Simulation of the costs and consequences of potential vaccines for Plasmodium falciparum malaria

Malaria is one of the major public health problems for low income countries, a major global health priority, and it has also a dramatic economic impact. Funding for malaria control is on the rise and both international donors and governments of malaria endemic countries need tools and evidence to assess which are the best and most efficient strategies to control malaria. Standard tools traditionally used to assess the public health and economic impact of malaria control interventions, such as efficacy trials and static cost-effectiveness analyses, capture only short term effects. They fail to take into account long term and dynamic effects due to the complex dynamic of malaria, and to the interactions between intervention effectiveness and health systems. This thesis is part of a wider research project, conducted by the Swiss Tropical Institute, aimed at developing integrated mathematical models for predicting the epidemiologic and economic effects of malaria control interventions. The thesis specifically combines innovative mathematical models of malaria epidemiology with innovative modeling of the health system and of the costs and effects of malaria control interventions. These approaches are applied to simulate the epidemiological impact and the cost-effectiveness of hypothetical malaria vaccines. Chapter 1 describes why malaria is a public health priority, the increasing relevance of conducting economic analyses in the health sector, the economic evaluation framework, and the economic consequences of malaria. Chapter 2 presents an approach to dynamically modeling the case management of malaria in Sub-Saharan Africa. Chapter 3 describes an approach to costing the delivery of a hypothetical malaria vaccine through the Expanded Programme on Immunization (EPI), on the basis of the information available on the likely characteristics of the vaccine most advanced in development. The results show that, although the vaccine price determines most of the total delivery costs, other costs are relevant and should be taken into account before planning its inclusion into the EPI. Chapter 4 and 5 combine modeling of malaria transmission and control with predictions of parasitologic and clinical outcomes, to assess the epidemiological effects and the potential short and long term cost-effectiveness of a pre-erythrocytic vaccine delivered via the EPI. The results suggest a significant impact on morbidity and mortality for a range of assumptions about the vaccine characteristics, but only small effects on transmission intensities. They also suggest that at moderate to low vaccine prices, a pre-erythrocytic vaccine providing partial protection, and delivered via the EPI, may be a cost-effective intervention in countries where malaria is endemic. Chapter 6 simulates the cost-effectiveness of three different vaccine types: Preerythrocytic vaccines (PEV), Blood stage vaccines (BSV), mosquito-stage transmission-blocking vaccines (MSTBV), and combinations of these, each delivered via a range of delivery modalities (EPI, EPI with booster, and mass vaccination combined with EPI). The simulations presented in this Chapter show that PEV are more effective and cost-effective in low transmission settings. In contrast to PEV, BSV are predicted to be more effective and cost-effective at higher transmission settings than low transmission. Combinations of BSV and PEV are predicted to be more efficient than PEV, in particular in moderate to high transmission settings, but compared to BSV, combinations are more cost-effective in mostly moderate to low transmission settings. Combinations of MSTBV and PEV or PEV and BSV do not increase the effectiveness or the cost-effectiveness compared to PEV and BSV alone when delivered through the EPI. However, when applied with EPI and mass vaccinations, combinations with MSTBV provide substantial incremental health benefits at low incremental costs in all transmission settings. This highlights the importance of developing other vaccine candidates as they have potential to facilitate a PEV/BSV combination vaccine to be more beneficial. Chapter 6 simulations indicate that the transmission setting and the vaccine delivery modality adopted are important determinants of the cost-effectiveness of malaria vaccines. Alternative vaccine delivery modalities to the EPI may sometimes, but not always, be more costeffective than the EPI. In general, at moderate vaccine prices, most vaccines and delivery modalities simulated are likely to present cost-effectiveness ratios, which compare favorably with those of other malaria interventions. Chapter 7 discusses the implications of approaches and results presented in the thesis, their limitations and potentials. The approach used in this research represents the first attempt to develop dynamic models of malaria transmission and disease to evaluate the cost-effectiveness of malaria control interventions. Combining advanced stochastic simulation modeling of malaria epidemiology with health system dynamic modeling is a crucial innovation proposed by the approaches presented in this thesis. In fact, while it is well known that the interactions between malaria and health systems take place under temporal and spatial heterogeneity, integration of health system metrics in epidemiological modeling is rarely done. The cost-effectiveness analyses are based on an approach to model the health system characteristics of the settings where a new intervention, such as a malaria vaccine, will be implemented, The rationale of this approach rests on: a) the need to capture the long term health and economic impact due to the interactions between malaria control interventions and the health system - e.g. the impact on the health system of variations in transmission intensity due to an intervention; b) the recognition that policy makers are more interested in cost-effectiveness predictions that are specifically tailored to their health system context rather than on a hypothetical one. The approaches developed provide a platform that could be used to model the effects of integrated strategies for malaria control. The increase in computer power available makes possible simulating complex scenarios with several dimensions/variables in a relatively short time. This, coupled with the increasing availability of information on malaria endemic countries health systems, should be exploited to further modeling health system dynamics, which is fundamental to assess integrated malaria control strategies. The models and the approaches presented could be applied to inform decisions at several levels. Further applications might include simulating the epidemiology, the costs and consequences of packages of interventions, allowing estimating both effectiveness and (technical and allocative) efficiency. This would, thus, help policy makers to determine which intervention or, most likely, which package of interventions, might be most effective and efficient in a particular area. Additionally, it would be possible to simulate the implications of coverage extension of malaria control interventions, and of different strategies and service delivery modalities that can reach the poorest. The approaches developed could also allow identification of areas where intensified malaria control is the only feasible option, areas where malaria elimination is more likely to be achieved, the incremental cost-effectiveness of proceeding to elimination once a high level of control has been achieved, the optimal transmission levels at which to change strategy, and, in principle, economies of scope and or synergies in effectiveness and cost-effectiveness of new strategies. These are all research areas that have been identified as fundamental in the research agenda to be set up following the recent call for malaria elimination

