As the COVID-19 pandemic has developed, members of the research community have been working hard to understand and explain the various ways in which the virus is impacting society. The demographic community was no exception and members of the discipline have been sharing their knowledge with the general public. So what have we learned thus far and where do we go from here?
As part of the project ‘Post-Pandemic Populations. The Demographic Consequences of the COVID-19 Pandemic in Germany’, supported by the German Federal Ministry of Family, Seniors, Women and Youth, Population Europe hosted a High-Level Expert Meeting to discuss these questions. The meeting took place on 9 November 2020 with leading experts from the demography community in Europe and included: Valeria Bordone (Department of Sociology, University of Vienna), Maria Brandén (Department of Sociology, Stockholm University and Institute for Analytical Sociology, Linköping University), Giancarlo Camarda (Institut National d'Etudes Démographiques), Jennifer Dowd (Leverhulme Centre for Demographic Science, Department of Sociology, University of Oxford and Nuffield College), Christian Dudel (Max Planck Institute for Demographic Research), Albert Esteve Palós (Centre for Demographic Studies (CED) at the Autonomous University of Barcelona), Jane Falkingham OBE (ESRC Centre for Population Change; Faculty of Social Sciences, University of Southampton), Arun Frey (Department of Sociology, University of Oxford), Ilya Kashnitsky (Interdisciplinary Centre on Population Dynamics, University of Southern Denmark), Letizia Mencarini (Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University), Julia Mikolai (School of Geography and Sustainable Development and ESRC Centre for Population Change, University of St Andrews), Alessandra Minello (University of Florence) and Tomáš Sobotka (Vienna Institute of Demography / Wittgenstein Centre for Demography and Global Human Capital). Emily Lines (Max Planck Institute for Demographic Research / Population Europe) moderated the discussion.
Demographers’ Contribution During the Pandemic
Naturally, epidemiology and virology have moved to the centre stage during the pandemic. However, as several participants pointed out, not only has demography benefitted from the public’s attention shifting to wanting to understand the virus, but the public has also benefitted from demographers being able to share their knowledge at this critical time. Demographers provide an important perspective thanks to their unique, interdisciplinary background, enabling them to communicate with researchers from other fields. They are also interested in linking the micro- and macro-level, which is important as more data becomes available, and they can help interpret this data and identify the consequences of the pandemic in a rigorous and empirical manner.
An important distinction was made at the beginning of the meeting between formal demography and social demography. Early on in the pandemic, demographers began by analysing data related to formal demography to discuss the population level differences in the risks of COVID-19 spread. For example, this included papers about the importance of demographic composition, particularly age structures, to understand why certain countries were experiencing and expected to see larger effects from the outbreak than others. Age- and sex-specific mortality and morbidity trends and patterns were also discussed. With their expertise in data analysis, demographers were among the first to make calls for improved and comparable data, specifically to national statistics offices and public health authorities. One example given was the agreement by the Spanish statistical office to make improvements that will allow data to be entered digitally. This would mean data regarding an individual’s death could be submitted and become available the next day to researchers.
For the general public, the focus has been more about short-term consequences, such as the concern about the likelihood of becoming infected and, once infected, the risk of dying as a result of COVID-19 and the factors influencing it. Policymakers also continue to be most concerned about controlling the virus spread and reducing mortality – immediate, short-term goals. Funding agencies released calls for projects focused on COVID-19 research and much of the research being published was centred around the pandemic. This increase in attention made it possible for some demographers to publish their research in top journals, which are typically less open to publishing demographic research. Attention within the media also grew during this time, helping to spread demographic research among the public and potentially indirectly to policymakers. Overall, demographers were able to provide information about how to gather and compare data across countries, regions and populations related to COVID-19, the role of social networks in the spread of the virus, analysis of excess deaths, importance of one’s household structure and even the importance of wearing face masks.
In addition to being able to provide analyses and explanations about mortality and the spread of the virus, as truly interdisciplinary researchers, demographers are able to understand the future effects and long-term consequences of the pandemic. This includes social demography issues, such as how the pandemic is affecting family life, work-life balance, care needs and mental health, as well as research on the life course and what it means to be infected or affected by the virus. The interest of demographers in the broader consequences of the pandemic on excess mortality, fertility, family life and migration, and their long-term perspective makes them valuable in the evolving scientific debates on the on-going pandemic.
