, Geneva, 1211, Switzerland.
  • Mwamwitwa KW; Tanzania Medicines and Medical Devices Authority, Dar es Salaam, Tanzania, 11000, Tanzania.
  • Rodriguez Cairoli F; Institute for Clinical Effectiveness and Health Policy (IECS-CONICET), Ciudad de Buenos Aires, Buenos Aires, 1414, Argentina.
  • Anderson SA; U. S. Food & Drug Administration, Silver Spring, Maryland, 20993, USA.
  • McClure EM; Social, Statistical and Environmental Sciences, Research Triangle Institute, Durham, North Carolina, 27709, USA.
  • Guillard C; World Health Organization, Geneva, Geneva, 1211, Switzerland.
  • Nakimuli A; Department of Obstetrics and Gynaecology, School of Medicine, Makerere University, Kampala, Kampala, 0000, Uganda.
  • Stergachis A; School of Pharmacy, University of Washington, Seattle, Washington, 98195, USA.
  • Buekens P; School of Public Health, University of Washington, Seattle, Seattle, Washington, 98195, USA.
Gates Open Res ; 5: 99, 2021.
Article em En | MEDLINE | ID: mdl-39049963
ABSTRACT

Background:

Given that pregnant women are now included among those for receipt coronavirus disease 2019 (COVID-19) vaccines, it is important to ensure that information systems can be used (or available) for active safety surveillance, especially in low- and middle-income countries (LMICs). The aim of this study was to build consensus about the use of existing maternal and neonatal data collection systems in LMICs for COVID-19 vaccines active safety surveillance, a basic set of variables, and the suitability and feasibility of including pregnant women and LMIC research networks in COVID-19 vaccines pre-licensure activities.

Methods:

A three-stage modified Delphi study was conducted over three months in 2020. An international multidisciplinary panel of 16 experts participated. Ratings distributions and consensus were assessed, and ratings' rationale was analyzed.

Results:

The panel recommended using maternal and neonatal data collection systems for active safety surveillance in LMICs (median 9; disagreement index [DI] -0.92), but there was no consensus (median 6; DI 1.79) on the feasibility of adapting these systems. A basic set of 14 maternal, neonatal, and vaccination-related variables. Out of 16 experts, 11 supported a basic set of 14 maternal, neonatal, and vaccination-related variables for active safety surveillance. Seven experts agreed on a broader set of 26 variables. The inclusion of pregnant women for COVID-19 vaccines research (median 8; DI -0.61) was found appropriate, although there was uncertainty on its feasibility in terms of decision-makers' acceptability (median 7; DI 10.00) and regulatory requirements (median 6; DI 0.51). There was no consensus (median 6; DI 2.35) on the feasibility of including research networks in LMICs for conducting clinical trials amongst pregnant women.

Conclusions:

Although there was some uncertainty regarding feasibility, experts recommended using maternal and neonatal data collection systems and agreed on a common set of variables for COVID-19 vaccines active safety surveillance in LMICs.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Gates Open Res Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Argentina

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Gates Open Res Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Argentina
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