/COVID-19 in Mauritius and other tourist paradises

COVID-19 in Mauritius and other tourist paradises

The COVID-19 pandemic brings new information every day (e.g. Helsinki Graduate School of Economics Situation Room 2020), and the factors contributing to the large differences in trajectories are the subject of intense investigation. This column summarises findings from our recent study (Melo et al. 2020) where we analyse island states, given the little attention they have received so far. The Mauritian case is covered in some detail, which is then compared with 23 other island states with a population over 100,000 in the Our World in Data (OWD) database. The sharing of common characteristics across islands is a first-pass crude attempt at ‘apple vs. apple’ comparisons.  Since several islands do not have any active cases currently, this is a progress report. We show that islands that acted early, taking tough lockdowns with relatively long containment periods, have exited recently.

The ‘stringency corridor’ in island economies

The COVID-19 pathogen has caught most countries by surprise, not giving them enough time to conduct universal testing (as carried out by Iceland, which is one of the islands in our sample) or random testing. Either approach would have helped separate those infected or suspected, allowing others to continue working. Even with a ramping up of testing, this is still not the case currently. The rapid spread has overloaded many healthcare systems. For island states most often hit later, the choice was between a strict immediate lockdown (the case of Mauritius) and a more progressive lockdown as cases evolved, in order to build immunity. Under both strategies, the countries face a double challenge: the health constraint, which relates to how hard and how long to press on the brake to prevent overload of the healthcare system, and the wealth constraint, which is also related to how long and how hard to shut down the economy. These constraints place economies on a narrow ‘stringency corridor’ (Baldwin 2020) that has become more difficult to hold as weeks of public health and social measures go by.

Island economies are often small —so less diversified — and geographically isolated. Small markets mean the share of trade in GDP is high. Climatic conditions contribute to tourism, which contributes heavily to overall GDP — often in the 20-30% range, at times reaching over 50%. On the supply side, for a given infection rate, the share of jobs that can be carried out from home is lower than in more diversified economies. Moreover, the more concentrated production structure gives the economy less resilience when production activities resume post-confinement. On the demand side, even with well-designed policies — including a credible virus-free environment — jump-starting tourism is largely beyond national control. All these factors mean that the double supply and demand pandemic shock is felt with extreme intensity on islands.

Fortunately, island economies are also blessed with an advantage in responding to pandemic shocks: it is easier to enforce confinement policies in these countries. Their geographical isolation combined with the small area prove useful characteristics when it comes to closing the borders.1  Tolerance for a longer period of reduced activity is also easier to sell politically since demand for tourism-related services would be nil during the exit of confinement policies and there would be no pressure from the hotel industry to re-open business. Also, hotels in tourist destinations are relatively pleasant environments for quarantine, even if those in quarantine resent being confined to their rooms.  

Notwithstanding the precarity of health system calling for a flattening of the epidemiological curve to prevent overload, warnings have been issued about the efficacy of strict lockdowns, especially in developing countries. Loayza (2020) provides case evidence against lockdowns and argues that they are unlikely to work in the mega-cities of the developing world. Lockdowns may also lead to the virus spreading to rural areas as migrant workers flee the cities. Additionally, if they are strict and long-lasting they exacerbate economic losses. In short, they do not meet what Baldwin (2020) calls the double imperative: the health constraint and the wealth constraint.

The Mauritian case

Mauritius followed the ‘Act fast. Act now. Keep the lights on’ approach rather than the act slow immunisation strategy followed by Sweden and the UK. The health authorities followed the contact-tracing route. Figure 1 shows no active cases as of 17 May with the last reported case on 25 April. Tests have been carried out on approximately 17% of the population, ranking Mauritius in the top 7% in the OWD database and first in Africa with respect to COVID testing. With 10 deaths, the naïve case fatality rate (CFR), a standard estimate of the lethality of a pandemic, is 3%. Notably, the low death rate during the first quarter was helped by the lower death toll from road accidents.2

Figure 1 Timeline of confinement measures

Source: Authors’ compilation from BeSafeMoris and press announcements, 2020

Notes: (1) WAP: Work Access Permit; (2) WFH: Work From Home; (3) WAS: Wage Assistance Scheme. The scheme targets businesses in the private sector and their employees drawing a monthly basic wage of up to Rs 50,000; (4) SEAS: Self Employed Assistance Scheme. The aim of the scheme is to assist self-employed persons who have suffered a loss in revenue as a consequence of the lockdown.; (5) *Customers are allowed to enter supermarkets as per alphabetical order on specific days. They must have their national identity cards and wear masks. Basic essential products are also limited to three units per person. 

