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 genetics-based approaches.
Genetics-based control strategies can be grouped into two general categories - self-limiting and self-propagating strategies. In self-limiting strategies, introduced transgenes are 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 suppressing the mosquito population and hence disease transmission for a sustained period of time. In self-propagating strategies, a gene drive system (a genetic element that biases inheritance in its favor) is used to spread a disease-refractory gene or fitness load into the mosquito population. With the advent of the CRISPR 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 San Diego - 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 and the Vector Genetics Lab 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 the burden of mosquito-borne diseases to be reduced in a safe and socially responsible way. We serve as modeling lead for the UC Irvine Malaria Initiative to develop CRISPR-based gene drive systems to control Anopheles gambiae, the main African malaria vector. We also work with the Akbari Lab to develop gene drive and remediation systems for Aedes aegypti, the mosquito vector of dengue, chikungunya and Zika virus. We collaborate with the Tata Institute for Genetics and Society to develop CRISPR-based gene drive systems to control Anopheles stephensi, the main malaria vector in urban India, and work with Berkeley's Innovative Genomics Institute to explore the application of CRISPR-based genetic control strategies for insect agricultural pests. We have developed a general modeling framework, MGDrivE (Mosquito Gene Drive Explorer), to address research questions related to these projects. Initial work has focused on molecular biological considerations; however, as the technology moves closer to field application, our research interests are shifting to ecological characterization of mosquito populations, field trial design, and implications for human disease transmission.
2. Landscape genomics to quantify mosquito movement:
The safety and efficacy of mosquito genetic control strategies are critically dependent on an accurate understanding of mosquito movement patterns. To advance our understanding of the fine-scale movement patterns of mosquitoes, we are exploring the application of landscape genomic methods with Dr. Gordana Rašić of QIMR Berghofer Medical Research Institute in Australia. The particular methods we are interested in - close-kin mark-recapture - involve intensive landscape sampling efforts and subsequent genetic sequencing to the extent required to infer close familial relationships (parent-offspring, full sibling, half sibling, etc.). Observations of pairs of closely-related individuals then provide information on displacement on the timescale of a generation, which collectively may be used to parameterize a predictive model of mosquito movement. The same studies can also be used to infer other demographic parameters, such as population size and mating behavior. We are also investigating alternative genetic approaches to infer mosquito movement at larger spatial scales. This is of interest as mosquitoes are known to be transported by humans over large distances, with important implications for the wide-scale spread and reversibility of gene drive systems.
3. 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. Designing strategies to eliminate malaria from these settings therefore requires an understanding of: a) the hot spots that sustain transmission in these communities; and b) human movement patterns and the populations most likely to import infections. We are working with the Malaria Elimination Initiative at UCSF to address these issues. Our contribution to these projects is to use mathematical models of malaria transmission to prioritize areas where insecticide-based tools, artemisinin combination therapy drugs and novel intervention strategies could help to prevent outbreaks and progress towards local elimination.
We are particularly interested in mosquito vector control, and are developing a modeling framework, VCOM (Vector Control Optimization Model), in collaboration with Dr. Samson Kiware of the Ifakara Health Institute in Tanzania, to explore the potential of a range of new and forthcoming technologies at suppressing mosquito populations. Despite recent successes in reducing malaria transmission with insecticide-treated nets and indoor residual spraying with insecticides, the protective effect of these interventions is limited because they target mosquitoes solely indoors, while mosquito vectors increasingly feed on humans outdoors and also feed on 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 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. We are also contributing to another modeling framework, MASH (Modular Analysis and Simulation for human Health), led by Professor David Smith at the University of Washington, that accounts for the spatial heterogeneities that exist in real landscapes.
4. Ethical, social, cultural and regulatory aspects of our work:
We have an active interest in contributing to the ongoing discussion on the ethical, social, cultural and regulatory implications of our work. We advocate for the safe and responsible use of technology to reduce the human disease burden, while respecting the wishes of communities and nation states, the environment, and national and international law. In previous work, we have explored the application of the Cartagena Protocol, the fundamental regulatory document of the United Nations on the international movement of transgenic organisms, to gene-edited mosquitoes, and have conducted surveys of public attitudes on transgenic approaches to mosquito control in sub-Saharan Africa.
