Route Optimization Tool (RoOT) for distribution of vaccines and health products.

Delivery of health products from provinces or districts to health facilities, including temperature-sensitive vaccines, is one of the most effective interventions to ensure availability of supplies and save lives in low- and middle-income countries. Currently, routes are hand drawn by logisticians that are adjusted based on vehicle availability and quantity of products. Easy-to-use supply chain tools are needed that planners can use in real-time to create or adjust routes for available vehicles and road conditions. Efficient and optimized distribution is even more critical with the COVID-19 vaccine distribution. We develop a Route Optimization Tool (RoOT) using a variant of a Vehicle Routing and Scheduling Algorithm (VeRSA) that is coded in Python, but reads and writes Excel files to make data input and using outputs easier. The tool takes into account cold chain distribution, is easy-to-use, and provides routes quickly within two minutes. RoOT can be used for routine operations or in emergency situations, such as delivery of new COVID-19 vaccine. The tool has a user-centric design with easy dropdown menus and the ability to optimize on time, risk, or combination of both. Training of logisticians in Mozambique indicate that RoOT is easy to use and provides a tool to improve planning and efficient distribution of health products, especially vaccines. We illustrate using RoOT in an emergency situation, such as a cyclone. RoOT is an open-source tool for optimal routing of health products. It provides optimized routes faster than most commercial software, and is tailored to meet the needs of government stakeholders. Currently, RoOT does not allow multi-day routes, and is designed for trips that can be completed within twenty-four hours. Areas for future development include multi-day routing and integration with mapping software to facilitate distance calculations and visualization of routes.

Route Optimization Tool (RoOT) for distribution of vaccines and health products [version 2;peer review: 1 approved, 2 approved with reservations]

Ensuring the delivery and availability of health products, including temperature-sensitive vaccines, is vital to saving lives in low- and middle-income countries (LMICs).  In many LMICs routes are hand drawn by logisticians and are adjusted based on vehicle availability and product quantities. Easy-to-use real-time supply chain tools are needed to create or adjust routes for available vehicles and road conditions. Having more efficient and optimized distribution is especially critical for COVID-19 vaccine distribution. Route Optimization Tool (RoOT) works best for planning routes for 50 health facilities or less, in two minutes. We develop RoOT using a variant of a Vehicle Routing and Scheduling Algorithm (VeRSA) that is coded in Python but reads and writes Excel files to make data input and using outputs easier. RoOT can be used for routine operations or in emergency situations, such as delivery of new COVID-19 vaccine. The tool has a user-centric design with easy dropdown menus and the ability to optimize on time, risk, or combination of both. RoOT is an open-source tool for optimal routing of health products. It provides optimized routes faster than most commercial software and is tailored to meet the needs of government stakeholders We trained supply chain logisticians in Mozambique on using RoOT, and their feedback validates that RoOT is a practical tool to improve planning and efficient distribution of health products, especially vaccines. We also illustrate how  RoOT can be adapted for an emergency situation by using a test scenario of a cyclone. Currently, RoOT does not allow multi-day routes, and is designed for trips that can be completed within twenty-four hours. Areas for future development include multi-day routing and integration with mapping software to facilitate distance calculations and visualization of routes.

COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society.

As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.