Health-related measures

Figure 1 shows the timeline of the containment measures. Screening starting on 22 January 2020, with suspected tourists sent to quarantine. These precautionary measures must have contributed to a relatively small pool of cases when the first three cases were announced on 18 March. Two days later, a strict sanitary lockdown (only health and essential workers could leave their residences) was put in place for 7 days with a reopening of supermarkets under strict sanitary conditions from 30 March. This lockdown was extended twice until 1 June with the re-opening of the economy in phases, starting with construction and government services on 15 May. Daily progress reports by the cabinet and health officials were aired every evening in three languages (creole, French and Hindi). People were warned of severe penalties for breaking the confinement measures and issuing false news.

Wealth-related measures

Daily press communiques by the COVID National Communication Committee and reports helped calm the population. At the start of the lockdown, the government announced an immediate distribution of 35,000 food packs to families in poverty (as per the Social Register of Mauritius), the disabled and at home residents.  All labour contracts set to expire this year were extended through to December 2020. Wage and income support measures were introduced ranging from  $125 to $315 for workers with salaries below $625 (15 days salary basis) per month, and  $315 for those in the  $625-1300 range (through the Government Wage Assistance Scheme). Workers earning over  $1300 received no support.  Self-employed individuals as well as trade persons in both the formal and the informal sectors received financial support of $130 (equivalent to half of the monthly minimum wage) through the Self Employed Assistance Scheme (SEAC). These measures were extended until 31 May.  The government also announced about 1.6% of GDP increase in spending along with extra tax deductions for SMEs.

Mauritius does not have unemployment insurance, but free health coverage is universal and all citizens over 60 receive a pension of $300 per month. These social support measures compare favourably with those provided in higher-income countries.

Even though Mauritius was hit hard by a fall in tourism receipts, estimated to reduce the GDP by over 10% for 2020, it was successful in eliminating the spread in 40 days. The government acted early and decisively at the outset. Stringent policies aided by geographical factors contributed to meeting the health constraint. Substantial income support contributed to meeting the wealth constraint, keeping the country in the narrow ‘stringency corridor’.

How unique is Mauritius? Comparisons with other islands

Figures 2 and 3 compare the performance at containing the spread across the 24 islands from the start of the first declared case in each country up until 17 May. Figure 2 reports the total number of cases per million for each country along with estimates of total tests and the evolution of a composite ordinal Stringency Index (SI) capturing the severity and geographical coverage of containment and closure measures (the Oxford COVID-19 Government Response Tracker). Figure 3 reports on a crude estimate of the case fatality rate (CFR), which is likely to be an overestimate because of low testing resulting in low reported cases.  At best, available data allow for caveat-ridden comparisons.

Take two examples of diversity. Bahrain, where the first case was reported on 24 February, has the second highest per capita income in the group but the third highest case rate. This could be because it implemented large scale testing: it has the second highest test rate  (Figure 2). Bahrain also has the lowest CFR in the sample (Figure 3), but is still far from closing (recovered plus deaths stand at around 45% of total cases). Sri Lanka, which reported its first case on 27 January, is the most populous. It registers virtually the lowest fatality rate, but like Comoros, Fiji, Guinea-Bissau, Haiti, and Sao Tomé, it has no data on tests nor a value for the SI.

