Developing a district level model for the spread of COVID-19 in South Africa (2020)
A jointly developed COVID-19 model is the current model being used to provide projections at the national and provincial levels. MASHA will extend this model spatially to the district level and include stratification by age in 10-year bands. MASHA will build a secure, online dashboard to disseminate model projections.
Funder: Clinton Health Access Initiative
Supporting decision-making for COVID-19 in South Africa (2020)
The disease models developed jointly by the Modelling and Simulation Hub, Africa (MASHA) and are already in use by the National government of South Africa to support decision-making on the COVID-19 epidemic. As a member of the South African COVID-19 Modelling Consortium, a group of experts convened to provide technical support to decision makers tackling the COVID-19 epidemic in South Africa, MASHA is well placed to conduct relevant, impactful research on epidemic modelling.
Supporting decision-making for COVID-19 in Mozambique (2020)
Through the COVID-19 International Modelling (CoMo) Consortium (Oxford University), MASHA took the role of the senior modeller advising Oxford COVID-19 modelling in Mozambique. The Consortium is working with partners in the National Ministry to use mathematical modelling to support key decisions that need to be made in their COVID-19 epidemic.
Supporting decision-making for COVID-19 in Namibia (2020)
MASHA is currently engaged with health officials in Namibia to advise on COVID-19 modelling conducted for the country through mathematical modelling. A COVID-19 modelling tool was developed for regions in Namibia to project future cases and hospitalisation.
Developing model applications to support national malaria elimination strategy design in Africa (2019-2020)
The project aims to develop computer-based model applications that can be used to predict the impact of malaria policy on a population of interest to aid the design of effective malaria policies. These tools will be made available to the National Malaria Control Programmes (NMCPs) of various countries in Africa.
Funder: Wellcome Trust: Research Innovation Award (GN: 214236/Z/18Z)
ENDGAME: Enhanced modelling for NMCP Decision-making in the GMS to Accelerate Malaria Elimination (2019-2021)
MASHA is supporting this Bill and Melinda Gates Foundation funded project that seeks to support country-led elimination efforts by filling key gaps in technical assistance for national malaria control programmes (NMCPs) with mathematical modelling and outbreak analysis. We are supporting this study through the Mahidol Oxford Tropical Medicine Research Unit where the focus is to produce a set of mathematical models for malaria elimination in countries in the Greater Mekong Subregion.
Investment Case for the elimination of malaria in South Africa (2018)
An investment case was commissioned by the South African National Department of Health to determine and mobilise resources to fill the funding gap required to achieve malaria elimination. MASHA provided mathematical modelling support to project the path to and cost of malaria elimination. The recommendations of this study were used to secure additional domestic resources (ZAR 319 million) to fund malaria elimination in South Africa over the next two years.
Funder: Malaria Elimination Initiative, University of California, San Francisco.
METCAP: Malaria Elimination Transmission and Costing in the Asia-Pacific (2016 - 2017)
The University of California San Francisco’s Global Health Group’s Malaria Elimination Initiative launched a comprehensive program of work “To increase and expand the amount of sustainable financing in support of achieving a malaria-free Asia Pacific by 2030”. MASHA supported the project through the development of a mathematical model and user interface to project the rates of decline to elimination by 2030 and determine the costs for and maintaining malaria elimination in the Asia Pacific region.
The malaria elimination agenda: Prospects for Ghana using mathematical tools (2016 – 2019)
Malaria remains a serious cause of morbidity and mortality in Ghana and the current national malaria control strategy aims to reduce the burden of malaria by 75% by the year 2020. The aim of the research is to develop and validate a suite of mathematical models that can be used to predict malaria transmission and investigate the impact of malaria interventions in Ghana.
Funder: Ghana Educational Trust and DST-NRF Centre for Epidemiological Modelling and Analysis
Mathematical modelling for malaria elimination in Manicaland, Zimbabwe (2017 – 2019)
This project focuses on developing mathematical models to simulate malaria transmission in the high burdened areas of Manicaland province, Zimbabwe. Mathematical modelling is being applied to this province with a particular focus on the impact of migration.
Funder: DST-NRF Centre for Epidemiological Modelling and Analysis
Effect of vaccination strategy on the burden of pertussis in South Africa: A modelling proposal (2017- 2019)
This study aims to use mathematical modelling to predict the epidemiological and economic impact of different vaccination strategies to reduce the burden of pertussis in South Africa. This is a collaboration with Vaccines For Africa (VACFA) based at the University of Cape Town.
Evidence-Based Vaccinology: Is there Evidence to Introduce Routine Hepatitis A Vaccination in South Africa? (2018- 2020)
This study aims to generate evidence for decision making on whether a routine vaccination program against Hepatitis A Vaccination should be introduced into the South African Expanded Program on Immunisations. Mathematical Modelling is one arm of the body of evidence to be generated by the study
Funder: DST-NRF Centre for Epidemiological Modelling and Analysis and Sanofi
Mathematical modelling for malaria elimination in Mpumalanga (2010 – 2014)
This project aimed to simulate the malaria transmission situation in Mpumalanga and to assess the impact human migration to and from neighbouring Mozambique has on the South African government’s efforts to achieve malaria elimination.
Funder: National Research Foundation of South Africa
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