1/10/2023: Welcome to Shuyi Yang who is joining the lab as a Biostatistics MA student working on statistical aspects of the close-kin mark-recapture project to estimate mosquito demographic parameters.
6/13/2022: Welcome to Alan Hu who is joining the lab as an undergrad researcher working on the close-kin mark-recapture project to characterize demographic and dispersal parameters of Aedes aegypti mosquitoes.
5/14/2022: Congratulations and thank you to Natasha Harrison who worked with us as a graduate researcher for the last two years and has now graduated from UC Berkeley with an MPH. Natasha's dissertation is on environmental predictors of malaria incidence in São Tomé and Príncipe.
5/14/2022: Congratulations and thank you to Darpa Anireddy who worked with us as an undergrad researcher for the last two years and has now graduated from UC Berkeley with a BA degree in Public Health.
12/1/2021: Agastya Mondal presents on "Target product profile modeling for mosquito gene drive systems" at Epidemics 8, the virtual 8th International Conference on Infectious Disease Dynamics.
11/19/2021: Rodrigo Corder presents on the contribution of low-density and asymptomatic infections to Plasmodium vivax transmission in the Amazon at the virtual 70th Annual Meeting of the American Society for Tropical Medicine and Hygiene.
10/26/2021: Lab presents on modeling of gene drives in Aedes aegypti at virtual DARPA Safe Genes Transition Meeting.
10/24/2021: Váleri Vásquez presents on optimizing release schemes for genetics-based mosquito control programs at the annual meeting of INFORMS in Anaheim.
9/15/2021: Welcome to Lillian Weng, Xingli Yu, Joanna Yoo and Ayden Salazar who are joining the lab as undergrad researchers through the Data Science Discovery Program working on the mosquito gene drive machine learning library.
8/30/2021: Welcome to Reine Ngnonsse and Kendall Dimson who are joining the lab as undergrad researchers working on datasets and analysis pipelines to better understand malaria and arbovirus transmission at potential field sites.
8/13/2021: Huge congratulations and thank you to Dr. Jared Bennett who has worked with us as a graduate researcher for the last four years and has now graduated from UC Berkeley with a PhD in Biophysics and a designated emphasis in Computational Biology. Jared's dissertation is entitled "In silico exploration and analysis of gene drive efficacy". His work has transformed our approach to gene drive modeling and close-kin simulation and he will be very much missed!
6/13/2021: Congratulations to Dr. Francois Rerolle who has worked with us for the last five years and has now graduated from UCSF with a PhD in Epidemiology & Biostatistics. Francois' dissertation is entitled "Importance, size and mobility of forest-going populations for malaria elimination in Lao People’s Democratic Republic".
6/11/2021: Welcome to Elijah Bartolome who is joining the lab as a recent UC Berkeley graduate working on machine learning regression and classification models for mosquito gene drive datasets.
5/15/2021: Congratulations and thank you to Ashley Zhang and Chris De Leon who worked with us as undergrad researchers for the last year and have now graduated from UC Berkeley with BS degrees in Computer Science and Statistics.
12/18/2020: Huge congratulations and thank you to Dr. Sean Wu who has worked with us as a graduate researcher for the last five years and has now graduated from UC Berkeley with a PhD in Epidemiology and a designated emphasis in Computational Biology. Sean's dissertation is entitled "Stochastic models for the control of mosquito-borne pathogens". His work has been central to the development of modeling frameworks in our lab and he will be very much missed!
12/17/2020: Congratulations to Váleri Vásquez and colleagues who have been awarded a Career Development Network Seed Grant to support the creation of design-conscious content for sharing the best practice of data science.
8/31/2020: Welcome to Ameek Bindra and Daniel López who are joining the lab as undergrad researchers working on analyzing mosquito ecology and gene drive datasets for the MGDrivE project.