Next, we compare ‘successful’ countries as revealed in the data. Fiji has 18 reported cases with no fatalities but lacks information on testing or containment measures. Iceland, an early reporter, has the highest case rate per million. With a CFR of 0.5% (Figure 3), it is among the most successful. Iceland succeeded with the combination of the highest testing rate and relatively loose containment measures. It therefore has the lowest SI score after two months because universal testing allowed them to effectively isolate the infected fraction of the population.  Ireland, which has the same population as New Zealand, reported its first case one month before New Zealand. However, Ireland now has the second highest case rate while New Zealand’s is among the lowest. Relatively greater geographical isolation and stricter confinement measures starting around the fourth week should have contributed to the lower number of cases and the lower CFR in New Zealand (Figure 3). South Cyprus, with a relatively higher case rate, carried out extensive testing and adopted relatively stringent containment measures early on. 

Incomplete data limit the lessons from these early comparisons. No regularities appear across the islands beyond the observation that low testing rates are generally associated with a low case rate. With the exception of Mauritius, the SI takes on higher values over the weeks. Figure 2 shows no correlation between the current case rates and population. Neither is there a correlation between case rates and per capita GDP; nor one with the number of days since the date of the first reported case. However, the correlation between the case rate and population density (not reported here) is 0.6.

Figure 2 Anatomy of COVID-19 in island nations (population>100,000)

Source: Authors’ compilation of data for 24 islands from Our World in Data (OWD), Worldometer and Oxford COVID-19 Government Response Tracker, 2020. 

Notes: (1) Left-hand axs: total number of confirmed COVID-19 cases per million as of May 15 and (2) total cummulative tests per 10,000. The data is not strictly comparable because of different reporting and multiple tests per person. Data on the number of COVID-19 tests effected is not available for Comoros. The cummulative COVID-19 tests per 10,000 are on the very low side for Suriname, Sao Tome and Principe, Guinea Bissau and Haiti. (3) Right-hand axis: Stringency index (range 0-100: higher values indicate stricter confinement measures). Data taken one week after first reported COVID-19 case in OWD. (4) Data on Stringency Index (SI) is not available for Bahamas, Fiji, Guinea Bissau, Haiti, Maldives, Malta, Sao Tome and Principe and Sri Lanka. (5) First COVID-19 case for each country is included at the top of each bar chart.  (6) X-axis should be read as: (population in thousand), country code, GDP per capita in thousand (USD). For example: (393) BHS (28) means Bahamas has a population of around 393,300 and a GDP per capita of around USD 28,000 as at 2018.  (7) Country codes and names: BHS – Bahamas; BHR – Bahrain; BRB -Barbados; CPV  -Cape Verde; COM – Comoros; CYP – Cyprus (excluding North); DOM – Dominican Republic; FJI – Fiji; GNB – Guinea Bissau; HTI – Haiti: ICE – Iceland; IRE – Ireland; JAM – Jamaica; MDV – Maldives; MLT – Malta; MUS – Mauritius; NZL – New Zealand; PRI – Puerto Rico; STP – Sao Tome and Principe; SGP – Singapore; LKA – Sri Lanka; SUR – Suriname; TTO – Trinidad and Tobago

Figure 3 also shows a cluster of countries in the range of 10-20 reported deaths. This suggests that these late comers have managed to contain the spread of the pandemic relatively well. The figure also shows a large range of CFR estimates. Even if we consider only the estimates for countries with more extensive testing and hence more reliable estimates (Iceland, Cyprus Malta, New Zealand, Mauritius, and Singapore), there is still a very large range of CFR from 0.25% to 3%. 

Figure 3 Total confirmed COVID-19 deaths vs. cases, 17 May 2020

Source: Authors’ Compilation from Our World in Data, 2020

Notes:  Fiji is missing. The number of confirmed cases is lower than the number of total cases. The main reason for this is limited testing. The grey lines show the corresponding case fatality rates (CFR, the ratio between confirmed deaths and confirmed caes). 

The display of the epidemiological trajectories (see figure 5 in the paper) shows two groups of countries as of 16 May. Group one, call it A, have 100% of their cases closed (Suriname, Mauritius, Trinidad and Tobago, Iceland, and New Zealand) or above 80% closed (Ireland, Barbados, Malta, Fiji, Cuba, Sri Lanka). The rest in group B are still active.