Where Improvements Need to be Made
Despite demographers becoming more recognised during the pandemic, it is uncertain to what extent their research results are directly influencing policy interventions. Demographers are competing with other researchers for the attention of policymakers, who are focused on reducing the number of COVID-19 cases, so epidemiologists and virologists are still the likely researchers they call on first. There was agreement that demographic research can be translated into policy and can have policy implications, but the key is making it clear to policymakers how the research can be used. Demographers need to look for ways to improve their communication and tailor their message to various audiences.
To do this, demographers should not shy away from their role of interpreting and analysing the data, especially since the implications of the findings are so far-reaching. Instead, they should take active steps to be included in the discussions and to have an influence on what happens. For example, demographers need to communicate that the effects of the pandemic are not just represented by deaths, but also there are many other short- and long-term health implications. More contact with researchers in other fields should be made, such as with the epidemiologists that are in touch with policymakers. By working with them, demographers can make sure demography-related issues are included in their analyses and passed along to policymakers.
Another important task for demographers and all researchers is to counteract the false information that is shared about the virus, particularly online. One specific example is the need to provide state-of-the-art evidence to prove that the argument ‘COVID-19 is just another flu’ is incorrect. Demographers should speak up to make sure the public is educated about the basic concepts of demography – which many people do not know – in order to combat the spread of this false narrative.
As the pandemic continues and with the chance of another pandemic at some point in the future, demographers should already look ahead towards creating a solid evidence base about what mitigation measures have and have not worked in addressing the COVID-19 pandemic, and what were their wider implications. This can include more cross-national and regional comparisons to learn what was successful in different countries. Research should also move towards looking at the indirect consequences of the pandemic as it might impact areas of life that are not solely health-related and may also affect those who were not directly affected by the virus. For example, this includes exploring the overall population’s mental health and well-being.
The COVID-19 pandemic is clearly the worst global public health crisis since the Spanish flu of 1918–19; it will have both short- and long-term implications. Most likely future demographic studies would have to routinely include a COVID-19 dummy variable, just like they do with World War II cohort. This data will be critical in studying, for example, children affected by school closures or women who left the workforce. Important and indicative research is still being published today about the 1918 pandemic, emphasising how important this data will be for many decades to come.
Demographers need to find ways to improve their communication with a variety of audiences to help spread information now about the various impacts of the pandemic on society. Policymakers in this situation are more likely to be politicians, who may not be as focused on the non-health impacts of the pandemic, but it needs to be made clear that there will be long-term consequences. Demographers and other researchers are not just arguing that their advice is best, but that there are a wide range of factors at play that need to be considered. Measures need to already be introduced that address these non-health and long-term consequences and demographers should be proactive in suggesting measures and making it clear that politicians should be addressing these issues now. A distinction also needs to be clearly made between developments that are caused by COVID-19 and that are based on other conditions, such as the population structure. One example from the meeting was the expected decline in the number of births in Italy next year, but this is not solely due to the pandemic. This is also closely related to the changing population structure in Italy.
The scientific conversation around COVID-19 is evolving to reflect how to live with the virus while continuing to protect the most vulnerable groups. This leads to a morally difficult debate on the trade-off between the loss of life versus the loss of one’s livelihood, a debate demographers should actively participate in. It will be important for demographers to lend their expertise of non-health-related impacts to the discussion so that the various aspects can be taken into consideration when designing new policies.
All participants recognised the contribution that has been made by demographers in understanding the impact of the pandemic. This work will be increasingly important to understand and address the long-term consequences of the pandemic and the needs from the pandemic arising from them. However, it is just as important that demographers make a greater effort to communicate their findings and how these findings could influence policy measures. They need to be more vocal in combating misinformation about the virus and conveying the non-health implications of this pandemic on society.
List of Selected Publications by the Participants
Aassve, A., Cavalli, N., Mencarini, L.,Plach, S. & Livi Bacci, M. (2020). The COVID-19 pandemic and human fertility. Science, 369(6502), 370-371.
Aburto, J.M., Kashyap, R., Scholey, J., Angus, C., Ermisch, J., Mills, M. and Dowd, J. B., 2020. Estimating the burden of COVID-19 on mortality, life expectancy and lifespan inequality in England and Wales: A population-level study. medRxiv.
