Cost-effectiveness analysis of surgical masks, N95 masks compared to wearing no mask for the prevention of COVID-19 among health care workers: Evidence from the public health care setting in India.

BACKGROUND: Nonpharmacological interventions, such as personal protective equipment for example, surgical masks and respirators, and maintenance of hand hygiene along with COVID-19 vaccines have been recommended to reduce viral transmission in the community and health care settings. There is evidence from the literature that surgical and N95 masks may reduce the initial degree of exposure to the virus. A limited research that has studied the cost-effective analysis of surgical masks and N95 masks among health care workers in the prevention of COVID-19 in India. The objective of this study was to estimate the cost-effectiveness of N95 and surgical mask compared to wearing no mask in public hospital settings for preventing COVID-19 infection among Health care workers (HCWs) from the health care provider's perspective. METHODS: A deterministic baseline model, without any mask use, based on Eikenberry et al was used to form the foundation for parameter estimation and to estimate transmission rates among HCWs. Information on mask efficacy, including the overall filtering efficiency of a mask and clinical efficiency, in terms of either inward efficiency(ei) or outward efficiency(e0), was obtained from published literature. Hospitalized HCWs were assumed to be in one of the disease states i.e., mild, moderate, severe, or critical. A total of 10,000 HCWs was considered as representative of the size of a tertiary care institution HCW population. The utility values for the mild, moderate and severe model health states were sourced from the primary data collection on quality-of-life of HCWs COVID-19 survivors. The utility scores for mild, moderate, and severe COVID-19 conditions were 0.88, 0.738 and 0.58, respectively. The cost of treatment for mild sickness (6,500 INR per day), moderate sickness (10,000 INR per day), severe (require ICU facility without ventilation, 15,000 INR per day), and critical (require ICU facility with ventilation per day, 18,000 INR) per day as per government and private COVID-19 treatment costs and capping were considered. One way sensitivity analyses were performed to identify the model inputs which had the largest impact on model results. RESULTS: The use of N95 masks compared to using no mask is cost-saving of $1,454,632 (INR 0.106 billion) per 10,000 HCWs in a year. The use of N95 masks compared to using surgical masks is cost-saving of $63,919 (INR 0.005 billion) per 10,000 HCWs in a year. the use of surgical masks compared to using no mask is cost-saving of $1,390,713 (INR 0.102 billion) per 10,000 HCWs in a year. The uncertainty analysis showed that considering fixed transmission rate (1.7), adoption of mask efficiency as 20%, 50% and 80% reduces the cumulative relative mortality to 41%, 79% and 94% respectively. On considering ei = e0 (99%) for N95 and surgical mask with ei = e0 (90%) the cumulative relative mortality was reduced by 97% and the use of N95 masks compared to using surgical masks is cost-saving of $24,361 (INR 0.002 billion) per 10,000 HCWs in a year. DISCUSSION: Both considered interventions were dominant compared to no mask based on the model estimates. N95 masks were also dominant compared to surgical masks.

Cost-effectiveness analysis of a multiplex lateral flow rapid diagnostic test for acute non-malarial febrile illness in rural Cambodia and Bangladesh.

Background: Multiplex lateral flow rapid diagnostic tests (LF-RDTs) may aid management of patients with acute non-malarial febrile illness (NMFI) in rural south and southeast Asia. We aimed to evaluate the cost-effectiveness in Cambodia and Bangladesh of a putative, as-yet-undeveloped LF-RDT capable of diagnosing enteric fever and dengue, as well as measuring C-reactive protein (CRP) to guide antibiotic prescription, in primary care patients with acute NMFI. Methods: A country-specific decision tree model-based cost-effectiveness analysis was conducted from a health system plus limited societal perspective considering the cost of antimicrobial resistance. Parameters were based on data from a large observational study on the regional epidemiology of acute febrile illness, published studies, and procurement price lists. Costs were expressed in US$ (value in 2022), and cost-effectiveness evaluated by comparing incremental cost-effectiveness ratios with conservative opportunity cost-based willingness-to-pay thresholds and the more widely used threshold of per capita gross domestic product (GDP). Findings: Compared to standard of care, LF-RDT-augmented clinical assessment was dominant in Cambodia, being more effective and cost-saving. The cost per disability-adjusted life year (DALY) averted in Bangladesh was US$482, slightly above the conservative opportunity cost-based willingness-to-pay threshold of US$388 and considerably lower than the GDP-based threshold of US$2687. The intervention remained dominant in Cambodia and well below the GDP-based threshold in Bangladesh when antimicrobial resistance costs were disregarded. Interpretation: These findings provide guidance for academic, industry, and policymaker stakeholders involved in acute NMFI diagnostics. While definitive conclusions cannot be made in the absence of established thresholds, our results suggest that similar results are highly likely in some target settings and possible in others. Funding: Wellcome Trust, UK Government, Royal Australasian College of Physicians, and Rotary Foundation.

