Modelling the last mile to elimination: Learning from China’s successes to inform malaria elimination in the Asia-Pacific

This joint PhD project will be based at The University of Melbourne with a minimum 12 month stay at the Shanghai Jiao Tong University.

Project description
China has not reported any local malaria cases since 2017 despite importations from neighbouring endemic countries. Learning from historical databases of the Chinese malaria elimination programs we will identify the interventions that were key to this success (e.g. the 1-3-7 strategy of surveillance and response) and integrate them into existing mathematical models of malaria transmission. These models will then be used to estimate the potential impact of these interventions in assisting other Asia-Pacific nations to cover the last mile to malaria elimination. The project will combine in-depth epidemiological analyses with advanced mathematical models.

Overall aim

Identifying key reasons for successful malaria elimination in China and investigate their potential to assist other Asia-Pacific countries in eliminating malaria.

Objectives

  • Develop spatio-temporal statistical and mathematical models for investigate very low-level malaria transmission
  • Apply these models to extensive historical databases to investigate key factors contributing to the successful malaria elimination in China
  • Develop models to investigate the potential of surveillance & response intervention in other malaria endemic areas in the Asia Pacific (e.g. Cambodia, Indonesia and/or Solomon Islands.

Approaches

Building on the approach developed by Routledge et al (2020, PLoS Comp Bio, 16(3): e1007707) we will investigate different ways to integrate different intervention by making the likelihood of transmission (as measure by the case reproduction number, Rc) dependent on the presence and application of different intervention at the time and location of the case.

To determine the best models, detailed analyses of data on malaria cases and intervention coverage will be necessary. This will require detailed analyses of different data sets collected in Yunnan pre- (2005-10) and post- launch of the National Malaria Elimination Program (2011-16) of the elimination program. These will include case data, data on local interventions as well as molecular and serological data from specific research surveys available at that National Institute of Parasitic Diseases (China CDC) and through the Yunnan malaria program.

This will include a critical examination of data quality and completeness. The analyses period will be restricted to years with good quality and cover the period before and after the “1-3-7” strategy as formalised and included into the Information Management System Specific to Malaria Elimination (Zhou et al 2015, Infect Dis Poverty, 4: 55). Fitting the spatio-temporal models to data from 2005-2016 we will then quantify the effectiveness of the impact of “1-3-7” strategy by determining the impact of increased coverage on case reproduction numbers (Rc).

As part of the Strengthening Preparedness in the Asia- Pacific Region through Knowledge (SPARK) project (led by Prof McVernon), Prof. Mueller, Prof. McCaw and colleagues are developing spatially-explicit models of malaria transmission for Cambodia, Indonesia and Papua New Guinea/Solomon Islands that allow to investigate  the individual and combined impact of different control interventions on local malaria transmission and assist endemic countries both with setting policies and day-to- day decision making. During the last part of the project these models will be adapted to determine where an implementation of surveillance and responses strategy such as “1-3-7” is operationally feasible and whether it may lead to local elimination.

Timelines

Year 1: Training in Malaria epidemiology and modelling – UoM/WEHI

The student will learn key concept of malaria epidemiology in eliminating countries, be trained in all necessary techniques for in-depth epidemiological analyses and familiarise him/herself with our existing SPARK models as well as Routledge and comparable diffusion network models.

Year 2: Epidemiological analyses of Chinese databases – SJTU

The SJTU-based supervisor will guide the student through the analyses of extensive historical databases on malaria    in China with the aim of identifying both key interventions and estimated their relative contribution to success. These analyses will also allow parametrising models incorporating these interventions into models. This part of the PhD will require both an in-depth knowledge of the Chinese malaria program and access to extensive local databases. Both are available at SJTU/NIPD.

Year 3: Development of models and application to other settings – UoM

Back in Melbourne the student will integrate the different interventions into existing SPARK models to develop “Surveillance & Response’  decision  systems and transmission models and application to Cambodia, Indonesia and Solomon Islands.

The project will be complemented by the project on Monitoring the continued absence of local transmission on border regions of Yunnan Province using novel serological markers of exposure to P. vivax infections and the collaboration will ensure a successful completion of the project.

Supervision team:

Professor Ivo Mueller (The University of Melbourne)

Professor Xiao-Nong Zhou (Shanghai Jiao Tong University)

How to apply

If you are interested in this opportunity, read the application guidelines before contacting the lead supervisor.