Replications file for "Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network" by Toru Kitagawa (UCL) and Guanyi Wang (UCL)
The files in this archive replicate the results reported in the "Simulation Exercises" section of the paper.
- MATLAB R2020b
Network_Generation: Generate the random network
- Multiple_Fixdensity_Generation.m: For each pair number of nodes and density levels, we generate 100 different erdos-renyi random networks. There are totally 9 pairs of number of nodes and density levels in large network setting.
- Multiple_small_Fixdenisty_Generation.m : For each pair number of nodes and density levels, we generate 100 different erdos-renyi random networks. There are totally 9 pairs of number of nodes and density levels in small network setting. -Multiple_SBM_Generation.m: For each number of nodes, we generate 100 different large random networks by using stochastic block model. -Multiple_small_SBM_Generation.m: For each number of nodes, we generate 100 different small random networks by using stochastic block model.
Greedy: Greedy Algorithm
- Greedy_fixden_multi.m: The greedy algorithm for multiple (in here we choose 100) large networks (generated by erdos-renyi model).
- Greedy_SBM_multi: The greedy algorithm for multiple (in here we choose 100) large networks (generated by stochastic block model).
- Greedy_SBM_small_multi: The greedy algorithm for multiple (in here we choose 100) small networks (generated by stochastic block model).
- Greedy_samll_fixden: The greedy algorithm for multiple (in here we choose 100) small networks (generated by erdos-renyi model).
- obj.m : Objective Function.
Global_opt: Brute Force Serach
- Global_fixden_multi.m: The global optimal solution for multiple (in here we choose 100) small networks (generated by erdos-renyi model).
- Global_SBM_multi.m: The global optimal solution for multiple (in here we choose 100) small networks (generated by stochastic block model).
- obj.m: Objective Function.
Random_Search: Random Allocation Rule
- Random_fixden_multi.m: The random allocation rules for multiple (in here we choose 100) small networks (generated by erdos-renyi model).
- Random_SBM_multi.m: The random allocation rules for multiple (in here we choose 100) large networks (generated by stochastic block model).
- obj.m: Objective Function.
Allocation_nonet: Targeting Without Network Information
- Allocation_Nonet_Fixden_multi.m: The allocation rule without network information for multiple (in here we choose 100) large networks (generated by erdos-renyi model).
- Allocation_Nonet_SBM_multi.m: The allocation rule without network information for multiple (in here we choose 100) large networks (generated by stochastic block model).
- obj.m: Objective Function.
Graph: Draw The Figure
- figure_compare_greedy_nonet.m: Draw the figure for the comparison between greedy algorithm and allocation without network information.
- figure_compare_greedy_random.m: Draw the figure for the comparision between greedy algorithm and random allocation.
Vaccination Ratio: The ratio of vaccinated younger units
- ratio.m: Calculate the percentage of vaccinated younger units compare to the total vaccinate units.