Pular para o conteúdo principal

ETHNOS_APP

Início • Busca • Periódicos • Lista 0

Data innovation in response to Covid-19 in Somalia

Application of a syndromic case definition and rapid mortality assessment method

Dados Bibliográficos

ID19530402
AutoresAndrew Seal (0000-0003-3656-4054, University College London, autor correspondente), Mohamed Jelle (0000-0002-2894-6549, University College London), Balint Nemeth (0000-0001-5214-3714, Norwegian Refugee Council, Oslo, Norway), Mohamed Yusuf Hassan (0000-0003-2443-3401, Norwegian Refugee Council, Nairobi, Kenya), Dek Abdi Farah (Norwegian Refugee Council, Nairobi, Kenya), Faith Mueni Musili (0000-0003-4141-5440, Norwegian Refugee Council, Nairobi, Kenya), George Samuel Asol (Norwegian Refugee Council, Nairobi, Kenya), Carlos S Grijalva-Eternod (0000-0002-2461-9954, University College London), Edward Fottrell (0000-0003-0518-7161, University College London)
Ano2021
Volume14
Fascículosup1
Páginas1983106-1983106
Data de publicação2021-10-26
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoGlobal Health Action (JOURNAL)
Identificadores do periódicoISSN: 1654-9716 • E-ISSN: 1654-9880
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/16549716.2021.1983106
PMID35377286
OpenAlexW4285342064
IdiomaEN
Citações recebidas1
Referências citadas7

BACKGROUND: During the COVID-19 pandemic, the importance of reliable public health data has been highlighted, as well as the multiple challenges in collecting it, especially in low income and conflict-affected countries. Somalia reported its first confirmed case of COVID-19 on 16 March 2020 and has experienced fluctuating infection levels since then. OBJECTIVES: To monitor the impact of COVID-19 on beneficiaries of a long-term cash transfer programme in Somalia and assess the utility of a syndromic score case definition and rapid mortality surveillance tool. METHODS: Five rounds of telephone interviews were conducted from June 2020 - April 2021 with 1,046-1,565 households participating in a cash transfer programme. The incidence of COVID-19 symptoms and all-cause mortality were recorded. Carers of the deceased were interviewed a second time using a rapid verbal autopsy questionnaire to determine symptoms preceding death. Data were recorded on mobile devices and analysed using COVID Rapid Mortality Surveillance (CRMS) software and R. RESULTS: The syndromic score case definition identified suspected symptomatic cases that were initially confined to urban areas but then spread widely throughout Somalia. During the first wave, the peak syndromic case rate (311 cases/million people/day) was 159 times higher than the average laboratory confirmed case rate reported by WHO for the same period. Suspected COVID-19 deaths peaked at 14.3 deaths/million people/day, several weeks after the syndromic case rate. Crude and under-five death rates did not cross the respective emergency humanitarian thresholds (1 and 2 deaths/10,000 people/day). CONCLUSION: Use of telephone interviews to collect data on the evolution of COVID-19 outbreaks is a useful additional approach that can complement laboratory testing and mortality data from the health system. Further work to validate the syndromic score case definition and CRMS is justified

2019-20 coronavirus outbreak · Data science · Disease · Economic growth · Economics · Geography · MEDLINE · Outbreak · Pandemic · Pathology · Political science · Computer Science · COVID-19 Digital Contact Tracing · COVID-19 epidemiological studies · Medicine · SARS-CoV-2 detection and testing · Virology

  • A life in death

    Open Access•Tedros Adhanom Ghebreyesus, Warren Graham•Global Health Action•2021

  • Real-time tracking of self-reported symptoms to predict potential Covid-19

    Open Access•Cristina Menni, Ana M Valdes et al.•Nature Medicine•2020

Obras citantes distintas1
Citações por ano0,2
Intervalo de citações2021 - 2021 (1)
Velocidade de citaçãohistorical
Altamente citadoNão
Tipos de citaçãoNeutras: 1
Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae