8 research outputs found

    Emulator-based Bayesian calibration of the CISNET colorectal cancer models

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    PURPOSE: To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET) 's SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally validate the model-predicted outcomes to calibration targets.METHODS: We used Latin hypercube sampling to sample up to 50,000 parameter sets for each CISNET-CRC model and generated the corresponding outputs. We trained multilayer perceptron artificial neural networks (ANN) as emulators using the input and output samples for each CISNET-CRC model. We selected ANN structures with corresponding hyperparameters (i.e., number of hidden layers, nodes, activation functions, epochs, and optimizer) that minimize the predicted mean square error on the validation sample. We implemented the ANN emulators in a probabilistic programming language and calibrated the input parameters with Hamiltonian Monte Carlo-based algorithms to obtain the joint posterior distributions of the CISNET-CRC models' parameters. We internally validated each calibrated emulator by comparing the model-predicted posterior outputs against the calibration targets.RESULTS: The optimal ANN for SimCRC had four hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had one hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 hours for SimCRC, MISCAN-Colon, and CRC-SPIN, respectively. The mean of the model-predicted outputs fell within the 95% confidence intervals of the calibration targets in 98 of 110 for SimCRC, 65 of 93 for MISCAN, and 31 of 41 targets for CRC-SPIN.CONCLUSIONS: Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis, like the CISNET CRC models.</p

    Moving away from the "unit cost". Predicting country-specific average cost curves of VMMC services accounting for variations in service delivery platforms in sub-Saharan Africa.

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    BACKGROUND: One critical element to optimize funding decisions involves the cost and efficiency implications of implementing alternative program components and configurations. Program planners, policy makers and funders alike are in need of relevant, strategic data and analyses to help them plan and implement effective and efficient programs. Contrary to widely accepted conceptions in both policy and academic arenas, average costs per service (so-called "unit costs") vary considerably across implementation settings and facilities. The objective of this work is twofold: 1) to estimate the variation of VMMC unit costs across service delivery platforms (SDP) in Sub-Saharan countries, and 2) to develop and validate a strategy to extrapolate unit costs to settings for which no data exists. METHODS: We identified high-quality VMMC cost studies through a literature review. Authors were contacted to request the facility-level datasets (primary data) underlying their results. We standardized the disparate datasets into an aggregated database which included 228 facilities in eight countries. We estimated multivariate models to assess the correlation between VMMC unit costs and scale, while simultaneously accounting for the influence of the SDP (which we defined as all possible combinations of type of facility, ownership, urbanicity, and country), on the unit cost variation. We defined SDP as any combination of such four characteristics. Finally, we extrapolated VMMC unit costs for all SDPs in 13 countries, including those not contained in our dataset. RESULTS: The average unit cost was 73 USD (IQR: 28.3, 100.7). South Africa showed the highest within-country cost variation, as well as the highest mean unit cost (135 USD). Uganda and Namibia had minimal within-country cost variation, and Uganda had the lowest mean VMMC unit cost (22 USD). Our results showed evidence consistent with economies of scale. Private ownership and Hospitals were significant determinants of higher unit costs. By identifying key cost drivers, including country- and facility-level characteristics, as well as the effects of scale we developed econometric models to estimate unit cost curves for VMMC services in a variety of clinical and geographical settings. CONCLUSION: While our study did not produce new empirical data, our results did increase by a tenfold the availability of unit costs estimates for 128 SDPs in 14 priority countries for VMMC. It is to our knowledge, the most comprehensive analysis of VMMC unit costs to date. Furthermore, we provide a proof of concept of the ability to generate predictive cost estimates for settings where empirical data does not exist

    Actionable Information - Research Briefs - Stringency Index

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    Includes both static PDF version and the dynamic web version.Explore the association between the government's response to contain the pandemic and measurements of mobility reduction, economic activity, and unemployment

    Actionable Information - Research Briefs - Excess Mortality

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    Includes both static PDF version and the dynamic web version.Compare the total deaths per week during the 2020 pandemic against the expected deaths according to the reported in the previous four years

    A meta-analysis approach for estimating average unit costs for ART using pooled facility-level primary data from African countries

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    Objective: To estimate facility-level average cost for ART services and explore unit cost variations using pooled facility-level cost estimates from four HIV empirical cost studies conducted in five African countries. Methods: Through a literature search we identified studies reporting facility-level costs for ART programmes. We requested the underlying data and standardised the disparate data sources to make them comparable. Subsequently, we estimated the annual cost per patient served and assessed the cost variation among facilities and other service delivery characteristics using descriptive statistics and meta-analysis. All costs were converted to 2017 US dollars ().Results:WeobtainedandstandardiseddatafromfourstudiesacrossfiveAfricancountriesand139facilities.TheweightedaveragecostperpatientonARTwas). Results: We obtained and standardised data from four studies across five African countries and 139 facilities. The weighted average cost per patient on ART was 251 (95% CI: 193–308). On average, 46% of the mean unit cost correspond to antiretroviral (ARVs) costs, 31% to personnel costs, 20% other recurrent costs, and 2% to capital costs. We observed a lot of variation in unit cost and scale levels between countries. We also observed a negative relationship between ART unit cost and the number of patients served in a year. Conclusion: Our approach allowed us to explore unit cost variation across contexts by pooling ART costs from multiple sources. Our research provides an example of how to estimate costs based on heterogeneous sources reconciling methodological differences across studies and contributes by giving an example on how to estimate costs based on heterogeneous sources of data. Also, our study provides additional information on costs for funders, policy-makers, and decision-makers in the process of designing or scaling-up HIV interventions

    Assessment of Post-Dengue Rheumatic Symptoms Using the WOMAC and DAS-28 Questionnaires in a Honduran Population after a Four-Month Follow-Up

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    Introduction: Alphaviruses may cause arthritis, but there is a lack of studies assessing it in flaviviruses such as dengue. Through the 28 Joint Disease Activity Score (DAS-28), incorporating swollen joint counts, and through the Arthritis Index from Western Ontario and McMaster Universities (WOMAC), we assessed pain, stiffness, and dimensions of arthritic function in post-DENV patients. Methods: Prospective study of a cohort of participants who were diagnosed with dengue in centres in Honduras from December 2019 to February 2020, with a follow-up period of 4 months to evaluate post-dengue rheumatological disease through the WOMAC and DAS-28 questionnaires. Results: After a four-month follow-up phase with 281 participants, the final cohort comprised 58.8% women and 41.20% men. After the follow-up, 63.02% persisted with the clinical findings. According to WOMAC, joint involvement was higher in women with (58.76%) (p &lt; 0.0001) these symptoms or functional limitations when performing daily activities were limited to pain when walking (34.81% vs. 5.51%), climbing or descending stairs (36.46% vs. 8.66%), and at night at bedtime (28.73% vs. 7.08%). With the DAS-28, we found at least one alteration with inflammation or pain in 14.91% of the participants, primarily women (p &lt; 0.01). Discussion: Joint involvement was high during the dengue epidemic in 2019. We observed a significant proportion of women with inflammation and joint pain, showing that dengue may lead to the development of chronic rheumatological findings, although lower than in CHIKV, still affecting everyday life and, consequently, their quality of life. Additional long-term evaluation studies after dengue are required
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