Introduction

When the COVID-19 pandemic began in early 2020, speculation about the short- and long-term demographic effects of the health crisis—and measures taken to mitigate it—dominated headlines globally. Experts debated potential scenarios, including both significant declines and significant increases in birth rates, disruptions in health care access and use, and declines in life expectancy, among other possibilities. Until recently, however, the evidence around the pandemic’s impact on key demographic indicators has been limited.

In the 2022 World Population Data Sheet’s special focus on COVID-19, we explore the recently available evidence on the pandemic’s effects on births and deaths around the world. How did the COVID-19 pandemic, and government responses that limited social interactions and movements, affect the number of deaths? Did the pandemic shape access to health care, including family planning, or change couples’ fertility intentions in ways that increased or decreased births? Were all populations affected equally? Explore these questions to get a deeper understanding of the impact of the COVID-19 pandemic.

The Pandemic’s Influences on Fertility Are Mostly Limited and Temporary

In the COVID-19 pandemic’s early days, demographers proposed a range of scenarios for how it would impact fertility rates, from increases in births to decreases in births. The data now available show that the effects on fertility have, in fact, been generally limited.

Where an effect on fertility has been observed—primarily in high-income countries—it appears to be temporary. Data from countries such as Italy, Germany, and the United States demonstrate that births experienced a small decline in 2020 and rebounded or stabilized in 2021.

In low- and middle-income countries, data suggest the pandemic had little to no impact on fertility. Middle-income countries such as Costa Rica, South Africa, and Türkiye, where births were declining prior to the pandemic, continued to follow a similar trajectory in 2020 and 2021.

These largely modest and temporary impacts on fertility suggest trends from prior to the pandemic will most likely continue.

Births per 1,000 Population, 2018-2021
Number of births per 1,000 population

Sources: National Statistical Offices from listed countries.

Age and Education Highlight Variations in Vulnerability to Pandemic-Driven Disruptions in Family Planning Access and Use

Many health experts originally feared that the COVID-19 pandemic would significantly curtail family planning access and use, but data to date suggest these programs were resilient to disruptions. At the same time, population-level estimates showing sustained or even increased contraceptive use may mask groups of individuals who did not experience this same resiliency.

To gain a fuller picture of women’s vulnerability to disruptions in family planning services, we examined changes in contraceptive use and demand among women across different characteristics one year into the pandemic. Looking at how the changes differ across age groups and educational status among women who are at risk of pregnancy—meaning women who are fecund, sexually active, and not pregnant—provides insights on the pandemic’s impacts on family planning status in Burkina Faso and Kenya, two countries with longitudinal data available from prior to the pandemic and one year later.

Age

Among all women in Burkina Faso who had unmet need for family planning at the start of the pandemic, older women ages 35 to 49 were more likely to still have unmet need one year later compared with younger age groups. Among women initially using contraceptives, those ages 25 to 34 were less likely to still be using them a year later compared with women in other age groups.

Among the Burkinabé women in this age group who had stopped using family planning in the first year of the pandemic, a majority wanted to have a child within one year and had no need for family planning, but more than a quarter of them reported having unmet need.

Similarly, in Kenya, among women who had unmet need at the start of the pandemic, older women ages 35 to 49 were most likely to still have unmet need one year later. Younger women—ages 15 to 24 and ages 25 to 34—were more likely to have a change in fertility intentions and develop a need for contraception during the pandemic’s first year.

