Preliminary results
We compute the ratio of the number of deaths occurring in the cooperative scenario over the number of deaths occurring in uncooperative (status-quo) scenario until December 31, 2021, and we obtain that 3 out of 10 deaths could be potentially averted.
Status quo weight for each country computed as:
Total vaccinations in country
/ Total vaccinations worldwide
Status quo weights are used to allocate new available doses
----OR longer version---->
Doses are distributed between countries using the observed share of total vaccinations distributed to country i over the total number of worldwide vaccination.
E.g. if up to end of April 2021 country i had been receiving 20% of the worldwide doses, it will keep receiving 20% of the worldwide doses until December, 2021 (up to a number of doses equal to twice the population in i, +10% tolerance).
Starting June 1, 2021 doses are allocated proportionally to countries’ populations.
Priority weights are not considered, only population size matters
Global Epidemic and Mobility Model (GLEAM): a stochastic, multi-strain, spatial and age-structured epidemic model based on a metapopulation approach [1-6]. The model divides the world into over 3,200 geographic subpopulations constructed using a Voronoi tessellation of the Earth’s surface. Subpopulations are centered around major transportation hubs (e.g. airports). GLEAM integrates a human mobility layer - represented as a network - that uses both short-range (i.e. commuting) and long-range (i.e. flights) mobility. Age-stratified contact matrices are generated by using highly detailed macro (census) and micro (survey) data on key socio-demographic features [7].
The infection dynamics occur within each subpopulation and we adopt a classic SLIR-like model properly extended to account for the presence of multiple strains and vaccination protocols.
Policy interventions are applied to modify disease transmissibility and population mobility. International travel restrictions are dynamically introduced in the model as reported by the Oxford Covid-19 Government Response Tracker (OxCGRT) [8]. International and domestic travel flows are adjusted using real time origin-destination data from OAG.
Short-range mobility is adjusted using as proxy the fraction of workplace visits, with respect to a pre-pandemic baseline, as reported in the Google’s COVID-19 Community Mobility Reports [9].
Contact patterns and mixing rates between age groups are modulated considering the effect of policy interventions on individuals behaviors.
View poster on "Estimating the effect of equitable vaccine allocation strategies on the international disease burden of COVID-19".
Status-quo distribution until June 1, 2021. Two alternative strategies starting June 1, 2021 until end of December 2021
We compute the deaths in the uncooperative and cooperative scenarios by the end of 2021 and estimate the percentage of deaths that could potentially be averted. The countries shown will reduce the number of total deaths in the case vaccines are distributed proportionally to their population. The countries in grey were included in the analysis but do not show a significant gain or loss.
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To study the spatiotemporal COVID-19 spread, we use the Global Epidemic and Mobility Model (GLEAM), an individual-based, stochastic, and spatial epidemic model [1, 2, 3, 4, 5, 6]. GLEAM uses real-world data to perform in-silico simulations of the spatial spread of infectious diseases at the global level. We use the model to analyze the spatiotemporal spread and magnitude of the COVID-19 epidemic in the countries of interest. The model generates an ensemble of possible epidemic projections described by the number of newly generated infections, hospitalizations, and deaths. The model is calibrated on weekly deaths data from the Johns Hopkins Centers for Civic Impact by using an information theoretical approach.
Disclaimer: There are large uncertainties around the transmission of COVID-19, the effectiveness of different policies and the extent to which the population is compliant to social distancing measures. The presented material is based on modeling scenario assumptions informed by current knowledge of the disease and subject to change as more data become available.
Acknowledgements: This work was supported by the Bill & Melinda Gates Foundation.
Northeastern University/MOBS Lab
• Matteo Chinazzi
• Jessica T. Davis
• Kunpeng Mu
• Ana Pastore y Piontti
• Alessandro Vespignani
