Abstract
With a WHO-estimated excess mortality burden of 14.9 million over the course of 2020 and 2021, the COVID-19 pandemic has had a major human impact so far. It has also affected a range of disciplines, systems and practices from mathematical modelling to behavioural sciences, pharmaceutical development to health system management. This article explores these developments and, to set the scene, this paper summarizes the global epidemiology of COVID-19 from January 2020 to June 2021 and considers some potential drivers of variation.
Introduction
The pandemic has evolved differently in every nation and region of the world, but some broad phases can be distinguished: first, early emergence in China and rising rates in Europe and North America in early 2020; second, wider global spread, emergence of variants and implementation of vaccines and therapeutics worldwide in later 2020 and 2021.1
Global epidemiology of COVID-19
Early emergence and initial global spread
SARs-CoV-2 was first identified following a pneumonia outbreak of unexplained origin that was reported in Wuhan, China, on 31 December 2019.2–5 After initial entry into the human population, the virus rapidly spread and by mid-January 2020 cases of COVID-19 were rising exponentially in Wuhan and spreading to other Chinese provinces and East Asian countries; Thailand saw its first case as early as 13 January 2020.6–8 In response to this rapid spread and early indications on the nature of the disease, the WHO declared a Public Health Emergency of International Concern on 30 January 2020.9
Alongside early responses to the epidemic, there were major global scientific efforts, particularly in China, to gather important evidence. For example, initial case series with biological sampling and laboratory-based characterization helped assess host–virus interactions and virus biology, early sequencing enabled the rapid development of a PCR test, and epidemiological studies helped explore transmission dynamics and disease severity.8–14 Existing research and development infrastructure and pathways were built on to identify new and repurposed pharmaceutical interventions (PIs), and to fast track safe and effective candidates, such as the RECOVERY platform trial in the UK, to test repurposed therapeutics for use against COVID-19.15
However, evidence on effective PIs took time to develop, and in the interim epidemiological studies and surveillance helped guide the predominant response to the epidemic in the first half of 2020: non-pharmaceutical interventions (NPIs). NPIs ranged from standard infection prevention and control practice such as case isolation or population-level advice on hand and environmental hygiene, to full-scale population ‘lockdowns’ with citizens confined to their homes, wide-ranging settings closures including schools and restrictions on public gatherings, in many cases for a number of months.16
Wuhan was the first to enter lockdown: from 24 January 2020, residents were confined to their homes and restrictions on outbound travel were not lifted until 8 April 2020.17 There is evidence that lockdowns were effective in reducing community transmission of COVID-19: one study estimated that, in the first week of the Wuhan lockdown, the effective reproduction number dropped from 3.5 to 1.2.18 There are potential social, economic and health costs associated with introducing such measures, although it is difficult to separate these from the counter-factual costs of high case rates in the event of not ‘locking down’.19
Several countries implemented travel restrictions in late January to avoid importations from areas known to have high transmission, although case ascertainment was not always sufficiently complete or rapid to give a full picture of importation risks, and this was complicated by non-specific symptoms and varying testing capacity worldwide.20 In the UK, for example, a genomic surveillance study later revealed several hundred incursions during February 2020 from areas not considered to be a high-case importation risk at the time.21
In February 2020, the epicentre began to shift to parts of the Middle East and Europe, then to parts of North America in March 2020 where phylogenetic analysis implicated early importations from Europe (Figures 1–6).23 Case, hospitalization and death rates from COVID-19 rapidly rose in these areas: Italy, for example, recorded 15 887 COVID-19 deaths less than 6 weeks after the first indigenous case was reported.24 In recognition of this global spread, on 11 March 2020 the WHO declared a pandemic.25 In response to rising case rates in these regions, a series of national lockdowns were implemented, not just in Europe and North America, but also across many regions with lower case rates; in March 2020 all regions of the world saw some form of mobility restrictions.26 As the pandemic spread to new populations, new evidence emerged on COVID-19, for example, highlighting obesity as a comorbidity.27
Figure 1.
Europe region. Under this WHO categorization of the European region, some non-independent territories (the Isle of Man, Jersey, Guernsey and Gibraltar) are listed in addition to the UK. Reproduced from WHO. Published figures showing new deaths reported to the WHO by week, per 1 million population, by WHO region.22 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figure 6.