Women’s Family Planning Status by Age

Ages 35-49 | Using → Ages 35-49 | Using 40% Ages 25-34 | Using → Ages 25-34 | Using 31% Ages 15-24 | Using → Ages 15-24 | Using 34% Ages 15-24 | No Demand → Ages 15-24 | No Demand 18% Ages 25-34 | Unmet Need → Ages 25-34 | Unmet Need 12% Ages 25-34 | No Demand → Ages 25-34 | No Demand 12% Ages 35-49 | Unmet Need → Ages 35-49 | Unmet Need 12% Ages 25-34 | Using → Ages 25-34 | No Demand 9% Ages 25-34 | Unmet Need → Ages 25-34 | No Demand 9% Ages 25-34 | No Demand → Ages 25-34 | Using 9% Ages 35-49 | No Demand → Ages 35-49 | No Demand 9% Ages 25-34 | Unmet Need → Ages 25-34 | Using 8% Ages 35-49 | Unmet Need → Ages 35-49 | Using 9% Ages 25-34 | No Demand → Ages 25-34 | Unmet Need 7% Ages 35-49 | No Demand → Ages 35-49 | Unmet Need 9% Ages 15-24 | Unmet Need → Ages 15-24 | No Demand 9% Ages 15-24 | No Demand → Ages 15-24 | Unmet Need 9% Ages 15-24 | No Demand → Ages 15-24 | Using 8% Ages 15-24 | Unmet Need → Ages 15-24 | Using 7% Ages 35-49 | No Demand → Ages 35-49 | Using 7% Ages 15-24 | Unmet Need → Ages 15-24 | Unmet Need 7% Ages 15-24 | Using → Ages 15-24 | No Demand 7% Ages 35-49 | Using → Ages 35-49 | Unmet Need 5% Ages 35-49 | Using → Ages 35-49 | No Demand 5% Ages 25-34 | Using → Ages 25-34 | Unmet Need 4% Ages 35-49 | Unmet Need → Ages 35-49 | No Demand 4% Ages 15-24 | Using → Ages 15-24 | Unmet Need 4% Ages 15-24 | Using 359.38 Ages 15-24 | Using359 Ages 15-24 | Using 407.94 Ages 15-24 | Using408 Ages 15-24 | No Demand 283.58 Ages 15-24 | No Demand284 Ages 15-24 | Unmet Need 197.51 Ages 15-24 | Unmet Need198 Ages 15-24 | No Demand 278.90 Ages 15-24 | No Demand279 Ages 15-24 | Unmet Need 153.63 Ages 15-24 | Unmet Need154 Ages 35-49 | Unmet Need 227.86 Ages 35-49 | Unmet Need228 Ages 35-49 | No Demand 220.06 Ages 35-49 | No Demand220 Ages 35-49 | Using 444.45 Ages 35-49 | Using444 Ages 25-34 | Unmet Need 310.94 Ages 25-34 | Unmet Need311 Ages 25-34 | No Demand 298.83 Ages 25-34 | No Demand299 Ages 25-34 | Using 478.57 Ages 25-34 | Using479 Ages 25-34 | Unmet Need 249.56 Ages 25-34 | Unmet Need250 Ages 25-34 | No Demand 322.08 Ages 25-34 | No Demand322 Ages 25-34 | Using 516.70 Ages 25-34 | Using517 Ages 35-49 | Unmet Need 230.59 Ages 35-49 | Unmet Need231 Ages 35-49 | No Demand 163.60 Ages 35-49 | No Demand164 Ages 35-49 | Using 498.18 Ages 35-49 | Using498
Ages 25-34 | Using → Ages 25-34 | Using 68% Ages 35-49 | Using → Ages 35-49 | Using 71% Ages 15-24 | Using → Ages 15-24 | Using 64% Ages 25-34 | Unmet Need → Ages 25-34 | Using 7% Ages 35-49 | Unmet Need → Ages 35-49 | Using 9% Ages 25-34 | No Demand → Ages 25-34 | Using 5% Ages 15-24 | Unmet Need → Ages 15-24 | Using 9% Ages 25-34 | No Demand → Ages 25-34 | No Demand 5% Ages 35-49 | Unmet Need → Ages 35-49 | Unmet Need 6% Ages 25-34 | Using → Ages 25-34 | Unmet Need 4% Ages 35-49 | Using → Ages 35-49 | Unmet Need 5% Ages 15-24 | No Demand → Ages 15-24 | Using 6% Ages 25-34 | Unmet Need → Ages 25-34 | Unmet Need 3% Ages 25-34 | Using → Ages 25-34 | No Demand 3% Ages 15-24 | Unmet Need → Ages 15-24 | Unmet Need 5% Ages 15-24 | Using → Ages 15-24 | Unmet Need 4% Ages 25-34 | Unmet Need → Ages 25-34 | No Demand 2% Ages 15-24 | No Demand → Ages 15-24 | No Demand 4% Ages 15-24 | Using → Ages 15-24 | No Demand 4% Ages 35-49 | No Demand → Ages 35-49 | No Demand 3% Ages 35-49 | No Demand → Ages 35-49 | Using 3% Ages 25-34 | No Demand → Ages 25-34 | Unmet Need 2% Ages 35-49 | Using → Ages 35-49 | No Demand 2% Ages 15-24 | Unmet Need → Ages 15-24 | No Demand 2% Ages 35-49 | No Demand → Ages 35-49 | Unmet Need 1% Ages 35-49 | Unmet Need → Ages 35-49 | No Demand 1% Ages 15-24 | No Demand → Ages 15-24 | Unmet Need 1% Ages 15-24 | Using 650.91 Ages 15-24 | Using651 Ages 15-24 | Using 716.13 Ages 15-24 | Using716 Ages 15-24 | No Demand 106.12 Ages 15-24 | No Demand106 Ages 15-24 | Unmet Need 148.14 Ages 15-24 | Unmet Need148 Ages 15-24 | No Demand 90.80 Ages 15-24 | No Demand91 Ages 15-24 | Unmet Need 98.24 Ages 15-24 | Unmet Need98 Ages 25-34 | Using 1,186.22 Ages 25-34 | Using1,186 Ages 25-34 | Using 1,264.61 Ages 25-34 | Using1,265 Ages 25-34 | No Demand 193.76 Ages 25-34 | No Demand194 Ages 25-34 | Unmet Need 198.13 Ages 25-34 | Unmet Need198 Ages 25-34 | No Demand 172.12 Ages 25-34 | No Demand172 Ages 25-34 | Unmet Need 141.38 Ages 25-34 | Unmet Need141 Ages 35-49 | Using 960.94 Ages 35-49 | Using961 Ages 35-49 | Using 1,016.36 Ages 35-49 | Using1,016 Ages 35-49 | No Demand 85.35 Ages 35-49 | No Demand85 Ages 35-49 | No Demand 70.40 Ages 35-49 | No Demand70 Ages 35-49 | Unmet Need 186.57 Ages 35-49 | Unmet Need187 Ages 35-49 | Unmet Need 146.10 Ages 35-49 | Unmet Need146

