Fertility decline in the later phase of the COVID-19 pandemic: The role of policy interventions, vaccination programmes, and economic uncertainty
Notice bibliographique
Résumé
Abstract BACKGROUND During the COVID-19 pandemic, birth rates in most higher-income countries first briefly declined and then shortly recovered, showing no common trends afterwards until early 2022, when they unexpectedly dropped. STUDY FOCUS We analyse monthly changes in total fertility rates in higher-income countries during the COVID-19 pandemic, with a special focus on 2022, when birth rates declined in most countries. We consider three broader sets of explanatory factors: economic uncertainty, policy interventions restricting mobility and social activities outside the home, and the role of vaccination programmes. STUDY DESIGN, DATA This study uses population-wide data on monthly total fertility rates adjusted for seasonality and calendar effects provided in the Human Fertility Database (HFD, 2023). Births taking place between November 2020 and October 2022 correspond to conceptions occurring between February 2020 and January 2022, i.e., after the onset of the pandemic but prior to the Russian invasion of Ukraine. The data cover 26 countries, including 21 countries in Europe, the United States, Canada, Israel, Japan and the Republic of Korea. METHODS First, we provide a descriptive analysis of the monthly changes in the total fertility rate (TFR). Second, we estimate the effects of the explanatory factors on the observed fertility swings using linear fixed effects (within) regression models. MAIN RESULTS We find that birth trends during the COVID-19 pandemic were associated with economic uncertainty, as measured by increased inflation, the stringency of pandemic policy interventions, and the progression of the COVID-19 vaccination campaign, whereas unemployment did not show any link to fertility during the pandemic. LIMITATIONS, REASONS FOR CAUTION Our research is restricted to higher-income countries with relatively strong social support policies provided by the government as well as wide access to modern contraception. Our data do not allow analysing fertility trends by key characteristics, such as age, birth order and social status. WIDER IMPLICATIONS OF THE FINDINGS This is the first multi-country study of the drivers of birth trends in a later phase of the COVID-19 pandemic. In the past, periods following epidemics and health crises were typically associated with a recovery in fertility. In contrast, our results show that the gradual phasing out of pandemic containment measures, allowing increased mobility and a return to more normal work and social life, contributed to declining birth rates in most countries. In addition, our analysis indicates that some women avoided pregnancy during the initial vaccination roll-out.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».