A systematic literature review of economic evaluation studies of interventions impacting antimicrobial resistance.

BACKGROUND: Antimicrobial resistance (AMR) is accelerated by widespread and inappropriate use of antimicrobials. Many countries, including those in low- and middle- income contexts, have started implementing interventions to tackle AMR. However, for many interventions there is little or no economic evidence with respect to their cost-effectiveness. To help better understand the scale of this evidence gap, we conducted a systematic literature review to provide a comprehensive summary on the value for money of different interventions affecting AMR. METHODS: A systematic literature review was conducted of economic evaluations on interventions addressing AMR. a narrative synthesis of findings was produced. Systematic searches for relevant studies were performed across relevant databases and grey literature sources such as unpublished studies, reports, and other relevant documents. All identified economic evaluation studies were included provided that they reported an economic outcome and stated that the analysed intervention aimed to affect AMR or antimicrobial use in the abstract. Studies that reported clinical endpoints alone were excluded. Selection for final inclusion and data extraction was performed by two independent reviewers. A quality assessment of the evidence used in the included studies was also conducted. RESULTS: 28,597 articles were screened and 35 articles were identified that satisfied the inclusion criteria. The review attempted to answer the following questions: (1) What interventions to address AMR have been the subject of an economic evaluation? (2) In what types of setting (e.g. high-income, low-income, regions etc.) have these economic evaluations been focused? (3) Which interventions have been estimated to be cost-effective, and has this result been replicated in other settings/contexts? (4) What economic evaluation methods or techniques have been used to evaluate these interventions? (5) What kind and quality of data has been used in conducting economic evaluations for these interventions? DISCUSSION: The review is one of the first of its kind, and the most recent, to systematically review the literature on the cost-effectiveness of AMR interventions. This review addresses an important evidence gap in the economics of AMR and can assist AMR researchers' understanding of the state of the economic evaluation literature, and therefore inform future research. Systematic review registration PROSPERO (CRD42020190310).

A model-based study to estimate the health and economic impact of health technology assessment in Thailand.

OBJECTIVES: Health technology assessment (HTA) plays a central role in the coverage and reimbursement decision-making process for public health expenditure in many countries, including Thailand. However, there have been few attempts to quantitatively understand the benefits of using HTA to inform resource allocation decisions. The objective of this research was to simulate the expected net monetary benefit (NMB) from using HTA-based decision criteria compared to a first-come, first-served (FCFS) approach using data from Thailand. METHODS: A previously published simulation model was adapted to the Thai context which aimed to simulate the impact of using different decision-making criteria to adopt or reject health technologies for public reimbursement. Specifically, the simulation model provides a quantitative comparison between an HTA-based funding rule and a counterfactual (FCFS) funding rule to make decisions on which health technologies should be funded. The primary output of the model was the NMB of using HTA-based decision criteria compared to the counterfactual approach. The HTA-based decision rule in the model involved measuring incremental cost-effectiveness ratios against a cost-effectiveness threshold. The counterfactual decision rule was a FCFS (random) selection of health technologies. RESULTS: The HTA-based decision rule was associated with a greater NMB compared to the counterfactual. In the investigated analyses, the NMB ranged from THB24,238 million (USD725 million) to THB759,328 million (USD22,719 million). HTA-based decisions led to fewer costs, superior health outcomes (more quality-adjusted life-years). CONCLUSIONS: The results support the hypothesis that HTA can provide health and economic benefits by improving the efficiency of resource allocation decision making.

A protocol for a systematic literature review of economic evaluation studies of interventions to address antimicrobial resistance.

BACKGROUND: Antimicrobial resistance (AMR) is accelerated by the widespread and often indiscriminate use of antimicrobials in humans, animals, and the environment. In 2015, the World Health Organization recognised AMR as one of the top ten global health threats, due to its potential to neutralise humanity's advancements in western medicine by enabling the emergence of new strains of existing pathogens, many of which have no available treatments. Over the past decade, several countries, including those in low- and middle-income contexts, have started implementing interventions to tackle AMR. However, economic evidence regarding the cost-effectiveness of these interventions remains weak. To address this evidence gap, we will conduct a systematic literature review to provide a comprehensive summary on the value for money of different AMR interventions. METHODS: We aim to conduct a systematic literature review of all available economic evaluations on interventions addressing AMR and will provide a narrative synthesis of our findings. Systematic searches for relevant studies will be performed across all suitable databases as well as in grey literature sources such as unpublished studies, reports, and other relevant documents. All economic evaluation studies will be included as long as they report an economic outcome and have stated that the analysed intervention will reduce antimicrobial resistance or antimicrobial use in the abstract. Those studies reporting clinical endpoints alone will be excluded. Selection for final inclusion and data extraction will be performed by two independent reviewers. DISCUSSION: The review will be one of the first of its kind, and the most recent, to systematically review literature on the cost-effectiveness of AMR interventions, an important evidence gap in the economics of AMR. The findings will enable policy and decision-makers, particularly in resource-constrained settings, to better use available resources when selecting interventions to address AMR burdens, SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020190310.

