A realist impact evaluation of a tool to strengthen equity in local government policy-making.

BACKGROUND: Local governments have a critical role to play in addressing health inequities. Health equity impact assessments are recommended to help governments apply an equity lens to the development and implementation of policies and programs. Despite evidence of equity-positive benefits of such tools, adoption remains limited, prompting calls for evaluations to assess their impact and identify factors that will promote uptake across various contexts. METHODS: We conducted a mixed method study to evaluate the impact of an equity impact assessment (EIA) tool and process on policies and organisational capacity in a local government in Victoria, Australia, and identify factors that influenced this impact. We analysed 33 documents related to 18 EIAs, and conducted surveys (n = 40) and in-depth interviews (n = 17) with staff involved in EIAs. RESULTS: Almost all (17 of 18) EIAs resulted in equity-positive changes to policies and programs, most frequently addressing individual-level factors, such as making community communications and consultations more accessible to under-represented or under-served groups. Structural-level recommendations from one EIA, such as increasing diversity in decision-making panels, were found to impact both the current policy and a broad range of future, related projects and services. Improvements in equity-centric organisational culture and capacity (including staff awareness, skills and confidence) and increased engagement with under-represented communities were also reported. Factors perceived to influence the impact of EIA's related to organisational commitment and capacity to prioritise equity, process-level factors related to the type and timing of EIAs, and extent of implementation support. CONCLUSION: Our study supports wider uptake of health equity impact assessments in local government policies and programs. Legislation, leadership and resources from upper-tiers of government can help increase the adoption of equity tools to reduce disparities in population health.

Optimizing BenMAP health impact assessment with meteorological factor driven machine learning models.

This study aims to address accuracy challenges in assessing air pollution health impacts using Environmental Benefits Mapping and Analysis Program (BenMap), caused by limited meteorological factor data and missing pollutant data. By employing data increment strategies and multiple machine learning models, this research explores the effects of data volume, time steps, and meteorological factors on model prediction performance using several years of data from Tianjin City as an example. The findings indicate that increasing training data volume enhances the performance of Random Forest Regressor (RF) and Decision Tree Regressor (DT) models, especially for predicting CO, NO2, and PM2.5. The optimal prediction time step varies by pollutant, with the DT model achieving the highest R2 value (0.99) for CO and O3. Combining multiple meteorological factors, such as atmospheric pressure, relative humidity, and dew point temperature, significantly improves model accuracy. When using three meteorological factors, the model achieves an R2 of 0.99 for predicting CO, NO2, PM10, PM2.5, and SO2. Health impact assessments using BenMap demonstrated that the predicted all-cause mortality and specific disease mortalities were highly consistent with actual values, confirming the model's accuracy in assessing health impacts from air pollution. For instance, the predicted and actual all-cause mortality for PM2.5 were both 3120; for cardiovascular disease, both were 1560; and for respiratory disease, both were 780. To validate its generalizability, this method was applied to Chengdu, China, using several years of data for training and prediction of PM2.5, CO, NO2, O3, PM10, and SO2, incorporating atmospheric pressure, relative humidity, and dew point temperature. The model maintained excellent performance, confirming its broad applicability. Overall, we conclude that the machine learning and BenMap-based methods show high accuracy and reliability in predicting air pollutant concentrations and health impacts, providing a valuable reference for air pollution assessment.

Better accounting for long-term health effects in economic assessments: an illustration for air pollution in the Canton of Geneva.

OBJECTIVES: We propose a general framework for estimating long-term health and economic effects that takes into account four time-related aspects. We apply it to a reduction in exposure to air pollution in the Canton of Geneva. STUDY DESIGN: Methodological developments on the evaluation of long-term economic and health benefits, with an empirical illustration. METHODS: We propose a unified framework-the comprehensive impact assessment (CIA)-to assess the long-term effects of morbidity and mortality in health and economic terms. This framework takes full account of four time-related issues: cessation lag, policy/technical implementation timeframe, discounting and time horizon. We compare its results with those obtained from standard quantitative health impact assessment (QHIA) in an empirical illustration involving air pollution reduction in the canton of Geneva. RESULTS: We find that by neglecting time issues, the QHIA estimates greater health and economic benefits than the CIA. The overestimation is about 50% under reasonable assumptions and increases ceteris paribus with the magnitude of the cessation lag and the discount factor. It decreases both with the time horizon and with the implementation timeframe. CONCLUSION: A proper evaluation of long-term health and economic effects is an important issue when they are to be used in cost-benefit analyses, particularly for mortality, which often represents the largest fraction. We recommend using the CIA to calculate more accurate values.

