Groundbreaking study reveals how we can overcome monkeypox epidemic with limited vaccine supply

Providing more monkeypox vaccines to areas that have high epidemic potential and the maximum number of initial cases could help us end this epidemic.
Rupendra Brahambhatt
Monkeypox virus stock photo.
Monkeypox virus stock photo.


In the early days of a virus outbreak, the way vaccine doses are distributed in different parts of a country amidst their limited supply could play a major role in controlling the infection and the rate at which it spreads. For instance, administering more COVID vaccines in a region with a large population and a high COVID infection rate could result in faster herd immunity than doing the same for an area with a small population and low rate of infection. 

Interestingly, a team of researchers at Unity Health Toronto in Canada has proposed a monkeypox vaccine allocation model that aims at delivering the best results with a limited vaccine supply, according to a press release. In their study, the researchers mention that there are 1,444 patients with monkeypox, disproportionately among members of the GBMSM community (men having sexual relationships with other men, gay, and bisexual population). 

They further reveal that the availability of vaccines for the GBMSM population having disproportionate risks of monkeypox virus (MPXV) is very limited. So they have developed an effective vaccine allocation strategy that could curb the infection in such a case.  

Ensuring optimal allocation of monkeypox vaccines 

The researchers modeled two supposed cities as partially connected networks having a combined GBMSM population of 100,000. The first city, referred to as city A, represented a model of a big city like Toronto, and it had a GBMSM population of 80,000. Whereas city B, which represented medium and small cities, had only 20,000 GBMSM members. 

First, MPXV is introduced in the model, and after 45 days, they administer 5,000 vaccine shots over the course of 30 days. The vaccines are distributed in the networks on the basis of city size, percentage of initial cases, and epidemic potential. 

“This potential is often quantified via the basic reproduction number R0, which reflects the expected number of secondary infections generated by a person who is infected in a fully susceptible population,” the authors note in their study. They further explain that an optimal vaccine allocation approach for both their cities would be the one that results in the lowest monkeypox infection rate by day 90.

Throughout this experiment, the total number of vaccine doses was kept limited to 5,000 for both cities. The researchers implemented different vaccine allocation strategies involving both equal and unequal vaccine distribution scenarios. 

Based on the infection rates noticed during these different scenarios, they concluded that the best approach is to allocate maximum vaccine doses to an area that has the highest epidemic potential and the maximum number of initial cases. 

The authors said in the paper, “Because of the larger population size, greater epidemic potential (R0), and having all imported or seed cases in city A in this scenario, allocating all 5000 vaccine doses to city A yielded the fewest infections (550) by day 90 (optimal strategy). Allocating vaccines proportionally to city size yielded 615  infections (broken line), whereas no vaccination yielded 1020 infections.”

They further explain that giving the maximum number of doses to a city based on R0  and initial cases could also lead to high monkeypox infection rates in another city. However, since most of the infection is already prevented within a small duration (90 days), it would be easy to control the rest of the cases in the city with low R0 once the vaccine supply increases.   

As of November 25, more than 29,000 monkeypox cases (and 14 deaths) have been reported in the US alone. The researchers hope that their findings will help policymakers in Canada and various other countries to come up with an optimal vaccine allocation strategy for controlling the current monkeypox outbreak.  

The study was published in the Canadian Medical Association Journal.

Study Abstract:

Background: The current global monkeypox virus (MPXV) outbreak has disproportionately affected gay, bisexual and other men who have sex with men (GBMSM). Given that many jurisdictions have been faced with limited supplies of MPXV vaccine, we aimed to explore optimal vaccine allocation between 2 linked GBMSM transmission networks over a short-term time horizon, across several epidemic conditions.

Methods: We constructed a deterministic compartmental MPXV transmission model. We parameterized the model to reflect 2 representative, partially connected GBMSM sexual networks ( cities), using 2022 data from Ontario. We simulated a roll-out of 5000 vaccine doses over 30 days that started 45 days after epidemic seeding with 10 imported cases. Within this model, we varied the relative city (network) sizes, epidemic potentials (R0), between-city mixing and distribution of seed cases between cities. For each combination of varied factors, we identified the allocation of doses between cities that maximized infections averted by day 90.

Results: Under our modelling assumptions, we found that a limited MPXV vaccine supply could generally avert more early infections when prioritized to networks that were larger, had more initial infections or had greater R0. Greater between-city mixing decreased the influence of initial seed cases and increased the influence of city R0 on optimal allocation. Under mixed conditions (e.g., fewer seed cases but greater R0), optimal allocation required doses shared between cities.

Interpretation: In the context of the current global MPXV outbreak, we showed that prioritization of a limited supply of vaccines based on network-level factors can help maximize infections averted during an emerging epidemic. Such prioritization should be grounded in an understanding of context-specific risk drivers and should acknowledge potential connectedness of multiple transmission networks.

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