RESUMEN
BACKGROUND: During the COVID-19 pandemic, governments and researchers have used routine health data to estimate potential declines in the delivery and uptake of essential health services. This research relies on the data being high quality and, crucially, on the data quality not changing because of the pandemic. In this paper, we investigated those assumptions and assessed data quality before and during COVID-19. METHODS: We obtained routine health data from the DHIS2 platforms in Ethiopia, Haiti, Lao People's Democratic Republic, Nepal, and South Africa (KwaZulu-Natal province) for a range of 40 indicators on essential health services and institutional deaths. We extracted data over 24 months (January 2019-December 2020) including pre-pandemic data and the first 9 months of the pandemic. We assessed four dimensions of data quality: reporting completeness, presence of outliers, internal consistency, and external consistency. RESULTS: We found high reporting completeness across countries and services and few declines in reporting at the onset of the pandemic. Positive outliers represented fewer than 1% of facility-month observations across services. Assessment of internal consistency across vaccine indicators found similar reporting of vaccines in all countries. Comparing cesarean section rates in the HMIS to those from population-representative surveys, we found high external consistency in all countries analyzed. CONCLUSIONS: While efforts remain to improve the quality of these data, our results show that several indicators in the HMIS can be reliably used to monitor service provision over time in these five countries.
Asunto(s)
COVID-19 , Embarazo , Humanos , Femenino , COVID-19/epidemiología , Pandemias , Laos/epidemiología , Nepal/epidemiología , Etiopía , Sudáfrica/epidemiología , Haití/epidemiología , CesáreaRESUMEN
The social and behavioural determinants of COVID-19 vaccination have been described previously. However, little is known about how vaccinated people use and rate their health system. We used surveys conducted in 14 countries to study the health system correlates of COVID-19 vaccination. Country-specific logistic regression models were adjusted for respondent age, education, income, chronic illness, history of COVID-19, urban residence, and minority ethnic, racial, or linguistic group. Estimates were summarised across countries using random effects meta-analysis. Vaccination coverage with at least two or three doses ranged from 29% in India to 85% in Peru. Greater health-care use, having a regular and high-quality provider, and receiving other preventive health services were positively associated with vaccination. Confidence in the health system and government also increased the odds of vaccination. By contrast, having unmet health-care needs or experiencing discrimination or a medical mistake decreased the odds of vaccination. Associations between health system predictors and vaccination tended to be stronger in high-income countries and in countries with the most COVID-19-related deaths. Access to quality health systems might affect vaccine decisions. Building strong primary care systems and ensuring a baseline level of quality that is affordable for all should be central to pandemic preparedness strategies.