A systematic review of whether Health Impact Assessment frameworks support best practice principles.

OBJECTIVES: Health Impact Assessment (HIA) is an evidence-based approach to assess the likely public health impacts of a policy or plan in any sector. Several HIA frameworks are available to guide practitioners doing a HIA. This systematic review sought to determine whether these support practitioners to meet best practice principles defined by the International Association for Impact Assessment. STUDY DESIGN: This was a systematic review. METHODS: Three complementary search strategies were used to identify frameworks in June 2022. We used three databases to find completed HIAs published in the last five years and hand-searched their reference lists for frameworks. We also searched 23 HIA repositories using Google's Advanced function and contacted HIA practitioners via two international mailing lists. We used a bespoke quality appraisal tool to assess frameworks against the principles. RESULTS: The search identified 24 HIA frameworks. None of the frameworks achieved a 'good' rating for all best practice principles. Many identified the principles but did not provide guidance on how to meet them at all HIA steps. The highest number of frameworks were rated 'good' for ethical use of evidence and comprehensive approach to health (n = 15). Eight frameworks were rated as 'good' for participation, and two for equity. The highest number of frameworks rated 'poor' for sustainability (n = 11). CONCLUSIONS: There is marked variation in the degree to which HIA frameworks support the best practice principles. HIA practitioners could select elements from different frameworks for practical guidance to meet all the best practice principles.

Risk-based public health impact assessment for drinking water contamination emergencies.

Chemical spills in surface waters pose a significant threat to public health and the environment. This study investigates the public health impacts associated with organic chemical spill emergencies and explores timely countermeasures deployable by drinking water facilities. Using a dynamic model of a typical multi-sourced New England drinking water treatment facility and its distribution network, this study assesses the impacts of various countermeasure deployment scenarios, including source switching, enhanced coagulation via poly­aluminum chloride (PACl), addition of powdered activated carbon (PAC), and temporary system shutdown. This study reveals that the deployment of multiple countermeasures yields the most significant reduction in total public health impacts, regardless of the demand and supply availability. With the combination PAC deployed first with other countermeasures proving to be the most effective strategies, followed by the combination of facility shutdowns. By understanding the potential public health impacts and evaluating the effectiveness of countermeasures, authorities can develop proactive plans, secure additional funding, and enhance their capacity to mitigate the consequences of such events. These insights contribute to safeguarding public health and improving the resilience of drinking water systems in the face of the ever-growing threat of chemical spills.

Health Impact Assessment in protected areas: a proposal for urban contexts in Brazil.

The use of Health Impact Assessment (HIA) in the establishment of an urban protected area can enhance the positive impacts and mitigate the negative impacts resulting from its implementation. Brazil hosts some of the most important biodiversity hotspots in the world and the HIA may benefit biodiversity and human health. These areas are commonly created without any preceding survey to assess their impacts on health. Protected areas located in urban zones are essential to maintain environmental balance and quality of life in cities. It promotes positive impacts on health, providing ecosystem services and salutogenic benefits. However, they can generate negative impacts such as the violation of human rights, property speculation, spread of vectorial diseases, and psychosocial stress. Based on the identification of the potential impacts of urban protected areas on health and best practices, this qualitative and exploratory study justifies the use of HIA in urban protected areas, especially in the Brazil, and indicates the main elements for the construction of a methodological approach to contribute to the Sustainable Development Goals and one of its alternatives, the Buen Vivir approach.

Current status and influencing factors of policy identification in health impact assessment: a case study of Zhejiang Province.

