Physical distancing and risk of COVID-19 in small-scale fisheries: A remote sensing assessment in coastal Ghana

Published: 12 July 2020| Version 1 | DOI: 10.17632/2s6x25xsrd.1
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Description

The dataset includes all data collected and analysed for the study on "Physical distancing and risk of COVID-19 in small-scale fisheries: A remote sensing assessment in coastal Ghana." The novel coronavirus is predicted to have dire implications on global food systems including fisheries value chains due to restrictions imposed on human movements in many countries. In Ghana, food production, both agriculture and fisheries, is exempted from restrictions as an essential service. We employed an Unmanned Aerial Vehicle (UAV) in assessing the risk of artisanal fishers to the pandemic using physical distancing as a proxy. From analysis of cumulative distribution function (G-function) of the nearest-neighbour distances (NND), this study underscored crowding at all surveyed fish landing beaches and identified potential “hotspots” for disease transmission. Aerial images were obtined. The locations of people in orthomosaic images were manually extracted as point data in ESRI ArcMap v.10.3 using the editor tool. From the point data, the distance from each point to the nearest other point, that is the nearest-neighbour distance (NND), was measured for all individuals presents in each of the six landing beaches in this study. The median distances were compared to the World Health Organisation (WHO) and Centre for Disease Control (CDC) standards on physical (social) distancing.

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Institutions

University of London Saint George's, WorldFish, James Cook University, University of Rhode Island, University of Cape Coast

Categories

Infectious Disease, Remote Sensing, Unmanned Aerial Vehicle (Space Vehicle), Spatial Aggregation, Coastal Fisheries, Risk, COVID-19

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