RESUMO
BackgroundEven with good progress on vaccination, SARS-CoV-2 infections in the UK may continue to impose a high burden of disease and therefore pose substantial challenges for health policy decision makers. Stringent government-mandated physical distancing measures (lockdown) have been demonstrated to be epidemiologically effective, but can have both positive and negative economic consequences. The duration and frequency of any intervention policy could, in theory, could be optimised to maximise economic benefits while achieving substantial reductions in disease. MethodsHere we use a pre-existing SARS-CoV-2 transmission model to assess the health and economic implications of different strengths of control through time in order to identify optimal approaches to non-pharmaceutical intervention stringency in the UK, considering the role of vaccination in reducing the need for future physical distancing measures. The model is calibrated to the COVID-19 epidemic in England and we carry out retrospective analysis of the optimal timing of precautionary breaks in 2020 and the optimal relaxation policy from the January 2021 lockdown, considering the willingness to pay for health improvement. ResultsWe find that the precise timing and intensity of interventions is highly dependent upon the objective of control. As intervention measures are relaxed, we predict a resurgence in cases, but the optimal intervention policy can be established dependent upon the willingness to pay (WTP) per QALY loss avoided. Our results show that establishing an optimal level of control can result in a reduction in net monetary loss of billions of pounds, dependent upon the precise WTP value. ConclusionsIt is vital, as the UK emerges from lockdown, but continues to face an on-going pandemic, to accurately establish the overall health and economic costs when making policy decisions. We demonstrate how some of these can be quantified, employing mechanistic infectious disease transmission models to establish optimal levels of control for the ongoing COVID-19 pandemic.
RESUMO
ObjectiveTo provide an early global assessment of the impact of government stringency measures on the rate of growth in deaths from COVID-19. We hypothesized that the overall stringency of a governments interventions and the speed of implementation would affect the growth and level of deaths related to COVID-19 in that country. DesignObservational study based on an original database of global governmental responses to the COVID-19 pandemic. Daily data was collected on a range of containment and closure policies for 170 countries from January 1, 2020 until May 27, 2020 by a team of researchers at Oxford University, UK. These data were combined into an aggregate stringency index (SI) score for each country on each day (range: 0-100). Regression was used to show correlations between the speed and strength of government stringency and deaths related to COVID-19 with a number of controls for time and country-specific demographic, health system, and economic characteristics. InterventionsNine non-pharmaceutical interventions such as school and work closures, restrictions on international and domestic travel, public gathering bans, public information campaigns, as well as testing and contact tracing policies. Main outcomes measuresThe primary outcome was deaths related to COVID-19, measured both in terms of maximum daily deaths and growth rate of daily deaths. ResultsFor each day of delay to reach an SI 40, the average daily growth rate in deaths was 0.087 percentage points higher (0.056 to 0.118, P<0.001). In turn, each additional point on the SI was associated with a 0.080 percentage point lower average daily growth rate (-0.121 to -0.039, P<.001). These daily differences in growth rates lead to large cumulative differences in total deaths. For example, a week delay in enacting policy measures to SI 40 would lead to 1.7 times as many deaths overall. ConclusionsA lower degree of government stringency and slower response times were associated with more deaths from COVID-19. These findings highlight the importance of non-pharmaceutical responses to COVID-19 as more robust testing, treatment, and vaccination measures are developed.