Associations between the stringency of COVID-19 containment policies and health service disruptions in 10 countries

Abstract

Background: Disruptions in essential health services during the COVID-19 pandemic have been reported in several countries. Yet, patterns in health service disruption according to country responses remain unclear. In this paper, we investigate associations between the stringency of COVID-19 containment policies and disruptions in 31 health services in 10 low- middle- and high-income countries in 2020.

Methods: Using routine health information systems and administrative data from 10 countries (Chile, Ethiopia, Ghana, Haiti, Lao People's Democratic Republic, Mexico, Nepal, South Africa, South Korea, and Thailand) we estimated health service disruptions for the period of April to December 2020 by dividing monthly service provision at national levels by the average service provision in the 15 months pre-COVID (January 2019-March 2020). We used the Oxford COVID-19 Government Response Tracker (OxCGRT) index and multi-level linear regression analyses to assess associations between the stringency of restrictions and health service disruptions over nine months. We extended the analysis by examining associations between 11 individual containment or closure policies and health service disruptions. Models were adjusted for COVID caseload, health service category and country GDP and included robust standard errors.

Findings: Chronic disease care was among the most affected services. Regression analyses revealed that a 10% increase in the mean stringency index was associated with a 3.3 percentage-point (95% CI -3.9, -2.7) reduction in relative service volumes. Among individual policies, curfews, and the presence of a state of emergency, had the largest coefficients and were associated with 14.1 (95% CI -19.6, 8.7) and 10.7 (95% CI -12.7, -8.7) percentage-point lower relative service volumes, respectively. In contrast, number of COVID-19 cases in 2020 was not associated with health service disruptions in any model.

Conclusions: Although containment policies were crucial in reducing COVID-19 mortality in many contexts, it is important to consider the indirect effects of these restrictions. Strategies to improve the resilience of health systems should be designed to ensure that populations can continue accessing essential health care despite the presence of containment policies during future infectious disease outbreaks.

Keywords: COVID-19 restrictions; Health care disruptions; Health services; Health system resilience; Health systems; Pandemic response.

Fig. 1

Trends in relative service volumes and the OxCGRT stringency index from April to December 2020. The post-COVID months of April (month 4) through December (month 12) 2020 are shown on the x-axes. The left y-axis is the relative service volume (%) and the right y-axis is the OxCGRT stringency index. The red line is the mean stringency index over these nine months. The navy dots represent the relative service volume (%) for individual health services each month (listed in Supplemental Table 1). The navy line is the mean relative service volume (%) per service type over time. The black line is a reference line for 100% relative service volume and 100% stringency index. CHL is Chile, ETH is Ethiopia, GHA is Ghana, HTI is Haiti, KOR is South Korea, KZN is KwaZulu-Natal Province, LAO is Lao People’s Democratic Republic, MEX is Mexico, NEP is Nepal and THA is Thailand

Fig. 2

Results from multi-level effects linear regression models for the association between individual COVID-19 containment policies and relative service volumes. Associations between individual COVID-19 containment and closure policies were assessed. Each of the 11 containment policies were added separately to regression models with same fixed and random effects structure described. The model included COVID-19 cases as the COVID-19 cases per million monthly in each country, service type categories for service volume (1) reproductive, maternal, or newborn, (2) service use overall and injuries, (3) child health services, (4) antiretroviral therapy and (5) chronic diseases), GDP as GDP per capita, rescaled to a factor of 1000. The public information campaigns policy, collected by OxCGRT, was excluded as the policy was always in place in all countries over the study period