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Establishing an early warning event management system at Africa CDC.
Mercy, Kyeng; Salyer, Stephanie J; Mankga, Comfort; Hedberg, Calle; Zondo, Phumzile; Kebede, Yenew.
Afiliação
  • Mercy K; Africa Centres for Disease Control and Prevention, Division of Surveillance and Disease Intelligence, Addis Ababa, Ethiopia.
  • Salyer SJ; Africa Centres for Disease Control and Prevention, Division of Surveillance and Disease Intelligence, Addis Ababa, Ethiopia.
  • Mankga C; United States Centers for Disease Control and Prevention, Division of Global Health Protection, Atlanta, Georgia; United States of America.
  • Hedberg C; Health Information Systems Program South Africa, Pretoria, South Africa.
  • Zondo P; Health Information Systems Program South Africa, Pretoria, South Africa.
  • Kebede Y; Health Information Systems Program South Africa, Pretoria, South Africa.
PLOS Digit Health ; 3(7): e0000546, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38976663
ABSTRACT
Africa is home to hotspots of disease emergence and re-emergence. To adequately detect and respond to these health threats, early warning systems inclusive of event-based surveillance (EBS) are needed. However, data systems to manage these events are not readily available. In 2020, Africa Centres for Disease Control and Prevention developed an event management system (EMS) to meet this need. The district health information software (DHIS2), which is free and open-source software was identified as the platform for the EMS because it can support data capture and analysis and monitor and report events. The EMS was created through a collaborative and iterative prototyping process that included modifying key DHIS2 applications like Tracker Capture. Africa CDC started piloting the EMS with both signal and event data entry in June 2020. By December 2022, 416 events were captured and over 140 weekly reports, including 19 COVID-19 specific reports, were generated and distributed to inform continental awareness and response efforts. Most events detected directly impacted humans (69%), were considered moderate (50%) to high (29%) risk level and reflected both emerging and endemic infectious disease outbreaks. Highly pathogenic avian influenza, specifically H5N1, was the most frequently detected animal event and storms and flooding were most frequently detected environmental events. Both data completeness and timeliness improved over time. Country-level interest and utility resulted in four African countries adapting the EMS in 2022 and two more in 2023. This system demonstrates how integrating digital technology into health systems and utilising existing digital platforms like DHIS2 can improve early warning at the continental and country level by improving EBS workflow.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article