A participatory modelling approach for investigating the spread of Covid-19 in countries of the Eastern Mediterranean Region to support public health decision-making

Datos Bibliográficos

ID21880225
AutoresKeyrellous Adib (0000-0001-9995-8400, World Health Organization Regional Office for the Eastern Mediterranean, autor de correspondencia), P A Hancock (0000-0001-5531-1082, University of Oxford), Aysel Rahimli (0000-0002-3639-5425, World Health Organization Regional Office for the Eastern Mediterranean), Bridget Mugisa (0000-0003-4589-6616, World Health Organization Regional Office for the Eastern Mediterranean), Fayez Abdulrazeq (0000-0003-3131-2042, World Health Organization Regional Office for the Eastern Mediterranean), Ricardo Águas (0000-0002-6507-6597, University of Oxford), Lisa J White (0000-0002-6523-185X, University of Oxford), Rana Hajjeh (0000-0002-0401-6603, World Health Organization Regional Office for the Eastern Mediterranean), Lubna Al Ariqi (0000-0002-3343-6359, World Health Organization Regional Office for the Eastern Mediterranean), Pierre Nabeth (0000-0002-1567-6252, World Health Organization Regional Office for the Eastern Mediterranean)
Año2021
Volumen6
Número3
Páginase005207
Fecha de publicación2021-03-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaBMJ Global Health (JOURNAL)
Identificadores de la revistaISSN: 2059-7908 • E-ISSN: 2059-7908
EditorialBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2021-005207
PMID33762253
OpenAlexW3131330833
IdiomaEN
Citas recibidas7
Referencias citadas18

Early on in the COVID-19 pandemic, the WHO Eastern Mediterranean Regional Office recognised the importance of epidemiological modelling to forecast the progression of the COVID-19 pandemic to support decisions guiding the implementation of response measures. We established a modelling support team to facilitate the application of epidemiological modelling analyses in the Eastern Mediterranean Region (EMR) countries. Here, we present an innovative, stepwise approach to participatory modelling of the COVID-19 pandemic that engaged decision-makers and public health professionals from countries throughout all stages of the modelling process. Our approach consisted of first identifying the relevant policy questions, collecting country-specific data and interpreting model findings from a decision-maker’s perspective, as well as communicating model uncertainty. We used a simple modelling methodology that was adaptable to the shortage of epidemiological data, and the limited modelling capacity, in our region. We discuss the benefits of using models to produce rapid decision-making guidance for COVID-19 control in the WHO EMR, as well as challenges that we have experienced regarding conveying uncertainty associated with model results, synthesising and comparing results across multiple modelling approaches, and modelling fragile and conflict-affected states

Business · Citizen journalism · Economic shortage · Environmental planning · Geography · Pandemic · Political science · Public health · Computer Science · COVID-19 epidemiological studies · Medicine · Viral Infections and Outbreaks Research · Zoonotic diseases and public health · Epidemiology