Notes: Data from Burkina Faso are from two surveys conducted in February 2020 and March 2021. Data from Kenya are from two surveys conducted in December 2019 and December 2020. The sample size for the analysis is 2,830 in Burkina Faso and 3,940 in Kenya. Percentages of women in different family planning status categories may not sum to 100% for each age group due to rounding.
Source: Performance Monitoring for Action (PMA) family planning surveys phases 1 and 2 for Burkina Faso and Kenya.

Education Status

In Burkina Faso, women with no education or only primary school education were not only less likely to use contraception at the start of the COVID-19 pandemic but, if they were using contraception, they were also less likely to still be using it one year later compared with women who had more education. In addition, these women with less education who entered the pandemic with unmet need were more likely to still have that need unmet a year later compared with those who had more education.

In contrast, education made little difference among Kenyan women in whether they were using contraceptives both prior to the pandemic and one year later. However, education did have an impact on patterns of unmet need. Women with primary education or less who had unmet need at the start of the pandemic were less likely to be using contraception one year later compared with their peers who had more education.

When health system shocks like the COVID-19 pandemic occur, it is essential to ensure that women who may be more vulnerable to disruptions in access, such as those who are older and who have less education, are prioritized in efforts to address unmet need and sustain contraceptive services.

Women’s Family Planning Status by Education Status

Never Attended | Using → Never Attended | Using 30% Never Attended | No Demand → Never Attended | No Demand 14% Secondary School+ | Using → Secondary School+ | Using 53% Never Attended | Unmet Need → Never Attended | Unmet Need 13% Never Attended | No Demand → Never Attended | Unmet Need 10% Primary School | Using → Primary School | Using 33% Never Attended | Unmet Need → Never Attended | Using 8% Never Attended | No Demand → Never Attended | Using 8% Never Attended | Unmet Need → Never Attended | No Demand 7% Never Attended | Using → Never Attended | No Demand 6% Never Attended | Using → Never Attended | Unmet Need 4% Primary School | No Demand → Primary School | No Demand 11% Primary School | Unmet Need → Primary School | No Demand 10% Primary School | Unmet Need → Primary School | Unmet Need 9% Primary School | No Demand → Primary School | Using 9% Secondary School+ | No Demand → Secondary School+ | No Demand 10% Primary School | No Demand → Primary School | Unmet Need 8% Secondary School+ | Unmet Need → Secondary School+ | Using 9% Primary School | Using → Primary School | No Demand 8% Secondary School+ | Using → Secondary School+ | No Demand 9% Primary School | Unmet Need → Primary School | Using 7% Secondary School+ | No Demand → Secondary School+ | Using 7% Secondary School+ | Unmet Need → Secondary School+ | No Demand 5% Secondary School+ | Using → Secondary School+ | Unmet Need 4% Primary School | Using → Primary School | Unmet Need 4% Secondary School+ | No Demand → Secondary School+ | Unmet Need 2% Secondary School+ | Unmet Need → Secondary School+ | Unmet Need 2% Never Attended | Using 733.26 Never Attended | Using733 Never Attended | Using 833.80 Never Attended | Using834 Never Attended | No Demand 568.50 Never Attended | No Demand569 Never Attended | Unmet Need 520.40 Never Attended | Unmet Need520 Never Attended | No Demand 503.60 Never Attended | No Demand504 Never Attended | Unmet Need 484.76 Never Attended | Unmet Need485 Secondary School+ | Unmet