7 research outputs found

    Modelling reactive case detection strategies for interrupting transmission of Plasmodium falciparum malaria

    Get PDF
    As areas move closer to malaria elimination, a combination of limited resources and increasing heterogeneity in case distribution and transmission favour a shift to targeted reactive interventions. Reactive case detection (RCD), the following up of additional individuals surrounding an index case, has the potential to target transmission pockets and identify asymptomatic cases in them. Current RCD implementation strategies vary, and it is unclear which are most effective in achieving elimination.; OpenMalaria, an established individual-based stochastic model, was used to simulate RCD in a Zambia-like setting. The capacity to follow up index cases, the search radius, the initial transmission and the case management coverage were varied. Suitable settings were identified and probabilities of elimination and time to elimination estimated. The value of routinely collected prevalence and incidence data for predicting the success of RCD was assessed.; The results indicate that RCD with the aim of transmission interruption is only appropriate in settings where initial transmission is very low (annual entomological inoculation rate (EIR) 1-2 or prevalence approx

    Theory of reactive interventions in the elimination and control of malaria

    Get PDF
    Reactive case detection (RCD) is an integral part of many malaria control and elimination programmes and can be conceived of as a way of gradually decreasing transmission. However, it is unclear under what circumstances RCD may have a substantial impact on prevalence, how likely it is to lead to local elimination, or how effective it needs to be to prevent reintroduction after transmission has been interrupted.; Analyses and simulations of a discrete time compartmental susceptible-infectious-susceptible (SIS) model were used to understand the mechanisms of how RCD changes transmission dynamics and estimate the impact of RCD programmes in a range of settings with varying patterns of transmission potential and programme characteristics. Prevalence survey data from recent studies in Zambia were used to capture the effects of spatial clustering of patent infections.; RCD proved most effective at low prevalence. Increasing the number of index cases followed was more important than increasing the number of neighbours tested per index case. Elimination was achieved only in simulations of situations with very low transmission intensity and following many index cases. However, RCD appears to be helpful in maintaining the disease-free state after achieving malaria elimination (through other interventions).; RCD alone can eliminate malaria in only a very limited range of settings, where transmission potential is very low, and improving the coverage of RCD has little effect on this range. In other settings, it is likely to reduce disease burden. RCD may also help maintain the disease-free state in the face of imported infections. Prevalence survey data can be used to estimate a targeting ratio (the ratio of prevalence found through RCD to that in the general population) which is an important determinant of the effect of RCD

    The Transferability of Lipid-Associated Loci Across African, Asian and European Cohorts

    Get PDF
    Abstract: Most genome-wide association studies are based on samples of European descent. We assess whether the genetic determinants of blood lipids, a major cardiovascular risk factor, are shared across populations. Genetic correlations for lipids between European-ancestry and Asian cohorts are not significantly different from 1. A genetic risk score based on LDL-cholesterol-associated loci has consistent effects on serum levels in samples from the UK, Uganda and Greece (r = 0.23–0.28, p < 1.9 × 10−14). Overall, there is evidence of reproducibility for ~75% of the major lipid loci from European discovery studies, except triglyceride loci in the Ugandan samples (10% of loci). Individual transferable loci are identified using trans-ethnic colocalization. Ten of fourteen loci not transferable to the Ugandan population have pleiotropic associations with BMI in Europeans; none of the transferable loci do. The non-transferable loci might affect lipids by modifying food intake in environments rich in certain nutrients, which suggests a potential role for gene-environment interactions

    Model development, data, and public health: A combined approach against malaria

    Get PDF
    The health burden of infectious diseases remains substantial. Within ever-changing public health landscapes, characterised by complex disease biologies and limited operational resources, appropriate control strategies are often difficult to identify. In recent years, there has been an explosive increase in the popularity of mathematical modelling to bridge evidence gaps and support (policy) decision-making. To ensure accurate predictions, e.g. on the public health impact of new interventions, models must be grounded in plausible assumptions and calibrated to diverse data on multiple epidemiological and biological relationships. Through a comprehensive investigation of the modelling process from development to application, my research aims to prompt discussions about the role of infectious disease modelling in decision-making and about opportunities for modernisation. With application to malaria modelling, I present methodological advancements, structural analyses and discussions, and application case studies. This includes the development of a novel, machine learning-based calibration approach that outperforms previous methods. A generalisable framework for incorporating calibration data while accounting for contextual covariates is developed and applied to a database of PfPR-incidence records. I subsequently discuss the link between model calibration decisions and the model's later uses in simulating epidemiological relationships. Taking the leap from model development to application, I assess the use of surveillance-response interventions for malaria elimination, addressing the various technical challenges of quantifying elimination itself. Finally, I shift perspective towards the potentials and pitfalls of using modelling to support decision-making. The research presented in this thesis contributes to keeping malaria modelling up-to-date with computational methods and global health developments. Many of the principles presented here encompass general discussions of infectious disease modelling, and aim to encourage conversations about the place of modelling at the public health decision-making table

    Population health impact and economic evaluation of the CARDIO4Cities approach to improve urban hypertension management.

    No full text
    Cardiovascular disease (CVD) is the leading cause of mortality worldwide, with 80% of that mortality occurring in low- and middle-income countries. Hypertension, its primary risk factor, can be effectively addressed through multisectoral, multi-intervention initiatives. However, evidence for the population-level impact on cardiovascular (CV) event rates and mortality, and the cost-effectiveness of such initiatives is scarce as long-term longitudinal data is often lacking. Here, we model the long-term population health impact and cost-effectiveness of a multisectoral urban population health initiative designed to reduce hypertension, conducted in Ulaanbaatar (Mongolia), Dakar (Senegal), and in the district of Itaquera in São Paulo (Brazil) in collaboration with the local governments. We based our analysis on cohort-level data among hypertensive patients on treatment and control rates from a real-world effectiveness study of the CARDIO4Cities approach (built on quality of care, early access, policy reform, data and digital, Intersectoral collaboration, and local ownership). We built a decision tree model to estimate the CV event rates during implementation (1-2 years) and a Markov model to project health outcomes over 10 years. We estimated the number of CV events averted and quality-adjusted life-years gained (QALYs through the initiative and assessed its cost-effectiveness based on the costs reported by the funder using the incremental cost effectiveness ratio (ICER) and published thresholds. A one-way sensitivity analysis was performed to assess the robustness of the results. The modelled patient cohorts included 10,075 patients treated for hypertension in Ulaanbaatar, 5,236 in Dakar, and 5,844 in São Paulo. We estimated that 3.3-12.8% of strokes and 3.0-12.0% of coronary heart disease (CHD) events were averted during 1-2 years of implementation in the three cities. We estimated that over the subsequent 10 years, 3.6-9.9% of strokes, 2.8-7.8% of CHD events, and 2.7-7.9% of premature deaths would be averted. The estimated ICER was USD 748 QALY gained in Ulaanbaatar, USD 3091 in Dakar, and USD 784 in São Paulo. With that, the intervention was estimated to be cost-effective in Ulaanbaatar and São Paulo. For Dakar, cost-effectiveness was met under WHO-CHOICE standards, but not under more conservative standards adjusted for purchasing power parity (PPP) and opportunity costs. The findings were robust to the sensitivity analysis. Our results provide evidence that the favorable impact of multisector systemic interventions designed to reduce the hypertension burden extend to long-term population-level CV health outcomes and are likely cost-effective. The CARDIO4Cities approach is predicted to be a cost-effective solution to alleviate the growing CVD burden in cities across the world
    corecore