C-19: So, which countries are really locking down their populations?

Updated: May 11

There is much debate across countries as to the right strategy to stop the spread of COVID-19. While Italy, Spain and UK have almost fully locked themselves down, reeling from the shock of close to a thousand deaths a day; others like Sweden, Brazil, Belarus, South Korea, Singapore and Japan refuse overly stringent measures; opting instead to stay open for business and deploy lighter controls for social distancing. But is one countries lock-down strategy really the same as the next; and are there difference in effectiveness of execution? Here we glean data from Google's recently released COVID-19 Community Mobility Report (GCMR) that tracks changes in population mobility across 131 countries to extract some answers to these questions. This article is Part I of a two part series - link to Part II

TL;DR key-takeaways

  • Study of mobility data from Google's COVID-19 Mobility Reports (covering 131 countries) provides strong confirmation of lock-down and control measures taken by various countries to prevent the spread of the virus

  • Some countries in spite of low infection figures, have taken hard stances in locking down; on the other hand some other countries may have taken action too late to be effective. In Brazil, the population has opted to reduce mobility drastically despite not having an official lock-down policy in place

  • Mobility is indeed still relatively high in countries that have opted to do away with harsh lock-downs, e.g. Japan, South Korea, Belarus and Singapore. This is a reassuring trend, as it allows their economies to still operate while (hopefully) keeping the threat of the virus at bay. This is perhaps something other countries could learn from and adapt to their own situations


Introduction

**UPDATE 20 April: Google Mobility data is now available on a daily basis and has been incorporated into our daily reporting.

The GCMR measures changes in location mobility across 6 types of locations/destinations, defined by activity: residential/dwelling, retail and recreation, groceries & pharmacy, parks & green space, transit stations, and workplaces.

The data is gathered from logged location data obtained from mobile smartphones throughout the period under study. Refer to figure below for a brief background and a source reference.

Figure 1: Sample excerpt from Google's COVID-19 Community Mobility Report that tracks and reports changes in physical activity from baseline across 131 countries and reports. So far two reports have been released:

  • Up to 5 April 2020, % changes from baseline date 23 February

  • Up to 29 March 2020, % changes from baseline date 16 February

Source: https://www.google.com/covid19/mobility/


Overall country summary

Refer to data in tables further below.

  • It is clear that there is a correlation between COVID-19 cases and deaths with reduced mobility in each country, especially in retail & recreation and transit stations, followed by grocery & pharmacy and workplaces; although it is impossible to tell how strong the causal link is. Some countries show a distinct rise in park visits, namely Denmark, Germany, Czechia, South Korea, Sweden and Switzerland; while all countries registered an overall increase in residential activity as most the population opted to stay and work from home.

  • Broadly speaking, countries that had the largest reduction in non-residential activity leading up to 29 March were; Italy, Spain, France, Colombia, Ecuador, New Zealand, France, Sri Lanka, Belgium and Malaysia (largest reduction to least). It is perhaps unsurprising for Spain, Italy and France to be on this shortlist having been hard-hit by a surge in deaths during this very period - each country had no less than 2,600 deaths; however Sri Lanka, New Zealand and Columbia respectively registered less than 10 deaths and 700 cases at this point, while Malaysia and Ecuador had less than 2,500 cases and 60 deaths respectively.

  • It is rather remarkable how perhaps news of the pandemic's death toll in Europe during this time, coupled with policy actions by some governments, had driven populations as far as South America, South Asia and New Zealand to brace down for impact. Many countries had in fact implemented movement controls and lock-down during the month of March.

  • On the other hand, countries such as South Korea, Sweden, Japan and Belarus registered the least amount of change in non-residential mobility, consistent with lighter or non existent lock-down measures. For example, there was even a +25% increase in park visits from baseline for the case of Denmark, South Korea and Belarus. It is perhaps interesting to note that Singapore, while had no lock-down, still registered a marked decrease in activity in transit stations as well as retail & recreation.


Table 1: Changes in community mobility across countries compared with COVID-19 cases and deaths [29 Mar from baseline 16 Feb]


Table 2: Changes in community mobility across countries compared with COVID-19 cases and deaths [5 April from baseline 23 Feb]


Update 16 April: Added Apple mobility data from baseline date 13 January 2020, up to 13 April 2020

Notes & discussion:

  • Source datasets: https://www.apple.com/covid19/mobility. Data source is from usage of Apple Maps so may not be fully representative of each countries' population The report covers three activity types: walking, driving and in transit, and provides granular city level tracking with daily data (unlike Google)

  • Trendlines generally show a very clear 'reverse logistic curve' (flipped along the x-axis), consistent with assumptions we make on transmission factor reduction taking 3 phases (initial growth, taper reduction, and eventual residual transmission - see our article here). In general, the data is consistent with Google data, showing varied levels of stringency existing from country to country, but close agreement within quite a narrow band save for a few countries

  • Interestingly, countries like Singapore and South Korea in particularly, as well as Malaysia, Philippines and Thailand show a distinct reduction in mobility even as early as early to mid February. This is consistent with our thoughts on early awareness here, and is a credible reason why we think these countries may have been better prepared. Meanwhile, countries like Japan and Sweden show much less reduction in mobility, consistent with their policy of no/light lock-downs


Figure 1-3: Raw data (13 January - 13 April 2020), multiple mobility types


Figure 4 & 5: 7-day smoothed datasets with focus on Southeast Asian countries - driving and walking mobilities




Cluster deep dive analysis and summary

For a more detailed comparison, several clusters were explored further. Data used was the change in mobility from baseline date 16 Feb, to 29 March.