Hepatitis C prevalences in the psychiatric setting: Cost-effectiveness of scaling-up screening and direct-acting antiviral therapy.

BACKGROUND & AIMS: Patients hospitalised because of mental illness often have risk factors for contracting HCV. Scaling-up HCV screening for all psychiatric inpatients as a case-detection strategy for viral elimination is underexplored. This study aimed to evaluate the cost-effectiveness of scaling-up HCV screening and treatment for psychiatry hospital admissions in Switzerland vs. the current standard-of-care risk-based approach, where only those with a history of substance misuse disorder are offered testing. METHODS: HCV prevalence by history of substance misuse disorder was analysed in medical records from inpatient admissions to a Swiss psychiatry department. Cost-effectiveness was analysed from a healthcare provider perspective through a decision-tree screening model, using these HCV prevalence data. Model and parameter uncertainty were assessed using deterministic and probabilistic sensitivity analyses. RESULTS: Prevalence of HCV in psychiatry inpatients with a history of substance misuse disorder (n = 1,013) was 25.7%, compared with 3.5% among the remaining inpatients (n = 3,535). Scaling up HCV screening and treatment for all psychiatry admissions was cost-effective vs. the risk-based approach, with an incremental cost-effectiveness ratio of US$9,188 per quality-adjusted life-year gained. The incremental cost-effectiveness ratio remained cost-effective considering a HCV prevalence as low as 0.07%. The population-level net monetary benefit of the generalised screening approach was US$435,156,348, with 917 additional patients per year detected and treated at a cost of US$3,294 per person (vs. US$2,122 under risk-based screening). CONCLUSIONS: Scaling up HCV screening and treatment at diagnosis with all-oral, interferon-free regimens as a generalised approach for psychiatric admissions was cost-effective and could support reaching World Health Organization targets for HCV elimination by 2030. LAY SUMMARY: Patients hospitalised because of mental illness often have risk factors for HCV. We found that testing all psychiatry patients in hospital for HCV was cost-effective compared with testing only patients who have a history of substance misuse. Scaling up HCV testing and treatment could help to wipe out HCV.

Avoiding health technology assessment: a global survey of reasons for not using health technology assessment in decision making.

INTRODUCTION: Despite the documented benefits of using health technology assessments (HTA) to inform resource allocation in health care systems, HTA remains underused, especially in low- and middle-income countries. A survey of global health practitioners was conducted to reveal the top reasons ("excuses") that they had heard from colleagues, policymakers or other stakeholders for not using HTA in their settings. METHODS: There were 193 respondents to the survey. Most responses were from individuals in research organisations (37%), ministries of health (27%) and other government agencies (14%). Participants came from Southeast Asia (40%), the Western Pacific (30%), Africa (15%), Europe (7%), the Americas (7%) and the Eastern Mediterranean region (2%). RESULTS: The top five reasons encountered by respondents related to lack of data, lack of technical skills for HTA, the technocratic nature of the work, the lack of explicit decision rules and the perception that HTA puts a "price on life". CONCLUSIONS: This study aimed to understand and address the top reasons for not using HTA. They fall into three categories: (1) misconceptions about HTA; (2) feasibility issues; and (3) values, attitudes and politics. Previous literature has shown that these reasons can be addressed when identified, and even imperfect HTA analyses can provide useful information to a decision-maker.

Avoiding Trouble Ahead: Lessons Learned and Suggestions for Economic Evaluations of COVID-19 Vaccines.

With vaccines for coronavirus disease 2019 (COVID-19) being introduced in countries across the world, policy makers are facing many practical considerations about how best to implement a vaccination programme. The supply of vaccines is insufficient for the global population, so decisions must be made as to which groups are prioritised for any vaccination and when. Furthermore, the aims of vaccination programmes will differ between countries, with some prioritising economic benefits that could stem from the relaxation of non-pharmaceutical interventions and others seeking simply to reduce the number of COVID-19 cases or deaths. This paper aims to share the experiences and lessons learned from conducting economic evaluations in Singapore and Thailand on hypothetical COVID-19 vaccines to provide a basis for other countries to develop their own contextualised economic evaluations, with particular focus on the key uncertainties, technical challenges, and characteristics that modellers should consider in partnership with key stakeholders. Which vaccines, vaccination strategies, and policy responses are most economically beneficial remains uncertain. It is therefore important for all governments to conduct their own analyses to inform local policy responses to COVID-19, including the implementation of COVID-19 vaccines in both the short and the long run. It is essential that such studies are designed, and ideally conducted, before vaccines are introduced so that policy decisions and implementation procedures are not delayed.