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
PH 295: infectious disease modeling seminar 

Research Description: 

The Marshall Lab research efforts are focused on three key areas:

1. Genetics-based strategies to control mosquito-borne diseases:
Malaria, dengue, Zika 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 under the age of five in sub-Saharan Africa, and over 50,000,000 people are infected with dengue each year, ~10,000 of whom die from the disease. For malaria, recent declines in transmission have been seen following wide-scale distribution of bed nets and antimalarial drugs; however, these tools are not expected to be sufficient to eliminate malaria from highly-endemic areas. For dengue, there is no cure or vaccine available that is effective against all four serotypes. Consequently, there is interest in novel strategies to control these diseases, including the use of genetically modified (GM) mosquitoes.

Control strategies using GM mosquitoes can be grouped into two general categories - 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 fitness load into the mosquito population. With the advent of the CRISPR-Cas9 revolution, these systems have become much easier to engineer. Proof-of-principle systems have recently been engineered that could: a) spread malaria-refractory genes into mosquito populations, rendering them unable to transmit the disease to humans; and b) disrupt a gene required for female fertility as they spread, potentially eliminating the mosquito vector entirely.

Understanding how these gene drive systems spread through populations of mosquitoes requires mathematical models and knowledge of the ecology and environment into which they could be introduced. Our research in this area therefore falls at the interface between molecular biology and ecology. We work with molecular biologists - Professor Anthony James at UC Irvine, Professor Ethan Bier at UC San Diego and Professor Omar Akbari at UC Riverside - to determine how the constructs they engineer in the lab could be expected to behave in the wild. In doing so, we contribute to the discussion on construct design. We also work with population geneticist Professor Greg Lanzaro at UC Davis to better understand the dispersal patterns of mosquitoes, their genetic variation, seasonal changes in their abundance and other aspects of their population biology. Our goal is to move this field forward in a way that allows: a) the burden of mosquito-borne diseases to be reduced; and b) the technology to be implemented in a safe, controllable and socially responsible way. Our work, therefore, focuses on technologies that, while having potential for wide-scale impact, could first be trialled in a safe, reversible and confinable way.

2. Mathematical modeling to support 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. First, spatial heterogeneity in transmission is becoming increasingly relevant as a growing body of research highlights how transmission can be sustained within malaria “hot spots” where there is an abundance of mosquito vectors and/or inadequate protection against them. Second, imported infections are contributing to a higher proportion of local transmission in a growing number of elimination settings. Indeed, in Swaziland and Zanzibar, malaria control programs are already focusing their efforts largely on imported infections. Designing strategies to eliminate malaria from these settings therefore requires an understanding of: a) the "micro-epidemiology" and "hot spots" that sustain transmission in these communities; and b) human movement patterns and the populations most likely to import infections. Our group is working with the Malaria Elimination Initiative at UCSF to address these issues.

First, we are working with the DiSARM project to help inform decision making on prioritization and targeting of malaria interventions in elimination settings. DiSARM, led by Professor Hugh Sturrock at UC San Francisco, is a unique disease surveillance and risk mapping system initially being developed to provide decision support for national malaria control programs in an intuitive way that suits its users. The system combines case and intervention data from malaria control programs with satellite-derived environmental and climatic variables from the Google Earth Engine. Using machine learning algorithms, it refines models of malaria risk based on available data and uses these to produce risk maps that shift with weather patterns and disease importation. Our contribution to this project is to use mechanistic models of malaria transmission to prioritize areas where indoor residual spraying (IRS), insecticide-treated nets (ITNs) and mass drug administration could prevent outbreaks and help progress towards local elimination.

Second, we are developing two modeling frameworks - VCOM and MASH - to explore the potential impact of a range of new and forthcoming vector control tools at suppressing mosquito populations. Despite recent successes in reducing malaria transmission with ITNs and IRS, the protective effect of these interventions is limited because they target mosquitoes solely indoors, while the vectors of malaria increasingly feed upon humans outdoors and also feed upon non-human hosts such as cattle. Novel vector control tools are now becoming available that target mosquitoes both indoors and outdoors and at different stages of their life cycle. VCOM (Vector Control Optimization Model) is a population-based model that enables us to explore the impact of these interventions by modeling the entire mosquito life cycle and adult feeding cycle and the point at which each intervention has its impact. MASH (Modular Analysis and Simulation for human Health), led by Professor David Smith at the University of Washington, is an individual-based model that, in additional to modeling the mosquito life and feeding cycles, accounts for the spatial heterogeneities that exist in real landscapes.

3. Mathematical epidemiology and social science:
The methods we use are broadly applicable to modeling a wide range of infectious processes. We are currently collaborating with Professor Eva Harris and Professor Mike Boots at UC Berkeley on models of arbovirus transmission. In particular, we are interested in: a) how the human immune response shapes the transmission dynamics of co-circulating arboviruses - dengue, Chikungunya and Zika - and b) assessing the impact of community-based interventions at suppressing local mosquito populations. At UC Berkeley, we are also collaborating with Professor Justin Remais on models of macroparasite transmission. In particular, we are interested in the use of novel metrics to assess elimination potential. We are also working with Professor Magdalena Cerda at UC Davis and Professor Katherine Keyes at Columbia University to explore the application of parameter estimation techniques commonly used in infectious disease epidemiology to areas of social epidemiology, such as the incidence of gang-related violence. We are open to new collaborations applying these methods to other systems.

