Importance of population-based longitudinal studies to understanding the impact of Covid-19
Bibliographic Data
| ID | 11175707 |
|---|---|
| Authors | Panayotes Demakakos (0000-0002-7663-2122, Department of Epidemiology and Public Health, University College London, London, WC1E 6BT, UK, corresponding author) |
| Year | 2021 |
| Volume | 75 |
| Issue | 9 |
| Pages | 815-816 |
| Publication date | 2021-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Epidemiology and Community Health (JOURNAL) |
| Journal identifiers | ISSN: 0143-005X • E-ISSN: 1470-2738 |
| Publisher | BMJ (PUBLISHER • GB) |
| DOI | 10.1136/jech-2021-217114 |
| PMID | 34031167 |
| OpenAlex | W3165021558 |
| Language | EN |
| Citations received | 3 |
| References cited | 8 |
High-quality population-based surveillance studies such as the COVID-19 Infection Survey and Real-time Assessment of Community Transmission Study primarily serve the purpose of generating timely and accurate estimates of the COVID-19 infection and transmission rates. However, describing the evolution of the COVID-19 pandemic is a different objective from understanding its multidimensional impact on people’s lives and describing the post-COVID-19 trajectories of the population. Surveillance studies can neither be used to study the COVID-19 period effect within life course and ageing perspectives nor be informative about a multitude of COVID-19 related impacts and implications beyond the short-term health impact. Against this backdrop, multidisciplinary population-based longitudinal studies can substantially add to our knowledge of the COVID-19 pandemic and its impact. In the UK, many population-based longitudinal studies have only recently incorporated serological tests and this impedes their ability to provide accurate estimates of COVID-19 status over the entire pandemic period. However, there are important dimensions of the COVID-19 pandemic that population-based longitudinal studies are well placed to study. Below I discuss some of these dimensions. The COVID-19 pandemic has short-term, medium-term and long-term implications. To fully understand them, one needs rich data that cover the COVID-19 period. They also need an appropriate pre-COVID-19 comparison basis, that is, data about how the population was doing before COVID-19. In the UK, several high-quality population-based longitudinal studies offer such data. For example, the English Longitudinal Study of Ageing (ELSA) has collected rich individual-level health, behavioural and social data from a representative sample aged ≥50 years over a period of 20 years, from 2002 to today. These data can be used to study the effect of
Coronavirus disease 2019 (COVID-19) · Disease · Environmental health · Infectious disease (medical specialty) · Longitudinal study · Pandemic · Population · Sociology · COVID-19 and healthcare impacts · COVID-19 epidemiological studies · Demography · Health disparities and outcomes · Medicine
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| Citations per year | 0.75 |
|---|---|
| Citation span | 2022 - 2023 (2) |
| Highly cited | No |