A simulation framework for gene drive releases in spatially explicit mosquito populations, and its application to mosquito borne diseases control

IDDconf 2018
Héctor M. Sánchez C., Jared Bennett*, Sean L. Wu*, Valeri Vasquez, John M. Marshall
Contact: Website:

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1. Background [3 minutes]
2. The Model [3 minutes]
3. Application [5 minutes]
4. Closing Remarks [1 minutes]
5. Questions [3 minutes]

1. Background

A. Diseases
B. Gene-Drive Approaches
C. Hurdles to Overcome

1A. Diseases

1B. Gene-Drive Approaches

1C. Hurdles to Overcome

(from a modelling perspective)

2. MGDrivE

A. Modules
B. Tensor Equations
C. Demo

2A. Modules

2B. Tensor Equations

1) Genetic Inheritance

$$ \begin{align*} \overline{O(T_x)} = & \sum_{j=1}^{n} \Bigg( \bigg( (\beta*\overline{s} * \overline{ \overline{Af_{[t-T_x]}}}) * \overline{\overline{\overline{Ih}}} \bigg) * \Lambda \Bigg)^{\top}_{ij}\\ \end{align*}$$

2) Migration

$$ \begin{align*} \overline{Am_{(t)}^{i}}= &\sum{\overline{A_{m}^j} \otimes \overline{\overline{\tau m_{[t-1]}}}} \\ \overline{\overline{Af_{(t)}^{i}}}= &\sum{\overline{\overline{A_{f}^j}} \otimes \overline{\overline{\tau f_{[t-1]}}}} \end{align*} $$

3) Life History

$$ \begin{align*} \overline{L_{[t]}}= &\overline{L_{[t-1]}} * (1-\mu_{l}) * F(\overline{L_{[t-1]})} +\overline{O(T_e)}* \theta_{e} - \overline{O(T_e+T_l)} * \theta_{e} * D(\theta_l,0)\\ \overline{E^{'}}=& \overline{O(T_e+T_l+T_p)} * \bigg(\overline{\xi_m} * (\theta_{e} * \theta_{p}) * (1-\mu_{ad}) * D(\theta_l,T_p) \bigg)\\ \overline{Am_{[t]}}=& \overline{Am_{[t-1]}} * (1-\mu_{ad})*\overline{\omega_m} + (1-\overline{\phi}) * \overline{E^{'}} + \overline{\nu m_{[t-1]}}\\ \overline{\overline{Af_{[t]}}}=& \overline{\overline{Af_{[t-1]}}} * (1-\mu_{ad}) * \overline{\omega_f} + \bigg( \overline{\phi} * \overline{E^{'}}+\overline{\nu f_{[t-1]}}\bigg)^{\top} * \bigg( \frac{\overline{\eta}*\overline{Am_{[t-1]}}}{\sum{\overline{Am_{[t-1]}}}} \bigg)\\ \end{align*} $$

2C. Demo

3. Application

A. Drive: Threshold-Dependent Systems
B. Geography: Yorkeys Knob
C. Experiments: Factorial Sweeps
D. Results: Fixation Response Surfaces
E. Results: Remediation Response Surfaces

3A. Threshold-Dependent Systems

3B. Yorkeys Knob

3C. Experimental Setup

  • Time: 3 years
  • Households: 943
  • Household population: 15 mosquitos (around 14k total)
  • Release size proportion: 20 mosquitos
  • Releases location selection scheme: randomly uniform
  • Gene Drives: Reciprocal Translocations and Threshold Dependent Underdominance
  • Releases number: 0 to 20
  • Releases coverage: 0% to 100%
  • Outcome: Fixation/Dilution

3D. Fixation Response Surface

Reciprocal Translocations

3D. Fixation Response Surface

Threshold Dependent Underdominance

3D. Fixation Response Surface

Translocations VS Threshold Dependent Underdominance


3E. Remediation Response Surface

Threshold Dependent Underdominance

4. Closing Remarks

A. Conclusions and Future Work
B. The Team

4A. Conclusions and Future Work

4B. The Team

Developed in: John Marshall's Lab by

Lead: Héctor M. Sánchez C.
Core Dev: Sean L. Wu, Jared Bennett
Environmental Factors: Tomás León
Releases Optimization: Valeri Vasquez
Spatial Analysis: Biyonka Liang, Sarafina Smith, Sabrina Wong
Movement Kernels: Partow Imani
Auxiliary Dev: Chase Violet