BACKGROUND: Health impact assessment (HIA) is a procedure, method and tool for evaluating the potential health impacts of policies, plans and construction projects, as well as the distribution of these impacts on population. Majority of international studies on health impact assessment have focussed on conceptual papers or case evaluations, neglecting participants' views on policies. METHODS: A semi-structured interview with 30 health impact assessment experts was employed in this study, and the Nvivo software was utilized to analyse factors that influence policy identification. Subsequently, a multi-stage stratified random sampling method was adopted to survey 655 pilot staff members involved in health impact assessment in Zhejiang Province. Descriptive statistics were used to describe the current status and identify the factors influencing policy identification. In addition, hierarchical linear regression analysis and structural equation modelling were employed to determine the relationship between policy identification and influencing factors. RESULTS: Statistically significant differences were found among participants in the level of identification of policies across three dimensions. The policy sentiment dimension had the highest score (4.137 ± 0.664), followed by policy cognition (4.075 ± 0.632) and policy evaluation (3.631 ± 0.797) dimensions. Subject trust had a positive impact on policy cognition (ß = 0.503, P < 0.001), policy sentiment (ß = 0.504, P < 0.001) and policy evaluation (ß = 0.465, P < 0.001). Procedural justice had a positive impact on policy sentiment (ß = 0.085, P < 0.01) and policy evaluation (ß = 0.084, P < 0.05), but not policy cognition (ß = 0.056, P > 0.05). Policy identification is influenced by age and average monthly salary among other factors. CONCLUSION: These results highlight the importance of subjective trust and procedural justice in policy identification of health impact assessment. They provide valuable insights to developing interventions to overcome barriers to the implementation and enhancement of global identification of policies. Going forward, cross-sectoral synergies, enhanced international communication and training to increase participants' trust in the policy should be optimized to improve health impact assessment. Additional measures should be taken, such as ensuring seamless communication channels, embedding health impact assessment in administrative mechanisms, and establishing strong oversight and grievance mechanisms to improve fairness and transparency in the implementation and results of health impact assessment.

Model Choice for Quantitative Health Impact Assessment and Modelling: An Expert Consultation and Narrative Literature Review.

BACKGROUND: Health impact assessment (HIA) is a widely used process that aims to identify the health impacts, positive or negative, of a policy or intervention that is not necessarily placed in the health sector. Most HIAs are done prospectively and aim to forecast expected health impacts under assumed policy implementation. HIAs may quantitatively and/ or qualitatively assess health impacts, with this study focusing on the former. A variety of quantitative modelling methods exist that are used for forecasting health impacts, however, they differ in application area, data requirements, assumptions, risk modelling, complexities, limitations, strengths, and comprehensibility. We reviewed relevant models, so as to provide public health researchers with considerations for HIA model choice. METHODS: Based on an HIA expert consultation, combined with a narrative literature review, we identified the most relevant models that can be used for health impact forecasting. We narratively and comparatively reviewed the models, according to their fields of application, their configuration and purposes, counterfactual scenarios, underlying assumptions, health risk modelling, limitations and strengths. RESULTS: Seven relevant models for health impacts forecasting were identified, consisting of (i) comparative risk assessment (CRA), (ii) time series analysis (TSA), (iii) compartmental models (CMs), (iv) structural models (SMs), (v) agent-based models (ABMs), (vi) microsimulations (MS), and (vii) artificial intelligence (AI)/machine learning (ML). These models represent a variety in approaches and vary in the fields of HIA application, complexity and comprehensibility. We provide a set of criteria for HIA model choice. Researchers must consider that model input assumptions match the available data and parameter structures, the available resources, and that model outputs match the research question, meet expectations and are comprehensible to end-users. CONCLUSION: The reviewed models have specific characteristics, related to available data and parameter structures, computational implementation, interpretation and comprehensibility, which the researcher should critically consider before HIA model choice.

The role of ecotoxicology in the health impact assessment: an innovative ecosystem approach for the protection of human health in Italy.

BACKGROUND: The Health Impact Assessment (HIA) is a procedure with the aim to protect the populations exposed to the impacts deriving from the establishment or upgrading of large industrial enterprises, i.e. large combustion plants (>300 MWth). In Italy a guideline for the HIA procedure has been published in compliance with the 2014/52/EU Directive on the Environmental Impact Assessment (EIA) requirements. Italian HIA procedure. An ecotoxicological approach has been included for the first time in the HIA procedure with the aim to detect toxic effects caused by unknown not-monitored contaminants or mixtures in the ecosystem components affected by the potential emissions, discharges and releases of large industrial enterprises. Ecotoxicology plays an important bridge role between environment and human health in the scoping and monitoring step of the HIA procedure with a key function of early warning system and screening. The aim of this paper is to present the Italian experience in the first three years of the application of the new approach, proposing recommendations on specific case studies. Conclusion and future perspective. 80% of enterprises, that applied HIA, have delivered a robust, integrated and detailed documentation in relation to the ecotoxicological assessment, this positive feedback will generate environmental and human health benefits to the areas where the plants are established.