Alwan, N. A., Burgess, R. A., Ashworth, S., Beale, R., Bhadelia, N., Bogaert, D., Dowd, J., Eckerle, I., Goldman, L. R., Greenhalgh, T. & Gurdasani, D. (2020). Scientific consensus on the COVID-19 pandemic: We need to act now. The Lancet, 396(10260), E71-E72.
Aradhya, S., Brandén, M., Drefahl, S., Obućina, O., Andersson, G., Rostila, M., Mussino, E. & Juárez, S. P. (2020). Lack of acculturation does not explain excess COVID-19 mortality among immigrants. A population-based cohort study. Stockholm Research Reports in Demography, 2020:44.
Arpino, B., Bordone, V. & Pasqualini, M. (2020). No clear association emerges between intergenerational relationships and COVID-19 fatality rates from macro-level analyses. Proceedings of the National Academy of Sciences, 117(32): 19116-19121.
Arpino, B., Bordone, V. & Pasqualini, M. (2020). Reply to Dowd et al.: Dangerous to overemphasize the importance of specific COVID-19 risk factors based on (unadjusted) macro-level analyses. Proceedings of the National Academy of Sciences, 117(42), 25977-25978.
Arpino, B., Pasqualini, M., Bordone, V. & Solé-Auró, A. (2020). Older people’s nonphysical contacts and depression during the COVID-19 lockdown. The Gerontologist, gnaa144.
Arpino, B., Pasqualini, M., Bordone, V. & Solé-Auró, A. (2020). Indirect consequences of COVID-19 on people’s lives. Findings from an on-line survey in France, Italy and Spain. SocArXiv.
Basellini, U., Alburez-Gutierrez, D., Del Fava, E., Perrotta, D., Bonetti, M., Camarda, C. G. & Zagheni, E. (2020). Linking excess mortality to Google mobility data during the COVID-19 pandemic in England and Wales. SocArXiv.
Basellini, U. & Camarda, C. G. (2020). Modelling COVID-19 mortality at the regional level in Italy. SocArXiv.
Battiston, P., Kashyap, R. & Rotondi, V. (2020). Trust in science and experts during the COVID-19 outbreak in Italy. OSF Preprints, Center for Open Science.
Billingsley, S., Brandén, M., Aradhya, S., Drefahl, S., Andersson, G., and Mussino, E. (2020). Deaths in the Frontline: Occupation-Specific COVID-19 Mortality Risks in Sweden. Stockholm Research Reports in Demography, 2020:36.
Block, P., Hoffman, M., Raabe, I. Dowd, J. B., Rahal, R., Kashyap, R. & Mills, M. C. (2020). Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world. Nature Human Behaviour, 4, 588–596.
Brandén, M. (2020). Förlust av familjemedlemmar i covid-19 – skillnader mellan sociodemografiska grupper och områden [The loss of family members in COVID-19 – differences between sociodemographic groups and areas]. Report 4 in the Delegation against Segregation (Delmos) series Segregation and COVID-19.
Brandén, M., Aradhya, S., Kolk, M., Härkönen, J., Drefahl, S., Malmberg, B., Rostila, M., Cederström, A., Andersson, G. & Mussino, E. (2020). Residential context and COVID-19 mortality among adults aged 70 years and older in Stockholm: a population-based, observational study using individual-level data. The Lancet Healthy Longevity, 1(2), e80-e88.
Bohk-Ewald, C., Dudel, C. & Myrskylä, M. (2020): A Demographic Scaling Model for Estimating the Total Number of COVID-19 Infections. International Journal of Epidemiology: forthcoming.
Drefahl, S., Wallace, M., Mussino, E., Aradhya, S., Kolk, M., Brandén, M., Malmberg, B. & Andersson, G. (2020). A population-based cohort study of socio-demographic risk factors for COVID-19 deaths in Sweden. Nature communications, 11(1), 1-7.
Dowd, J. B., Andriano, L., Brazel, D. M., Rotondi, V., Block, P., Ding, X. & Mills, M. C. (2020). Reply to Nepomuceno et al.: A renewed call for detailed social and demographic COVID-19 data from all countries. Proceedings of the National Academy of Sciences, 117(25), 13884-13885.
Dowd, J. B., Andriano, L., Brazel, D. M., Rotondi, V., Block, P., Ding, X., Liu, Y. & Mills, M. C. (2020). Demographic science aids in understanding the spread and fatality rates of COVID-19. Proceedings of the National Academy of Sciences, 117(18), 9696-9698.
