Related Experiment Video
Updated: Jul 25, 2025

Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19
Published on: February 16, 2022
COVID-19 Impact on DTP Vaccination Trends in Africa: A Joinpoint Regression Analysis
Ines Aguinaga-Ontoso1,2, Sara Guillen-Aguinaga1, Laura Guillen-Aguinaga1,3
1Department of Health Sciences, Public University of Navarra, 31008 Pamplona, Spain.
Insights
COVID-19 significantly disrupted childhood vaccination in Africa, leading to a decline in DTP3 coverage. This trend highlights the pandemic's impact on essential immunization programs across the continent.
Area of Science:
- Public Health
- Epidemiology
- Immunization Programs
Background:
- Vaccine-preventable diseases remain a leading cause of mortality in African children.
- Achieving high vaccine coverage is critical for reducing infant mortality rates.
- The COVID-19 pandemic has strained healthcare systems, potentially impacting routine vaccination services.
Purpose of the Study:
- To analyze trends in DTP3 vaccine coverage in Africa from 2012 to 2021.
- To assess the impact of the COVID-19 pandemic on DTP3 vaccination rates.
- To identify specific regions and countries experiencing changes in vaccine coverage.
Main Methods:
- Utilized UNICEF database records for DTP3 vaccine coverage data (2012-2021).
- Employed joinpoint regression analysis to identify significant trend changes in coverage.
- Calculated Annual Percentage Change (APC) and compared coverage between 2019 and 2021 using Chi-square tests.
Main Results:
- Overall DTP3 vaccine coverage in Africa showed a positive trend (APC 1.2%) until 2019.
- A significant decline in DTP3 coverage was observed from 2019 to 2021 (APC -3.5%, p < 0.001).
- Decreased vaccination rates were noted in multiple Sub-Saharan African countries, particularly in Eastern and Southern Africa.
Conclusions:
- The COVID-19 pandemic demonstrably disrupted vaccine coverage across Africa.
- There was a notable decrease in DTP3 vaccination rates in numerous African nations post-2019.
- The findings underscore the vulnerability of immunization programs to global health crises.
Background:
Deaths due to vaccine-preventable diseases are one of the leading causes of death among African children. Vaccine coverage is an essential measure to decrease infant mortality. The COVID-19 pandemic has affected the healthcare system and may have disrupted vaccine coverage.
Methods:
DTP third doses (DTP3) Vaccine Coverage was extracted from UNICEF databases from 2012 to 2021 (the last available date). Joinpoint regression was performed to detect the point where the trend changed. The annual percentage change (APC) with 95% confidence intervals (95% CI) was calculated for Africa and the regions. We compared DTP3 vaccination coverage in 2019-2021 in each country using the Chi-square test.
Result:
During the whole period, the vaccine coverage in Africa increased with an Annual Percent change of 1.2% (IC 95% 0.9-1.5): We detected one joinpoint in 2019. In 2019-2021, there was a decrease in DTP3 coverage with an APC of -3.5 (95% -6.0; -0,9). (p < 0.001). Vaccination rates decreased in many regions of Sub-Saharan Africa, especially in Eastern and Southern Africa. There were 26 countries (Angola, Cabo Verde, Comoros, Congo, Côte d'Ivoire, Democratic Republic of the Congo, Djibouti, Ethiopia, Eswatini, The Gambia, Guinea-Bissau, Liberia, Madagascar, Malawi, Mauritania, Mauritius, Mozambique, Rwanda, Senegal, Seychelles, Sierra Leone, Sudan, Tanzania, Togo, Tunisia, Uganda, and Zimbabwe) where the vaccine coverage during the two years decreased. There were 10 countries (Angola, Cabo Verde, Comoros, Democratic Republic of the Congo, Eswatini, The Gambia, Mozambique, Rwanda, Senegal, and Sudan) where the joinpoint regression detected a change in the trend.
Conclusions:
COVID-19 has disrupted vaccine coverage, decreasing it all over Africa.
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Bias in Epidemiological Studies
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Steps in Outbreak Investigation
Principles of Disease Surveillance
Confounding in Epidemiological Studies