Walkability and urban built environments-a systematic review of health impact assessments (HIA).

BACKGROUND: Urban environments are important determinants of human health. The term walkability summarizes features of the urban built environment that promote walking and other types of physical activity. While the beneficial effects of active and public transport have been well established, the health impact of other features of walkability are less well documented. METHODS: We conducted a systematic review of health impact assessments (HIAs) of walkability. Studies were identified through PUBMED and Science Direct, from two German websites related to urban health and reference tracking. Finally, 40 studies were included in the present review. We applied qualitative thematic analysis to summarize the major results from these studies. RESULTS: Most of the HIAs (n = 31) reported the improvement of health or health behaviour resulting from an investigated project or policy. However, three HIAs reported a lack of improvement or even a decrease of health status. In parallel, 13 HIAs reported a gain in economic value, whereas one reported a lack or loss of economic effects. Moreover, three HIAs reported on social effects and six HIAs gave additional recommendations for policies or the implementation of projects or HIAs. CONCLUSIONS: Most HIAs investigate the impact of increasing active or public transport. Other features of walkability are less well studied. With few exceptions, HIAs document beneficial impacts of improving walkability on a variety of health outcomes, including reductions of mortality and non-communicable diseases.

Implementation of Health Impact Assessment in the Healthcare System of the Republic of Kazakhstan.

The Health Impact Assessment (hereinafter referred to as HIA) is an effective method for predicting potential health impacts from decisions. Little is known about the implementation of the HIA in the Republic of Kazakhstan (further, RK). In addition, the Russian language literature has not yet been reviewed in terms of HIA-related knowledge. By conducting a literature review of enabling factors, including Russian language literature, on the implementation of the HIA and studying governance systems in RK, we aim to suggest an implementation process to implement the HIA in RK. After careful analysis of the governance system, we suggest set up of a HIA support unit under the National Scientific Center for Health Development and discuss the possible benefits. The proposed center should guide the implementation of the HIA in RK.

Health impact assessment of local policies: methodology and tools.

The aim of this work was to design some tools and a procedure for performing the Health Impact Assessment of municipal policies. A working group made up of municipal and public health specialists from the Valencian Community (Spain) was set up. After reviewing the tools used in other contexts, the Fem Salut? questionnaire for the simplified Health Impact Assessment of regional policies was adapted for use at the local level. A pilot study was carried out in six municipalities and local initiatives promoted by different sectors were analysed. Two workshops were held per municipality (with specialists and with citizens) and participatory techniques were used to identify the possible impacts on the social determinants of health, the population groups more particularly affected and the proposals for improvement. The feasibility of the methodology and the difficulties involved in carrying it out were discussed. A procedure was defined for the Health Impact Assessment of local initiatives in six steps: Describe (the municipality and the project), Extract (screening phase), Co-produce (participatory workshops), Integrate (the scientific evidence with the qualitative information obtained), Disseminate (to politicians, specialists and community) and Evaluate (direct and indirect results) (DECIDE). A guide was developed to facilitate its application at the local level along with two complementary tools (a questionnaire and worksheets). The technical group rated the process as simple and flexible, as well as being easy to adapt to the characteristics of the municipality and project. In addition to the cross-sectoral approach, the incorporation of citizen participation in the process is an important added value.

Health impact assessment should be based on correct methods.

The methodology of health impact assessment (HIA), originally proposed by WHO, is widely used to predict the potential health effects in a community living in a place in which a new project (e.g., an industrial plant) will be implemented. One of the key quantities to calculate the impact (i.e., the number of attributable cases) is the baseline (i.e., before the project implementation) rate of selected diseases in the community. In a recent paper on this journal, this methodology has been challenged. Specifically, the use of baseline rate has been questioned, proposing to use only the fraction of the baseline rate due to the exposures related to the project, and not the rate due to all risk factors for the disease. In this commentary, we argue that the proposal is logically and epidemiologically unsound, and devoid of scientific motivation. The conclusion that the traditional approach overestimates the health impact should be rejected as based on flawed assumptions. On the contrary, the proposal may produce a (seriously biased) underestimation of attributable cases.

Health Impact Assessment: A Missed Opportunity for MCH Professionals in Their Quest to Address the Social Determinants of Health.