Africa region. Reproduced from WHO. Published figures showing new deaths reported to the WHO by week, per 1 million population, by WHO region.22 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figure 2.
Americas region. Reproduced from WHO. Published figures showing new deaths reported to the WHO by week, per 1 million population, by WHO region.22 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figure 3.
Western Pacific region. Reproduced from WHO. Published figures showing new deaths reported to the WHO by week, per 1 million population, by WHO region.22 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figure 4.
South-East Asia region. Reproduced from WHO. Published figures showing new deaths reported to the WHO by week, per 1 million population, by WHO region.22 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figure 5.
Eastern-Mediterranean region. Reproduced from WHO. Published figures showing new deaths reported to the WHO by week, per 1 million population, by WHO region.22 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Wider global spread, emergence of variants and implementation of vaccines and therapeutics worldwide in later 2020 and 2021
In mid-2020, as the northern hemisphere reached summer, first waves receded across much of Europe and North America, with corresponding relaxation in NPIs. The Southern Hemisphere showed the opposite trend: in May 2020, the WHO declared South America the ‘new epicentre’ of the pandemic as Brazil, Argentina and Peru reported some of the highest death-per-capita rates globally. Brazil reported more than 1 million cases by 19 June 2020.28 Many countries in Africa, too, saw community transmission by June 2020, although reported rates were comparatively low. This was perhaps a true difference due to, for example, rapid early introduction of NPIs, relatively young populations in many nations, a hot and dry climate in many areas of the region; or a difference in reporting due to the varying scale of testing facilities and a relatively high proportion of asymptomatic cases in the region.26,29
Relaxation in travel and other restrictions during the European summer with increasing population mobility was followed by the emergence and subsequent spread of new and more transmissible variants. A second wave of infections linked to the more transmissible Alpha variant hit Europe and USA from October 2020 with the highest daily number of cases recorded in many countries between October 2020 and March 2021.23 In March to June 2021, the epicentre of the pandemic again shifted to South America and South Asia, in particular India, as the Delta variant established as the dominant strain globally.
Two PIs were key to reducing morbidity and mortality during second and subsequent waves of the pandemic. First, dexamethasone, which was extensively trialled in hospitalized patients during the first wave in the UK and approved for use just 6 months into the pandemic, significantly reduced morbidity and mortality in the most severely unwell hospitalized patients.30 Later in 2021, evidence began to emerge on more targeted drugs, such as small-molecule, directly acting antivirals and monoclonal antibodies that were provided for vulnerable groups and hospitalized patients during the third wave in the UK.
Second, rapid development and deployment of safe and effective vaccines during 2021 significantly reduced transmission and disease severity in countries with access and ability to distribute. By the end of 2021, more than 57% of the global population had received at least one dose of COVID-19 vaccine.31
In 2021 the combination of NPIs and large-scale vaccination campaigns meant that many countries exited their second wave by the end of May. The emergence of highly transmissible variants was mitigated by rising immunity (both infection- and vaccination-derived) and effective therapeutics, although continued intermittent waves were observed as new variants arose and established worldwide.
Significant global inequity in vaccine distribution, however, remains an important issue: in January, 2022, less than 10% of lower-middle income country populations had received a single dose of any COVID-19 vaccine, with uptake rates lower than 10% in many countries in Africa, and in Syria, Yemen, Papua New Guinea and Haiti.32
Global variation in pandemic impacts
There was considerable geographic and temporal variation in the global epidemiology of COVID-19 from January 2020 to June 2021, although this is often difficult to interpret due to differences in surveillance systems and methods of reporting worldwide.26 There are also a number of indirect health effects from the pandemic that such reporting may miss, such as unmet health needs due to pressures on health systems or health effects of pandemic responses.33
Therefore, we focus here on findings from WHO-modelled estimates of global all-cause excess mortality in 2020 and 2021, which in many cases are at odds with reported COVID-19 deaths (particularly in upper-middle- and lower-middle-income countries).34 The data supporting these models, of course, will not have been comparable across all countries and some effects may not be experienced for some time to come. Nevertheless, there are some important indications for global variation of pandemic effects. For example, global excess mortality fell below zero in early spring 2020, perhaps due to early public health interventions and population-level precautionary behaviours such as hand-washing that reduced not only COVID-19 but also other infectious disease risks (Figure 7).
