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Currently submitted to: Journal of Medical Internet Research

Date Submitted: Jul 29, 2020
Open Peer Review Period: Jul 29, 2020 - Sep 23, 2020
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Estimating the COVID-19 spread through real-time population mobility patterns: surveillance in Low- and Middle- income countries

  • Stefanos Tyrovolas; 
  • Iago Giné-Vázquez; 
  • Daniel Fernández; 
  • Mariathi Morena; 
  • Ai Koyanagi; 
  • Mark Janko; 
  • Josep Maria Haro; 
  • Yang Lin; 
  • Paul Lee; 
  • William Pan; 
  • Somnath Chatterji; 
  • Alex Molassiotis; 

ABSTRACT

Background:

On January 30, 2020, World Health Organization (WHO) declared the current novel coronavirus disease 2019 (COVID-19) as a public health emergency of international concern and later characterized it as a pandemic. Since then the virus has also rapidly spread among Latin American, Caribbean and African countries.

Objective:

The first aim of this study was to identify new emerging COVID-19 clusters over time and in space in Latin American, Caribbean, and African regions [mostly low and middle-income countries (LMICs)], using a prospective space-time scan measurement approach. The second aim was to assess the impact of real-time population mobility patterns between January 21st to May 18th, under the implemented government interventions, measurements and policy restrictions, on COVID-19 spread, among those regions and globally.

Methods:

We created a global COVID-19 database merging WHO daily case reports (of 218 countries, regions and territories) with other measures such as population density, country income levels for January 21st to May 15th, 2020. A score of government policy interventions was created ranging from “light”, “intermediate”, and “high”, to “very high” interventions. Prospective space-time scan statistic methods were applied in five time periods between January to May 2020 and a stepped-wedged regression mixed model analysis was used.

Results:

We found that COVID-19 emerging clusters within these five periods of time grew from 7 emerging clusters to 28 by mid-May. We also detected various increasing and decreasing relative risk estimates of COVID-19 spread among Latin American, Caribbean and African countries within the period of analysis. Globally, as well as regionally (Latin American, Caribbean and Africa), population mobility to parks and similar leisure areas during all the implemented control policies were related with accelerated COVID-19 spread. For countries in Africa, population mobility for work reasons during high and very high levels of implemented control policies were related with increased virus spread.

Conclusions:

Prospective space-time scan is a measurement approach that LMICs countries could easily use to detect emerging clusters in a timely manner and implement specific control policies and interventions to slow down COVID-19 transmission. In addition, real time population mobility obtained from crowdsourced digital data could be useful for current and future targeted public health and mitigation policies among Latin American, Caribbean and African countries as well as globally.


 Citation

Please cite as:

Tyrovolas S, Giné-Vázquez I, Fernández D, Morena M, Koyanagi A, Janko M, Haro JM, Lin Y, Lee P, Pan W, Chatterji S, Molassiotis A

Estimating the COVID-19 spread through real-time population mobility patterns: surveillance in Low- and Middle- income countries

JMIR Preprints. 29/07/2020:22999

DOI: 10.2196/preprints.22999

URL: https://preprints.jmir.org/preprint/22999

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