INTRODUCTION: Public health professionals, especially ones concerned with maternal and child health (MCH), need to engage in cross-sector collaborations to address social determinants of health. Health Impact Assessment (HIA) systematically brings public health perspectives into non-health decision-making contexts that influence social determinants. Alignment of MCH and HIA practice has not previously been documented. METHODS: An exploratory review of HIAs conducted in the United States considered several dimensions of MCH-HIA alignment and produced data to test the hypothesis that HIAs involving MCH stakeholders are more likely to address MCH populations and relevant measures. The review examined three key variables for each HIA: inclusion of MCH-focused stakeholders, level of focus on MCH populations, and presence of MCH-relevant content. RESULTS: Of the 424 HIAs included in the database of US HIAs, 350 were included in this review. Twenty-four percent (84) included MCH-focused stakeholders, and 42% (148) focused on MCH populations. Ninety percent (317) included metrics or content relevant to at least one Title V National Performance Measure (NPM). HIAs that clearly included MCH stakeholders had seven times the odds of including both a focus on MCH populations and at least one NPM-relevant topic compared to HIAs that did not clearly include MCH stakeholders (OR 6.98; 95% CI 3.99, 12.20). DISCUSSION: Despite low engagement of MCH stakeholders in HIAs, many still consider MCH populations and measures. Intentional engagement of MCH workforce in HIAs could ensure greater alignment with existing MCH priorities (such as addressing the social determinants of health and equity) in a given jurisdiction.

The Built Environment and Health in Low- and Middle-Income Countries: a Review on Quantitative Health Impact Assessments.

PURPOSE OF REVIEW: Features and attributes of the built environment (BE) impact positively and negatively on health, especially in cities facing unprecedented urban population growth and mass motorization. A common approach to assess the health impacts of built environment is health impact assessment (HIA), but it is rarely used in low- and middle-income countries (LMICs) where urbanization rates are fastest. This article reviews selected HIA case studies from LMICs and reports the methods and tools used to support further implementation of quantitative HIAs in cities of LMICs. RECENT FINDINGS: In total, 24 studies were reviewed across Algeria, Brazil, China, India, Iran, Kenya, Thailand, Turkey, and Mauritius. HIAs examine specific pathways through which the built environment acts: air pollution, noise, physical activity, and traffic injury. Few HIAs of BE addressed more than one exposure pathway at a time, and most studies focused on air pollution across the sectors of transport and energy. A wide number of tools were used to conduct exposure assessment, and different models were applied to assess health impacts of different exposures. Those HIAs rely on availability of local concentration data and often use models that have set exposure-response functions (ERFs). ERFs were not adapted to local populations except for HIAs conducted in China. HIAs of BE are being successfully conducted in LMICs with a variety of tools and datasets. Scaling and expanding quantitative health impact modeling in LMICs will require further study on data availability, adapted models/tools, low technical capacity, and low policy demand for evidence from modeling studies. As case studies with successful use of evidence from modeling emerge, the uptake of health impact modeling of BE is likely to increase in favor of people and planet.

Using dynamic time warping self-organizing maps to characterize diurnal patterns in environmental exposures.

Advances in measurement technology are producing increasingly time-resolved environmental exposure data. We aim to gain new insights into exposures and their potential health impacts by moving beyond simple summary statistics (e.g., means, maxima) to characterize more detailed features of high-frequency time series data. This study proposes a novel variant of the Self-Organizing Map (SOM) algorithm called Dynamic Time Warping Self-Organizing Map (DTW-SOM) for unsupervised pattern discovery in time series. This algorithm uses DTW, a similarity measure that optimally aligns interior patterns of sequential data, both as the similarity measure and training guide of the neural network. We applied DTW-SOM to a panel study monitoring indoor and outdoor residential temperature and particulate matter air pollution (PM2.5) for 10 patients with asthma from 7 households near Salt Lake City, UT; the patients were followed for up to 373 days each. Compared to previous SOM algorithms using timestamp alignment on time series data, the DTW-SOM algorithm produced fewer quantization errors and more detailed diurnal patterns. DTW-SOM identified the expected typical diurnal patterns in outdoor temperature which varied by season, as well diurnal patterns in PM2.5 which may be related to daily asthma outcomes. In summary, DTW-SOM is an innovative feature engineering method that can be applied to highly time-resolved environmental exposures assessed by sensors to identify typical diurnal (or hourly or monthly) patterns and provide new insights into the health effects of environmental exposures.

