Page 115 - IJPS-10-1

International Journal of
Population Studies Migration and mobility data in COVID-19 response

Rwanda, and Uganda implemented these containment countries, focusing on the management of migration. The
measures immediately, Tanzania and Burundi took a GCM reiterates the importance of data on migration, with
different approach, by playing down the significance of the first objective tasking member states to collect and
the pandemic, due to political reasons (Brima, 2021). By utilize accurate and disaggregated migration data as a basis
June 2020, Rwanda began implementing the protection for evidence-based policies (UN, 2018). Guided by the
measures such as health messaging, while Tanzania later already-known connection between human mobility and
set up a COVID-19 response taskforce almost a year later, global dissemination of virus, the COVID-19 pandemic
in April 2021 (Manirambona et al., 2021). provides a timely opportunity to explore whether
migration and mobility data available in a timely, accurate,
The spread of COVID-19 pandemic is closely tied
to global mobility, as migration played a key role in the and disaggregated manner can inform suitable policy
spread of the virus across the globe (Benton et al., 2021; response to the pandemic.
De Bruin et al., 2020). As different countries unilaterally This systematic review of literature focuses on the
or within coalitions put in place mitigation measures to preliminary response to the COVID-19 pandemic between
manage the pandemic, it is necessary to understand how 2020 and 2021, examining how migration and mobility
mobility and migration data were accessed and utilized statistics were incorporated to strengthen the response
in the COVID-19 mitigation measures. The migration plans. The centerpiece of this review reflects the necessity
and mobility data serve to identify recent travelers and of intelligently applying timely and disaggregated data for
their close contacts as well the population at risk of evidence-based decision making, which is the aspiration of
infection, which are important determining factors for the Global Compact for Migration. The next section of this
implementing mitigation measures. For example, in many paper details the methods and analytical approach, and
countries, once a victim was positively identified to have the last three sections deal with the results, discussion, and
contracted COVID-19, information such as travel history recommendations for future pandemic response efforts.
and possible contacts made during the travel will be The main objective of this review is to showcase
collected. This way, COVID-19-positive individuals will the application of migration and mobility data in the
be monitored during quarantine and their contacts traced management and response to the COVID-19 pandemic in
to prevent the infection from dissemination to others the EAC region.
(Nachega et al., 2021; Braithwaite et al., 2020; Jordana &
Triviño-Salazar, 2020). 2. Data and methods
Pandemics pose serious public health challenges and This systematic review was conducted based on the
usually require instant, accessible data to inform planning Preferred Reporting Items for Systematic Reviews and
and formulate suitable response, and mitigation measures Meta-Analyses (PRISMA) reporting guidelines (Moher
(Pergolizzi et al., 2021; Desai et al., 2019). Response efforts et al., 2009). Studies were identified from the available
require granular data which, at times, are unavailable; electronic databases, including but not limited to, African
therefore, model-derived proxies of mobility are commonly Journals Online (AJOL), Google Scholar, Jstor, PubMed,
employed. Perez & Dragicevic (2009) developed such a and Medline. The review focused on studies conducted in
model based on community mobility flows to predict the Burundi, Kenya, Rwanda, Tanzania, and Uganda. Despite
spread of communicable disease in Canada. Such agent- being a member state of the EAC, South Sudan was
based models have been applied to model the spread of omitted in this review; additionally, studies conducted in
COVID-19 in the Global North countries (Hoertel et al., the Democratic Republic of Congo, which had not yet been
2020; Venkatramanan et al., 2018). For example, Fortaleza ratified as a member of the EAC regional economic bloc,
et al. (2021) used health geography modeling technique to were omitted from the review.
understand the early dispersion of COVID-19 in São Paulo, The review included published and gray literature
Brazil, using COVID-19 surveillance data to model the that captures data on migration and mobility and its use
spread within the municipalities combined with tracking in the management of COVID-19 within the countries
of air travel into and out of Brazil. Their results showed that of the EAC region from January 2020 to December 2021.
SARS-CoV-2 virus spread within Brazil due to increased This was complemented by literature found in health,
movement of people to regions with better transport mobility, migration, and health specialist platforms
infrastructure, with higher cases being initially reported in hosted by international or local organizations, including
the bigger cities before spreading to smaller ones. universities in the member states, as well as in data and
The Global Compact on Safe, Orderly, and Regular research publications from the International Organization
Migration (GCM) is a negotiated treaty adopted by 152 for Migration (IOM), through its Migration Research

Volume 10 Issue 1 (2024) 109 https://doi.org/10.36922/ijps.357