pandemic

C ovid - 19 A nd m igr A tion in t H e m editerr A ne A n r egion 41

BOX 1.2 Data limitations in measuring migration flows during the COVID-19 pandemic

Several of the data sources used in this chapter to explain migration flows come with some limitations. First, several bureaucratic agencies were fully or partially closed during early periods of the pandemic, slowing down the processing of visas, permits, and asylum applications. Second, some of the applications for asylum and visas may have been filed by migrants who were already in Europe when the pandemic struck. Thus, the drops in the processing and issuance of these legal documents may reflect the limited capacity of government agencies to supply migrants with legal documents at that time rather than an actual drop in migration flows or demand for such documents.

Second, the use of Facebook’s advertising platform to collect data is a relatively new methodology. Pötzschke and Braun (2017) first used Facebook advertising as a more effective way to target survey participants, and they found this survey methodology could reach previously hard-to-reach populations. Zagheni, Weber, and Gummadi (2017) were among the first to use the Facebook advertising platform to estimate international migrant stocks. Comparing their statistics with the US Census Bureau’s American Community Survey, they conclude that despite some sources of bias, this bias can be estimated and corrected.

Figure B1.2.1 Destinations of emigrants from Senegal, by data source

a. UN DESA data, 2020 b. Facebook location data, 2021

Distribution

France Belgium Number of migrants 440 400 360 320 280 240 200 160 120 80 40 0

Italy Germany Coverage (in thousands) 440 400 360 320 280 240 200 160 120 80 40 0

United States Switzerland Spain Portugal Number of migrants Distribution

Canada Other United Kingdom

Sources: international migrant stock 2020 dataset, Population division, United nations department of economic and social Affairs (Un desA): https://www.un.org/development/desa/pd/content/international -migrant-stock; world bank internal data collection from Facebook’s advertising platform.

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42 b U ilding resilient migr A tion s Y stems in t H e mediterr A ne A n region

BOX 1.2 continued

Figure B1.2.2 Destinations of emigrants from Nigeria, by data source

a. UN DESA data, 2020 b. Facebook location data, 2021

Distribution

United States Ireland 1,000 900

Number of migrants 800 700 600 500 400 300 200 100 0

Coverage (in thousands) 1,000 900 800 700 600 500 400 300 200 100 0 Number of migrants

United Kingdom United Arab Emirates Italy Australia Other India Germany France Distribution

Canada Spain

Sources: international migrant stock 2020 dataset, Population division, United nations department of economic and social Affairs (Un desA): https://www.un.org/development/desa/pd/content/international -migrant-stock; world bank internal data collection from Facebook’s advertising platform.

However, Facebook data also have several limitations. First, numbers of migrants are rounded to the nearest thousand, so there is some measurement error. Second, besides the fact that not everyone uses Facebook, these data could also capture the presence of foreigners in a country who are not necessarily migrants, such as tourists, travelers for business, and so on. Third, not every country supports Facebook’s advertising platform. Rampazzo and Weber (2020) report that only 17 African countries support the platform and that United Nations Department of Economic and Social Affairs (UN DESA) estimates of African migrants abroad in other African countries are 64 percent higher than their estimates using Facebook data. When comparing the Facebook 2021 data with UN DESA 2020 data, for some nationalities such as Senegalese emigrants, the distribution of the data is relatively similar, though the coverage of the Facebook data is only about half that of the UN DESA data. On the other hand, the Facebook data have a wider coverage of Nigerians abroad, though the distribution across destinations is not entirely compatible with the UN DESA data.

Despite its nuances, the Facebook data has the benefit of being collected more frequently and at a smaller level of regional granularity. However, given the incomplete penetration of Facebook data in capturing all people on the move, the biases in the data should be corrected (Zagheni, Weber, and Gummadi 2017) and interpreted with caution.