Need 72.49 Secondary School+ | Unmet Need72 Secondary School+ | No Demand 87.92 Secondary School+ | No Demand88 Secondary School+ | Using 314.87 Secondary School+ | Using315 Secondary School+ | Unmet Need 37.45 Secondary School+ | Unmet Need Secondary School+ | Using 328.22 Secondary School+ | Using328 Secondary School+ | No Demand 109.61 Secondary School+ | No Demand110 Primary School | Unmet Need 143.30 Primary School | Unmet Need143 Primary School | No Demand 146.15 Primary School | No Demand146 Primary School | Using 233.81 Primary School | Using234 Primary School | Unmet Need 111.50 Primary School | Unmet Need112 Primary School | No Demand 151.46 Primary School | No Demand151 Primary School | Using 260.30 Primary School | Using260
Primary School or Less | Using → Primary School or Less | Using 68% Secondary School+ | Using → Secondary School+ | Using 68% Primary School or Less | Unmet Need → Primary School or Less | Using 8% Secondary School+ | Unmet Need → Secondary School+ | Using 8% Primary School or Less | Unmet Need → Primary School or Less | Unmet Need 6% Secondary School+ | No Demand → Secondary School+ | Using 6% Primary School or Less | Using → Primary School or Less | Unmet Need 4% Secondary School+ | No Demand → Secondary School+ | No Demand 4% Secondary School+ | Using → Secondary School+ | Unmet Need 4% Primary School or Less | No Demand → Primary School or Less | No Demand 4% Secondary School+ | Using → Secondary School+ | No Demand 4% Primary School or Less | No Demand → Primary School or Less | Using 3% Primary School or Less | Unmet Need → Primary School or Less | No Demand 3% Secondary School+ | Unmet Need → Secondary School+ | Unmet Need 3% Primary School or Less | Using → Primary School or Less | No Demand 2% Primary School or Less | No Demand → Primary School or Less | Unmet Need 2% Secondary School+ | No Demand → Secondary School+ | Unmet Need 1% Secondary School+ | Unmet Need → Secondary School+ | No Demand 1% Primary School or Less | Using 1,450.95 Primary School or Less | Using1,451 Primary School or Less | Using 1,549.41 Primary School or Less | Using1,549 Primary School or Less | No Demand 178.87 Primary School or Less | No Demand179 Primary School or Less | Unmet Need 333.80 Primary School or Less | Unmet Need334 Primary School or Less | No Demand 168.11 Primary School or Less | No Demand168 Primary School or Less | Unmet Need 246.10 Primary School or Less | Unmet Need246 Secondary School+ | Using 1,346.88 Secondary School+ | Using1,347 Secondary School+ | No Demand 206.32 Secondary School+ | No Demand206 Secondary School+ | Unmet Need 198.90 Secondary School+ | Unmet Need199 Secondary School+ | Using 1,447.30 Secondary School+ | Using1,447 Secondary School+ | No Demand 165.21 Secondary School+ | No Demand165 Secondary School+ | Unmet Need 139.59 Secondary School+ | Unmet Need140

Note: Data from Burkina Faso are from two surveys conducted in February 2020 and March 2021. Data from Kenya are from two surveys conducted in December 2019 and December 2020. The sample size for the analysis is 2,829 in Burkina Faso and 3,940 in Kenya. Percentages of women in different family planning status categories may not sum to 100% for each education group due to rounding.
Source: Performance Monitoring for Action (PMA) family planning surveys phases 1 and 2 for Burkina Faso and Kenya.

Teenage Pregnancy Significantly Impacted by COVID
The Case of Uganda

Girls’ education, especially secondary education, plays a critical role in reducing teenage pregnancy. While the COVID-19 pandemic appears to have had a modest effect on access to family planning, it created major disruptions in education through extended school closures, with potentially significant effects on teenage pregnancy.