Evaluation of human exposure to parabens in north eastern Poland through hair sample analysis.

Parabens (PBs) are a group of substances commonly used in industry. They also pollute the environment, penetrate into living organisms and adversely affect various internal organs. During this study, the degree of exposure of people living in Olsztyn, a city in north eastern Poland, to selected parabens most often used in industry was studied. The chemicals under investigation included: methyl paraben-MePB, ethyl paraben-EtPB, propyl paraben-PrPB, benzyl paraben BePB and butyl paraben -BuPB. To this aim, hair samples collected from the scalps of 30 volunteers were analyzed using a liquid chromatography-mass spectrometry technique. All PBs studied were present in a high percentage of analyzed samples (from 76.7% in the case of BePB to 100% in the case of MePB and PrPB). The mean concentration levels were 4425.3 pg/mg for MeBP, 704.0 pg/mg for EtPB, 825.7 pg/mg for PrPB, 135.2 pg/mg for BePB and 154.5 pg/mg for BuPB. Significant differences in PB concentration levels between particular persons were visible. On the other hand, gender, age and artificial hair coloring did not cause statistically significant differences in PB levels. Obtained results have clearly indicated that people living in north eastern Poland are exposed to various PBs, and therefore these substances may affect their health status. However, the evaluation of PBs influence on human health requires further research.

ICP-MS Determination of 23 Elements of Potential Health Concern in Liquids of e-Cigarettes. Method Development, Validation, and Application to 37 Real Samples.

The lack of interest in the determination of toxic elements in liquids for electronic cigarettes (e-liquids) has so far been reflected in the scarce number of accurate and validated analytical methods devoted to this aim. Since the strong matrix effects observed for e-liquids constitute an exciting analytical challenge, the main goal of this study was to develop and validate an ICP-MS method aimed to quantify 23 elements in 37 e-liquids of different flavors. Great attention has been paid to the critical phases of sample pre-treatment, as well as to the optimization of the ICP-MS conditions for each element and of the quantification. All samples exhibited a very low amount of the elements under investigation. Indeed, the sum of their average concentration was of ca. 0.6 mg kg-1. Toxic elements were always below a few tens of a µg per kg-1 and, very often, their amount was below the relevant quantification limits. Tobacco and tonic flavors showed the highest and the lowest concentration of elements, respectively. The most abundant elements came frequently from propylene glycol and vegetal glycerin, as confirmed by PCA. A proper choice of these substances could further decrease the elemental concentration in e-liquids, which are probably barely involved as potential sources of toxic elements inhaled by vapers.

COVID-19 vaccination in Sindh Province, Pakistan: A modelling study of health impact and cost-effectiveness.

BACKGROUND: Multiple Coronavirus Disease 2019 (COVID-19) vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh Province, Pakistan (population: 48 million). METHODS AND FINDINGS: We fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalisation outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability-adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario. We project that 1 year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70% efficacy and 2.5-year duration of protection is likely to avert around 0.9 (95% credible interval (CrI): 0.9, 1.0) million cases, 10.1 (95% CrI: 10.1, 10.3) thousand deaths, and 70.1 (95% CrI: 69.9, 70.6) thousand DALYs, with an ICER of $27.9 per DALY averted from the health system perspective. Under a broad range of alternative scenarios, we find that initially prioritising the older (65+) population generally prevents more deaths. However, unprioritised distribution has almost the same cost-effectiveness when considering all outcomes, and both prioritised and unprioritised programmes can be cost-effective for low per-dose costs. High vaccine prices ($10/dose), however, may not be cost-effective, depending on the specifics of vaccine performance, distribution programme, and future pandemic trends. The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age-specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses. This study is limited by model approximations, available data, and future uncertainty. Because the model is a single-population compartmental model, detailed impacts of nonpharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritising groups like healthcare or other essential workers. The model is only fitted to the reported case and death data, which are incomplete and not disaggregated by, e.g., age. Finally, because the future impact and implementation cost of NPIs are uncertain, how these would interact with vaccination remains an open question. CONCLUSIONS: COVID-19 vaccination can have a considerable health impact and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact. However, the advantage of prioritising older, high-risk populations is smaller in generally younger populations. This reduction is especially true in populations with more past transmission, and if the vaccine is likely to further impede transmission rather than just disease. Those conditions are typical of many low- and middle-income countries.