Impact of COVID-19 Containment Measures on Unemployment: A Multi-Country Analysis Using A Difference-In-Differences Framework

Background: At the start of the COVID-19 pandemic, in the absence of pharmaceutical interventions, countries resorted to containment measures to stem the spread of the disease. In this paper, we have conducted a global study using a sample of 46 countries to evaluate whether these containment measures resulted in unemployment.Methods: We use a difference-in-differences (DID) specification with a heterogenous intervention to show the varying intensity effect of containment measures on unemployment, on a sample of 46 countries. We explain variations in unemployment from January-June 2020 using stringency of containment measures, controlling for GDP growth, inflation rate, exports, cases of COVID-19 per million, COVID-19-specific fiscal spending, time fixed effects, region fixed effects, and region trends. We conduct further subset analyses by COVID-cases quintiles and GNI per capita quintiles.Results: The median level of containment stringency in our sample was 43.7. Our model found that increasing stringency to this level would result in unemployment increasing by 1.87 percentage points (or 1.67 pp, after controlling for confounding). For countries with below median COVID-19 cases and below median GNI per capita, this effect is larger.Conclusion: Containment measures have a strong impact on unemployment. This effect is larger in poorer countries and countries with low COVID-19 cases. Given that unemployment has profound effects on mortality and morbidity, this consequence of containment measures may compound the adverse health effects of the pandemic for the most vulnerable groups. It is necessary for governments to consider this in future pandemic management, and to attempt to alleviate the impact of containment measures via effective fiscal spending.

Cost-effectiveness of a mental health drop-in centre for young people with long-term physical conditions.

BACKGROUND: Paediatric patients being treated for long-term physical health conditions (LTCs) have elevated mental health needs. However, mental health services in the community are difficult to access in the usual course of care for these patients. The Lucy Project - a self-referral drop-in access point-was a program to address this gap by enrolling patients for low-intensity psychological interventions during their treatment for LTCs. In this paper, we evaluate the cost-effectiveness of the Lucy Project. METHODS: Using a pre-post design, we evaluate the cost-effectiveness of the intervention by calculating the base-case incremental cost-effectiveness ratio (ICER) using outcomes data and expenses recorded by project staff. The target population was paediatric patients enrolled in the program with an average age of 9 years, treated over a time horizon of 6 months. Outcome data were collected via the Paediatric Quality of Life Inventory, which was converted to health utility scores using an instrument found in the literature. The QALYs were estimated using these health utility scores and the length of the intervention. We calculate a second, practical-case incremental cost-effectiveness ratio using streamlined costing figures with maximum capacity patient enrolment within a one-year time horizon, and capturing lessons learned post-trial. RESULTS: The base-case model showed an ICER of £21,220/Quality Adjusted Life Years (QALY) gained, while the practical model showed an ICER of £4,359/QALY gained. The practical model suggests the intervention garners significant gains in quality of life at an average cost of £309 per patient. Sensitivity analyses reveal use of staff time was the greatest determinant of the ICER, and the intervention is cost-effective 75% of the time in the base-case model, and 94% of the time in the practical-case model at a cost-effectiveness threshold of £20,000/QALY gained. CONCLUSIONS: We find the base-case intervention improves patient outcomes and can be considered cost-effective according to the National Institute for Health and Care Excellence (NICE) threshold of £20,000-£30,000/QALY gained, and the practical-case intervention is roughly four times as cost-effective as the base-case. We recommend future studies incorporate a control group to corroborate the effect size of the intervention.

COVID-19 attributed mortality and ambient temperature: a global ecological study using a two-stage regression model.

A negative correlation between ambient temperature and COVID-19 mortality has been observed. However, the World Meteorological Organization (WMO) has reinforced the importance of government interventions and warned countries against relaxing control measures due to warmer temperatures. Further understanding of this relationship is needed to help plan vaccination campaigns opportunely. Using a two-stage regression model, we conducted cross-sectional and longitudinal analyses to evaluate the association between monthly ambient temperature lagged by one month with the COVID-19 number of deaths and the probability of high-level of COVID-19 mortality in 150 countries during time t = 60, 90, and 120 days since the onset. First, we computed a log-linear regression to predict the pre-COVID-19 respiratory disease mortality to homogenize the baseline disease burden within countries. Second, we employed negative binomial and logistic regressions to analyze the linkage between the ambient temperature and our outcomes, adjusting by pre-COVID-19 respiratory disease mortality rate, among other factors. The increase of one Celsius degree in ambient temperature decreases the incidence of COVID-19 deaths (IRR = 0.93; SE: 0.026, p-value<0.001) and the probability of high-level COVID-19 mortality (OR = 0.96; SE: 0.019; p-value<0.001) over time. High-income countries from the northern hemisphere had lower temperatures and were most affected by pre-COVID respiratory disease mortality and COVID-19 mortality. This study provides a global perspective corroborating the negative association between COVID-19 mortality and ambient temperature. Our longitudinal findings support the statement made by the WMO. Effective, opportune, and sustained reaction from countries can help capitalize on higher temperatures' protective role including the timely rollout of vaccination campaigns.

Country-level factors associated with the early spread of COVID-19 cases at 5, 10 and 15 days since the onset.

The COVID-19 pandemic is causing a significant global health crisis. As the disease continues to spread worldwide, little is known about the country-level factors affecting the transmission in the early weeks. The present study objective was to explore the country-level factors, including government actions that explain the variation in the cumulative cases of COVID-19 within the first 15 days since the first case reported. Using publicly available sources, country socioeconomic, demographic and health-related risk factors, together with government measures to contain COVID-19 spread, were analysed as predictors of the cumulative number of COVID-19 cases at three time points (t = 5, 10 and 15) since the first case reported (n = 134 countries). Drawing on negative binomial multivariate regression models, HDI, healthcare expenditure and resources, and the variation in the measures taken by the governments, significantly predicted the incidence risk ratios of COVID-19 cases at the three time points. The estimates were robust to different modelling techniques and specifications. Although wealthier countries have elevated human development and healthcare capacity in respect to their counterparts (low- and middle-income countries) the early implementation of effective and incremental measures taken by the governments are crucial to controlling the spread of COVID-19 in the early weeks.