  1. Southeast Asian countries (Malaysia, Thailand, Singapore etc.) + Australia / New Zealand

  2. Countries with no or minimal lock-down measures in place

  3. Countries hardest hit by COVID-19 deaths

  4. The 50 states of the United States


A) Southeast Asian countries + Australia / New Zealand

  1. Singapore appears the most relaxed in its control measures, aligned to their policy of no lock-downs, with most activities only -(10-20%) down. Australia also appears fairly relaxed in this regard with park activities for example still only -30% down from baseline levels.

  2. Malaysia, Philippines, and India appear to have some of the most stringent measures in place. Across the board non residential activities were down -(50-90%) over this period. It is perhaps a tremendous feat for a country the size of India to reach these levels of activity reduction in such a short time. Among these countries, New Zealand has been the most stringent with multiple activities such as retail, parks and transit stations all down -80% or more.

  3. For Indonesia, Vietnam and Thailand the change in workplace activity was only -15%, -20% and -21% fown respectively, while the same figure was at least -30% for all other countries in this cluster. For comparison Malaysia, New Zealand and Philippines registered reductions of -52%, -54% and -54% respectively.


Figure 2: % changes in activities across Southeast Asia and NZ countries


B) Countries with no or minimal lock-down measures in place

  1. South Korea, Sweden and Belarus register the lowest changes in activities since baseline. This is consistent with there being no lock-downs. Sweden and Belarus namely have totally resisted any such measures; in fact the Belarusian President has outright rejected any plans for lockdowns in the country.

  2. In Brazil, despite no lockdown policy its population has clearly taken steps to dramatically reduce mobility in activities such as retail, transit stations, and going to work. Yes, the population decided to lock themselves down in absence of any strong policy direction from their government. The Brazilian President has been cited saying that COVID-19 is no more than a 'little flu'.

  3. In the middle of the road are Singapore and Japan with some reduction in activity but not as drastic; both countries coincidentally have since put in place harder control measures for social distancing within the past week (as at 14 April) - suggesting that perhaps their previous stances were not stringent enough. Regardless the reduction in mobility is only down -10% for most non residential activities.


Figure 3: % changes in activities across countries with low / no lock-down policies in place


C) Countries hardest hit by COVID-19 deaths

  1. There is no question here, countries like Italy, Spain, France and Belgium are on the most stringent lockdowns, having faced the threat of 500-1000 deaths every day during this period.

  2. The UK, Switzerland, and Germany had severely reduced retail activity, but still showed reasonably high levels of mobility in parks compared to the previous group.

  3. Of all these countries, the US seems the most lax, psrticularly as thereappears to be inconsistent restrictions from state to state (see next section)

Figure 4: % changes in activities across countries hard-hit by COVID-19 deaths.


D) The 50 states of the United States

  1. There is a distinct reduction in retail and workplaces ranging from -30% to -60% from baseline levels. Transit hubs are down by almost -80% in some states.

  2. Hard hit states like New York and New Jersey seem to be placing more stringent control against retail, transportation and even park use.

  3. Meanwhile, Ohio, South Dakota, and Nebraska amongst others, have surged in park use since the baseline date.


Discussion

  1. Clearly, COVID-19 related policy actions such as lock-downs, social distancing and movement control orders have greatly reduced mobility across a wide range of countries. Reduction in retail & recreation as well as transit station activities have been very distinct as countries avoid congregating large public crowds - given this tends to be a strong vector for COVID-19 transmission. Grocery & pharmacy activity follows next, and lastly workplaces. It is interesting to note that while by 5th April workplaces registered negative mobility across the board, for some countries like Belarus, Singapore, Japan, Sweden and South Korea this reduction ranged from just -9% to -13%.

  2. As we have seen through this analysis, the implementation of such controls is not necessarily consistent from country to country. While headline policies are similar; i.e. business closures, school closures, restrictions on movement outdoors, and so on, in reality the reduction in movement can vary quite a bit across different countries. What is consistent however, is how countries without lock-downs in place have managed to keep mobility relatively high particularly to workplaces, and in retail & recreation. This insight is perhaps crucial for countries considering a loosening of their control measures over the coming weeks and months to help revive their economies.

  3. It is curious to see how countries like the US are taking a wide range of control stringency across states. While retail and workplaces by and large have seen a reduced mobility of -10% or more, grocery & pharmacy as well as transit stations mobility remain high, and park visits have increased dramatically over the period. Time will tell whether this strategy yields a positive outcome; so far states like New York, New Jersey and Michigan have been hard hit, whereas some other states only report a small number of cases, e.g. Alaska, Nebraska, North Dakota.


Read more in Part II of this article


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