OCHA-Bucky: A COVID-19 Model to Inform Humanitarian Operations - Model Methodology (October 2020)

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Publication language
English
Pages
15pp
Date published
30 Oct 2020
Type
Tools, guidelines and methodologies
Keywords
Data, Early warning, COVID-19, Epidemics & pandemics, humanitarian action, Research methodology

In late 2019, the United Nations (UN) Office for the Coordination of Humanitarian Affairs (OCHA) Centre for Humanitarian Data created a new workstream for predictive analytics. This was based on demand from OCHA’s leadership to “use data, and especially the tools of predictive analytics to get ahead, to be more anticipatory, to predict what is about to happen and to trigger the response earlier.” This ambition aligns with the overall goal of the Centre, which is to increase the use and impact of data in the humanitarian sector. The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Anticipatory action is no longer an abstract idea but something populations are actively doing by staying home and increasing the number of hospital beds to protect the most vulnerable populations.

Epidemic forecasting is one tool through which we can gain an understanding of the final outbreak size and indicators of when the COVID-19 epidemic peaks in a country. This provides decision-makers with the capability to plan, surge, and manage resources during a pandemic. UN OCHA and the Johns Hopkins University Applied Physics Laboratory have therefore established a partnership to inform COVID-19 strategies for humanitarian interventions by both national authorities and the humanitarian community in selected high-priority countries, resulting in increased technical capacity to predict new and compounded humanitarian needs, and use of data science to arrive at interventions to mitigate them.

This partnership developed a series of adjustments to a novel COVID-19 model (JHUAPL-Bucky) that incorporates different vulnerability factors to provide insights on the scale of the crisis in priority countries at national and sub-national levels, how different response interventions are expected to impact the epidemic curve, and the duration of the crisis in specific locations. The resultant model (OCHA-Bucky) stratifies COVID-19 dynamics by age and population vulnerability. Input to the model consists of geographically distributed COVID-19 cases and deaths, as well as attributes such as inter-regional mobility, population vulnerability, nonpharmaceutical interventions (NPIs) , and social contact matrices. Model output consists of future projections of these same quantities, as well as severe cases (defined as a proportion of total cases). The model considers both inter-regional mobility of the population and time-varying NPIs. OCHA-Bucky has been used to provide weekly projections to six OCHA country offices: Afghanistan, the Democratic Republic of Congo, Iraq, Somalia, Sudan, and South Sudan.