8/19/2020: Welcome to Agastya Mondal who is joining the lab as an Epidemiology PhD student working on models of mosquito-borne disease transmission.
8/19/2020: Welcome to Darpa Anireddy, Chris De Leon, Ashley Zhang and Priscilla Zhang who are joining the lab as undergrad researchers working on tracking malaria cases and machine learning algorithms for the MGDrivE project.
8/4/2020: Welcome to Natasha Harrison who is joining the lab as an Epidemiology & Biostatistics MPH student working on statistical analyses of malaria surveillance data from São Tomé and Príncipe.
6/10/2020: Lab participates in #ShutDownSTEM and condemns racism and all forms of white supremacy including police brutality.
6/5/2020: The UC Berkeley School of Public Health publishes a free online course on "Managing the COVID-19 Pandemic" with a module on mathematical modeling presented by John Marshall.
5/20/2020: Welcome to Hao Wang who is joining the lab as a Graduate Student Researcher working on monitoring and surveillance needs for genetics-based mosquito control trials.
5/16/2020: Congratulations and thank you to Thien-An Ha who worked with us as a graduate researcher for the last year and has now graduated from UC Berkeley with an MPH. Thien-An's dissertation is on household risk factors for Aedes aegypti mosquito proliferation in Guayaquil, Ecuador.
5/16/2020: Congratulations and thank you to Maya Shen and Gillian Chu who worked with us as undergrad researchers for the last two years and have now graduated from UC Berkeley with BS degrees in Computer Science and Bioengineering.
10/28/2019: Congratulations to Váleri Vásquez who passed her PhD qualifying exam today!
10/25/2019: Yogita Sharma and Jared Bennett present their work on close-kin mark-recapture and modeling of gene drive laboratory experiments at the Computational and Genomic Biology Retreat at UC Berkeley.
10/18/2019: Thien-An Ha presents her summer project on mosquito biting rates near cemeteries in Borbón, Ecuador at the Global Health Annual Fellows Symposium at UC Berkeley.
10/11/2019: Congratulations to Sean Wu who passed his PhD qualifying exam today!
10/10/2019: Welcome to Rodrigo Careaga, a Masters student at Tecnológico de Monterrey, Mexico, who is visiting the lab as part of our CITRIS project to develop machine learning algorithms to predict mosquito densities.
9/24/2019: Héctor Sánchez and Sean Wu represent lab at meeting of the Malaria Modeling Consortium in Seattle, WA.
9/6/2019: Lab research featured in UCSF News video discussing the prospects for global malaria eradication by 2050.
3/4/2019: Welcome to Sejal Mohata who is joining the lab as an undergrad researcher working on machine learning approaches to identifying landscape features relevant to potential field trials of genetics-based mosquito interventions.
11/10/2018: Sean Wu, Héctor Sánchez and Jared Bennett present on "Spatio-temporal force of infection modeling" and "MGDrivE: The original trilogy"at the UC Berkeley Computational and Genomic Biology Retreat in Point Reyes.
11/7/2018: Lab receives CITRIS-ITESM Seed Funding, in collaboration with Prof. Edgar Emmanuel Vallejo of Instituto Tecnológico de Monterrey, Mexico, to develop machine learning algorithms to predict mosquito densities and vector-borne disease incidence in Ecuador and Paraguay.
11/6/2018: Sean Wu presents on "Spatio-temporal force of infection modeling" at the Second SMBE Satellite Workshop on Genome Evolution in Pathogen Transmission and Disease in Kyoto, Japan.
10/15/2018: Welcome to Victor Ferman who is joining the lab as a postdoc working on our gene drive modeling framework and statistical and machine learning methods to inform mosquito habitat distribution.
6/1/2018: Welcome to Yi Li who is joining the lab as a visiting undergrad researcher from Ohio State University working on statistical approaches to infer mosquito movement patterns based on kinship data.
6/1/2018: Welcome to Váleri Vásquez who is joining the lab as an Energy and Resources Group PhD student working on the application of dynamic programming to optimal release strategies.