Figure 4 plots the value of the SI index against the average reduction in mobility one month after the first reported case.  The correlation between the two indices is significant at 1% with a value of -0.93. Tough containment measures are reflected in sharp reductions in mobility. The successful countries had the most extensive containment policies reflected in reduction in mobility in the 40%- 60% range below the average during the month of January (vehicle circulation in the US in this spring is estimated to have fallen by 40%). Bahrain stands out as having lax containment policies while the data for Singapore and Sri Lanka is for end February, before the recent surge in cases that led Sri Lanka to adopt stricter containment policies.

Figure 4 Stringency Index and average mobility reduction one month after first reported COVID-19 case



Source: authors’ caculation from Oxford COVID-19 Government Response Tracker, 2020 and Google Mobility Report, 2020. Data on mobility is the average change in mobility from the reference period which is the average over 3 January – 3 February. SI index ranges from 0 to 100. Higher values indicate stronger confirmnment measures. 
Notes: (1) Data on mobility for Singapore and Sri Lanka is taken for the six weeks after the first COVID case. (2) Data on Stringency Index (SI) is not available for Bahamas, Fiji, Guinea Bissau, Haiti, Maldives, Malta and Sao Tome and Principe. (3) Data on mobility is not available for Bahamas, Iceland, Maldives, Cuba, Cyprus, Suriname. 

In sum, in spite of many common characteristics, the group of islands covered here followed different containment strategies to avoid a run on their health care systems. Among the more successful countries, Mauritius followed a strict 40-day long confinement strategy early on accompanied by substantial income support. This combination kept the country in the stringency corridor. New Zealand, Suriname, and Trinidad and Tobago succeeded by following a more progressive containment path. Others usually followed less aggressive containment strategies.


Baldwin, R (2020a), “Remobilising the Workforce for ‘World War Covid’: A Two Imperatives Approach”, VoxEU.org, 13 April.

Chapelle, G (2020), “1918 Influenza in the US”, Covid Economics Volume 8, London: CEPR Press.

Chicala, S, S Holland, E Mansur, N Zuller and A Yates (2020), “Expected Health Effects of Reduced Air Pollution from Covid-19 Social Distancing”, NBER Working Paper #27135.

Correia, S, S Luck and E Verner (2020) “Pandemics Depress the Economy, Public Health Interventions do not: Evidence from the 1918 Flu”, NBER Working Paper.

Hale, T, A Petherick, T Philips and S Webster (2020), “Variation in Government responses to COVID-19”, Blavatnik School of Government.

Helsinki Graduate School of Economics Situation Room (2020), “Real-time economic analysis of the COVID-19 crisis: Lessons from Finland“, VoxEU.org, 21 May. 

Jeensa, R and K Sukon (2020), “The Mauritian Response to Covid-19: Rapid bold Actions in the Right direction”, VoxEU.org, 9 May.

Melo, J. de, V. Tandrayen-Ragoobur and B. Seetanah (2020) “COVID-19 in Mauritius and other tourist paradises: a progress report”, Working Paper.

Lavezzo, E, E Franchin et al. (2020), “Suppression of Covid-19 Outbreak in the Municipality of Vo, Italy”, MedRxiv, preprint.

Loayza, N (2020), “Smart containment and mitigation measures to confront the COVID-19 pandemic: Tailoring the pandemic response to the realities of developing countries”, Worldbank.org, 7 April.


1 It is physically easier to impose checks in small islands with only one airport and one or two major ports. It is also easier administratively to limit circulation. For example in federal countries like Switzerland, the Federal council does not have the authority to prevent people to move across cantons. 

2 Over the Feb-April 2020, the average monthly death toll from road accidents was 3, considerably less than the 6-7- monthly death toll in 2019 and 2018 % (statistics-mauritius)  . In the US, vehicle travel in the Spring of 2020 is estimated to have fallen by 40%, reducing CO2 emissions by 19%. The improved air quality has been estimated to reduce health-related baseline deaths of 1500 by 25 (Cicala et al. 2020).

Original Source