Dowd, J. B., Block, P., Rotondi, V., Mills, M.C. (2020). Dangerous to claim 'no clear association' between intergenerational relationships and COVID-19. Proceedings of the National Academy of Sciences, 117(42), 25975-25976.
Dudel, C., Riffe, T., Acosta, E., van Raalte, A. & Myrskylä, M. (2020). Monitoring Trends and Differences in COVID-19 Case Fatality Rates Using Decomposition Methods: Contributions of age structure and age-specific fatality. PLoS ONE 15: e0238904.
Engzell, P., Frey, A. & Verhagen, M. D. (2020, October 29). Learning Inequality During the Covid-19 Pandemic. SocArXiv.
Esteve, A., Permanyer, I., Boertien, D. & Vaupel, J. (2020). National age and coresidence patterns shape COVID-19 vulnerability. Proceedings of the National Academy of Sciences, 117(28), 16118-16120.
Esteve, A., Permanyer, I. & Boertien, D. (2020). La vulnerabilidad de las provincias españolas a la covid-19 según su estructura por edad y de coresidencia: implicaciones para el (des)confinamiento. Perspectives Demogràfiques, 19: 1-4.
Garcia, J., Torres, C., Barbieri M., Cambois, E., Camarda, C. G., Caporali, A., Meslé, F., Poniakina, S. & Robine, J.-M. (2020). Differences in COVID-19 Mortality: the implications of imperfect and diverse data collections. Under revision.
Gaye, B., Khoury, S., Cene, C. W., Kingue, S., N’Guetta, R., Lassale, C., Baldé, D., Diop, I. B., Dowd, J. B., Mills, M. C. & Jouven, X. (2020). Sociodemographic and epidemiological considerations of Africa’s COVID-19 response: What is the possible pandemic course? Nature Medicine, 26, 996–999.
Goldstein, J. R., & Atherwood, S. (2020). Improved measurement of racial/ethnic disparities in COVID-19 mortality in the United States. MedRxiv.
Goldstein, J. R. & Lee, R. D. (2020). Demographic Perspectives on Mortality of Covid-19 and Other Epidemics (Working Paper No. 27043; Working Paper Series). National Bureau of Economic Research.
Heuveline, P. (2020). The Mean Unfulfilled Lifespan (MUL): A New Indicator of a Disease Impact on the Individual Lifespan. MedRxiv.
Kashnitsky, I. & Aburto, J. M. (2020). COVID-19 in unequally ageing European regions. World Development, 136, 105170.
Medford, A. & Trias-Llimós, S. (2020). Population age structure only partially explains the large number of COVID-19 deaths at the oldest ages. Demographic Research, 43(19), 533–544.
Mikolai, J., Keenan, K. & Kulu, H. (2020). Intersecting household-level health and socio-economic vulnerabilities and the COVID-19 crisis: An analysis from the UK. SSM – Population Health 12: 100628.
Rostila, M., Cederström, A., Wallace, M., Brandén, M., Malmberg, B. & Andersson, G. (2020). Disparities in Covid-19 Deaths by Country of Birth in Stockholm, Sweden: A Total Population Based Cohort Study. Stockholm Research Reports in Demography, 2020:39.
Sobotka, T., Brzozowska, Z., Muttarak, R., Zeman, K., and di Lego, V. (2020). Age, gender and COVID-19 infections. medRxiv.
Trias-Llimós, S., & Bilal, U. (2020). Impact of the COVID-19 pandemic on life expectancy in Madrid (Spain). Journal of Public Health, 42(3), 635–636.
Trias-Llimós, S., Riffe, T. & Bilal, U. (2020). Monitoring life expectancy levels during the COVID-19 pandemic: Example of the unequal impact of the first wave on Spanish regions. PLoS ONE, 15(11), e0241952.
Verdery, A. M., Newmyer, L., Wagner, B. & Margolis, R. (2020). National Profiles of Coronavirus Disease – 2019 Mortality Risks by Age Structure and Preexisting Health Conditions. The Gerontologist, gnaa152.
Verhagen, M. D., Brazel, D. M., Dowd, J. B., Kashnitsky, I. & Mills, M. C. (2020). Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales. BMC medicine, 18(1), 1-11.