Figure 7.
WHO-modelled estimates of global mean excess deaths (count), 2020–2021.35 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Looking to World Bank global income groups (Figures 8–12), modelled estimates show low-income countries collectively seeing the lowest excess mortality at just 0.64 million, perhaps as a consequence of younger populations.36 Higher-income countries also experienced relatively low excess mortality at 2.16 million, despite their generally older populations with a number of comorbidities for COVID-19. This could be a consequence of better healthcare access in higher-income settings, and the ability of populations to adhere to interventions such as lockdowns, although such summaries mask important variation within countries.37 Upper-middle-income countries had double the excess mortality of high-income at 4.24 million, with the highest mortality in autumn to winter 2021. Lower-middle-income countries collectively saw the highest excess mortality at 7.87 million, with a similar curve to South-East Asia showing a stark peak in spring 2021 coinciding with the spread of the Delta variant in the region.38
Figures 8.
Reproduced WHO figures showing modelled estimates of excess mortality by World Bank income bracket, 2020–2021.35 The chart has a baseline of zero, representing the number of deaths that should be expected on the basis of existing average mortality data from 2015 to 2019. The shaded area depicts the number of COVID-19 deaths that have been reported to WHO by countries. The lines depict the estimated excess mortality, dipping below zero when there is lower mortality than expected. This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figure 12.
WHO-modelled estimates for cumulative excess deaths (mean) by World Bank income bracket, 2020–2021.35 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figures 9.
Reproduced WHO figures showing modelled estimates of excess mortality by World Bank income bracket, 2020–2021.35 The chart has a baseline of zero, representing the number of deaths that should be expected on the basis of existing average mortality data from 2015 to 2019. The shaded area depicts the number of COVID-19 deaths that have been reported to WHO by countries. The lines depict the estimated excess mortality, dipping below zero when there is lower mortality than expected. This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figures 10.
Reproduced WHO figures showing modelled estimates of excess mortality by World Bank income bracket, 2020–2021.35 The chart has a baseline of zero, representing the number of deaths that should be expected on the basis of existing average mortality data from 2015 to 2019. The shaded area depicts the number of COVID-19 deaths that have been reported to WHO by countries. The lines depict the estimated excess mortality, dipping below zero when there is lower mortality than expected. This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figures 11.
Reproduced WHO figures showing modelled estimates of excess mortality by World Bank income bracket, 2020–2021.35 The chart has a baseline of zero, representing the number of deaths that should be expected on the basis of existing average mortality data from 2015 to 2019. The shaded area depicts the number of COVID-19 deaths that have been reported to WHO by countries. The lines depict the estimated excess mortality, dipping below zero when there is lower mortality than expected. This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Marked disparities in excess deaths are also evident across WHO regions: while South-East Asia saw nearly 6 million excess deaths, the Western Pacific region saw just 0.12 million (Figures 13–18).35 The Eastern Mediterranean and Africa similarly showed low excess mortality at 1.08 and 1.25 million, respectively with peaks in late spring 2020, winter 2020–21 and spring 2021, the latter two coinciding with the global spread of Alpha and Delta variants. Europe, with overall excess mortality at 3.25 million, saw a peak in autumn 2020 as the Alpha variant emerged, followed by rising excess mortality throughout 2021 with the establishment of the Delta and Omicron variants. Trends are more difficult to determine in the Americas, which show continually high excess mortality between three peaks in spring 2020, winter 2020–21 and autumn 2021—perhaps due to combining seasonal trends from the Northern and Southern Hemispheres.
Figures 13.
Reproduced WHO figures showing modelled estimates of excess mortality by WHO Region, 2020–2021.35 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figures 18.
Reproduced WHO figures showing modelled estimates of excess mortality by WHO Region, 2020–2021.35 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figures 14.
Reproduced WHO figures showing modelled estimates of excess mortality by WHO Region, 2020–2021.35 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figures 15.
Reproduced WHO figures showing modelled estimates of excess mortality by WHO Region, 2020–2021.35 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figures 16.