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Figure 1.12 Changes in migrant stocks from selected African countries to selected destination countries, April 2020 to January 2021

Change (%)

20 10 0 −10 −20 −30 −40 −50 −60 −70 −80 −90 −100 a. Algeria

TotalFranceCanadaUnited States Spain United KingdomBelgiumGermany Russian FederationUnited Arab Emirates Change (%)

20 10 0 −10 −20 −30 −40 −50 −60 −70 −80 −90 −100 b. Morocco

TotalFrance Spain ItalyBelgiumUnited States United Arab EmiratesCanadaGermanyNetherlands

Change (%)

20 10 0 −10 −20 −30 −40 −50 −60 −70 −80 −90 −100 c. Nigeria

Total United StatesUnited KingdomUnited Arab Emirates Italy FranceIndiaCanadaGermany Spain Change (%)

20 10 0 −10 −20 −30 −40 −50 −60 −70 −80 −90 −100 d. Senegal

TotalFrance ItalySpain United StatesCanadaBelgiumGermany United Kingdom India

Source: world bank internal data collection from Facebook’s advertising platform. Note: destination countries were selected based on available data.

them the option to work remotely from their home country. The government is encouraging these return migrants to stay because it could promote innovation, competition, and tax revenue (Bubola 2021). Similarly, in spring 2020, more than 1.5 million Romanians and 54,000 Poles returned home from countries such as Italy, Spain, and other Western European countries (Paul 2020).

Although this phenomenon has been leading to a shortage of essential workers in host countries, this reverse migration is increasing the human capital of the sending countries. Bakalova et al. (2021) estimate that across the EU, 2.7–3.7 million migrants in white-collar occupations could potentially return home and work

44 b U ilding resilient migr A tion s Y stems in t H e mediterr A ne A n region

remotely, including 2–2.6 million to other EU member states and 321,000 to 446,000 to countries in the Middle East and North Africa.

On the other hand, border closures, strained budgets, and logistical difficulties led many migrants to become stranded. For example, from March to July 2020, Morocco closed its borders, preventing seasonal agricultural migrant workers abroad from returning home (Le Coz and Newland 2021). An estimated 2.75 million migrants whose movements were affected by COVID-19 were stranded worldwide in October 2020 (IOM 2020b). Of these 2.75 million, approximately 1.3 million people were in the Middle East and North Africa, 201,000 were in the European Economic Area and Switzerland, and 58,000 were in Eastern Europe and Central Asia. In June 2020, in West and Central Africa, the IOM counted approximately 50,000 migrants stranded at international borders, in transit centers, or in quarantine (Schöfberger and Rango 2020). For instance, when the Niger government closed its borders, 764 migrants were stranded at the Algerian border in quarantine, and 256 migrants were stranded at the Libyan border (MMC 2020).

Predeparture measures such as presenting negative PCR tests, among others, presented challenges for many people on the move. For example, difficulty in getting a test left more than 2,000 Nigerians stranded in transit in Libya in the early months of the pandemic (Lau, Hooper, and Zard 2021). In the United Arab Emirates, migrant workers were stranded for months after being laid off in the midst of the pandemic, trying to secure a way to return home (Horwood and Frouws 2021).

The effectiveness of travel restrictions: a call for research

Historical research has generally shown that border and travel restrictions do not stop virus transmission. Some historical research indicates that travel restrictions, especially if not implemented in a timely manner, have no effect on the spread of diseases. Brownstein, Wolfe, and Mandl (2006) look at the temporary reduction in air travel due to restrictions following the September 11, 2001, terrorist attacks on the spread of the flu virus, and they find that only immediate air travel closures would have an impact on containing the virus.

A recent study by Clemens and Ginn (2020) concludes that the case for permanent limits on international mobility to reduce the harm of future pandemics is weak. Using data on the influenza pandemics that began in 1889, 1918, 1957, and 2009, they find that a 50 percent reduction in prepandemic international mobility is associated with a one- to two-week delay in arrival of the virus to a destination and no detectable reduction in final mortality. They find no evidence that delayed arrival correlates systematically with lower morbidity or mortality in any of the pandemics. In a review of past research, Bier (2020) similarly shows that largely reducing air traffic can only slightly delay a pandemic—by one to six weeks at best—but not stop it (Bajardi et al. 2011; Cooper et al. 2006; Epstein et al. 2007; Ferguson et al. 2006;