John Marshall PhD

Assistant Professor in Residence, Biostatistics and Epidemiology
Education: 

PhD - Biomathematics, University of California, Los Angeles

MS - Biomathematics, University of California, Los Angeles

BTech (Hons) - Optoelectronics, University of Auckland, New Zealand

BSc - Biological Sciences, University of Auckland, New Zealand

Courses: 

PH 252B: Modeling the dynamics of infectious disease processes

Research Description: 

I am a new assistant professor at UC Berkeley, having recently completed postdoctoral research on malaria epidemiology at Imperial College, population genetics at Caltech and field work at the Malaria Research and Training Center in Mali. I am broadly interested in the following research areas and welcome interested students to contact me.

1. Genetic control of mosquito-borne diseases:
Malaria, dengue fever and other mosquito-borne diseases pose a major global health burden throughout much of the world. Over 600,000 people die each year from malaria, most of whom are children in sub-Saharan Africa under the age of five, and over 25,000 people die each year from dengue fever. For malaria, declines in transmission have been seen recently following wide-scale distribution of bed nets and antimalarial drugs; however, these tools are not expected to eliminate malaria from highly-endemic areas. For dengue, there is currently no cure or vaccine available. Consequently, there is interest in novel control strategies, including the use of genetically modified (GM) mosquitoes.

Control strategies using GM mosquitoes can be grouped into two general categories*mdash;self-limiting and self-propagating strategies. In self-limiting strategies, the transgene is eliminated from the population over time. The best example of this is a release of genetically sterile males. By mating with wild females after a release, these mosquitoes produce no viable offspring, thus reducing the mosquito population and hence disease transmission over time. In self-propagating strategies, a selfish genetic element is used to spread a disease-refractory gene or a fitness load into the mosquito population. Examples include the use of Medea elements to spread malaria-refractory genes into mosquito populations, or the use of homing endonuclease genes to induce a male-bias in the offspring ratio at the same time as spreading into a population, eventually causing a population crash.

My research has thus far focused on the use of self-propagating GM mosquito strategies to control malaria in sub-Saharan Africa. It is thought that these strategies hold promise here due to their potential to control disease on a wide scale, independent of human participation. In 2008, I conducted a survey on perspectives of people in Mali, West Africa to the use of GM mosquitoes for malaria control. Results from this survey suggested that people would be supportive of GM mosquito projects that had already been shown to work in confined field trials. To this end, in collaboration with researchers at Prof. Bruce Hay’s lab at Caltech, I am developing genetic systems that will be confineable to partially-isolated mosquito populations in Africa. Additionally, in collaboration with researchers at the Vector Genetics Lab at UC Davis and the Center for Theoretical Evolutionary Genomics at UC Berkeley, I am developing methods to quantify the degree of isolation between neighboring mosquito populations, which is of relevance to both confined trials and eventual wide-scale releases.

I am interested in future projects using mathematical models to predict the utility of genetic control strategies for a variety of mosquito-borne diseases. I am also interested in agricultural applications of this technology, such as the use of GM psyllids to control the spread of citrus huanglongbing in California and elsewhere.

2. Human movement, parasite genomics and malaria elimination:
As malaria prevalence declines in many parts of Africa and human populations become increasingly mobile, the dominant factors influencing malaria transmission are beginning to shift. In particular, imported infections are expected to contribute to a growing proportion of local transmission, and controlling these imported infections is becoming an increasingly important aspect of local malaria control. Indeed, malaria control programs in several areas currently aiming for elimination, such as Swaziland and Zanzibar Island in Tanzania, are already focusing on imported infections. Designing optimal strategies to target these imported infections will require a detailed understanding of: (a) human movement patterns and “hot pops” at most risk of importing infections; and (b) the “micro-epidemiology” and “hot spots” of transmission in the local elimination setting.

My work in this area has thus far focused on part (a). As part of the malaria modeling group at Imperial College, I led surveys of human movement patterns of relevance to malaria transmission in Mali, Burkina Faso, Zambia and Tanzania. Trips recorded in these surveys were fitted to models describing patterns of human movement which were then incorporated into large-scale, data-driven models of malaria transmission spanning the African continent. These models have been used to inform malaria policy at the World Health Organization and Gates Foundation. The surveys have also been useful in characterizing the contribution of various traveler groups – such as youth workers and women traveling with children – to disease importation, and for correcting biases in other human movement data sets – such as anonymous cell phone signal data sets used as a proxy to understand human movement patterns.

I am interested in future projects of relevance to part (b) – understanding the fine-scale transmission patterns of malaria in elimination settings and modeling intervention delivery strategies tailored to these settings. I have initiated collaborations with researchers at UCSF in this area. The PlasmoTrack project led by Dr. Bryan Greenhouse at UCSF enables local networks of transmission to be inferred from parasite genomic sequences, and provides a wealth of information for modeling intervention strategies in elimination settings. Furthermore, researchers at the Malaria Elimination Initiative led by Dr. Roly Gosling at UCSF are developing strategies for interrupting transmission in low transmission settings including the porous border region of Zambezi in Namibia, and Vietnam, where drug-resistant malaria parasites are currently emerging. I am interested in projects using mathematical models to design optimal control strategies to eliminate local malaria transmission from these areas.

3. Mathematical modeling of infectious diseases:
I am teaching a course this spring on modeling the dynamics of infectious diseases. The course will lead students through the process of designing mathematical models, fitting them to data, and using them as public health tools. Students will work on a project in which they will design a model of their own disease of interest and use it to answer a specific research question. I welcome this as an opportunity to broaden my own research interests. I am also very happy to provide modeling advice regarding a range of infectious diseases to epidemiologists on campus at UC Berkeley and beyond. Please contact me if interested.