Reproduced WHO figures showing modelled estimates of excess mortality by WHO Region, 2020–2021.35 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Figures 17.
Reproduced WHO figures showing modelled estimates of excess mortality by WHO Region, 2020–2021.35 This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.
Discussion: possible drivers of global variation in pandemic impacts
There are several potential drivers of global variation in COVID-19 epidemiology. It is difficult (and likely misleading) to cite individual factors in causing variation. Instead, we set out here some global differences in populations at the outset of the pandemic, in the evolving epidemiology of the pandemic, and finally in interventions to reduce transmission and severe disease: all of which may have influenced global variation in pandemic impacts.
First, there were important differences between population demographics, health, living conditions, social norms and economic structures globally at the outset of the pandemic. For example, the spread of risk factors for severe COVID-19 such as age, obesity or immunosuppression varied globally.39,40 The built environment, population density and household structures (both size and intergenerational composition) also vary not only across regions but also within countries, and are important in COVID-19 transmission.41 Varying local climates may also influence transmission through both environmental stability of the SARS-CoV-2 virus and population behaviours such as mixing indoors during colder seasons.42 Health, public health and social care access and system resilience may also influence pandemic effects, although this is difficult to assess; across comparable high-income health systems, for example, ITU admission criteria and bed capacity varied in spring 2020 but ITU mortality rates were broadly similar at 35%–40%.43 Social and behavioural norms also vary worldwide, such as around physical proximity when socializing or masking when unwell, which influences both transmission and the policy options deemed acceptable to reduce it. Many social and behavioural norms adjusted in response to the pandemic itself, of course, so this is not a static question. Economic structures, too, can influence both transmission of COVID-19 and practicable responses to reduce it: high levels of digital employment, for example, can enable widespread working from home to reduce transmission.44
Second, epidemiological factors such as the spread of initial case importations, or the timing and location of variant establishment, were important in pandemic impacts. In the UK, for example, the arrival several hundred independent incursions in March 2020 probably contributed to the rapid rise in case rates seen that month.32
Finally, responses to the pandemic varied globally and this had important implications for pandemic effects, although it is difficult to quantify the impacts of individual interventions partly because of their variable implementation and definitions across different countries and the fact most countries implemented several interventions simultaneously. Lockdowns, for example, differed in length and intensity across the world, perhaps due to differences in the feasibility of intensive and long lockdowns in different societies and economies as well as strategic policy choices such as pursuit of ‘Zero COVID-19’.44 Variable implementation and targeting of travel restrictions, meanwhile, may have influenced early seeding and subsequent transmission, although the influence of travel restrictions in the longer term is disputed, particularly when community transmission has established.8,45 A number of other public health interventions—such as hand and environmental hygiene advice, requirements to wear masks or face coverings and physical distancing—which (particularly together) can work to reduce transmission, have also been implemented in very different ways globally with some countries requiring surgical masks in public spaces and others with no requirement for face coverings.46 It is difficult to assess what impact such variation may have had on the course of the pandemic globally, partly because of the dynamic relationships between local epidemiology, public responses and adjustments to interventions.
There is a clearer link, however, between the availability and uptake of PIs worldwide—particularly vaccines—and effects of the pandemic. Modelling has estimated that vaccination prevented 19.8 million (95% credible interval 19.1–20.4) deaths from COVID-19 across 185 countries and territories in the first year of implementation, representing an estimated global reduction of 63% in total deaths.35
Conclusion
There has been significant global variation in the epidemiology of, and responses to, the COVID-19 pandemic so far, and there remain important disparities globally that continue to influence the epidemiology of COVID-19, most notably vaccine availability. Different countries’ readiness and ability to respond to new infectious disease threats—whether SARS-CoV-2 variants or other pathogens—is of paramount importance, and will remain so as countries worldwide recover from pandemic impacts.
Acknowledgements
None.
Contributor Information
Polly Ashmore, Health Education England, Stewart House, 32 Russell Square, London WC1B 5DN, UK.
Emma Sherwood, Health Education England, Stewart House, 32 Russell Square, London WC1B 5DN, UK.
Funding
Open Access CC-BY-NC is sponsoring open access for this paper. This paper was published as part of a supplement financially supported by an educational grant from Roche Molecular Systems.
Transparency declarations
None to declare.
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