Stark choices: exploring health sector costs of policy responses to COVID-19 in low-income and middle-income countries
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Abstract
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.
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SciScore for 10.1101/2020.08.23.20180299: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our methods are subject to many limitations. Normally we would estimate ‘real world’ costs collecting extensive primary cost data on actual service delivery. In the case of COVID-19, we have not been able to do this. We have …
SciScore for 10.1101/2020.08.23.20180299: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our methods are subject to many limitations. Normally we would estimate ‘real world’ costs collecting extensive primary cost data on actual service delivery. In the case of COVID-19, we have not been able to do this. We have therefore had to rely substantially on data collected for other purposes and on expert opinion from LMICs to make key assumptions on how services may be delivered. We aimed to include the total costs to the health system and our aim was to estimate ‘real world costs’ in terms of the resource needs to deliver the most essential care. However, our costs are unlikely to reflect actual expenditures, as countries may either provide more care to specific patients, or struggle to provide even the most essential care given the current restrictions on expenditure. Likewise, the case numbers that our estimates rely upon are unlikely to match the real case numbers currently being observed in many LMICs, as they represent single policy options, and a time period of one year from the start of the epidemic. Finally, we do not include the costs of protecting health care workers delivering other essential services outside the COVID-19 response. Despite these limitations, our work highlights several critical qualitative recommendations for those working in COVID-19 policy. First, it is imperative, that global agencies and funders continue to act to ensure sufficient resources are made available globally for LMICs to respond, as the epidemic evolves. While much of the focu...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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