Effective coverage and systems effectiveness for malaria case management in sub-saharan african countries

Scale-up of malaria preventive and control interventions over the last decade resulted in substantial declines in mortality and morbidity from the disease in sub-Saharan Africa and many other parts of the world. Sustaining these gains will depend on the health system performance. Treatment provides individual benefits by curing infection and preventing progression to severe disease as well as community-level benefits by reducing the infectious reservoir and averting emergence and spread of drug resistance. However many patients with malaria do not access care, providers do not comply with treatment guidelines, and hence, patients do not necessarily receive the correct regimen. Even when the correct regimen is administered some patients will not adhere and others will be treated with counterfeit or substandard medication leading to treatment failures and spread of drug resistance. We apply systems effectiveness concepts that explicitly consider implications of health system factors such as treatment seeking, provider compliance, adherence, and quality of medication to estimate treatment outcomes for malaria case management. We compile data for these indicators to derive estimates of effective coverage for 43 high-burden Sub-Saharan African countries. Parameters are populated from the Demographic and Health Surveys and other published sources. We assess the relative importance of these factors on the level of effective coverage and consider variation in these health systems indicators across countries. Our findings suggest that effective coverage for malaria case management ranges from 8% to 72% in the region. Different factors account for health system inefficiencies in different countries. Significant losses in effectiveness of treatment are estimated in all countries. The patterns of inter-country variation suggest that these are system failures that are amenable to change. Identifying the reasons for the poor health system performance and intervening to tac them become key priority areas for malaria control and elimination policies in the region

A network analysis of patient referrals in two district health systems in Tanzania

Patient referral systems are fragile and overlooked components of the health system in Tanzania. Our study aims at exploring patient referral networks in two rural districts in Tanzania, Kilolo and Msalala. Firstly, we ask whether secondary-level facilities act as gatekeepers, mediating referrals from primary- to tertiary-level facilities. Secondly, we explore the facility and network-level determinants of patient referrals focusing on treatment of childhood illnesses and non-communicable diseases. We use data collected across all public health facilities in the districts in 2018. To study gatekeeping, we employ descriptive network analysis tools. To explore the determinants of referrals, we use exponential random graph models. In Kilolo, we find a disproportionate share of patients referred directly to the largest hospital due to geographical proximity. In Msalala, small and specialized secondary-level facilities seem to attract more patients. Overall, the results call for policies to increase referrals to secondary facilities avoiding expensive referrals to hospitals, improving timeliness of care and reducing travel-related financial burden for households

Burden of Covid-19 restrictions: National, regional and global estimates

Background: A growing literature has documented the high global morbidity, mortality and mental health burden associated with the current Covid-19 pandemic. In this paper, we aimed to quantify the total utility and quality of life loss resulting from Covid-19-related government restrictions imposed at the national, regional and global levels. Methods : We conducted quality of life online surveys in France, India, Italy, UK and the United States of America between June 21st and September 13th 2021, and used regression models to estimate the average quality of life loss due to light and severe restrictions in these countries. We then combined estimated disutility weights from the pooled sample with the latest data on Covid-19 restrictions exposure in each country to estimate the total disutility generated by restrictions at the national, regional and global level. We also embedded a discrete choice experiment (DCE) into the online survey to estimate average willingness to pay to avoid specific restrictions. Findings : A total of 947 surveys were completed. Thirty-five percent of respondents were female, and 69.5% were between 18 and 39 years old. The weighted average utility weight was 0.71 (95% CIs 0.69−0.74) for light restrictions, and 0.65 (0.63−0.68) for severe restrictions. At the global scale, this implies a total loss of 3259 million QALYs (95% 3021, 3496) as of September 6th, 2021, with the highest burden in lower and upper middle-income countries. Utility losses appear to be particularly large for closures of schools and daycares as well as restaurants and bars, and seem relatively small for wearing masks and travel restrictions. Interpretation: The results presented here suggest that the QALY losses due to restrictions are substantial. Future mitigation strategies should try to balance potential reductions in disease transmission achievable through specific measures against their respective impact on quality of life. Additional research is needed to determine differences in restriction-specific disutilities across countries, and to determine optimal policy responses to similar future disease threats