Selected Publications: 

Marshall, J. M., and B. A. Hay, 2014 Medusa: A novel gene drive system for confined suppression of mosquito populations. PLoS ONE 9: e102694.

Okorie, P. N., J. M. Marshall, M. O. Akpa, and A. O. George, 2014 Perceptions and recommendations by scientists for a potential release of genetically modified mosquitoes in Nigeria. Malar. J. 13: 154.

White, M. T., D. Lwetoijera, J. M. Marshall, G. Caron-Lormier, D. A. Bohan, I. Denholm, and G. J. Devine, 2014 Negative cross resistance mediated by co-treated bed nets: A potential means of restoring pyrethroid-susceptibility to malaria vectors. PLoS ONE 9: e95640.

Marshall, J. M., M. T. White, A. C. Ghani, Y. Schlein, G. C. Muller, J. C. Beier, 2013 Quantifying the mosquito's sweet tooth: Modelling the effectiveness of attractive toxic sugar baits (ATSB) for malaria vector control. Malar. J. 12: 291.

Akbari*, O., K. D. Matzen*, J. M. Marshall*, H. Huang, C. M. Ward, and B. A. Hay, 2013 A synthetic gene drive system for local, reversible modification and suppression of insect popualtions. Curr. Biol. 23: 671-677. *Equal contribution

Gatton, M. L., N. Chitnis, T. Churcher, M. J. Donnelly, A. C. Ghani, H. C. J. Godfray, F. Gould, I. Hastings, J. M. Marshall, H. Ranson, M. Rowland, J. Shaman, S. W. Linsay, 2013 The importance of mosquito behavioral adaptations to malaria control in Africa. Evolution 67: 1218-1230.

Marshall, J. M., and B. A. Hay, 2012 Confinement of gene drive systems to local populations: A comparative analysis. J. Theor. Biol. 294: 153-171.

Marshall, J. M., and B. A. Hay, 2012 General principles of single-construct chromosomal gene drive. Evolution. 66: 2150-2166.

De Silva, P., and J. M. Marshall, 2012 Factors contributing to urban malaria transmission in sub-Saharan Africa: A systematic review. J. Trop. Med. doi: 10.1155/2012/819563.

Akbari*, O., C. H. Chen*, J. M. Marshall*, H. Huang, I. Antoshechkin, and B. A. Hay, 2012 Novel synthetic Medea selfish genetic elements drive population replacement in Drosophila; a theoretical exploration of Medea-dependent population suppression. ACS Synth. Biol. doi: 10.1021/sb300079h. *Equal contribution

Marshall, J. M., G. W. Pittman , A. B. Buchman, and B. A. Hay, 2011 Semele: A killer-male, rescue-female system for suppression and replacement of insect disease vector populations. Genetics 187: 535-551.

Marshall, J. M., and B. A. Hay, 2011 Inverse Medea as a novel gene drive system for local population replacement: A theoretical analysis. J. Hered. 102: 336-341.

Marshall, J. M., 2011 The toxin and antidote puzzle: New ways to control insect pest populations through manipulating inheritance. Bioeng. Bugs. 2: 1-6.

Marshall, J. M., 2011 The Cartagena Protocol in the context of recent releases of transgenic and Wolbachia-infected mosquitoes. AsPac. J. Mol. Biol. Biotechnol. 19: 93-100.

Marshall, J. M., 2010 The Cartagena Protocol and genetically modified mosquitoes. Nat. Biotech. 28: 896-897.

Marshall, J. M., M. B. Touré, M. M. Traore, S. Famenini, and C. E. Taylor, 2010 Perspectives of people in Mali toward genetically modified mosquitoes for malaria control . Malaria J. 9: 128.

Marshall, J. M., M. B. Touré, M. M. Traore, and C. E. Taylor, 2010 Towards a quantitative assessment of public attitudes to transgenic mosquitoes: Questions based on a qualitative survey in Mali. AsPac. J. Mol. Biol. Biotechnol. 18: 251-273.

Marshall, J. M., and C. E. Taylor, 2009 Malaria control with transgenic mosquitoes. PLoS Medicine 6: e1000020.

Marshall, J. M., 2009 The effect of gene drive on containment of transgenic mosquitoes. J. Theor. Biol. 258: 250-265.

Marshall, J. M., 2008 A branching process model for the early spread of a transposable element in a diploid population. J. Math. Biol. 57: 811-840.

Marshall, J. M., 2008 The impact of dissociation on transposon-mediated disease control strategies. Genetics 178: 1673-1682.

Marshall, J. M., K. Morikawa, N. Manoukis, and C. E. Taylor, 2007 Predicting the effectiveness of population replacement strategy using mathematical modeling. J. Vis. Exp. 5: 227.

Marshall, J. M., and R. E. Weiss, 2006 A Bayesian heterogeneous analysis of variance approach to inferring recent selective sweeps. Genetics 173: 2357-2370.

Wills, P. R., J. M. Marshall, and P. J. Smith, 2004 Genetic information and self-organized criticality. Europhysics Letters 68: 901-907.

In press

Marshall, J. M., and O. Akbari, 2014 Gene drive systems in mosquitoes. In: Adelman, Z. N. (editor) Genetic Control of Dengue and Malaria. Elsevier/Academic Press, New York.

Marshall, J. M., 2014 Measuring public attitudes to releases of transgenic mosquitoes for disease control. In: Tyagi, B. K. (editor) WHO/TDR Biosafety Manual for Genetically Modified Mosquitoes. WHO Press, Geneva.

Marshall, J. M., 2014 The Cartagena Protocol and genetically modified mosquitoes. In: Tyagi, B. K. (editor) WHO/TDR Biosafety Manual for Genetically Modified Mosquitoes. WHO Press, Geneva.

Profile Updated: April 7, 2016