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.
7/1/2017:Welcome to Héctor Sánchez who is joining the lab as a PostDoc working on modeling aspects of the UCI Malaria Initiative to control malaria using sustainable, genetics-based approaches.
7/1/2017: Welcome to Jared Bennett who is joining the lab as a Biophysics PhD student working on genomic and population genetic aspects of resistance to CRISPR-Cas9-based gene drive systems in mosquitoes.
6/19/2017: Paper published in Nature Scientific Reports on the role that multiplexing of guide RNAs could play in enabling homing-based gene drive systems to suppress disease-transmitting mosquito populations on a potentially global scale. Corresponding molecular work outlines successful multiplexing in Drosophila (https://www.nature.com/articles/s41598-017-02744-7).
5/13/2017: Welcome to Suzanne Dufault and Partow Imani who are joining the lab as Graduate Student Researchers working on mathematical models of mosquito dispersal and site selection considerations for potential trials of genetically modified mosquitoes.
5/1/2017: Welcome to Jared Bennett who is joining the lab as a Biophysics rotation student for the summer working on evolutionary considerations related to the use of CRISPR-Cas9-based homing systems for gene drive in mosquitoes.
4/26/2017: Congratulations to Héctor Sánchez who has just graduated with his PhD in computer science working on individual-based models of mosquito population dynamics and control!
4/21/2017: Lab receives funds to contribute to the development of mathematical models of schistosomiasis transmission as part of an NSF Ecology and Evolution of Infectious Diseases grant awarded to Professor Justin Remais at UC Berkeley.
4/18/2017: Welcome to Francois Rerolle, a PhD student with the Malaria Elimination Initiative at UCSF, who is collaborating with our lab to estimate the effect size of insecticide-treated nets and indoor residual spraying in Zambia using malaria surveillance and survey data.
4/7/2017: Lab receives sub-award to work on individual-based models of malaria transmission, control and elimination with Professor David Smith at the University of Washington.
1/23/2017: Welcome to Qinlong Jing, vice section chief at Guangzhou Center for Disease Control and Prevention, who is joining the lab as a visiting PhD student working on analysis of surveillance data from a recent dengue outbreak in Guangzhou, China.
12/15/2016: John Marshall gives invited talk at the Joint Genome Institute, US Department of Energy on “Gene drive: What is possible at the population level with currently available molecular components?”
8/4/2016: Welcome to Chloe Tarrasch who is joining the lab as an undergrad researcher working on a mathematical model of novel mosquito control methods for a project sponsored by the Parker Foundation.
5/1/2016: UC Davis collaborator, Yoosook Lee, is awarded Vector-Borne Disease Pilot Grant working towards the eradication of Aedes aegypti in California (John Marshall is co-investigator).
9/14/2015: Welcome to Sean Wu who is joining the lab as a Graduate Student Researcher working on a mathematical model of mosquito swarm spraying and other novel mosquito control interventions for a project sponsored by the Parker Foundation.
7/1/2015: John Marshall joins DisARM team at UCSF to lead development of mathematical models to convert malaria risk maps to intervention decision maps to support malaria elimination activities in Swaziland and Zimbabwe.
6/26/2015: Lab receives UC MEXUS Collaborative Research Grant in collaboration with Prof. Edgar Emmanuel Vallejo of Instituto Tecnológico de Monterrey, Mexico to determine optimal strategies for the control of mosquito-borne diseases in Mexico and the US.
6/26/2015: Congrats to Samson Kiware on being awarded a Wellcome Trust Research Training Fellowship to develop an informatics system and mathematical models for mosquito ecology and control.
5/21/2015: Welcome to Raira Marotta who is joining the lab as a summer research student working on mathematical models of violence and violence prevention sponsored by the International Institute of Education, Brazil.