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BACKGROUND: How best to prioritise COVID-19 vaccination within and between countries has been a public health and an ethical challenge for decision-makers globally. We reviewed epidemiological and economic modelling evidence on population priority groups to minimise COVID-19 mortality, transmission, and morbidity outcomes. METHODS: We searched the National Institute of Health iSearch COVID-19 Portfolio (a database of peer-reviewed and pre-print articles), Econlit, the Centre for Economic Policy Research, and the National Bureau of Economic Research for mathematical modelling studies evaluating the impact of prioritising COVID-19 vaccination to population target groups. The first search was conducted on March 3, 2021, and an updated search on the LMIC literature was conducted from March 3, 2021, to September 24, 2021. We narratively synthesised the main study conclusions on prioritisation and the conditions under which the conclusions changed. RESULTS: The initial search identified 1820 studies and 36 studies met the inclusion criteria. The updated search on LMIC literature identified 7 more studies. 43 studies in total were narratively synthesised. 74% of studies described outcomes in high-income countries (single and multi-country). We found that for countries seeking to minimise deaths, prioritising vaccination of senior adults was the optimal strategy and for countries seeking to minimise cases the young were prioritised. There were several exceptions to the main conclusion, notably that reductions in deaths could be increased if groups at high risk of both transmission and death could be further identified. Findings were also sensitive to the level of vaccine coverage. CONCLUSION: The evidence supports WHO SAGE recommendations on COVID-19 vaccine prioritisation. There is, however, an evidence gap on optimal prioritisation for low- and middle-income countries, studies that included an economic evaluation, and studies that explore prioritisation strategies if the aim is to reduce overall health burden including morbidity.
Assuntos
Vacinas contra COVID-19 , COVID-19 , Adulto , Humanos , Saúde Pública , SARS-CoV-2 , VacinaçãoRESUMO
BACKGROUND: Countries designing a health benefit package (HBP) to support progress towards universal health coverage (UHC) require robust cost-effectiveness evidence. This paper reports on Pakistan's approach to assessing the applicability of global cost-effectiveness evidence to country context as part of a HBP design process. METHODS: A seven-step process was developed and implemented with Disease Control Priority 3 (DCP3) project partners to assess the applicability of global incremental cost-effectiveness ratios (ICERs) to Pakistan. First, the scope of the interventions to be assessed was defined and an independent, interdisciplinary team was formed. Second, the team familiarized itself with intervention descriptions. Third, the team identified studies from the Tufts Medical School Global Health Cost-Effectiveness Analysis (GH-CEA) registry. Fourth, the team applied specific knock-out criteria to match identified studies to local intervention descriptions. Matches were then cross-checked across reviewers and further selection was made where there were multiple ICER matches. Sixth, a quality scoring system was applied to ICER values. Finally, a database was created containing all the ICER results with a justification for each decision, which was made available to decision-makers during HBP deliberation. RESULTS: We found that less than 50% of the interventions in DCP3 could be supported with evidence of cost-effectiveness applicable to the country context. Out of 78 ICERs identified as applicable to Pakistan from the Tufts GH-CEA registry, only 20 ICERs were exact matches of the DCP3 Pakistan intervention descriptions and 58 were partial matches. CONCLUSION: This paper presents the first attempt globally to use the main public GH-CEA database to estimate cost-effectiveness in the context of HBPs at a country level. This approach is a useful learning for all countries trying to develop essential packages informed by the global database on ICERs, and it will support the design of future evidence and further development of methods.
Assuntos
Análise Custo-Benefício , Cobertura Universal do Seguro de Saúde , Paquistão , Humanos , Cobertura Universal do Seguro de Saúde/economia , Cobertura Universal do Seguro de Saúde/organização & administração , Saúde Global/economiaRESUMO
OBJECTIVES: COVID-19 has altered health sector capacity in low-income and middle-income countries (LMICs). Cost data to inform evidence-based priority setting are urgently needed. Consequently, in this paper, we calculate the full economic health sector costs of COVID-19 clinical management in 79 LMICs under different epidemiological scenarios. METHODS: We used country-specific epidemiological projections from a dynamic transmission model to determine number of cases, hospitalisations and deaths over 1 year under four mitigation scenarios. We defined the health sector response for three base LMICs through guidelines and expert opinion. We calculated costs through local resource use and price data and extrapolated costs across 79 LMICs. Lastly, we compared cost estimates against gross domestic product (GDP) and total annual health expenditure in 76 LMICs. RESULTS: COVID-19 clinical management costs vary greatly by country, ranging between <0.1%-12% of GDP and 0.4%-223% of total annual health expenditure (excluding out-of-pocket payments). Without mitigation policies, COVID-19 clinical management costs per capita range from US$43.39 to US$75.57; in 22 of 76 LMICs, these costs would surpass total annual health expenditure. In a scenario of stringent social distancing, costs per capita fall to US$1.10-US$1.32. CONCLUSIONS: We present the first dataset of COVID-19 clinical management costs across LMICs. These costs can be used to inform decision-making on priority setting. Our results show that COVID-19 clinical management costs in LMICs are substantial, even in scenarios of moderate social distancing. Low-income countries are particularly vulnerable and some will struggle to cope with almost any epidemiological scenario. The choices facing LMICs are likely to remain stark and emergency financial support will be needed.