Selected Publications: 

Marshall JM, Buchman B, Sanchez HM, Akbari OS (2017) Overcoming evolved resistance to population-suppressing homing-based gene drives. Nature Scientific Reports 7: 3776.

Killeen GF, Marshall JM, Kiware SS, Andy S, Chaki PP, Govella NJ (2017) Measuring, manipulating and exploiting behaviors of adult mosquitoes to optimize malaria vector control impact. BMJ Global Health 2: e000212.

Marshall JM,  Bennett A, Kiware SS, Sturrock HJW (2016) The hitchhiking parasite: Why human movement matters to malaria transmission and what we can do about it. Trends Parasitol. 32: 752–755.

Marshall JM, Touré MB, Ouédraogo AL, Ndhlovu M, Kiware SS, Rezai A, Nkhama E, Griffin JT, Hollingsworth TD, Doumbia S, Govella NJ, Ferguson NM, Ghani AC (2016) Key traveller groups of relevance to spatial malaria transmission: A survey of movement patterns in four sub-Saharan African countries. Malar. J. 15: 200.

Cheng Q, Jing Q, Spear RC, Marshall JM, Yang Z, Gong P (2016) Climate and timing of imported cases as determinants of the dengue outbreak in Guangzhou, 2014: Evidence from a mathematical model. PLoS NTDs 10: e0004417.

Zhu L, Marshall JM, Qualls WA, Schlein Y, McManus JW, Arheart KL, Hlaing WM, Traore SF, Doumbia S, Müller GC, Beier JC (2015) Modelling optimum use of attractive toxic sugar bait stations for effective malaria vector control in Africa. Malar. J. 14: 492.

Zhu L, Qualls WA, Marshall JM, Arheart KL, DeAngelis DL, McManus JW, Traore SF, Doumbia S, Schlein Y, Müller GC, Beier JC (2015) A spatial individual-based model predicting a great impact of copious sugar sources and resting sites on survival of Anopheles gambiae and malaria parasite transmission. Malar. J. 14: 59.

Marshall JM, Hay BA (2014) Medusa: A novel gene drive system for confined suppression of mosquito populations. PLoS ONE 9: e102694.

Okorie PN, Marshall JM, Akpa MO, George AO (2014) Perceptions and recommendations by scientists for a potential release of genetically modified mosquitoes in Nigeria. Malar. J. 13: 154.

White MT, Lwetoijera D, Marshall JM, Caron-Lormier G, Bohan DA, Denholm I, Devine GJ (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 JM, White MT, Ghani AC, Schlein Y, Muller GC, Beier JC (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 OS, Matzen KD, Marshall JM, Huang H, Ward CM, Hay BA (2013) A synthetic gene drive system for local, reversible modification and suppression of insect populations. Curr. Biol. 23: 671-677.

Gatton ML, Chitnis N, Churcher T, Donnelly MJ, Ghani AC, Godfray HCJ, Gould F, Hastings I, Marshall JM, Ranson H, Rowland M, Shaman J, Lindsay SW (2013) The importance of mosquito behavioral adaptations to malaria control in Africa. Evolution 67: 1218-1230.

Marshall JM, Hay BA (2012) Confinement of gene drive systems to local populations: A comparative analysis. J. Theor. Biol. 294: 153-171.

Marshall JM, Hay BA (2012) General principles of single-construct chromosomal gene drive. Evolution. 66: 2150-2166.

De Silva P, Marshall JM (2012) Factors contributing to urban malaria transmission in sub-Saharan Africa: A systematic review. J. Trop. Med. 2012: 819563.

Akbari OS, Chen CH, Marshall JM, Huang H, Antoshechkin I, Hay BA (2012)Novel synthetic Medea selfish genetic elements drive population replacement in Drosophila; a theoretical exploration of Medea-dependent population suppression. ACS Synth. Biol. 3: 915-928.

Marshall JM, Pittman GW, Buchman AB, Hay BA (2011) Semele: A killer-male, rescue-female system for suppression and replacement of insect disease vector populations. Genetics 187: 535-551.

Marshall JM, Hay BA (2011) Inverse Medea as a novel gene drive system for local population replacement: A theoretical analysis. J. Hered. 102: 336-341.

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

Marshall JM (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 JM (2010) The Cartagena Protocol and genetically modified mosquitoes. Nat. Biotech. 28: 896-897.

Marshall JM, Toure MB, Traore MM, Famenini S, Taylor CE (2010) Perspectives of people in Mali toward genetically modified mosquitoes for malaria control. Malar. J 9: 128.

Marshall JM, Touré MB, Traore MM, Taylor CE (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 JM, Taylor CE (2009) Malaria control with transgenic mosquitoes. PLoS Medicine 6: e1000020.

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

Profile Updated: June 21, 2017