In Uganda, schools remained closed for more than two years. Health facility data on adolescent girls making their first antenatal care (ANC) visit show that the number of teenage pregnancies in 2021 was at least 6% higher compared to 2019. This percentage could mean an additional 20,800 pregnancies or more among girls ages 19 and below.

District-level data show substantial variations: Out of 143 districts for which data are available, 52 experienced at least a 10% increase in teenage pregnancy, including 8 districts experiencing a more than 30% increase in 2021 compared to 2019. Conversely, 15 districts experienced a reduction of more than 10% during the same period.

Percent Change in Number of First Antenatal Care Visits Among Ugandan Girls Ages <20 Between 2019 and 2021, by District

  • < -10%
  • -10% to -.1%
  • 0% to 9.9%
  • 10% to 29.9%
  • ≥ 30%
  • Missing

Note: All district names are as of 2021. The following districts represent the names of new districts after the original districts split in 2019: Arua City, Arua District, Gulu City, Gulu District, Holma City, Holma District, Jinja, Jinja City, Masaka, Masaka City, Mbale City, Mbale District, Mbarara, Mbarara City, Lira, Lira City, Soroti, and Soroti City.

Sources: Ministry of Health in Uganda, District Health Information System Version 2 (DHIS2); and United Nations Population Fund, “The Magnitude of Teenage Pregnancy in Uganda,” Population Matters, no. 19 (2022).

Excess Deaths Associated With the Pandemic Vary by Region and Country Context

The COVID-19 pandemic has impacted mortality around the world in multiple ways—and not just through the direct effect of the number of deaths caused by the disease. It also contributed to increases in deaths from other causes as a result of reduced access to care, and to decreases in deaths from other causes, such as traffic accidents and influenza, through its effects on people’s behavior.

To understand the pandemic’s full impact on mortality, we explored excess deaths due to the pandemic, which were estimated by the World Health Organization as differences between the total number of deaths and the deaths that would have been expected if the pandemic did not occur. Globally, 12% of the average total deaths in 2020 and 2021—7.46 million deaths—were estimated to be directly and indirectly caused by the pandemic.

The magnitude of this impact, however, varies across regions and countries, reflecting differences in population age structures, health infrastructures, COVID-19 containment measures, and social and economic conditions. Between January 2020 and December 2021, the pandemic contributed to 15% or more of total deaths in Western, Central, and South Asia and more than 20% of total deaths in Eastern Europe and Central and South America. In contrast, the pandemic and associated factors contributed little to total deaths in East Asia, and even averted deaths through its effects on people’s risk behaviors in Oceania.

Future pandemic preparedness and global health security efforts must account for regional and contextual variation in both direct and indirect impacts on mortality patterns.

Excess Deaths Due to the COVID-19 Pandemic as a Percent of Total Deaths, 2020-2021 Average
  • < 0%
  • 0% to 4%
  • 5% to 9%
  • 10% to 14%
  • 15% to 19%
  • ≥ 20%
  • Missing

Source: World Health Organization, Global Excess Deaths Associated With COVID-19 (modelled estimates) data set.

Death Rates Increased Sharply Among Young Americans During the Pandemic

In the United States, more than 1 million people have died from COVID-19. Older adults have the highest risk of severe illness and death from the disease, but the pandemic has also had profound social, economic, and health consequences for youth and working-age adults.

Between 2019 and 2021, death rates among Americans ages 15 to 24 increased by 29%. The spike in death rates was even more pronounced for adults ages 25 to 34 (39% increase) and ages 35 to 44 (47% increase). The 2021 data from the U.S. Centers for Disease Control and Prevention are preliminary but suggest that death rates rose sharply that year, despite the widespread availability of vaccines against COVID-19. The reason? A rising number of young Americans dying from other—preventable—causes, especially drug overdoses, homicides, and motor vehicle crashes. These excess deaths reflect pandemic-related changes in people’s emotional, social, and economic well-being and patterns of behavior during the past two years.

Young people of color have been disproportionately affected by rising death rates, reflecting longstanding socioeconomic disparities that will persist without intervention.

Age-Specific Death Rates per 100,000 Population in the United States, 2000-2020

Source: Centers for Disease Control and Prevention, CDC Wonder, Underlying Cause of Death 1999-2020; and Provisional Mortality Data, 2021.

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