Evaluation of the effectiveness and cost effectiveness of a Community-delivered Integrated Malaria Elimination (CIME) model in Myanmar: protocol for an open stepped-wedge cluster-randomised controlled trial.

INTRODUCTION: In the Greater Mekong Subregion, community health workers, known as malaria volunteers, have played a key role in reducing malaria in the control phase, providing essential malaria services in areas with limited formal healthcare. However, the motivation and social role of malaria volunteers, and testing rates, have declined with decreasing malaria burden and reorientation of malaria programmes from control to elimination. Provision of additional interventions for common health concerns could help sustain the effectiveness of volunteers and maintain malaria testing rates required for malaria elimination accreditation by the WHO. METHODS AND ANALYSIS: The Community-delivered Integrated Malaria Elimination (CIME) volunteer model, integrating interventions for malaria, dengue, tuberculosis, childhood diarrhoea and malaria Rapid Diagnostic Test (RDT)-negative fever, was developed based on global evidence and extensive stakeholder consultations. An open stepped-wedge cluster-randomised controlled trial, randomised at the volunteer level, will be conducted over 6 months to evaluate the effectiveness of the CIME model in Myanmar. One hundred and forty Integrated Community Malaria Volunteers (ICMVs, current model of care) providing malaria services in 140 villages will be retrained as CIME volunteers (intervention). These 140 ICMVs/villages will be grouped into 10 blocks of 14 villages, with blocks transitioned from control (ICMV) to intervention states (CIME), fortnightly, in random order, following a 1-week training and transition period. The primary outcome of the trial is blood examination rate determined by the number of malaria RDTs performed weekly. Difference in rates will be estimated across village intervention and control states using a generalised linear mixed modelling analytical approach with maximum likelihood estimation. ETHICS AND DISSEMINATION: The study was approved by Institutional Review Board, Myanmar Department of Medical Research (Ethics/DMR/2020/111) and Alfred Hospital Ethics Review Committee, Australia (241/20). Findings will be disseminated in peer-review journals, conferences and regional, national and local stakeholder meetings. TRIAL REGISTRATION NUMBER: NCT04695886.

Comparative performance of the finite element method and the boundary element fast multipole method for problems mimicking transcranial magnetic stimulation (TMS).

OBJECTIVE: A study pertinent to the numerical modeling of cortical neurostimulation is conducted in an effort to compare the performance of the finite element method (FEM) and an original formulation of the boundary element fast multipole method (BEM-FMM) at matched computational performance metrics. APPROACH: We consider two problems: (i) a canonic multi-sphere geometry and an external magnetic-dipole excitation where the analytical solution is available and; (ii) a problem with realistic head models excited by a realistic coil geometry. In the first case, the FEM algorithm tested is a fast open-source getDP solver running within the SimNIBS 2.1.1 environment. In the second case, a high-end commercial FEM software package ANSYS Maxwell 3D is used. The BEM-FMM method runs in the MATLAB® 2018a environment. MAIN RESULTS: In the first case, we observe that the BEM-FMM algorithm gives a smaller solution error for all mesh resolutions and runs significantly faster for high-resolution meshes when the number of triangular facets exceeds approximately 0.25 M. We present other relevant simulation results such as volumetric mesh generation times for the FEM, time necessary to compute the potential integrals for the BEM-FMM, and solution performance metrics for different hardware/operating system combinations. In the second case, we observe an excellent agreement for electric field distribution across different cranium compartments and, at the same time, a speed improvement of three orders of magnitude when the BEM-FMM algorithm used. SIGNIFICANCE: This study may provide a justification for anticipated use of the BEM-FMM algorithm for high-resolution realistic transcranial magnetic stimulation scenarios.