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Using Google Health Trends to investigate COVID-19 incidence in Africa

The COVID-19 pandemic has caused over 500 million cases and over six million deaths globally. From these numbers, over 12 million cases and over 250 thousand deaths have occurred on the African continent as of May 2022. Prevention and surveillance remains the cornerstone of interventions to halt the...

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Autores principales: Fulk, Alexander, Romero-Alvarez, Daniel, Abu-Saymeh, Qays, Saint Onge, Jarron M., Peterson, A. Townsend, Agusto, Folashade B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9173636/
https://www.ncbi.nlm.nih.gov/pubmed/35671301
http://dx.doi.org/10.1371/journal.pone.0269573
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author Fulk, Alexander
Romero-Alvarez, Daniel
Abu-Saymeh, Qays
Saint Onge, Jarron M.
Peterson, A. Townsend
Agusto, Folashade B.
author_facet Fulk, Alexander
Romero-Alvarez, Daniel
Abu-Saymeh, Qays
Saint Onge, Jarron M.
Peterson, A. Townsend
Agusto, Folashade B.
author_sort Fulk, Alexander
collection PubMed
description The COVID-19 pandemic has caused over 500 million cases and over six million deaths globally. From these numbers, over 12 million cases and over 250 thousand deaths have occurred on the African continent as of May 2022. Prevention and surveillance remains the cornerstone of interventions to halt the further spread of COVID-19. Google Health Trends (GHT), a free Internet tool, may be valuable to help anticipate outbreaks, identify disease hotspots, or understand the patterns of disease surveillance. We collected COVID-19 case and death incidence for 54 African countries and obtained averages for four, five-month study periods in 2020–2021. Average case and death incidences were calculated during these four time periods to measure disease severity. We used GHT to characterize COVID-19 incidence across Africa, collecting numbers of searches from GHT related to COVID-19 using four terms: ‘coronavirus’, ‘coronavirus symptoms’, ‘COVID19’, and ‘pandemic’. The terms were related to weekly COVID-19 case incidences for the entire study period via multiple linear and weighted linear regression analyses. We also assembled 72 variables assessing Internet accessibility, demographics, economics, health, and others, for each country, to summarize potential mechanisms linking GHT searches and COVID-19 incidence. COVID-19 burden in Africa increased steadily during the study period. Important increases for COVID-19 death incidence were observed for Seychelles and Tunisia. Our study demonstrated a weak correlation between GHT and COVID-19 incidence for most African countries. Several variables seemed useful in explaining the pattern of GHT statistics and their relationship to COVID-19 including: log of average weekly cases, log of cumulative total deaths, and log of fixed total number of broadband subscriptions in a country. Apparently, GHT may best be used for surveillance of diseases that are diagnosed more consistently. Overall, GHT-based surveillance showed little applicability in the studied countries. GHT for an ongoing epidemic might be useful in specific situations, such as when countries have significant levels of infection with low variability. Future studies might assess the algorithm in different epidemic contexts.
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spelling pubmed-91736362022-06-08 Using Google Health Trends to investigate COVID-19 incidence in Africa Fulk, Alexander Romero-Alvarez, Daniel Abu-Saymeh, Qays Saint Onge, Jarron M. Peterson, A. Townsend Agusto, Folashade B. PLoS One Research Article The COVID-19 pandemic has caused over 500 million cases and over six million deaths globally. From these numbers, over 12 million cases and over 250 thousand deaths have occurred on the African continent as of May 2022. Prevention and surveillance remains the cornerstone of interventions to halt the further spread of COVID-19. Google Health Trends (GHT), a free Internet tool, may be valuable to help anticipate outbreaks, identify disease hotspots, or understand the patterns of disease surveillance. We collected COVID-19 case and death incidence for 54 African countries and obtained averages for four, five-month study periods in 2020–2021. Average case and death incidences were calculated during these four time periods to measure disease severity. We used GHT to characterize COVID-19 incidence across Africa, collecting numbers of searches from GHT related to COVID-19 using four terms: ‘coronavirus’, ‘coronavirus symptoms’, ‘COVID19’, and ‘pandemic’. The terms were related to weekly COVID-19 case incidences for the entire study period via multiple linear and weighted linear regression analyses. We also assembled 72 variables assessing Internet accessibility, demographics, economics, health, and others, for each country, to summarize potential mechanisms linking GHT searches and COVID-19 incidence. COVID-19 burden in Africa increased steadily during the study period. Important increases for COVID-19 death incidence were observed for Seychelles and Tunisia. Our study demonstrated a weak correlation between GHT and COVID-19 incidence for most African countries. Several variables seemed useful in explaining the pattern of GHT statistics and their relationship to COVID-19 including: log of average weekly cases, log of cumulative total deaths, and log of fixed total number of broadband subscriptions in a country. Apparently, GHT may best be used for surveillance of diseases that are diagnosed more consistently. Overall, GHT-based surveillance showed little applicability in the studied countries. GHT for an ongoing epidemic might be useful in specific situations, such as when countries have significant levels of infection with low variability. Future studies might assess the algorithm in different epidemic contexts. Public Library of Science 2022-06-07 /pmc/articles/PMC9173636/ /pubmed/35671301 http://dx.doi.org/10.1371/journal.pone.0269573 Text en © 2022 Fulk et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Fulk, Alexander
Romero-Alvarez, Daniel
Abu-Saymeh, Qays
Saint Onge, Jarron M.
Peterson, A. Townsend
Agusto, Folashade B.
Using Google Health Trends to investigate COVID-19 incidence in Africa
title Using Google Health Trends to investigate COVID-19 incidence in Africa
title_full Using Google Health Trends to investigate COVID-19 incidence in Africa
title_fullStr Using Google Health Trends to investigate COVID-19 incidence in Africa
title_full_unstemmed Using Google Health Trends to investigate COVID-19 incidence in Africa
title_short Using Google Health Trends to investigate COVID-19 incidence in Africa
title_sort using google health trends to investigate covid-19 incidence in africa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9173636/
https://www.ncbi.nlm.nih.gov/pubmed/35671301
http://dx.doi.org/10.1371/journal.pone.0269573
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